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Genome instability in multiple myeloma-associated DIS3 exonuclease domain mutants Milbury, Karissa Lynn 2018

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 GENOME INSTABILITY IN MULTIPLE MYELOMA-ASSOCIATED DIS3EXONUCLEASE DOMAIN MUTANTSbyKARISSA LYNN MILBURYB.Sc., Dalhousie University, 2013A DISSERTATION SUBMITTED IN PARTIAL FULFILLMENT OF THEREQUIREMENTS FOR THE DEGREE OFDOCTOR OF PHILOSOPHYinTHE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES(Genome Science and Technology)THE UNIVERSITY OF BRITISH COLUMBIA(Vancouver)December 2018© Karissa Lynn Milbury, 2018COMMITTEEThe following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the dissertation entitled: Genome instability in multiple myeloma-associated  DIS3   exonuclease domain mutants          submitted by    Karissa Milbury                            in partial fulfillment of the requirements forthe degree of Doctor of Philosophy                                                                                  in  Genome Science and Technology                                                                        Examining Committee: Peter Stirling, Medical Genetics                                                                                                  Supervisor Philip Hieter, Medical Genetics                                                                                                   Supervisory Committee Member Christopher Loewen, Cellular & Physiological Sciences                                                            Supervisory Committee Member LeAnn Howe, Biochemistry & Molecular Biology                                                                     University Examiner Christopher Maxwell, Pediatrics                                                                                                 University ExaminerKrassimir Joseph Yankulov, Molecular and Cellular Biology, University of Guelph                 External ExaminerAdditional Supervisory Committee Members: Pamela Hoodless, Medical Genetics                                                                                            iiABSTRACTChromosome instability (CIN) is characterized by an increased rate of the unequal distribution of DNA between daughter cells. Such changes in chromosome structure or number can occur due to both mitotic defects leading to aneuploidy and DNA damage-induced chromosome rearrangements. Previous large-scale screens for CIN genes in the model organism Saccharomyces cerevisiae identified DIS3, which encodes a catalytic component of the core RNA exosome complex, as a novel CIN gene. Mutations in human DIS3 have been identified in roughly 11% of multiple myeloma (MM) cases. I sought to recapitulate MM-associated point mutations at conserved sites in yeast cells, in order to understand the mechanism of emergent CIN in MM. I have found that MM-associated DIS3 exonuclease mutations do increase the frequency of CIN. A temperature sensitive DIS3 mutant accumulates DNA:RNA hybrids, however analysis of DNA damage foci by microscopy revealed no increase in double-strand breaks in any of the tested strains. Yeast DIS3 exonuclease mutants experience growth retardation, temperature sensitivity, and an altered cell cycle. Microarray analysis of one MM mutant has additionally demonstrated downregulation of cell cycle components, consistent with the potential for mitotic defects, in addition of upregulation of a host of metabolic pathways. Further, genetic interaction profiling by synthetic genetic array indicates MM-associated DIS3 mutations synthetically interact with rRNA processing proteins, as well as a host of mitotic regulators and metabolic pathways, particularly those involved in spindle and kinetochore function. Further, I verify that DIS3 mutants have a functional spindle assembly checkpoint, and are in fact resistant to microtubule poisons. Finally, I discover that the fitnessdefects induced by these mutations can be abrogated through culturing on media containing only a non-fermentable carbon source, suggesting that growth on poor carbon sources may also rescue CIN.Together, these results demonstrate extensive phenotypic consequences of MM-associated iiipoint mutations in DIS3, and support a model for CIN in DIS3 mutants involving defects in mitotic progression.ivLAY SUMMARYCancer cells make a tough trade-off: as they evolve and grow aggressively, they develop DNA damage and mutations. This makes them very sensitive to drugs that further increase DNA damage, as they aren’t able to fix it as well as a healthy cell. If we can pinpoint which mutations cause damage to accumulate, they will also be the mutations which sensitize the cell to drugs.I’ve taken mutations that occur in the cancer multiple myeloma and recreated them in yeast cells to examine their effects. My research has found that mutations in the gene DIS3 cause an increasing amount of DNA damage through a process called chromosome instability. Specifically, DIS3 mutation interferes with the cell’s ability to separate copies of its DNA as it divides, which causes genetic changes. This work suggests that patients with DIS3 mutations may respond better to drugs that further inhibit this aspect of cell division.vPREFACEThe research described in Chapters 2 and 3 formed the basis of a manuscript currently in revision, titled “Exonuclease domain mutants of yeast DIS3 display genome instability”. Thispaper was co-written by myself and Dr. Stirling, and together we designed the experiments. I performed and analyzed most of the experiments described, with the exception of the RNA-FISH (which was performed by Biplab Paul and Ben Montpetit) and the expression microarray (performed by Zongli Luo). Claire Fowler, an undergraduate co-op student, constructed strains and performed spotting assays to validate the SGA experiments. Dr. Stirling also contributed to the analysis of the SGA data in producing the GO term and ReviGO plots. A portion of the data produced as part of the proteogenomic screen in Chapter 3 contributed to the paper, “Selective defects in gene expression control genome instability in yeast splicing mutants” published in the journal Molecular Biology of the Cell in November 2018 (Tam et al., 2018).The research described in the final portion of Chapter 3, as well as Chapter 4, will hopefully form the basis for a future publication. These experiments were designed by Dr. Stirling and I, and carried out entirely by me.viTABLE OF CONTENTSABSTRACT………………………………………………………………………………….iiiLAY SUMMARY……………………………………………………………………………..vPREFACE…....….…..….…..….….…...…...…...……..……………………………………..viTABLE OF CONTENTS……………………………………………………………………viiLIST OF TABLES……………………………………………………………………….…..xiiLIST OF FIGURES…………………………………………………………………….…...xiiiLIST OF ABBREVIATIONS & ACRONYMS…………………………………...………...xivACKNOWLEDGEMENTS………………………………………………………….…….xviiDEDICATION……………………………………………………………………………..xviii1 INTRODUCTION…………………………………………………………………………..11.1 The genetic code…………………………………………………………….……..11.2 The cell cycle………………………………………………….…………………...21.3 DNA mutation, damage, and repair………………………….…………………….31.4 Mutation, DNA damage, and evolution…………………………….……………...51.5 Chromosome instability in cancer…………………………………….…………...61.6 Saccharomyces cerevisiae: an ideal model for investigating CIN………….……...91.7 CIN induction in RNA processing mutants………….………….……….……….101.8 The essential gene DIS3 is a key RNA processing factor with many links toCIN……………………………………………………………………..……………..121.9 Multiple myeloma: progression and treatment…………………….……………..131.10 Recurrent DIS3 mutations in cancer…………………………….………………161.11 Research scope…...…....….….…........………......….….……….………………172 CHARACTERIZATION OF CANCER-ASSOCIATED DIS3 MUTANTS………………222.1 Introduction……………………………………………………………………….222.2 Methods………………………………………………………………….……….232.2.1 Yeast strains and culturing……………………………………..………..232.2.2 Strain construction……………………………………………………....24vii2.2.3 Spot assays……………………………………………….………….…..262.2.4 Live cell fluorescent microscopy………………………….…….….…...262.2.5 Chromosome spreads…………………………………..………….…….262.2.6 A-Like Faker assay………………………….………….…….………….272.3 Results………………………………………….……………………….………...272.3.1 Strain construction……………………………………………..………..272.3.2 Allele characterization……………………………………….….….……282.3.3 DIS3 mutants exhibit an increased frequency of A-like faker events...…302.3.4 The dis3-ts mutant accumulates R-loops, but not associated damage..…312.4 Discussion...…………….…….…………….……….……..…………….……….322.4.1 Cancer-associated DIS3 mutations induce aneuploidy in S.cerevisiae….………..….….……………..….….….……..……..............…….…..…332.4.2 R-loop accumulation is a feature of some DIS3 mutants, but does notelicit DNA damage…………………………………….……….……….……..352.4.3 Implications of expression of DIS3 from plasmid-borne alleles.….….....363 GENOME-WIDE CHARACTERIZATION OF DIS3 MUTANTS…………….................513.1 Introduction………………………………….……………………….…………...513.2 Methods…………………………………………………………….…………….523.2.1 Yeast strains and culturing…………………………………………..…..523.2.2 Spot assays…………………………………………………………..…..523.2.3 Microarray………………………………………………………..….…..533.2.4 Synthetic Genetic Array (SGA)…………………………………….…...533.2.5 GO ontology analysis…………………………………………..….…….543.2.6 Budding indices…………………………………………………..……...543.2.7 Western blot……………………………………………………..….……553.2.8 Reverse transcription quantitative polymerase chain reaction (RT-qPCR)…………………………………………………………………....…….563.3 Results………………………………………………………………………….....563.3.1 Microarray analysis of dis3E729K reveals diverse effects on thetranscriptome………………………………………………………………......56viii3.3.2 Synthetic genetic array of dis3-ts and dis3E729K indicates disruption ofmitotic regulation through anaphase………………………………….….……573.3.3 Overlap of enriched pathways, but not individual genes, indicatessynthetic interactions partially explained by transcriptome alterations….…....583.3.4 Altered budding index progression in plasmid-bearing DIS3 mutantstrains………………………………………………….…….………………...583.3.5 Altered tubulin expression in DIS3 mutants………….…….…………...593.3.6 Proteogenomic screen for tubulin expression in RNA processingmutants…………………………………………………..…………………….603.4 Discussion…….….….….….….….….….….…………………………………….613.4.1 Differences in expression of key transcripts in the DIS3 mutants……....623.4.2 Synthetic genetic array reveals novel interactions between dis3E729K andanaphase-associated proteins…………………………………………….…....623.4.3 Plasmid-borne DIS3 alleles influence budding index...…….……..….....643.4.4 Altered tubulin expression is a general feature of CIN-inducing RNAprocessing mutants………………………………………………………....….654 INVESTIGATING THE MECHANISM OF CIN INDUCTION IN DIS3 MUTANTS…..924.1 Introduction………………………………………………………………….....…924.2 Methods………………………………………………….……………………….934.2.1 Yeast strains and culturing………………..…….….….….….….….…...934.2.2 Spindle defect imaging………………………………….….…...........….934.2.3 Nocodazole escape imaging………….…………….…….….….…….…944.2.4 Budding indices…………………………………………..….…………..944.2.5 Fluorescence in-situ hybridization…………………….….……….…….954.2.6 Spotting assay……………………………………….….……………….954.3 Results………………………………………………….……………….….……..964.3.1 DIS3 mutants are resistant to the microtubule-destabilizing drugbenomyl…………………………………….………………….……….….…..964.3.2 DIS3 mutants exhibit abnormal timing of spindle dynamics….……..….964.3.3 DIS3 mutation alters cell cycle progression in the context of kinetochoreixdeficiency………………………………………………………………….…974.3.4 DIS3 mutants do not escape nocodazole-induced anaphase arrest…….98 4.3.5 MM-associated DIS3 mutations do not induce nucleolar poly(A)-RNAaccumulation…………………………………………………………....……994.3.6 Rescue of mutant fitness under non-fermentative growth....…….........1004.4 Discussion…...………………………………………………………………….1004.4.1 Spindle timing is altered in DIS3 mutants………………………...…...1014.4.2 DIS3 mutants have a functional SAC………………………………….1024.4.3 DIS3 point mutations do not induce nucleolar poly(A)-RNAaccumulation………………………………………………………………....1024.4.4 Fitness defects in DIS3 mutants are abrogated by respiratorygrowth……………………………………………………………..……..…..1035 CONCLUSIONS AND FUTURE DIRECTIONS…………………………….……....….1165.1 DIS3 separation-of-function alleles reveal specific contributions to genomestability maintenance………………………………………………….………..……1165.2 A potential role for Dis3 in mitotic exit signalling…………….……….……..…1175.2.1 Expression changes in cell cycle-related transcripts are a generalconsequence of DIS3 mutation……………………….…………..……….….1175.2.2 Cell cycle control of Dis3 and influence on mitotic spindleorganization……………………….………….…………….….….…….……1185.3 Rescue on non-fermentable media suggests timing of cell cycle progression is keyfor production of CIN in DIS3 mutants…………………………………….……….1195.4 Implications for DIS3 mutation in multiple myeloma……………….………….1205.5 Limitations to the chosen system…………………………………….…….……1215.5.1 Potential background effects of BY4741 that may influence thesedata……………………………………………….…………………….…….1215.5.2 System differences in S. cerevisiae vs. H. sapiens…..…….……...…..….1215.6 Conclusion………………………..…………….…….…………….…….….….122BIBLIOGRAPHY…………………………………………………………………...……..124APPENDICES…………………………………………………………………….….….…151xAppendix 1. gBlock sequences used for DIS3 mutant construction………………..151Appendix 2. Significantly altered genes in microarray comparing “WT” DIS3::URA3vs. dis3E729K, from greatest downregulation to greatest upregulation…………….…156Appendix 3. GO term enrichment analysis for the dis3E729K expressionmicroarray………………………………………………………………....………..178Appendix 4. Synthetic genetic array hits dis3-ts x DMA……………………..……212Appendix 5. Synthetic genetic array hits dis3-ts x CB-ts, DAmP………….….…...223Appendix 6. Synthetic genetic array hits dis3E729K x DMA…………………..…….240Appendix 7. Synthetic genetic array hits dis3E729K x CB-ts, DAmP…………….….252Appendix 8. GO term enrichment of dis3-ts positive interactions identified bysynthetic genetic array……………………………………………………...………263xiLIST OF TABLESTable 2.1 Yeast strains used in this study……………………………………………………46Table 2.2 PCR and qPCR primers used in this study………………………………………..48Table 2.3 Growth behaviour of DIS3 mutant alleles under the indicated stress…………….50Table 3.1 Enriched GO terms in the dis3E729K microarray…………………………………...79Table 3.2 Enriched GO terms in the dis3E729K and dis3-ts synthetic genetic arrays…………81Table 3.3 Previously published phenotypes of RNA processing α-tubulin screen hits.…......90xiiLIST OF FIGURESFigure 1.1 Forms of chromosome instability.........................……………………………….20Figure 1.2 DIS3 conservation and target transcripts….…........……………………………..21Figure 2.1 Characterization of DIS3 separation-of-function, cancer-associated andtemperature sensitive alleles…………………………………………………………………38Figure 2.2 Backcrossing of dis3-ts reduces suppressor production…………………………39Figure 2.3 P-body accumulation in DIS3 mutants…………………………………………..40Figure 2.4 Mutations in the DIS3 exonuclease domain cause genome instability………….41Figure 2.5 Detection of R-loop staining in a panel of DIS3 mutant alleles…………………43Figure 2.6 DNA damage foci do not accumulate in DIS3 mutants………………………….45Figure 3.1 RNP composition cluster expression changes in microarray of dis3E729K………..67Figure 3.2 Genomic profiling of dis3E729K indicates mitotic defects………………………...68Figure 3.3 Validation of kinetochore component interactions from the dis3E729K SGA….. ...70Figure 3.4 Expression microarray and SGA datasets contain few overlapping hits………...71Figure 3.5 Budding index of DIS3 mutants…………………………………………………72Figure 3.6 Protein expression of α-tubulin is decreased in DIS3 mutants…………………..74Figure 3.7 α-tubulin protein expression in a panel of RNA processing CIN mutants…...….76Figure 3.8 Protein expression of α-tubulin in RNA processing mutant strains synchronizedwith α-factor…………………………………………………………………………………78Figure 4.1 Benomyl resistance in DIS3 mutants grown at 25°C………………………......105Figure 4.2 Spindle dynamics in DIS3 mutants assessed by fluorescent microscopy…..….106Figure 4.3 The dis3E729K allele decreases the proportion of arrested dam1-1 cells………...108Figure 4.4 DIS3 mutants do not exacerbate fitness defects of mad1Δ or mad2Δ…………...110Figure 4.5 All DIS3 mutants have a functional SAC as assessed by ability to escapenocodazole arrest…………………………………………………………………….......…111Figure 4.6 Representative images of poly(A)-RNA FISH experiments in the indicated DIS3mutant strains……………………………………………………………………………….113Figure 4.7 Fitness defects of DIS3 mutants are rescued on nonfermentable media……….114Figure 4.8 Nonfermentable media has no effect on DIS3 mutant benomyl resistance…….115xiiiLIST OF ABBREVIATIONS & ACRONYMS5-FOA 5-fluoroorotic acid5-FU 5-fluorouracilAID Activation induced cytidine deaminaseALF A-like fakerAML Acute myeloid leukemiaARE AU-rich elementBER Base excision repairBSA Bovine serum albuminCIN Chromosomal instabilityCRAC In vivo RNA crosslinkingCTF Chromosome transmission fidelityCUT Cryptic unstable transcriptDAmP Decreased abundance by mRNA perturbationDAPI 4’,6-diamidino-2-phenylindoleDDR DNA damage responseDIC Differential interference contrastDMSO Dimethyl sulfoxideDNA Deoxyribonucleic aciddNTP Deoxynucleoside triphosphateDRIP-chip DNA:RNA immunoprecipitation microarrayDSB Double strand breakdsDNA Double stranded DNAFEAR Cdc fourteen early anaphase releaseFISH Fluorescence in situ hybridizationG418 GeneticinGFP Green fluorescent proteinGIN Genome instabilityGO Gene ontologyxivHDAC Histone deacetylaseHDMM Hyperdiploid multiple myelomaHR Homologous recombinationHRP Horseradish peroxidaseHU HydroxyureaIP ImmunoprecipitationMEN Mitotic exit networkMGUS Monoclonal gammopathy of unknown significanceMIN Microsatellite instabilityMM Multiple myelomaMMR Mismatch repairMMS Methyl methanesulfonatemRNA Messenger RNANER Nucleotide excision repairNHDMM Nonhyperdiploid multiple myelomaNHEJ Non-homologous end joiningOD Optical density at 600nmORF Open reading framePARP Poly ADP-ribose polymerasePBS Phosphate buffered salinePCR Polymerase chain reactionPEG Polyethylene glycolPoly(A) PolyadenylatedRNA Ribonucleic acidRNP Ribonucleoprotein particleROS Reactive oxygen speciesRPM Rotations per minuterRNA Ribosomal RNART-qPCR Reverse transcription quantitative polymerase chain reactionSAC Spindle assembly checkpointxvSC Synthetic complete (medium)s-CIN Structural CINSEM Standard error of the meanSGA Synthetic genetic arraysnoRNA Small nucleolar RNAsnRNA Small nuclear RNASSB Single strand breakSUT Stable uncharacterized transcriptTs Temperature-sensitiveUTR Untranslated regionw-CIN Whole chromosome CINWT Wild typeYFP Yellow fluorescent proteinYPD Yeast peptone dextrose (medium)xviACKNOWLEDGEMENTSI would like to first thank my thesis supervisor, Dr. Peter Stirling, for his guidance, mentorship, and patience throughout this project. As the first PhD graduating from the Stirling Lab, I can only hope I have fulfilled his expectations and set a strong example for those who will follow. I would also like to thank my thesis committee – Drs. Philip Hieter, Pamela Hoodless, and Christopher Loewen – for their mentorship and support. Their insightswere invaluable in building this project.I will also thank my labmates – in particular, Dr. Veena Mathew and Annie Tam, two incredible women with whom I have had the privilege of working for the past five years. Collaborating with them was a highlight of my time in the Stirling lab.As well, I thank the collaborators and contributors that have given time, resources, and expertise to this project. Dr. Claudia Schneider provided plasmids that formed the basis for many of the experiments described below, and Dr. Karim Mekhail provided the GFP-TUB1 plasmid used for the spindle imaging experiments. Dr. Alina Chan taught me to perform chromosome spreads. I would also like to thank Ben Montpetit and Biplab Paul, for performing the RNA-FISH and offering suggestions and edits for our manuscript.I acknowledge the generous financial support that has made this project possible: a College for Interdisciplinary Studies Graduate Award (later renamed a Faculty of Science Graduate Award), the Roman M. Babicki Fellowship in Medical Research from the Faculty of Medicine, and travel funding from the UBC Public Scholars Initiative. This project was further supported by a CIHR Bridge Grant.I would also like to thank Dr. Govinda Sharma, who sat with me in numerous Vancouver coffeeshops while writing his own doctorate thesis, and served as a confidante and cheerleader through my writing process. Finally, I would like to thank my family and friends for their patience through my 6 years of graduate work, and decade of post-secondary study. In particular I must thank my husband, Nicolas Pratt, for his limitless love and encouragement. xviiDEDICATIONSpending time in the mountains was an unparalleled pleasure that kept me sane over the course of this PhD. I dedicate this thesis to the people who ventured with me through those wild places. I wouldn’t have made it out of Despair Pass without you.xviii1 INTRODUCTION1.1 The genetic codeDeoxyribonucleic acid (DNA) is the molecule which acts as the basis of heredity for all known life. Its structure is comprised of four primary nucleobases – adenine and guanine (purines), thymine and cytosine (pyrimidines) – arranged in sequence along a phosphate-sugar backbone. Purines and pyrimidines bind to form base pairs, and maintain the DNA in a stable double-stranded state; the molecule adopts a natural curve to form a double helix (Watson & Crick, 1953). Different organisms contain different numbers of DNA strand molecules, which in their entirety, with associated proteins, are referred to as chromosomes.Under normal biological conditions, much of the double stranded DNA is wrapped around packaging proteins called histones (Luger, Mäder, Richmond, Sargent, & Richmond, 1997). These histone proteins are subject to modifications, in the form of an extensive set of chemical adjustments which collectively act to influence DNA accessibility and dictate the epigenetic state of the cell (Karlic, Chung, Lasserre, Vlahovicek, & Vingron, 2010). It is widely believed that such modifications represent, in large part, the mechanism through which cells express differential phenotypic identities from the same genetic code (Goldberg, Allis, & Bernstein, 2007). These epigenetic modifications may also influence higher-order DNA packaging, further condensing chromosomes into what is generally believed to be a transcriptionally silenced state (Maison et al., 2002).The primary function of DNA is to provide, through the sequence of base pairs, a “template” for the assembly of ribonucleic acids (RNAs) (Bremer & Konrad, 1964). The RNA molecules serve as templates for protein synthesis at the ribosome, but may also influence specific cellular processes in their own right (Geisler & Coller, 2013). Vast suites of proteins coordinate to transcribe the code of DNA bases into RNA. Modifiers of DNA methylation and histone methylation, acetylation, phosphorylation, ubiquitination, and other modifications must act in coordination to facilitate interaction with targeting proteins 1(Henikoff & Shilatifard, 2011). RNA polymerases, in conjunction with a vast array of coordinating proteins, then infiltrate at promoter regions – which are defined by DNA sequence as well as local histone occupancy – and coordinate the synthesis of RNA molecules (Yuan et al., 2005).1.2 The cell cycleThe propagation of all life requires careful regulation of the sequence, timing, and execution of cellular division. Though the specific proteins vary somewhat between organisms, the growth and division of cells follows a generalizable pattern known as the cell cycle. In the first phase of the cell cycle, also called the Gap phase 1 (G1), proteins are synthesized and the cell grows in size. Following G1, before dividing, the entire DNA content of the cell must be duplicated. A cell undergoing DNA replication is said to be in the S (synthesis) phase of the cell cycle. DNA polymerases, in conjunction with coordinating proteins, separate the double-stranded DNA and synthesize a new strand on each, to form two double-stranded molecules (Waga & Stillman, 1998). Each chromosome must be copied in its entirety in a relatively short period of time; organisms with larger genomes must expedite theprocess of DNA replication by allowing duplication to initiate at many different points along the molecule simultaneously (Huberman & Riggs, 1965).Once replication is complete, the cell enters the third phase of the cell cycle, Gap phase 2 (G2). The replicated sister DNA molecules remain tethered to one another by cohesin proteins, which are most abundant at a region known as the centromere (T. Tanaka, Cosma, Wirth, & Nasmyth, 1999). The centromere forms the basis for assembly of the kinetochore, aprotein complex which coordinates attachment to the microtubule spindles responsible for pulling the chromosomes apart (Espelin, Kaplan, & Sorger, 1997).When the cell is prepared to divide, the mitotic (M) phase of the cell cycle begins. In mitosis,chromosomes first condense (prophase), and then align at a central axis of the cell 2(metaphase) . Once the attachment of the spindles to kinetochores is made and tension is detected by the kinetochore complex, the spindle assembly checkpoint (SAC) is relieved and sister chromatid cohesion is dissolved, allowing spindles to proceed to pull the sister chromatids apart (Guacci, Koshland, & Strunnikov, 1997; Michaelis, Ciosk, & Nasmyth, 1997). One set of chromosomes is drawn into the daughter cell, and the other set remains in the original, mother cell; subsequently, cytokinesis proceeds, marking the permanent separation of the cellular contents of the two cells. It is critical that chromosome segregation completes before cytokinesis is triggered, as late-segregating chromosomes can become caught between the two cells and sustain tremendous amounts of damage, or fail to enter the daughter cell entirely (S. L. Thompson & Compton, 2008). The abnormal chromosome counts that result from such an event are known as aneuploidy.The coordination of sequential events that drive the cell cycle – the process of growth, DNA replication and segregation, and cellular division – can only be accomplished through the cooperation of virtually all cellular components, many of which are responsive to environmental circumstances in some way (Fingar & Blenis, 2004). Further, cells may restrict division as a response to various forms of DNA damage or other stresses, in order to provide time for repair mechanisms to resolve this damage and limit its transmission or intensification through the next division (Gartner, Milstein, Ahmed, Hodgkin, & Hengartner, 2000; Kuerbitz, Plunkett, Walsh, & Kastan, 1992).1.3 DNA mutation, damage, and repairDNA damage – that is, the chemical alteration of DNA molecules – is a considerable obstacleto fidelity of the genetic code. Endogenous DNA damage, particularly via reactive oxygen species (ROS), accumulates as a consequence of cellular respiration by the mitochondria and represent the largest source of DNA damage (Hegde, Hazra, & Mitra, 2009). Exogenous sources include environmental exposures to genotoxic chemicals (e.g. acetaldehyde in cigarette smoke), ultraviolet light, and drugs such as those employed for cancer therapies all cause mutations and, in many cases, DNA damage (Ames, 1989; Löfroth, Stensman, & 3Brandhorst-Satzkorn, 1991; Yan et al., 2006).The systems by which the cell responds to DNA damage are collectively referred to as DNA damage response (DDR) pathways. Base substitutions, insertions, and deletions are handled through the process of mismatch repair (MMR) while bulky damage-inducing lesions, such as adducts and dimers, are handled by the nucleotide excision repair (NER) pathway (Costa, Chiganças, Galhardo, Carvalho, & Menck, 2003; Modrich, 1991). In the case of a double-strand DNA break (DSB), where the chromosome is broken in two, the damaged chromosome can be repaired by the homologous recombination (HR) pathway, which uses the chromosome’s sister chromatid as a template and results in high fidelity repair (Liang, Han, Romanienko, & Jasin, 1998). In cases where no sister chromatid is available, the cell resorts to the use of non-homologous end joining (NHEJ), a process which directly ligates the broken chromosome ends together and often causes new mutations or deletions (Hefferin & Tomkinson, 2005). While NHEJ is the dominating form of DSB repair in human cells, yeast will preferentially utilize HR when a sister chromatid is available (Pâques & Haber, 1999; Sonoda, Hochegger, Saberi, Taniguchi, & Takeda, 2006).Faithful replication, repair, and segregation of DNA are critical to prevent mutations of DNA basepairs. Mutations are the substitution, loss, or gain of one or more DNA bases; this can take several forms. Substitutions may occur between bases of the same family (pyrimidine topyrimidine or purine to purine: “transition” mutations) or between bases of opposite families (pyrimidine to purine or vice versa: “transversion” mutations). In coding sequences, mutations may or may not alter the encoded protein. Due to redundancy in the genetic code, where the third base in each triplet codon often does not alter the amino acid for which it codes, many mutations have no affect at the level of protein production; these are known as synonymous, or silent mutations. It is important to note that while mutations may not affect protein sequence, synonymous mutations may influence mRNA stability and translation, and thus create fitness effects independent of protein alterations (Kristofich et al., 2018; Supek, Miñana, Valcárcel, 4Gabaldón, & Lehner, 2014). Amino acid-altering “missense” (non-synonymous) mutations may have little effect on fitness if they cause a substitution of a chemically similar amino acid, or alter a protein sequence in a disordered area without affecting its function (Thusberg & Vihinen, 2009). However, when focusing solely on non-synonymous mutations, it is estimated that less than 30% have truly neutral fitness effects (Eyre-Walker & Keightley, 2007). If a substitution results in the creation of a new stop codon (a “nonsense” mutation), the translation of the protein will be prematurely terminated. Further, loss or gain of one or more DNA bases can shift the reading frame of the gene, causing a massive change in amino acid sequence and increasing the likelihood of the emergence of a premature stop codon elsewhere in the gene.1.4 Mutation, DNA damage, and evolutionMutations and DNA damage can change the genetic sequence on both small and large scales.Small sequence changes can have profound effects on cellular function if they occur in critical coding regions of genes, or if they alter DNA structure at key regulatory regions (Drummond & Wilke, 2009; Wagner, 2000; Wray, 2007). The fitness consequences of mutations – when there are fitness consequences at all – are almost always negative (Haldane, 1927). However, mutation also provides a variable landscape on which selection pressures may act, which means that an increase in mutation rate will also increase the likelihood that a variant of increased fitness will arise in a given cell population (Loeb, 2011). Although evolution is presented in the context of populations of organisms, these mechanisms of mutation and selection also operate among populations of individual cells in multicellular organisms, and such processes govern the excessive proliferation that defines cancer (Merlo, Pepper, Reid, & Maley, 2006). Evolution of cancer cells involves the acquisition of mutations that benefit the cancer’s growth over that of adjacent cells; the course of such evolution is greatly influenced by contextual selective pressures, as mutations that would otherwise be detrimental from a fitness standpoint may confer advantages in the 5context of chemotherapy or the unique microenvironment created by the tumour itself (Mumenthaler et al., 2015; Silva & Gatenby, 2010).Genes that contribute to the initation or progression of cancerous phenotypes when mutated are referred to as oncogenes or tumour-suppressor genes (Weinberg, 1991). Oncogenes represent gain-of-function mutations that drive proliferation, whereas tumour-suppressor gene mutations are loss-of-function events that remove controls on growth and other cancer processes. Although it is rare for mutation to “improve” upon the function of a protein, a fitness advantage may paradoxically be gained by alterations that increase the risk of further damage (Cahill, Kinzler, Vogelstein, & Lengauer, 1999). This is often the case in cancer cells, which, in addition to increased growth, invasion, and immune evasion, also suffer excessive genetic damage (Hanahan & Weinberg, 2011). This damage not only causes the cells to behave unpredictably and often die, but also propels further evolution among the population of cells, sowing genetic heterogeneity and expanding the fitness landscape on which selection pressures may act. 1.5 Chromosome instability in cancerGenome instability (GIN) is a well-established hallmark of many cancers, imbuing cells withenhanced evolutionary capacity by increasing the potential for sequence and karyotypic changes (Hanahan & Weinberg, 2011). Instability in hereditary cancers often reflects an inherited mutation in one or more DDR pathways, while in spontaneous (non-hereditary) cancers, recurrent mutations in repair pathways are uncommon at diagnosis (Negrini, Gorgoulis, & Halazonetis, 2010). Instead, GIN in spontaneous cancers is hypothesized to be induced by oncogenes. Some oncogenes may drive cancer through the overactivation of proliferative programs that initiate excessive DNA replication forks, leading to depletion of available deoxyribonucleotide triphosphates (dNTPs), and the stalling, collapse, and/or collision of replication forks (and subsequently DSB formation) (Lord & Ashworth, 2012).GIN can be subdivided into microsatellite instability (MIN) and chromosome instability 6(CIN), which induce increases in mutation rate and the rate of aneuploidy, respectively (Geigl, Obenauf, Schwarzbraun, & Speicher, 2008). MIN was first identified by the observedexpansion or contraction of microsatellites, and usually reflects defective repair of replicationerrors (i.e. through deficiencies in the MMR pathway). CIN is characterized by a propensity for whole chromosome gain or loss (i.e. aneuploidy), recurrent breakage events and/or gross chromosomal rearrangements (Fig 1.1) (Pfau & Amon, 2012). Whether a genomic aberration results in the development of instability of whole chromosomes (w-CIN) or structural changes resulting from breaks and/or rearrangements (s-CIN) depends on the nature of the precipitating genome damage (K. Tanaka & Hirota, 2016). For example, loss of proper checkpoint signalling through deletion of a MAD2 allele induces w-CIN through expedited entry to anaphase and chromosome missegregation, an effect that induces tumourigenesis in mice (Michel et al., 2001).The maintenance of chromosome stability requires the proper functioning ofmany pathways, including machinery participating in DNA replication, chromosome segregation, checkpoint control, and DNA repair (Bakhoum & Compton, 2012; K. Tanaka & Hirota, 2016). Accumulated DNA damage, resulting either from increased rate of damage or impairment of damage resolution, can overwhelm systems responsible for stability maintenance and promote a feedback effect whereby additional damage is accrued at higher rates; this is believed to be a precipitating early event in the establishment of malignancy (Sieber, Heinimann, & Tomlinson, 2003). Epigenetic states also affect predisposition to instability, as post-transcriptional modifications are responsible for the propagation of key signalling pathways required for DNA maintenance (Huen & Chen, 2008). In addition to being hallmarks of cancer in their own right, CIN and aneuploidy are now recognized to exacerbate one another (Potapova, Zhu, & Li, 2013). CIN-induced events may further intensify the CIN phenotype: for example, chromosome breaks may result in re-incorporation of the broken fragment elsewhere in the genome, which can alter gene expression and cause subsequent damage on the receiving chromosome (Bunting & 7Nussenzweig, 2013). Breaks can also cause loss or retention of DNA fragments through the process of cell division, and mitotic errors can lead to formation of damage-prone micronuclei (chromosomes and fragments that are not incorporated into the nucleus) (Crasta et al., 2012). Aneuploidy has been demonstrated to have both tumour suppressive and oncogenic roles, and its influence on fitness may have a substantial relationship with the severity of aneuploidy and stage of cancer development (Weaver, Silk, Montagna, Verdier-Pinard, & Cleveland, 2007). More recently, CIN has been connected to late-stage cancer phenotypes, both as a contributor to metastatic potential and consequence of local tissue architecture (Bakhoum et al., 2018; Knouse, Lopez, Bachofner, & Amon, 2018). Due to the inherent complexity of such effects, the cellular circuits that sustain these phenotypes remain to be fully characterized.Extensive research over the past two decades has focused on the exploitation of CIN for cancer therapeutics. Most types of cancer exhibit CIN to some degree, however, methods of detection for CIN in an individual tumour are laborious and often indirect (L. L. Thompson, Jeusset, Lepage, & McManus, 2017). Nevertheless, drugs that exacerbate CIN by promoting instability are currently in clinical trials and show considerable promise. Perhaps the best example of this approach has been the use of poly ADP-ribose polymerase (PARP) inhibitorsfor BRCA-deficient cancers;  BRCA1 or BRCA2 mutations inhibit the HR pathway, and application of PARP inhibitors impairs parallel DDR pathways and greatly enhances cancer cell death (Bryant, Schultz, Thomas, & Parker, 2007). The chemotherapy drug paclitaxel induces instability through stabilizing microtubules, blocking cell cycle progression, and producing free radicals (Branham, Nadin, Vargas-Roig, & Ciocca, 2004; Conklin, 2004; Galletti, Magnani, Renzulli, & Botta, 2007). As well, histone deacetylase (HDAC) inhibitors interfere with DNA damage signalling, leaving cancer cells with mutations in DDR function particularly sensitive to damage that other, healthy cells with functional repair mechanisms can tolerate (J.-H. Lee, Choy, Ngo, Foster, & Marks, 2010; Roos & Krumm, 2016). Together,this indicates that the study of CIN in the context of human cancer is a fruitful realm of research, with great promise for the development of effective therapeutics.81.6 Saccharomyces cerevisiae: an ideal model for investigating CINSaccharomyces cerevisiae (A.K.A. Baker’s yeast, or budding yeast), is a unicellular fungus that has been cultured by humans for millenia; it is perhaps not surprising that it has become one of the best-characterized model organisms. There are many benefits to the use of yeast asa model. With only 12 Mb of DNA and 6,000 genes, sequencing of entire yeast genomes is considerably more affordable than for human cells (Duina, Miller, & Keeney, 2014). Yeast grow quickly, with a doubling time of roughly 90 minutes in rich media, and can be easily cultured as either haploids or diploids, lending them to a variety of genetic manipulations. Finally, while our two species are separated by vast distances of evolutionary time, humans and yeast share a remarkable level of similarity at the protein level: it is estimated that greater than 50% of budding yeast genes have a human homologue, and conversely, roughly 20% of human disease genes have yeast homologues (Forslund, Schreiber, Thanintorn, & Sonnhammer, 2011). Yeast has served as a useful model of human cancer for decades. Classic research performed by Hartwell and colleagues led to the identification of 35 cell division control (CDC) genes, many of which play a role in cancer development (Hartwell, Mortimer, Culotti, & Culotti, 1973). The process of cell division – and the necessary replication and segregation of geneticmaterial – involves many potential points of error, and the ease of studying these processes inthe yeast model system has allowed for the identification of many CIN pathways using a variety of assays.Mutants of RFA1 and RAD27, which code for key DNA replication proteins, exhibit an increased frequency of CIN as assessed by the gross chromosomal rearrangement assay, which monitors the structure of chrV by assaying for loss or retention of marker genes placedon either chromosome arm (Chen and Kolodner, 1999). Chromatin remodelling over the course of the cell cycle plays an important role in maintaining stability, and the chromatin-assembly factor I (CAF-I), which binds PCNA, is required for histone acetylation and induces accumulation of GCRs when its components are mutated (Myung et al., 2003; Kats 9et al., 2006). As well, inactivation of cell cycle regulators such as Cdc14 can induce instability by interfering with timely chromosome segregation (Quevedo et al., 2015). Inadequate repair of DNA-damaging events can also result in genome instability, such as in the case of the MRX complex mutants (Chen & Kolodner, 1999). Broadly speaking, cell cycle components and mitotic machinery are key players in genome stability maintenance, and perturbation of these processes are major contributors to CIN. More recently, and of particular interest to the current project, high-throughput screens using model organisms including Saccharomyces cerevisiae have allowed for comprehensive identification of pathway disruptions that foster CIN, including malfunctions of DNA repair, nuclear transport, proteasome function, RNA processing and degradation, and many others (Chan, Aristizabal, et al., 2014; Stirling et al., 2011). In many cases, the candidate CIN genesappear to act indirectly in their regulation of genome integrity; for instance, mutations influencing the production of iron-sulfur clusters in the mitochondria induce genome instability through impairing the production of iron-sulfur cluster-containing proteins involved in nuclear maintenance (Veatch et al., 2009). Screening approaches can implicate new CIN pathways without a priori assumptions of involvement in genome stability, allowing for the identification of genes without necessarily identifying the mechanism (Stirling et al., 2011). 1.7 CIN induction in RNA processing mutantsMany RNA processing factors have been implicated in genome integrity, and through their influence on many diverse transcripts throughout the cell, mutations in these pathways can induce a host of indirect effects. Mutation of proteins in the nuclear THO/TREX complex, which mediates nuclear export of ribonucleoprotein complexes, induce instability in the formof DSBs and increased recombination rate (Domínguez-Sánchez, Barroso, Gómez-González,Luna, & Aguilera, 2011). Cytoplasmic processing bodies (P-bodies) have been implicated in stability maintenance through their role in the regulation of histone transcripts during stress (Herrero & Moreno, 2011). Thanks to recent screening efforts, many additional RNA 10processing factors have been identified as candidate CIN genes, including proteins involved in splicing, degradation, and 3’ end processing (Stirling et al., 2011). In many cases the mechanism of CIN induction is not immediately clear, and dissecting these effects remains a major ongoing focus in our lab.The most obvious consequence of RNA processing deficiencies would be diverse changes in the transcriptome, many of which could influence stability through effects on cell cycle progression, DNA replication, and mitotic fidelity. For example, a temperature sensitive mutant of RRB1, which codes for a protein that contributes to ribosome assembly, induces CIN in yeast in the form of defective chromosome segregation (Killian et al., 2004). Inadequate mRNA decay can cause damaging transcript accumulation, as was demonstrated in P-body mutants that accumulate YOX1 mRNAs, leading to downregulation of DNA replication stress resistance pathways (Loll-Krippleber & Brown, 2017). Alterations in centromeric transcription are also a potential source of instability, as transcription in these regions facilitates proper assembly of the kinetochore and promote faithful chromosome segregation (Ohkuni & Kitagawa, 2011).One alternate mechanism by which RNA processing defects may induce CIN is by promoting the accumulation of three-stranded nucleic acid structures known as R-loops. These structures typically arise during transcription, when the nascent RNA molecule re-anneals to its complementary template strand, forming a DNA:RNA hybrid and exposing non-template ssDNA (Roy, Yu, & Lieber, 2008). These structures play critical regulatory roles in locations throughout the genome by increasing chromatin accessibility of promoters for transcription, inducing transcriptional termination, and permitting modification by enzymes such as activation induced cytidine deaminase (AID) during class switch recombination in B cells (Sollier et al., 2014). Inappropriate R-loop accumulation can also predispose genetic material to damage (Amon &Koshland, 2016). In addition to increased susceptibility to endogenous mutagens, R-loops may block replication forks leading to single- and/or double-stranded breaks in DNA, 11resulting in mutation and aneuploidy (Gan et al., 2011). A collection of mutants from the CINscreen described above were subsequently screened for R-loop accumulation, and, interestingly, several proteins previously unassociated with R-loops were identified, including several RNA processing and degradation mutants (Chan, Aristizabal, et al., 2014). It was speculated that in these cases, R-loop accumulation may be the underlying cause of CIN in these mutants.The establishment and resolution of R-loops must be tightly regulated in order to prevent excessive accumulation. Co-transcriptional factors such as the THO/TREX complex prevent R-loop formation by sequestering nascent RNA, ensuring proper processing and export (Santos-Pereira, García-Rubio, González-Aguilera, Luna, & Aguilera, 2014). RNaseH is the primary enzyme responsible for resolution of R-loops through its activity in degrading the RNA moiety (Keller & Crouch, 1972). Helicases such as SETX (Sen1 in yeast) appear to participate in unwinding during transcriptional termination to prevent extended RNA residence at the DNA template, while the repair protein BRCA2 may prevent R-loops by enhancing accessibility for key processing factors (Bhatia et al., 2014; Mischo et al., 2011). Surprisingly, the RNA exosome has been implicated as a cofactor of Sen1 at transcription-associated DNA damage sites, suggesting that this complex may degrade the DNA:RNA hybrid similarly to RNaseH (Richard, Feng, & Manley, 2013).1.8 The essential gene DIS3 is a key RNA processing factor with many linksto CINOne of the novel hits in the CIN screen described in Section 1.6 was a temperature sensitive (ts) allele of DIS3, the primary catalytic component of the exosome complex (Dziembowski, Lorentzen, Conti, & Séraphin, 2007). Dis3 is a highly conserved 3'-5' RNA processing gene containing an endonuclease PIN (PilT N-terminal) and exonuclease RNB (RNaseII/R) domain and bears considerable similarity to E. coli RnaseII; the exosome itself has homologyto RNase PH proteins in archaea (Fig 1.2) (Schaeffer et al., 2009; Zuo & Deutscher, 2001). Humans have three homologues – DIS3, DIS3L, and DIS3L2 – which vary in domain 12structure and subcellular location (Lubas et al., 2013; Tomecki et al., 2010).The RNA exosome complex was first described by Tollervey and colleagues in yeast two decades ago (Mitchell, Petfalski, Shevchenko, Mann, & Tollervey, 1997). The human homologue was identified soon after (Shiomi et al., 1998). Over the intervening years, DIS3, and the exosome more broadly, have been implicated in the processing and degradation of many diverse RNA species, including turnover of inadequately polyadenylated (poly(A)) RNAs, degradation of AU-rich element (ARE)-containing mRNAs, and processing of ribosomal RNA (rRNA), small nucleolar RNA (snoRNA), and small nuclear RNA (snRNA) (Allmang et al., 1999; Milligan, Torchet, Allmang, Shipman, & Tollervey, 2005; Mukherjee et al., 2002). Dis3 also participates in kinetochore assembly in Schizosaccharomyces pombe by contributing to pericentromeric chromatin silencing (Murakami et al., 2007). In humans, the exosome complex is involved in targeting of activation induced cytidine deaminase (AID) enzymes to immunoglobulin variable regions in the B cell genome, stimulating somatic hypermutation and contributing to proper lymphocyte maturation (Basu et al., 2011).Also, hDIS3 appears to regulate a subset of miRNAs through its degradation of factors that regulate their expression (Segalla et al., 2015). Most recently, studies in Drosophila melanogaster and Caenorhabditis elegans revealed that Dis3 is a target of CDK1 phosphorylation, and this phosphorylation reduces Dis3’s exonuclease function in the G2 phase of the cell cycle, inducing a cell cycle arrest (Snee et al., 2016). DIS3 mutants suffer from impaired RNA processing, defective microtubule and kinetochore assembly, growth retardation, and temperature sensitivity (Smith, Kiss, Turk, Tartakoff, & Erik, 2011; Tomecki et al., 2014).  Having multiple enzymatic activities, pleiotropic phenotypes upon mutation, and multiple indirect effects on the transcriptome have made the contribution of Dis3 to genome stability difficult to determine.1.9 Multiple myeloma: progression and treatmentMultiple myeloma (MM) is a cancer characterized by the uncontrolled growth of bone 13marrow plasma cells (Fonseca et al., 2014). These cells are typically responsible for the production of antibodies in response to diverse pathogens. Plasma cell progenitors (B cells) diversify their antibody repertoire during maturation through direct modification of the immunoglobulin (Ig) locus (Stavnezer et al., 2008). MM is a genetically heterogenous neoplasm responsible for 10-15% of all blood malignancies, and is characterized by activation of MYC, KRAS, NRAS, and FGFR3 in addition to a host of recurrent aneuploidies, including loss of 13q14 and 17p13 (Chapman et al., 2013; Lionetti et al., 2015; Weißbach et al., 2014). In many cases, activation of the aforementioned pathways is driven by recurrent translocations that place these oncogenes under control of the strong IgH promoter, increasing their expression and driving cancer growth (Weißbach et al., 2014; Morgan et al., 2012).The precursor to MM is a condition known as monoclonal gammopathy of unknown significance (MGUS), where a patient’s level of monoclonal immunoglobulin protein is significantly elevated above normal, such that it is detectable by protein electrophoresis (Fonseca et al., 2014). While some chromosomal abnormalities associated with MM are present in MGUS – notably, IgH translocations and 13q deletions – they do not necessarily indicate imminent progression to MM (Kaufmann et al., 2004). Although patients often remain asymptomatic until late-stage disease, early symptoms may include fatigue, dizziness,and paleness (due to anemia), dehydration, thirst, and nausea (due to high blood calcium), excessive bleeding and bruising from minor injuries (due to low platelet counts), as well as bone fragility, weight loss, muscle pain, and numbness (“Symptoms of multiple myeloma”, n.d.). Patients eventually progression to “smoldering phase”, a further (often asymptomatic) stage where monoclonal protein in the serum and risk of progression rise substantially (Kyle et al., 2007). Once MM develops, it can be classified into either hyperdiploid MM (HDMM) or nonhyperdiploid MM (NHDMM), each characterized by different genetic abnormalities and the latter carrying a significantly worse prognosis (Fonseca et al., 2003). Of particular significance is the deletion of the chromosome arm 17p, which usually includes loss of TP5314and is highly associated with increased aggressiveness and progression (Fonseca et al., 2014). However, the primary defining feature of NHDMM is its high correlation with the presence of IgH translocations, indicating that such translocation events may significantly contribute to poor prognosis in these cases (Fonseca et al., 2003).Typical treatment involves induction therapy with the alkylating agent melphalan, in combination with stem cell transplant when appropriate, and the proteasome inhibitor bortezomib (Cavo, Pantani, & Petrucci, 2012). Therapy may also include lenalidomide, and other thalidomide derivatives; these immunomodulatory agents reduce inflammatory immuneresponses, confer anti-angiogenic effects, and are believed to directly interfere with proliferative signalling driving malignant MM plasma cell growth (Quach et al., 2010). As well, therapy may involve treatment with monoclonal antibodies such as daratumumab, which targets CD38, an antigen frequently overexpression on the surface of MM cells (Lokhorst et al., 2015). More recently, the RNA Pol I inhibitor CX-5461 has been demonstrated to be highly effective in MM cell lines and primary samples, with potent reduction in downstream MYC signalling, and has now entered clinical trials for several cancers including MM (H. C. Lee et al., 2017). Ongoing research is focused heavily on risk stratification of patients based on cytological abnormalities for drug selection (Fonseca, Monge, & Dimopoulos, 2014). If the activation of genome-destabilizing mechanisms negatively influences MM patient outcomes, therapeutic strategies that target ongoing genome instability may prove valuable. Recently, Caracciolo and colleagues demonstrated that MM cell survival can be effectively counteracted by suppression of LIG3, an often hyperactivated gene that appears to support survival in the context of genome instability by promoting DNA repair (Caracciolo et al., 2018). As well, bortezomib has been reported to sensitize MM to PARP inhibitors by interfering with DSB response pathways (Neri et al., 2011). Given the preponderance of evidence suggesting that genome instability-associated events correlate with poor prognosis in MM, it is imperative that we delineate the genetic aberrations that contribute to the emergence of this phenotype. 151.10 Recurrent DIS3 mutations in cancerDelineating the cellular effects of DIS3 perturbation has become of medical importance over the past decade as DIS3 mutations have been identified in roughly 11% of MM cases (Weißbach et al., 2014). DIS3 mutations in MM are often hemizygous, occurring as a point mutation in the context of a deletion of the second allele, and often appear together with KRAS mutations (Lohr et al., 2014). These mutations appear to be clustered in the RNB exonuclease domain (Weißbach et al., 2014).  Sequencing studies focusing on newly-diagnosed patients with plasma cell dyscrasia (including multiple myeloma, as well as primary and secondary plasma cell leukemia) and 20MM cell lines indicated that 18.5% carry DIS3 mutations at diagnosis, suggesting that penetrance of DIS3 mutant alleles may depend on disease stage, treatment history, and particular cytogenetic abnormalities (Lionetti et al., 2015). Indeed, DIS3 mutations are more prevalent in tumours of the aggressive NHDMM subtype (Lohr et al., 2014). Mutations and deletions affecting the DIS3 locus are significantly associated with lower overall survival (Weißbach et al., 2014). As well, these mutations are highly correlated with several recurrent translocations – t(11;14), t(4;14) and t(14;16) – all of which involve the relocation of IgH to genomic loci, inducing overexpression of oncogenes such as MMSET, CCND1, FGFR3, and MAF (Weißbach et al., 2014; Morgan et al., 2012). In a recent study of 1273 newly diagnosed MM patients (the largest whole exome sequencinganalysis of MM to date), 9.98% carried at least one DIS3 mutation, an estimate that matches closely with previously reported prevalence of 11% by studies analyzing smaller sets of MM patient samples exclusively (Weißbach et al., 2014; Walker et al., 2018). In 6.4% of all cases,the tumours exhibited biallelic inactivation of DIS3 – either homozygous deletion of the locus, or loss of one allele in addition to mutation of the second (Walker et al., 2018). The loss of 13q21.33 (at the DIS3 locus) was evident in 38.6% of cases. As well, 69.4% of the identified DIS3 mutations were recurrent and missense, with 14.2% of the DIS3 mutations affected a single codon (R780). Further, the authors once again identified the association 16between DIS3 mutation and non-hyperdiploidy, t(4;14), and t(14;16). Finally, this analysis revealed a novel oncogenic dependency between DIS3 mutation and del13q, implying that loss of 13q – which would include the DIS3 locus – must occur before mutation of the other DIS3 allele (Walker et al., 2018).Mutations arising early in tumourigenesis implicates DIS3 as a potential driver gene in a loss-of-function manner, however the same group also analyzed the DIS3 mutational patternsin these patients using SomInaClust and calculated that DIS3 is likely acting as an oncogene (Van den Eynden, Fierro, Verbeke, & Marchal, 2015). As well, following identification of two isoforms of DIS3 present in human cell lines, researchers then demonstrated a skew towards expression of the longer isoform (which exhibits less PIN domain function) in haematological cancers (Robinson et al., 2018). The preponderance of sequencing data produced over the past eight years contains many potential explanations for DIS3 mutation inMM, but unfortunately, these studies have not been paired with more precise functional investigations into the biochemical consequences of cancer-associated DIS3 mutations.In addition to MM, recurrent DIS3 aberrations have now been detected in AML (mutation) (Ding et al., 2012) and colorectal cancer (overexpression) (Groen et al., 2014), but precise estimations of the contributions of DIS3 alterations in progression and prognosis of these cancers remain to be assessed. 1.11 Research scopeIn screens of essential yeast genes, mutations in RNA processing and degradation geneswere identified as CIN-inducing. The goal of this project was to decipher mechanisms by which Dis3 may influence chromosome stability; particularly, I explore the role of Dis3 in chromosome instability by elucidating the role of this enzyme in mitotic progression. This project has the potential to reveal fundamental principles by which RNA degradation helps tomaintain the genome and suggest roles of DIS3 mutations in multiple myeloma. I will explore this topic by addressing the following Aims:17Aim 1: Characterize instability phenotypes of cancer-associated DIS3 mutants. While previous work has demonstrated that dis3-ts exhibits CIN when tested by the chromosome transmission fidelity (CTF) assay, it remains to be seen if this effect is reproducible in strains bearing cancer-associated point mutations observed in MM. Further, the underlying mechanism of CIN induction has not been tested; preliminary data indicate that genome-destabilizing R-loops accumulate in this mutant, but this has not been demonstrated to contribute to CIN in this particular case. Finally, while a CTF phenotype is most likely produced as a consequence of mitotic fidelity errors, direct testing of the prevalence of aneuploidy in DIS3 mutants has not been carried out. This project attempts to address these gaps through direct testing of cancer-associated point mutations at conserved sites for CIN induction. I then demonstrate that this CIN phenotype isnot due to accumulation of R-loops, and does not correlate with sensitivity to DNA damagingagents. Aim 2: Identify the mechanism of CIN induction through genome-wide analyses and targetedapproaches. The mutation of DIS3 has diverse and pleiotropic effects on cellular function, through this enzyme’s influence on virtually every RNA species in the cell. Unbiased screening approaches offer an opportunity to elucidate pathways that are buffering cancer-associated DIS3 mutations, and therefore implicate DIS3 in previously unrecognized genomestabilizing processes. Given the data produced through Aim 1, I focus specifically on pathways relating to mitotic progression and chromosome segregation.Here, I use genome-wide synthetic interaction screening to identify novel candidate functionsof this enzyme in maintenance of cell cycle control and mitotic fidelity. Interestingly, these point mutations do not influence cell cycle progression; yet, a cell cycle delay is evident in mutants carrying DIS3 on a plasmid, regardless of the gene’s mutational status. Further, thesemutations induce downregulation of α-tubulin, although this phenotype does not correlate with the severity of CIN. I expanded the scope of this analysis to assess aberrant tubulin 18expression as a common feature among the RNA processing hits in the original CIN screen. This effort has allowed me to identify 13 candidate RNA processing mutations that lower expression of α-tubulin, and subsequently, I demonstrate that this expression is not simply a consequence of cell cycle delay.Aim 3: Interrogation of mitotic progression in  DIS3  mutants  .  Having demonstrated genetic interactions between disruption of anaphase components and DIS3 MM-associated point mutations, I have implicated DIS3 in chromosome segregation fidelity. In addition to previous studies investigating mitotic defects emerging as a consequence of DIS3 loss, it remains imperative to demonstrate whether cancer-associated mutations, which do not completely ablate Dis3 function, can also produce such effects. Further, correlation of these phenotypes with the severity of CIN that I have assigned to this set of mutants would allow us to narrow in on which cellular perturbations are relevant in producing the genome-destabilizing events relevant to the context of MM.I demonstrate by live cell microscopy that DIS3 mutants have a functional spindle assembly checkpoint (SAC) as assessed by the frequency at which they escape from drug-induced arrest. However, in the context of kinetochore defects, DIS3 mutation appears to permit mitotic progression and weaken the G2/M arrest induced by the SAC. Further, by fluorescence microscopy assays to probe the function of mitotic spindles in Dis3 mutants, I demonstrate that one DIS3 mutant experiences a slight, though significant, delay in spindle elongation following spindle anchoring at the bud neck in one DIS3 mutant; yet, again, this effect does not correlate with CIN severity and does not appear to be related to cell cycle defects. Finally, I demonstrate that decreased fitness is rescued through growth on non-fermentable media, suggesting not only that DIS3 mutants lack mitochondrial defects, but also that metabolism may play a role in the induction of instability as a consequence of MM-associated mutations. This work demonstrates that MM-associated point mutations in DIS3 induce CIN in yeast through an as-of-yet unidentified mechanism related to cellular metabolism and mitosis.19Figure 1.1 Forms of chromosome instability. Chromosome instability may affect whole chromosomes (w-CIN), involving the gain or loss of whole chromosomes, or may affect the structure of individual chromosomes (s-CIN), involving the loss or rearrangement of chromosome portions.20Figure 1.2 DIS3 conservation and target transcripts. (A) Conservation of DIS3 gene domains between S. cerevisiae and the 3 human homologues. (B) Known nuclear and cytoplasmic targets of DIS3 in eukaryotic cells.212 CHARACTERIZATION OF CANCER-ASSOCIATED DIS3 MUTANTS2.1 IntroductionDIS3 has two catalytic domains – an endonuclease PIN (PilT N-terminal) and exonuclease RNB (RNaseII/R) – and previous work has demonstrated that mutants lacking DIS3 exonuclease function are considerably sicker than their endonuclease-deficient counterparts (Tomecki et al., 2014). As well sequencing data indicates that it is more often the exonuclease domain of DIS3, as opposed to the endonuclease domain, that tends to accumulate mutations in MM (Cerami et al., 2012; Gao et al., 2013). Based upon this evidence, we hypothesized that it is the exonuclease, and not endonuclease, function of DIS3 which mediates its influence on CIN.There are a number of possible mechanisms by which RNA processing mutants can influencegenome stability. Various cellular pathways buffer genome stability directly (e.g. cell cycle checkpoints and repair systems), but genes with seemingly unrelated functions can influence DNA transactions such as DNA repair, replication, or mitosis, if they have an impact on critical cellular processes (e.g. transcription, translation, and cellular energy status). Numerous RNA processing factors have now been implicated in genome maintenance (Chan,Hieter, & Stirling, 2014). I considered two hypotheses to be the most likely explanations for the induction of CIN as a consequence of DIS3 mutation. One model invokes the accumulation of unprocessed RNA leading to R-loops (DNA:RNA hybrids) which impair DNA replication causing DNA damage, as accumulation of these damage-prone structures was previously identified in the DIS3 temperature sensitive mutant (Chan, Aristizabal, et al., 2014). The other model involveschanges in gene expression that dysregulate the expression of proteins functioning in canonical genome maintenance pathways such as DNA repair or mitotic function. Previous 22research has demonstrated that loss of Dis3 activity has a considerable influence on ribosomebiogenesis, cryptic transcript abundance, cellular fitness, and chromatin silencing (Vasiljeva, Kim, Terzi, Soares, & Buratowski, 2008; Schneider et al., 2011; Tomecki et al., 2014, Szczepińska et al., 2015). For this reason, modified expression of one or more transcripts downstream of Dis3 could influence genome stability.I have observed variable growth defects among the DIS3 mutant set established for this project, with dis3-EXO exhibiting the most severe defect, in agreement with previous studies of these domain-inactivating alleles. As well, these mutations induce an increase in A-Like Faker (ALF) event frequency, corresponding to disruption of a reporter locus allowing for aberrant mating behaviour, demonstrating that specific cancer-associated point mutations elicit genome instability phenotypes. Further, in order to test our hypothesis that genome-destabilizing R-loops induce the observed phenotypes, I interrogated the DIS3 mutant strains by chromosome spread; while dis3-ts exhibits R-loop accumulation as noted previously (Chan, Aristizabal, et al., 2014), the DIS3 cancer-associated mutants do not. As well, these mutations do not cause increased DNA damage as assessed by Rad52-YFP foci, and also do not appear to render these cells sensitive to DNA damaging agents. 2.2 Methods2.2.1 Yeast strains and culturingYeast were grown in rich media (containing yeast extract, peptone, and dextrose - “YPD”) or synthetic complete media with appropriate drop-out amino acids at 30°C unless otherwise noted (Sherman, 1991). Strains used in this study are listed in Table 2.1. Additional strains were taken from the collections described below (see Methods: “SGA”).Plasmid and oligonucleotide transformations were performed using a standard lithium acetateprotocol with heat shock (Schiestl & Gietz, 1989). Briefly, strains were inoculated in YPD overnight at 30°C (25°C if the strain was temperature sensitive). The next morning, strains 23were diluted 1/10 and returned to the incubator for 2-4 hours. Cultures were washed with dH2O, then 100mM lithium acetate, before being resuspended in 360 μL L transformation mixture containing polyethylene glycol (PEG) (molecular weight: 3500), 1M lithium acetate,10 mg/ml herring sperm DNA, and 1-2 μL l of undiluted plasmid. Cells were incubated in transformation mix for 30-60 minutes at room temperature, then transferred to a 42°C waterbath for 30 minutes to heat shock (10 minutes if the strain was temperature sensitive). Cells were then pelleted and plated on media with appropriate nutritional or drug selection for the plasmid or genomic integration.2.2.2 Strain constructionThe dis3E729K strain was created with DNA oligo “gBlocks” (IDT) (Appendix 1). First, an internal DIS3 primer (PB2.08), paired with a URA3-flanking primer (PB2.09), were used in PCR amplification of wildtype DIS3 carried on the plasmid SB221 (Ben-Aroya, Pan, Boeke, & Hieter, 2010); this produced an amplicon containing the 3’ end of DIS3 and the entirety of URA3 (“3’ DIS3 + URA3”) (Appendix 1). Next, I designed gBlocks carrying sequence homologous to a portion of DIS3, containing thetwo most recurrent mutations identified by Weißbach et al.: g2540a (dis3R847K, the conserved site of hDIS3R780K), g2185a (dis3E729K, the conserved site of hDIS3E665K). Additionally, I designed a gBlock to create the g1651a point mutation to ablate the exonuclease domain activity of DIS3 (dis3D551N, the conserved site of hDIS3D488N). Amplicons were joined by “stitch” PCR using platinum HiFi Taq polymerase (Invitrogen). Briefly, the template produced by amplification of SB221 was mixed in equimolar amounts with the gBlock, and the two templates were amplified together in the presence of a DIS3 internal primer (PB2.22,specific only to the gBlock) and a reverse primer (PB2.23, specific only to the SB221-produced amplicon) containing an additional 50 bp of sequence homologous to the 3’ untranslated region (UTR) of DIS3. Integration of the two templates was verified by gel electrophoresis and the band was purified using a QIAquick gel extraction kit (Qiagen).24The PCR construct was transformed into wildtype BY4741 MATa cells using a standard lithium acetate protocol with heat shock (see Methods 2.2.1). The strains were confirmed by nutritional selection and sequencing of the DIS3 gene (Genewiz). Primers used in this PCR approach can be found in Table 2.2.Often, sequence verification revealed the presence of synonymous or non-synonymous point mutations, in addition to those introduced by the gBlock. After repeated attempts to create allthree DIS3 mutants, only dis3E729K was able to be constructed without unintentional mutation at other residues. Nonsynonymous mutations could influence stability or activity of the DIS3 enzyme, while synonymous mutations could have consequences on mRNA stability or translational efficiency (Kristofich et al., 2018). For this reason, mutants carrying additional point mutations were abandoned and we chose to pursue dis3E729K in addition to the strains described below.The pWT, dis3-EXO (dis3D551N) and dis3-ENDO (dis3D91N, E120Q, D171N, D198N) mutants are carried on plasmids which were kindly provided by Dr. Claudia Schneider (Schneider, Leung, Brown, & Tollervey, 2009). To create these strains, the pRS316-URA3-DIS3 plasmid (carrying wildtype DIS3) (“KM-B2”) was first transformed into BY4741. Transformants were plated on selective media. Meanwhile, the KanMX cassette was amplified from pFA6a-kanMX6 (BPH481) using KanMX primers with 50bp homology to the 5’ and 3’ flanking regions of DIS3 (PB2.74 + PB2.75). This amplicon was transformed into the KM-B2-carrying cells, and transformants were selected on media containing geneticin (G418). Deletion of the genomic copy of DIS3 was confirmed by PCR and by inviability on media containing 5-fluoroorotic acid (5-FOA). This strain was kept as “pWT”. Next, the cells were transformed with either pRS315-LEU2-dis3-(D551N) (“KM-B3”) or pRS315-LEU2-dis3-(D91N, E120Q, D171N, D198N) (“KM-B4”); in both cases, transformants were plated on selective media, then moved to media containing 5-FOA for counter-selection against KM-B2. Viable colonies were restruck and verified by retesting their genotypes on selective media for nutritional and drug markers.252.2.3 Spot assays For spot assays, liquid cultures were grown in selective media at 30°C overnight (or 25°C fortemperature sensitive strains), diluted to an optical density at 600nm (OD) of 0.6 in the morning, and serially diluted in YPD in 96-well plates. Liquid was transferred to the indicated media plates using a spot tool and plates were incubated at the indicated temperatures for 2-4 days prior to scanning. 2.2.4 Live cell fluorescent microscopyFor Rad52-YFP and Lsm1-GFP (P-body) imaging, indicated strains were grown overnight at a permissive temperature in either complete media (in the case of strains carrying drug selection markers) or appropriate drop-out selection media (in the case of strains carrying nutritional markers). The next day, the overnight cultures were diluted 1/10 and imaged after 1.5 hours, or shifted to the indicated temperatures for 2 further hours prior to imaging. Cultures were mounted on concanavalin-coated slides and imaged at 100x magnification on aLeica Dmi8 microscope using Metamorph software (Molecular Devices) and the appropriate fluorescent filter set. Final images were scored using Image J (rsbweb.nih.gov/ij/) as described (Stirling et al., 2011). A minimum of 98 cells per replicate, >400 in total across all replicates were counted, imaged in DIC and YFP (for Rad52-YFP) or GFP (for Lsm1-GFP) channels.2.2.5 Chromosome spreadsFor chromosome spreads, log-phase cultures incubated at 30°C were spheroplasted with 200 μL g/mL zymolyase-20T (final) for 45 minutes at 37°C, treated with 4% paraformaldehyde and1% lipsol, and manually spread onto glass slides. The following day, slides were incubated for 30 minutes in blocking buffer (5% BSA, 0.2% milk in PBS) at room temperature in a humid chamber (which was also used for all subsequent incubation steps). Immunostaining was performed with S9.6 antibody (Kerafast) diluted in blocking buffer (1 μL g/ml final) for 1 26hour at 25°C. Slides were washed with PBS and incubated with a goat anti-mouse Cy3-conjugated secondary (Jackson ImmunoResearch 115-165-003) diluted 1:1000 in blocking buffer for 1 hour at 25°C. Slides were washed, mounted with 100 ng/ml DAPI in Vectashield mounting media (Vector Laboratories H-1000), and imaged as described above in DAPI and Cy3 channels. A minimum of 115 cells per replicate and 400 cells in total across all replicateswas counted.2.2.6 A-Like Faker assayFor quantitative A-like faker (ALF), 9 independent colonies of each MATα mutant strain were inoculated overnight at permissive temperature in synthetic complete media. The next day, 100 μL l of the saturated overnight cultures was mixed with 300 μL L of a MATα mating tester strain, centrifuged at 3000 rpm for 3 minutes, and resuspended in 100 μL l distilled water. These MATα mixtures were then spotted on synthetic media lacking all supplements and only permitting prototrophic mated progeny to form colonies (Novoa, Ang, & Stirling, 2018). As well, the saturated overnight cultures were diluted by 1/100,000 and plated on YPD to ascertain colony viability. Plates were incubated at 30°C, and colonies counted once visible (typically after 3-4 days). Frequencies were calculated by dividing the number of colonies on depleted media by the colony count on YPD (which was multiplied by the dilution factor).2.3 Results2.3.1 Strain constructionI sequenced the dis3-ts allele to investigate temperature sensitivity with respect to Dis3 activity and found that dis3-ts carries 10 non-synonymous variants throughout the length of the gene (Figure 2.1a). As a result, it is difficult to ascribe CIN phenotypes in this allele to any particular Dis3 domain or activity. In addition to the dis3-ts allele identified as a candidate CIN hit, I have created three 27additional mutants and one control strain for the purposes of this study (Figure 2.1a). First, I introduced one MM-associated mutation to S. cerevisiae, dis3E729K, that was identified as a recurrent mutation orthologous to human hDIS3E665K (Weißbach et al., 2014). This mutation was additionally interesting to us as it is estimated to be highly deleterious by in silico estimates using the PredictSnp software, a computational method for predicting the functional impact of amino acid variants (Bendl et al., 2014). I also attempted to create one additional mutant, dis3R847K; however, after repeated attempts to introduce this mutation by a variety of approaches, I was unable to isolate mutants that did not carry additional unintended mutations in the DIS3 gene. The difficulty in generally producing single point mutants by standard methods represented a considerable progress delay, and for this reason, we were forced to abandon attempts to attain additional genomically integrated DIS3 mutants. In addition, integrated alleles obtained from other groups (Tomecki et al., 2014) also contained unreported secondary mutations when resequenced, suggesting that thisis a general problem with constructing Dis3 mutants for an unknown reason.In addition to the dis3-ts and dis3E729K alleles, I also employed two control strains bearing mutations that inactivate either the endonuclease (dis3-ENDO; D91N, E120Q, D171N, and D198N), or the exonuclease (dis3-EXO; D551N) domains of DIS3 (see Methods section: 2.2.2) (Schneider et al., 2009). Due to ongoing difficulties creating precise point mutations ina genomic context, these strains carry the mutant DIS3 allele on a plasmid with the genomic copy of DIS3 deleted; for this reason, a plasmid-borne version of wildtype DIS3 is used as anadditional control. 2.3.2 Allele characterization In order to compare general fitness of the DIS3 mutant strains, I prepared a spot dilution assay on YPD plates. After 2 days, there were notable differences in the growth rates of thesestrains (Figure 2.1b). First, the dis3-ts strain exhibits the predicted temperature sensitivity at 34ºC and 37ºC, presumably due to misfolding of Dis3 at these temperatures. As expected, and in agreement with previous studies (Tomecki et al., 2014), dis3-EXO suffers from severe 28growth defects at all temperatures, while dis3-ENDO appears to maintain near-wildtype growth under all conditions. Comparing the growth of these strains to dis3E729K revealed that dis3E729K exhibits a considerable temperature sensitivity. These data suggest that temperature sensitivity could be a feature specific to mutations that alter DIS3 exonuclease activity and provide a set of DIS3 alleles for characterization of genome maintenance. It is notable that dis3-EXO also corresponds to a recurrent mutation observed in multiple myeloma (Lionetti etal., 2015).It should be noted that I originally observed growth differences between the dis3-ts MATa, which was received from the Hieter lab, and dis3-ts MATα, which I created through backcrossing the MATa to wildtype (Figure 2.1b). The appearance of suppressor colonies canindicate several things; a reversion, an unlinked secondary mutation, or the presence of a second strain in what should be a monoculture of dis3-ts. In order to distinguish between these possibilities, I picked single dis3-ts MATa suppressor colonies and backcrossed them towildtype, and tested the progeny by spot assay again to see if robust growth at high temperatures segregated with the URA3 marker linked to DIS3 (Figure 2.2). In every case, the strains retained their high temperature viability, as well as viability on uracil-depleted media (data not shown), indicating that the phenotype is likely a reversion at the DIS3 locus. However, with so many mutations in dis3-ts, it is unlikely that this strain has reverted to wildtype. Instead, we presume one or more of the more deleterious dis3-ts mutations reverted, relieving it of its temperature sensitivity. Subsequent experiments were performed with strains that were not suppressed, where temperature sensitivity was clearly retained.Given Dis3’s extensive roles in RNA processing and degradation, reduction of function mutations would have diverse consequences on the transcriptome. Notably, a defect in RNA degradation should induce transcriptional stress and cause an increased reliance on cellular pathways buffering such effects. Stress is known to induce requirements for a parallel RNA degradation activity by cytoplasmic Processing-bodies (P-bodies), which are responsible for the sequestration and degradation of RNA species (Teixeira, Sheth, Valencia-Sanchez, Brengues, & Parker, 2005; Yoon, Choi, & Parker, 2010). To quantify the emergence of 29transcriptional stress in DIS3 mutants, I assayed for the accumulation of P-bodies by foci formation of a core P-body component, LSM1, tagged with GFP. Fluorescent imaging revealssignificant P-body accumulation in all of the DIS3 mutant strains tested (Figure 2.3a). If P-body function is important to help dis3-mutant cells survive loss of P-bodies should significantly reduce fitness. Consistent with this idea, when we additionally deleted LSM1, we found that the dis3-ts and dis3E729K fitness defects were greatly enhanced (Figure 2.3b). Together these data establish a new mutant system to test partial dis3 loss of function using a single integrated point mutant.2.3.3 DIS3 mutants exhibit an increased frequency of A-like faker eventsIn the original CIN screen, the dis3-ts allele was identified as a CIN hit through its chromosome transmission fidelity (CTF) phenotype. In order to assess if CIN is also exhibited by mutants carrying MM-associated mutations, and to explore the nature of this phenotype further, I performed a quantitative A-like faker (ALF) assay which tests for disruption of the MAT locus on chromosome III (ChrIII) (Figure 2.4a). This assay is described in further detail below. In accordance with previous data, dis3-ts also exhibits CIN by this assay (Figure 2.4b). Additionally, two other mutants – dis3E729K and dis3-EXO – produce significantly more ALF colonies than either wildtype control. In the case of dis3-EXO, the frequency of these events is considerably higher than any other strain. While it is unclear why CIN is so amplified in dis3-EXO, note that this allele completely ablates the exonuclease activity and is more penetrant in other assays, such as fitness.The dis3-ENDO strain also exhibits a significant increase in event frequency when comparedto the pWT strain; however, this significance vanishes in comparison to the true WT strain. Closer inspection of the data indicate that the pWT dataset contains multiple replicates that had a frequency of “0”, which, although it reflects the true values obtained in experiment, make the calculations of frequencies less accurate. It is more likely that the true values for these replicates were simply below the detection limit of the experiment – a hypothesis further strengthened by the fact that in many cases, WT would produce 1-2 colonies per 30replicate. For this reason, we conservatively settle with the null hypothesis in this case, where dis3-ENDO is not significantly different from WT in respect to ALF phenotypes.While a significant increase in ALF frequency caused by changing a single amino acid in DIS3 is compelling, it does not elucidate the precise mechanism by which instability occurs, as the ALF assay captures several different forms of CIN (Figure 2.4a). The MAT locus is located on ChrIII, which also has two silent mating loci (HML and HMR), one on the distal end of the left and right chromosome arms respectively. If the MATα locus is the site of a double strand DNA (dsDNA) breakage event, the HMR locus (which is a silenced copy of MATa) has sufficient homology that it may serve as a template for homologous recombination (HR), effectively causing conversion of the MAT locus from α to a. Due to theabsence of HO endonuclease in S. cerevisiae laboratory strains, this gene conversion event can only occur as a consequence of chromosome damage. Additionally, loss of the MATα locus will reprogram the cell to a MATa transcriptional program, rendering it susceptible to the pheromone α-factor. Under these conditions – which can occur either due to large genomic rearrangements, deletions, or loss of ChrIII in entirety – the cell will mate with a MATα cell to produce a sterile diploid. Finally, recent evidence demonstrates that 3% of all random aneuploidy-induced karyotypes – including those events affecting chromosomes other than ChrIII – induce loss of silencing at silent mating loci (Mulla et al., 2017).Finally, to further characterize this set of DIS3 alleles, I exposed the strains to a range of stresses, including DNA damaging agents (methyl methanesulfonate, “MMS”), disruptors of DNA replication (hydroxyurea, HU), a nucleotide poison (5-fluorouracil, “5-FU”), a topoisomerase poison (camptothecin), and microtubule poisons (benomyl and nocodazole). Asummary of these results is shown in Table 2.3. Surprisingly, DIS3 alleles had similar sensitivity to wildtype, or exhibited slight resistance to these stress treatments. 2.3.4 The dis3-ts mutant accumulates R-loops, but not associated damageOne mechanism of CIN in RNA processing mutants that could lead to an ALF phenotype is 31the accumulation of DNA:RNA hybrids in genomic DNA called R-loops (Gómez-González et al., 2011). Indeed, previous work has found that the exosome accessory complex TRAMP, and the alternative catalytic subunit Rrp6 are involved in suppressing R-loop associated CIN (Gavaldá, Gallardo, Luna, & Aguilera, 2013; Luna et al., 2005). I assessed R-loop levels by preparing chromosome spreads of each strain, and staining with the DNA:RNA hybrid-specific antibody, S9.6 (Wahba, Amon, Koshland, & Vuica-Ross, 2011). While this assay confirmed the previously reported R-loop increase in dis3-ts, I did not see significant levels of R-loops accumulate in the other mutants (Figure 2.5). Thus, R-loop increases do not correlate with the CIN phenotype measured by the ALF assay. R-loops typically lead to double strand breaks and hyper-recombination due to interference with DNA replication forks (Chang & Stirling, 2017). Indeed, R-loops or oxidative stress, which has previously been observed in DIS3 mutants (Tsanova, Spatrick, Jacobson, & van Hoof, 2014), could increase the frequency of DNA breaks requiring homologous recombination for repair leading to CIN (Prado & Aguilera, 2005; Ragu et al., 2007). To test this I measured the frequency of Rad52-YFP foci in the DIS3 alleles. This analysis showed no increase in Rad52 foci, suggesting that mutant-induced DNA damage is not a likely cause of genome instability (Figure 2.6). Indeed, this is consistent with the lack of any sensitivity togenotoxic chemicals which damage DNA (Table 2.3; i.e. MMS, HU, camptothecin).Again, the data indicated a significant increase in one of the plasmid-bearing mutants – in this case, dis3-EXO – however, this was only in comparison to the pWT strain, and appears to be mediated by a decrease in foci formation in pWT relative to the WT. Comparison of WT to dis3-EXO indicates no significant change in Rad52-YFP foci, and therefore, I conclude that none of the DIS3 mutant strains exhibit a Rad52 foci increase.2.4 DiscussionThe dis3-ts, dis3E729K, and dis3-EXO mutants exhibit significant instability by ALF, but this phenotype does not correlate with sensitivity to DNA damaging agents, Rad52-YFP foci 32formation, nor R-loop accumulation. Given the lack of DNA damage indicators, I conclude that the ALF phenotype is likely produced as a consequence of ChrIII loss. Taken together, these data indicate that the R-loops observed in dis3-ts are neither a general phenotype of DIS3 mutants, nor damage-prone, and are unlikely to explain the presence of CIN. Thus, the CIN phenotype is more likely mitotic in nature, resulting in aneuploidy and not dsDNA breaks. 2.4.1 Cancer-associated DIS3 mutations induce aneuploidy in S. cerevisiae. Given that dis3-ts, dis3E729K, and dis3-EXO all induce ALF phenotypes, and all carry mutations in the exonuclease RNB domain, CIN appears to be a general consequence of disruption of exonuclease activity in DIS3. While dis3-ENDO appears to have an ALF phenotype when compared versus pWT, this effect vanishes in statistical analyses that use the unmodified WT strain as its control; further, pWT exhibits a significantly lower ALF frequency than WT, indicating that the plasmid has some effect on the rate of these events occurring. Indeed, complete ablation of endonuclease activity by the dis3-ENDO mutations has no effect on cellular fitness as assessed by the assays described above. Notably, the two additional DIS3 homologues in humans, DIS3L and DIS3L2, both lack PIN domain function (Tomecki et al., 2010).It remains possible that the pWT strain does, in fact, have a substantially lower ALF frequency than WT. The copy number of the DIS3-carrying plasmid is unknown in these strains, and may influence chromosome stability in unpredictable ways. Indeed, even low-copy CEN plasmids can vary between 2 and 5 copies per cell (Karim, Curran, & Alper, 2013). Further, because DIS3 (and thus, the plasmid carrying it) would be essential in these cells, it is possible that the same genomic events that would lead to an ALF phenotype could cause loss of the plasmid, and kill the cell before it has the chance to mate. However, given our ability to read out ALF phenotypes in dis3-EXO and dis3-ENDO, this possibility seems unlikely.33The lack of Rad52-YFP foci accumulation in these MM-associated strains suggests that DIS3mutants experience whole chromosome CIN (w-CIN), and not structural CIN (s-CIN) involving DNA break events. It is tempting to compare the nature of CIN described in this study versus that observed in MM; however, while aneuploidy is detectable in 90% of MM cases, this disease is also characterized by many recurrent translocations and therefore wouldexhibit a significant increase of DNA breakage events as well (Drach et al., 1995; Fonseca et al., 2003). Undoubtedly the instability present in MM is a multifactorial phenotype, on whichDIS3 mutations, as well as many other cellular pathways, exert influence. Moreover, the human genome and transcriptome are much more complex than those of yeast and CIN phenotypes associated with human DIS3 mutants, if any, may manifest differently than in yeast.Although I did not observe DNA double strand break events by Rad52-YFP foci formation, itremains possible that DIS3 mutations cause CIN through increasing the rate of break formation. Microscopic foci analyses have a low sensitivity of detection, requiring the quantification of many individual cells in order to accurately distinguish between small, yet significant shifts in frequency. It is possible that my analysis was simply unable to capture such increases; however, how these small changes could exert the magnitude of stability effects seen in dis3-EXO is difficult to envision. Further, because this analysis involved calculating a frequency of Rad52-YFP foci among the total cell population in asynchronous culture, any delay in cell cycle progression could influence the counts – Rad52 foci typically form in S- or G2/M-phase cells. Nevertheless, other groups have reported such instability in DIS3 mutants. A temperature sensitive DIS3 mutant in S. pombe was demonstrated to carry abnormally small ChrIII as assessed by pulsed-field gel electrophoresis (S.-W. Wang, Stevenson, Kearsey, Watt, & Bähler, 2008). The authors speculate that loss of rDNA repeats on S. pombe ChrIII account for this shift in band size; such a phenotype would require the formation of DSBs. It remains unclear if this rDNA repeat contraction is specific to S. pombe and I did not assay for this phenotype in the context of this project.342.4.2 R-loop accumulation is a feature of some DIS3 mutants, but does not elicit DNA damage.Previous work has demonstrated R-loop accumulation in the dis3-ts mutant used in this study(Chan, Aristizabal, et al., 2014; Stirling et al., 2011). While R-loop accumulation is an attractive explanation for CIN induction, this phenotype is only apparent in dis3-ts: therefore,it does not correlate with the CIN phenotypes exhibited by dis3E729K and dis3-EXO by ALF. Further, R-loop accumulation would be expected to induce CIN primarily through inducing DSBs as a consequence of replication fork collisions (Domínguez-Sánchez et al., 2011). While an increase in R-loop formation or retention is interesting and may have influence on the CIN phenotype in dis3-ts, we chose not to pursue it further, as it does not appear to have relevance to our primary aim: to elucidate CIN induction in MM-associated mutants.It is possible that the R-loops in dis3-ts do not contribute to CIN at all. Recent research has demonstrated that R-loops will not induce recombination in the absence of histone H3S10 phosphorylation, indicating that the “error-prone” nature of R-loops may have less to do withtheir structure, and more to do with subsequent effects on local chromatin state (García-Pichardo et al., 2017). However, conditional knockouts of exosome components in mice demonstrate an increase in both H3S10phos, as well as R-loop formation (Pefanis et al., 2014). Importantly, the interaction between DIS3 and R-loops remains an important realm of inquiry, independent of the research questions addressed in this thesis. R-loops appear to playan important role in the targetting of activation induced cytidine deaminase (AID), which acts on ssDNA in the class switch recombination and somatic hypermutation responsible for B cell differentiation (Gómez-González & Aguilera, 2007; Yu, Chedin, Hsieh, Wilson, & Lieber, 2003). The exosome is believed to participate in AID targetting to the template strandof these regions by degrading the RNA moeity of the R-loop, although evidence for direct processing of R-loops by the exosome complex has yet to be demonstrated (Basu et al., 2011;35Laffleur, Basu, & Lim, 2017; Pefanis et al., 2014). A recent paper identified a direct physical interaction in immortalized B cells between DNA:RNA hybrids and a number of exosome components, including EXOSC3, EXOSC6, DIS3 and DIS3L (I. X. Wang et al., 2018). Given that DIS3 mutations are present in a significant percentage of MM, which is a plasma cell cancer, the link between the RNA exosome and R-loop formation is likely to be relevant and should be explored further in the context of a mammalian cell system.2.4.3 Implications of expression of DIS3 from plasmid-borne alleles.Use of plasmid-borne alleles was an unfortunate consequence of issues in construction of genomic DIS3 mutants at the inception of this project. However, such alleles have been used with success by other research groups, and broadly speaking, their influences on S. cerevisiae fitness and its transcriptome seem to align with those described by laboratories using genomically integrated mutant alleles (Schneider et al., 2012; Gudipati et al, 2012; Tomecki et al., 2014). For this reason, and bolstered by the availability of a plasmid-borne wildtype control, I chose to include these alleles in the mutant collection. Unfortunately, it appears that the presence of the plasmid likely influences CIN-relevant mechanisms as investigated by the approaches described above, as the plasmid-borne wildtype exhibits a significant reduction in CIN by the ALF assay.While the plasmids used in this study are designed to be maintained faithfully at low copy number, there remains a possibility that multiple copies could be stably propagated in a givenstrain. There are multiple potential mechanisms by which DIS3 overexpression, as a theoretical consequence of the plasmid-based expression system, could influence Dis3’s activity in the cell. First, while there have been no confirmed roles for Dis3 independent of the exosome complex, this enzyme does have activity in vitro independent of other core components, and therefore an increased number of Dis3 proteins could be functional and exert a dominant effect within the cell (Dziembowski, Lorentzen, Conti, & Séraphin, 2007). As well, an overabundance of Dis3 protein may interfere with exosome assembly; however, given the essential nature of this complex and the lack of negative consequences on growth 36in the pWT strain, this seems unlikely. Finally, in addition to high copy number, the converse is also problematic: expression of DIS3 from a plasmid requires that the plasmid is maintained, and loss of the plasmid could feasibly influence some experimental results. However, I consider this possibility extremely unlikely for a number of reasons. First, fitness of the pWT strain is comparable to WT, indicating it grows and divides robustly (Figure 2.1b). As well, as part of the plasmid shuffle protocol I used to establish the plasmid-borne strains, I confirmed integration of the KanMX cassette at the genomic DIS3 locus following transformation with the pWT plasmid by plating for viability on plates containing 5-FOA, which counter-selects against the URA3-marked pWT plasmid (see Methods section 2.2.2). The pWT strain was consistently inviable under these conditions, confirming that the plasmid, as a consequence of carrying an essential gene, must be maintained for pWT cells to survive. Therefore, loss of plasmid would be unable to produce CIN phenotypes captured by the ALF assay due to inviability.37Figure 2.1 Characterization of DIS3 separation-of-function, cancer-associated and temperature sensitive alleles. (A) Structure of major DIS3 domains, with the non-synonymous mutations in dis3-ENDO, dis3-EXO, dis3E729K, and dis3-ts indicated. Red flags indicate mutations predicted to be deleterious by PredictSNP; blue flags indicate predicted neutral mutations (Bendl et al., 2014). (B) Ten-fold serial dilution spots of wildtype controls versus DIS3 mutants. Indicated strains were grown in liquid selective media at 30°C overnight (or 25°C for temperature sensitive strains), prepared to equal optical density (OD), then serially diluted. Liquid was transferred to the indicated media, and plates were incubated at the indicated temperature for 2 days prior to scanning.38Figure 2.2 Backcrossing of dis3-ts reduces suppressor production. Ten-fold serial dilutionspots demonstrating temperature sensitivity of dis3-ts (1st row), an isolated suppressor colony(2nd row), and ten independent progeny. The suppressor was isolated by selecting for robust growth at 37°C, crossed with wildtype (PSY154), and sporulated; the progeny represent URA3-marked haploids isolated through dissection of 6 independent tetrads. Indicated strainswere grown in liquid selective media at 25°C overnight, prepared to equal optical density (OD), then serially diluted. Liquid was transferred to the indicated media, and plates were incubated at the indicated temperature for 2 days prior to scanning.39Figure 2.3 P-body accumulation in DIS3 mutants. (A) LSM1-GFP foci in asynchronous cultures visualized by fluorescent microscopy. Samples from actively growing cultures were mounted on concanavalin-coated slides and imaged at 100x magnification. A minimum of 98cells per replicate, >400 in total across all replicates were counted. Arrows indicate representative foci. Error bars indicate SEM. Significance was calculated using the Fisher’s exact test with Bonferroni-Holm p-value correction. (B) Spot dilution assays showing geneticinteraction of dis3-ts and dis3E729K with loss of the P-body component Lsm1. Indicated strainswere grown in liquid selective media at 30°C overnight (or 25°C for temperature sensitive strains), prepared to equal optical density (OD), then serially diluted. Liquid was transferred to the indicated media, and plates were incubated at the indicated temperature for 2 days prior to scanning.4041Figure 2.4 Mutations in the DIS3 exonuclease domain cause genome instability. (A) Schematic of ALF assay. Loss of MAT by gene conversion, deletion or whole chromosome loss leads to α-α mating. Saturated overnight cultures of MATα mutant strains were mixed with a MATα mating tester strain, and then spotted on media selective for prototrophic mated progeny. Plates were incubated at 30°C, and colonies counted once visible (typically after 3-4 days). Sample images of nine mating tests in WT or dis3E729K shown below (parallel viability plates, where each strain was diluted and plated on rich media, are not shown). (B) Observed frequencies of mating in ALF assay for indicated strains. The fold increase over WT is shown above each. Frequencies were calculated by dividing the number of colonies ondepleted media by the colony count on YPD (which was multiplied by the dilution factor). Error bars indicate SEM. Statistics were calculated by parametric unpaired t-test with Welch's correction and Bonferroni-Holm p-value correction.4243Figure 2.5 Detection of R-loop staining in a panel of DIS3 mutant alleles. (A) Immunofluorescent detection of R-loop accumulation by S9.6 on chromosome spreads. Samples from actively growing cultures were spheroplasted and treated with 4% paraformaldehyde and 1% lipsol, then manually spread onto glass slides. Slides were then blocked and immunostained with S9.6 antibody, followed by a Cy3-conjugated secondary, and mounted with DAPI in Vectashield mounting media prior to imaging. A minimum of 115cells per replicate and 400 cells in total across all replicates was counted. Arrows indicate representative foci. (B) Quantification of Cy3 intensity colocalizing with DAPI. Error bars indicate SEM. Significance was calculated by unpaired parametric t-test on pooled data with Bonferroni-Holm p-value correction.44Figure 2.6 DNA damage foci do not accumulate in DIS3 mutants. (A) Live cell fluorescent microscopy of Rad52-YFP and DIC channels in asynchronous cultures visualizedby fluorescent microscopy. Samples from actively growing cultures were mounted on concanavalin-coated slides and imaged at 100x magnification. A minimum of 98 cells per replicate, >400 in total across all replicates were counted. Arrows indicate representative foci. (B) Quantification of Rad52-YFP foci formation. Error bars indicate SEM. Significancewas calculated by Fisher’s exact test with Bonferroni-Holm p-value correction.45Table 2.1 Yeast strains used in this study. Strain ID Genotype SourcePSY153 MATa ura3Δ0 leu2Δ0 his3Δ1 met15Δ0 P. Hieter, University of British Columbia, Vancouver, BC, CanadaPSY154 MATα ura3Δ0 leu2Δ0 his3Δ1 lys2Δ0 P. Hieter, University of British Columbia, Vancouver, BC, CanadaPSYL044 MATa dis3-ts::URA3 can1Δ::LEU2-MFA1pr::HIS3 P. Hieter, University of British Columbia, Vancouver, BC, CanadaPSYL299 MATα dis3-ts::URA3 This studyPSYL1151 MATa dis3E729K::URA3 leu2D0 This studyPSYL1152 MATα dis3E729K::URA3 leu2D0 lys2D This studyPSYL189 MATα rnh1Δ::NatMX rnh201Δ::KanMX This studyPSYL629 MATa dis3Δ::KanMX + pKM-B2 {DIS3-szz-pRS316, URA3, AMP, CEN} This study/C. Schneider, NewcastleUniversity, Newcastle upon Tyne, UKPSYL634 MATa dis3Δ::KanMX + pKM-B4 {dis3-ENDO-(D91N, E120Q, D171N, D198N)-szz-pRS315, LEU2, AMP, CEN}This study/C. Schneider, NewcastleUniversity, Newcastle upon Tyne, UKPSYL635 MATa dis3Δ::KanMX + pKM-B5 {dis3-EXO-(D551N)-szz-pRS315, LEU2, AMP, CEN}This study/C. Schneider, NewcastleUniversity, Newcastle upon Tyne, UKPSYL1156 MATα dis3Δ::KanMX + pKM-B4 {dis3-ENDO-(D91N, E120Q, D171N, D198N)-szz-pRS315, LEU2, AMP, CEN}This study/C. Schneider, NewcastleUniversity, Newcastle upon Tyne, UKPSYL1157 MATα dis3Δ::KanMX + pKM-B5 {dis3-EXO-(D551N)-szz-pRS315, LEU2, AMP, CEN}This study/C. Schneider, NewcastleUniversity, Newcastle upon Tyne, UKPSY279 MATα RAD52-YFP::KanMX ura3Δ0 leu2Δ0 his3Δ1 lys2Δ P. Hieter, University of British Columbia, Vancouver, BC, CanadaPSYL1160 MATa RAD52-YFP::KanMX dis3-ts::URA3 This studyPSYL1161 MATa RAD52-YFP::KanMX dis3E729K::URA3 This studyPSYL1162 MATα RAD52-YFP::KanMX dis3Δ::KanMX + pKM-B2 {DIS3-szz-pRS316, URA3, AMP, CEN} This studyPSYL1158 MATa RAD52-YFP::KanMX dis3Δ::KanMX pKM-B5 {dis3-EXO-(D551N)-szz-pRS315, LEU2, AMP, CEN}This study46Strain ID Genotype SourcePSYL1159 MATα RAD52-YFP::KanMX  dis3Δ::KanMX pKM-B4 {dis3-ENDO-(D91N, E120Q, D171N, D198N)-szz-pRS315, LEU2, AMP, CEN}This studyPSYL1169 MATa dis3E729K::URA3 dam1-1::KanMX This studyPSYL1170 MATa dis3E729K::URA3 spc24 4-2::KanMX This studyPSYL1171 MATα dis3-ts::URA3 dam1-1::KanMX This studyPSYL1172 MATα dis3-ts::URA3 spc24 4-2::KanMX This studyPSYL1154 MATα dis3E729K::URA3 can1Δ::STE2pr-Sp_HIS5 leu2Δ0 his3Δ1 lyp1Δ ura3Δ0This studyPSYL1155 MATα dis3-ts::URA3 can1Δ::STE2pr-Sp_HIS5 leu2Δ0 his3Δ1 lyp1Δ ura3Δ0This studyPSYL1236 MATa DIS3::URA3 This studyPSYL1237 MATα DIS3::URA3 This study47Table 2.2 PCR and qPCR primers used in this study.ID Name Storage Date Sequence (5'-3') Tm Source CommentsPB1.03 KM01 Feb 12, 2014 AAT GGC GTT TTG TAC CAG50.6°C This study Dis3 internal forward primer 808 (for sequencing of DIS3)PB1.04 KM02 Feb 12, 2014 ATG TAG TAT CGA TCC TCC47.2°C This study Dis3 internal forward primer 1617 (for sequencing of DIS3)PB1.05 KM03 Feb 12, 2014 TTG GTT CGT ATC ATG TCG49.4°C This study Dis3 internal forward primer 2410 (for sequencing of DIS3)PB1.06 KM04 Feb 12, 2014 GCC AAC AAC ATA AAT TCT TC47.5°C This study Dis3 internal reverse primer 2198 (for sequencing of DIS3)PB1.07 KM05 Feb 12, 2014 CAC AAA GTG ACC TAA TGG47.8°C This study Dis3 internal reverse primer 1401 (for sequencing of DIS3)PB1.08 KM06 Feb 12, 2014 ACG ATC GTT GGT AAC AAG49.6°C This study Dis3 internal reverse primer 594 (for sequencing of DIS3)PB2.06 KM37 Oct 20, 2014 AAG CAT TAC GTC GTC TTG GA54.1°C This study F Gibson DIS3 WT fragment assemblyPB2.07 KM38 Oct 20, 2014 ACA ATA AGG CCT CTG TTT CAG55.4°C This study R Gibson DIS3 WT fragment assemblyPB2.08 KM39 Jan 15, 2015 CAG AAA GCA CAG AAA CGC CC57.0°C This study 2650F DIS3 internal forward primerPB2.09 KM40 Jan 15, 2015 AAG ATA CGA TTA AGA AAG AAT ATA CAT TTA AAT GTT TTA AAT ACA CCC TGG GCT CGC GAA AGC TTT TTC TTT CCA67.1°C This study URA3 3' UTR + DIS3 3' flanking reverse primer (for stitch PCR fragmentassembly)PB2.22 KM43 Feb 13, 2015 AGG CCA CGA TTG GAA GGC C60.7°C This study DIS3 internal forward for gBlock amplification(for stitch PCR fragmentassembly)48ID Name Storage Date Sequence (5'-3') Tm Source CommentsPB2.23 KM44 Feb 13, 2015 CGA CTA TAC CAT TAT TAA ATA CC46.4°C This study DIS3 3' reverse for gBlock amplification (for stitch PCR fragmentassembly)PB2.29 KM45 Mar 10, 2015 GAA TTG TCA TGC AAG GGC52.0°C Hieter lab URA3 internal F PB2.30 KM46 Mar 10, 2015 GCC CTT GCA TGA CAA TTC52.0°C Hieter lab URA3 internal R PB2.58 KM66 Sep 30, 2015 CTGCAGCGAGGAGCCGTAAT59.9°C Hieter lab KanB internal RPB2.59 KM67 Sep 30, 2015 TGATTTTGATGACGAGCGTAAT52.6°C Hieter lab KanC internal FPB2.64 KM68 Oct 22, 2015 GAATCAACACATCGCTGGAA53.2°C This study DIS3 long flank F (-917bp)PB2.65 KM69 Oct 22, 2015 TCCCGGTTTACTAGAATACGA52.5°C This study DIS3 long flank R (+968bp)PB2.74 KM78 Nov 9, 2015 GATCAAACGAGTTTTATTTATCATACTTGCATCATACAGGCCAAAACAACCACATACGATTTAGGTGACAC67.1°C This study KanMX NatMX HphMX knockout F primer +50bp DIS3 flanking sequence (for targetting)PB2.75 KM79 Nov 16, 2015 GTTATGAATTCCTTTTCGTTTTTATATCCTGATACTGAAGCATCTTCCATAATACGACTCACTATAGGGAG65.6°C This study KanMX NatMX HphMX knockout R primer +50bp DIS3 flanking sequence (for targetting)PB5.04 AT11 Aug 29, 2017 GTCGGTCAAGCTGGTTGTCAGATTGG61.6°C This study TUB1 F (for RT-qPCR)PB5.06 AT13 Aug 29, 2017 GGCCATCTTCTAGATGTCCATCCGGC62.6°C This study TUB1 R (for RT-qPCR)49Table 2.3 Growth behaviour of DIS3 mutant alleles under the indicated stress.Fitness change (relative to wildtype)Temperatures tested Condition (YPD +) dis3-ts dis3E729K pWT dis3-ENDO dis3-EXO25°C, 30°C, 37°C 5-FU 20 μL M 0 0 0 0 025°C, 30°C, 37°C MMS 0.01% 0 0 0 0 025°C, 30°C, 34°C, 37°C HU 100 mM 0 0 0 0 025°C, 30°C, 34°C, 37°C Camptothecin 10 μL g/ml0 0 - - -25°C, 30°C, 34°C, 37°C Nocodazole 4 μL g/ml + 0 0 + +25°C, 30°C, 34°C, 37°C Benomyl 15 μL g/ml + + 0 + +*(0 = no change, - = sensitive, + = resistant)503 GENOME-WIDE CHARACTERIZATION OF DIS3 MUTANTS3.1 IntroductionHints of DIS3’s role in genome stability maintenance have been evident since its discovery. DIS3 was originally identified in a screen of Schizosaccharomyces pombe for temperature-sensitive mutants exhibiting defective sister chromatid segregation (Ohkura et al., 1988). Early work on the Dis3 protein in pombe revealed it to be essential for viability, and further implicated it in mitotic fidelity through its ability to rescue temperature sensitive defects of cell cycle mutants when overexpressed (Kinoshita, Goebl, & Yanagida, 1991). The homologue in Saccharomyces cerevisiae was discovered through its direct interactions with Cnr1/Gsp1/Ran, a RAS superfamily protein involved in nucleocytoplasmic transport and mitotic regulation (Noguchi et al., 1996). There are a number of hypotheses regarding the potential mechanism by which Dis3, and its function in RNA processing and degradation, could exert an influence on mitotic fidelity. In Schizosaccharomyces pombe, the exosome participates in repression of centromere transcription, and subsequently, silencing at this region, which could influence kinetochore function (Murakami et al., 2007). Although the centromeres of S. cerevisiae are markedly different from those of S. pombe, previous work has suggested the importance of pericentromeric transcription in maintenance of stability in budding yeast (Ohkuni & Kitagawa, 2011). It is also possible that mitotic defects are a consequence of the transcriptional changes resulting from DIS3 mutations; RNA sequencing experiments of DIS3 temperature-sensitive S. cerevisiae mutants have revealed upregulation of gene ontology (GO) terms associated with mitosis, spindle assembly, and checkpoint control (Smith et al., 2011). The same group demonstrated that some DIS3 mutants are sensitive to the microtubule-destabilizing fungicide benomyl, accumulate abnormally high numbers of long astral spindles, and display mis-aligned mitotic spindles (Smith et al., 2011).  In order to elucidate the pathways by which DIS3 may exert influence on the cell cycle and 51mitotic stability, I performed high-throughput genetic interaction screening of two mutant strains, dis3-ts and dis3E729K. Paired with expression microarray analysis of dis3E729K, these experiments reveal an overdependence on cellular components governing spindle stability and kinetochore function. This indicated that the DIS3 mutants may have cell cycle defects, however, analysis by budding index revealed that only the plasmid-borne mutant alleles induce cell cycle perturbations, and the observed delay in G2/M is also present for the wildtype plasmid control. To extend the apparent interactions between DIS3 mutation and spindle-related pathways, I performed expression analysis for α-tubulin (Tub1). Although unperturbed at the mRNA transcript level, α-tubulin protein expression is reduced in dis3-ts and dis3E729K relative to wildtype, in contrast to a slight increase in protein levels seen in the pWT, dis3-ENDO, and dis3-EXO strains. I expanded upon this novel finding by screening allof the RNA processing mutants previously identified as candidate CIN alleles by (Stirling et al., 2011) and identify cases of increased or decreased tubulin protein expression. In many cases, downregulation of tubulin expression in RNA processing mutants is not simply a function of cell cycle perturbations, indicating more complex expression alterations that may be related to CIN in these mutants. Together, this data provides evidence for DIS3 functioning to support mitotic fidelity in yeast.3.2 Methods3.2.1 Yeast strains and culturingYeast were grown in rich media at 30°C by standard procedures unless otherwise noted.  Strains used in this study are listed in Table 2.1. Additional strains were taken from the collections described below (see Methods: “SGA”).3.2.2 Spot assays For spot assays, liquid cultures were grown at 30°C overnight (or 25°C for temperature sensitive strains), diluted to an optical density at 600nm (OD) of 0.6 in the morning, and serially diluted in YPD in 96-well plates. Liquid was transferred to the indicated media plates52using a spot tool and plates were incubated for 2-4 days prior to scanning. 3.2.3 MicroarrayMicroarray analyses were run on duplicate samples as described previously (Chan, Aristizabal, et al., 2014). Total RNA was isolated from 1 unit of A600 mid-log phase cells using a RiboPure Yeast kit (A&B Applied Biosystems). Amplification, labeling and fragmentation were performed with Message AmpTMIII RNA Amplification Kit (A&B Applied Biosystems). Microarrays were performed on a GeneChIP Yeast Genome 2.0 (Affymetrix). Hybridization, wash and staining of the arrays were performed using the GeneChip® Hybridization, Wash, and Stain Kit (Affymetrix). The hybridized arrays were scanned with the Gene Chip Scanner 3000 7G (Affymetrix). Expression data was extracted using Expression Console™ Software (Affymetrix) with RMA algorithm. Gene level differential analysis was performed for transcripts that met a fold change cut-off threshold of -2 (downregulated) or +2 (upregulated) using Affymetrix Transcriptome Analysis Console (TAC) Software. Statistical significance was determined by unpaired one-way between-subject ANOVA. For ribonucleoprotein particle (RNP) composition clusters, cluster data were downloaded from reference (Tuck & Tollervey, 2013) and up- or down-regulated genes meeting our cut-off from the microarray were identified in each cluster to create (Fig 3.1).3.2.4 Synthetic Genetic Array (SGA)High-throughput screens were performed using the MATa non-essential gene deletion collection (Winzeler et al., 1999), a ts-allele collection (Z. Li et al., 2011), and the Decreased Abundance by mRNA Perturbation (DAmP) collection (Breslow et al., 2008). All array manipulation was done with a Singer RoToR HDA. Media and steps were modified from (Tong et al., 2004). Query strains were expanded on synthetic drop-out media selecting for the DIS3 allele at permissive temperature, then mated with the collection strains on rich media for one day at 30°C. Colonies were replicated to diploid-selective media plates for oneday; this selection was repeated twice. Arrayed colonies were then replicated to sporulation media and allowed to grow at 25°C for 7 days. Sporulated arrays were expanded on haploid 53selection media in triplicate, and allowed to grow for roughly 30 hours; this haploid selectionwas then repeated a second time. Array plates were then replicated to haploid selective platesthat carried additional selection for the collection alleles (“single selection”) and incubated at30°C for 3 days. Finally, each plate was concurrently replicated to single selection, as well asdouble selection (which also selects for the query allele; in this case, DIS3) and allowed to grow for one further day. Output arrays were scanned as plate images and colony size was analyzed using Balony Software (Young & Loewen, 2013). Candidate hits were selected with a spot size difference (control vs experimental) cut-off of -0.2 and p-value < 0.05. Positive interactions were not validated for the purposes of this study as our protocol does not incorporate a counter-selection step against the query haploids prior to scanning.3.2.5 GO ontology analysisGO analysis was performed using the Generic GO term Finder (http://go.princeton.edu/cgi-bin/GOTermFinder) (Boyle et al., 2011). Fold enrichments were calculated by computing theratio of the number of genes associated with GO term in the hitlist and the number of genes associated with the GO term in the genome using a hypergeometric distribution with a Bonferroni correction. Enriched terms and fold enrichment values were plotted using the web-based ReviGO (Supek, Bošnjak, Škunca, & Šmuc, 2011) to create images in (Figure 3.3). 3.2.6 Budding indicesStrains were grown overnight in complete media, diluted in the morning, and allowed to grow for 2 hours to re-enter log phase. If a temperature shift was used, cells were diluted 1/10 in the morning, allowed to grow for 1.5 hours, then shifted to either 37°C for 2 hours, or25°C for 4 hours (to account for slower growth at lower temperatures). Cultures were mounted on slides coated with concanavalin A (Sigma) and imaged at 100x magnification ona fluorescent microscope (Leica) using Metamorph software (Molecular Devices) and imaged in only the DIC channel (Pemberton, 2014). Final images were scored using Image J (rsbweb.nih.gov/ij/) as described (Stirling et al., 2011). Cells were scored by bud size; “large-54budded” cells represent those with a bud 1/3 the size of the mother cell or greater. A minimum of 105 cells per replicate, 332 in total across all replicates were counted.3.2.7 Western blotStrains were inoculated overnight in complete media at permissive temperature. The next morning, the overnight cultures were diluted 1/10 and equal cell numbers collected after 2 hours, or shifted to the indicated temperatures for 3 further hours prior to collection. For the purposes of the proteogenomic screen for tubulin expression, mutants from the DMA and DAmP collections were cultured at 30°C throughout, while temperature sensitive mutants were cultured at 25°C overnight and shifted to 37°C for 3 hours prior to collection. For synchronization experiments, the cultures were arrested in 3 μL M (final) α-factor (Zymo Research) for two hours prior to collection.Pellets were flash frozen, then resuspended in lysis solution containing 1.85 M NaOH and 7.5% β-mercaptoethanol. Proteins were precipitated with trichloroacetic acid (TCA) and finallysate pellets resuspended in HU buffer (8 M urea, 5% SDS, 200 mM Tris-HCl pH 6.8, 0.1 mM EDTA, 0.5% bromophenol blue) containing 15 mg/mL dithiothreitol (DTT) and stored at -20°C until loading. 20 μL L of each sample was run on a standard SDS-PAGE gel, transferred using a Trans-Blot Turbo transfer system (Bio-Rad), and blocked using 5% milk in TBS-T buffer. Primary antibody (mouse anti-α-tubulin: Invitrogen 32-2500) was prepared at 1:1000 in 5% milk/TBS-T and applied to membranes overnight with rocking at 4°C. Following wash, secondary antibody (goat anti-mouse HRP: Thermo Scientific 31432) was prepared at 1:1000 dilution in 5% milk/TBS-T and applied to membranes for 1 hour at room temperature with rocking. Following final washes, membranes were developed using Pierce ECL western blotting substrates (Thermo Fisher Scientific). All membranes were subjected to ponceau staining; I posit that this is a more reliable loading control in the context of a screen where we expect that expression of many transcripts would be influenced in each mutant. All strains were prepared as lysates twice, and Western blots repeated; blots shown are the second blot for each.553.2.8 Reverse transcription quantitative polymerase chain reaction (RT-qPCR)Strains were inoculated overnight in complete media at permissive temperature. The next morning, the overnight cultures were diluted and equal cell numbers collected after 2 hours. RNA was extracted from flash-frozen pellets using the RiboPure RNA purification kit (Thermo Fisher) and reverse transcribed using a Transcriptor First Strand cDNA Synthesis kit (Roche). The cDNA samples were diluted to 1 μL g/mL and prepared for qPCR with Fast Sybr Green master mix (Thermo Fisher). Analysis was carried out using a StepOnePlus Real-Time PCR System (Thermo Fisher). Primers were designed in-house or adapted from literature where noted, and are listed in Table 2.2.3.3 Results3.3.1 Microarray analysis of dis3E729K reveals diverse effects on the transcriptomeSince the major impact of DIS3 mutation should be on the transcriptome, as has been previously shown for dis3-EXO and -ENDO (Schneider, Kudla, Wlotzka, Tuck, & Tollervey, 2012), I performed an expression microarray on dis3E729K at permissive conditions (30°C). This analysis revealed 227 upregulated and 204 downregulated transcripts according at a 2-fold cut-off (Appendix 2). Surprisingly, GO term enrichment analysis reveals a significant upregulation of metabolic processes, and downregulation of processes involved in cell cycle progression (Table 3.1, Appendix 3). Consistent with Dis3’s role in ribosomal RNA processing, downregulation of rRNA processing components was also observed in this dataset, indicating that loss of Dis3 activity may negatively influence ribosome production.Previous work has defined 10 clusters of RNAs transcriptome-wide based on RNA binding protein profiles (Tuck & Tollervey, 2013). We mapped the dis3E729K up- and down-regulated genes to these 10 RNA clusters (Figure 3.1). Stabilized or upregulated mRNAs were enriched, relative to downregulated genes, in clusters I-IV which represent those that behave like long non-coding RNAs and may be retained in the nucleus (Tuck & Tollervey, 2013). 56Dis3 and Rrp6 are known to have overlapping functions in degrading this type of transcript (Gudipati et al., 2012) so it is logical that they are stabilized in a loss-of-function mutant. Destabilized/downregulated mRNAs were particularly enriched in cluster V and VI, relative to upregulated genes. This was driven by cell cycle regulatory genes (Appendices 2-3) and mRNAs encoding proteins with nuclear functions were previously linked to these clusters (Tuck & Tollervey, 2013).3.3.2 Synthetic genetic array of dis3-ts and dis3E729K  indicates disruption of mitotic regulation through anaphaseAn unbiased way to identify cellular pathways depending on Dis3 function is through geneticinteraction profiling by synthetic genetic array (SGA) (Tong et al., 2004). We predicted that genes in genome maintenance pathways that are buffering specific CIN defects in DIS3 mutants would appear as negative interactions in the SGA data. I profiled both the dis3-ts anddis3E729K alleles since both alleles have CIN phenotypes and grow robustly at 30°C, but also have distinct characteristics (i.e. dis3-ts accumulates R-loops and is inviable at 37°C). I screened these two alleles against both the deletion collection comprised of non-essential gene knockouts and collections of DAmP (Decreased Abundance by mRNA Perturbation) and ts-alleles representing >80% of all essential genes (Breslow et al., 2008; Z. Li et al., 2011; Tong et al., 2004). In total, dis3-ts and dis3E729K had candidate negative genetic interactions surpassing our cut-off with 94 and 99 genes, respectively (Figure 3.2, Appendices 4-7). Gene ontology (GO) term analysis of the dis3-ts hits identified the expected terms related to RNA processing, surveillance and ribosome biogenesis (Figure 3.2a, Table 3.2) (Schneider et al., 2012). Unexpectedly, following p-value correction, microtubule and chromosome localization emerged as the only enriched terms in the dis3E729Kscreen results (Figure 3.2b). This result indicates that the dis3E729K point mutation may interfere with spindle function in some way, as interference with these processes have more significant negative consequences in the context of DIS3 mutation. As well, 19 alleles occurred as candidate hits in both datasets (Figure 3.2c). Some of these genes are ribosome 57components (NOP15, RPL40A), some are related to mitochondrial function (TBS1, ACP1, YOR060C) and several are involved in anaphase progression (SPC34, APC2, SGT1). I validated synthetic sick genetic interactions between dis3E729K and a number of genes that occur as hits in the dis3E729K SGA with spot dilution plating assays (Figure 3.3). Confirmed hits included mitotic mutants influencing the kinetochore (e.g. dam1-1, spc24 4-2, mif2-3), the Anaphase Promoting Complex (apc2-1), and the spindle pole body (cdc31-2). These data show variably mild and dramatic loss of fitness in double mutants between dis3E729K and the indicated alleles. Together these data show that dis3E729K makes cells more dependent on a robust mitotic machinery for survival.3.3.3 Overlap of enriched pathways, but not individual genes, indicates synthetic interactions partially explained by transcriptome alterationsWe predicted that genes whose expression is strongly downregulated in dis3 mutants, while unlikely to be direct genetic interaction partners of dis3E729K – as this would be epistatic – could function in the same pathways as the negative genetic interaction partners. Indeed, while relatively few of the downregulated genes were found in the SGA screens, GO analysisshowed strong enrichments for RNA and rRNA processing, as well as mitotic and cell cycle related processes (Figure 3.4). Thus, downregulation of RNAs with functions in the cell cycle in dis3E729K could account for some of the genetic interactions seen in the SGA screen of the same allele. Given the function of Dis3 in transcriptome regulation, we were gratified to see these functional links between transcriptome changes and the genetic interaction profile. More importantly, these data suggest that mitotic spindle dysfunction could underlie the CIN phenotype of some DIS3 alleles. Previous studies have observed mitotic defects in ts-alleles of DIS3 (Smith et al., 2011), but did not link those defects to the exonuclease domain or to ongoing genome instability.3.3.4 Altered budding index progression in plasmid-bearing DIS3 mutant strainsGiven the significant enrichment of cell cycle-related GO terms in both the SGA and 58microarray datasets, in addition to the evident growth defects in these strains (Figure 2.1b), I wished to determine if MM-associated DIS3 mutations influence cell cycle dynamics. To further characterize the nature of the defects leading to genetic interactions between DIS3 mutant alleles and mitotic regulators, I performed a budding index analysis of all DIS3 mutants in ansynchronous cultures grown at 30°C and 37°C. At 30°C, the dis3-EXO mutant exhibits a significant increase of large-budded cells, corresponding to the G2/M phase of the cell cycle (Figure 3.5a). Notably, both dis3-ENDO and dis3-EXO differ significantly from theWT control strain as well. Interestingly, at 37°C, all of the plasmid-borne DIS3 constructs conferred a significant increase in the proportion of G2/M cells compared to wildtype, including pWT (Figure 3.5b).The dis3-ENDO and dis3-EXO mutants did not significantly differ from pWT, suggesting this effect is entirely a consequence of the presence of the plasmid. As discussed in Chapter 2, phenotypes associated with the plasmids could be due to alterations in DIS3 copy number associated with CEN plasmids.3.3.5 Altered tubulin expression in DIS3 mutantsOne of our primary hypotheses is that DIS3 influences cell cycle regulation through its many regulatory activities impacting the transcriptome. A shift in tubulin expression could perturb spindle dynamics, and indeed, dysregulation of tubulin has been identified as a trigger for cell cycle defects and aneuploidy (Burke, Gasdaska, & Hartwell, 1989). Although the expression of TUB1, TUB2, and TUB3 did not change at the RNA level in the microarray analysis of dis3E729K, tubulin expression changes have been identified in a number of other RNA processing mutants, including previous studies of a DIS3 temperature sensitive allele (Smith et al., 2011). I wished to determine if there was a post-translational shift in expression that correlates with the observed spindle-related defects. I collected lysates from each strain and performed western blotting for α-tubulin (Tub1). The relative expression was assessed qualitatively by 59referencing Ponceau S-stained membranes. We chose to compare loading with Ponceau S staining, as opposed to a western blot of a loading control protein, since we suspect that the mutation of DIS3 influences expression of virtually all proteins through its role in ribosome assembly and therefore a single reasonable loading control protein cannot be assumed. Surprisingly, dis3E729K and dis3-ts appear to have reduced expression of α-tubulin, while the plasmid-borne DIS3 mutations exhibit normal α-tubulin expression (Figure 3.6a). However, in agreement with the absence of these transcripts in the microarray hits, the observed decrease was not reflected at the mRNA level as assessed by RT-qPCR (Figure 3.6b). Whether DIS3 mutation affects the transport or translation of TUB1 mRNA or affects the protein stability post-translationally remains unknown.3.3.6 Proteogenomic screen for tubulin expression in RNA processing mutants Tubulin protein expression abnormalities in RNA processing mutants have been reported by other groups, as well as ours (Dahan & Kupiec, 2002; Tam et al., 2018). To date this effect has mostly been observed in splicing mutants, and lower protein expression has subsequentlybeen attributed to defects in splicing of the TUB1 transcript. However, this is unlikely to be the case in DIS3 mutants, as this enzyme does not directly participate in the splicing process to our knowledge. This raises the possibility that tubulin expression may be influenced by RNA processing more broadly, and further, that mutations in RNA processing genes identified in our group’s CIN screen could be influencing genomic stability through regulation of tubulin levels.To test this hypothesis, I screened 173 alleles of 143 genes that exhibited significantly increased levels of CIN in the published screen by Western blotting (Stirling et al., 2011). This set included all of the identified mutants in the following categories: RNA processing (54 alleles), ribosome core and biogenesis (41 alleles), tRNA biogenesis and translation (26 alleles), and transcription factors and machinery (52 alleles). The proteogenomic screen identified 13 and 19 cases of increased or decreased tubulin protein expression, respectively (Figure 3.7).  RNA processing mutants comprise the bulk of the hits exhibiting decreased 60expression, while ribosome biogenesis and transcription-associated components are overrepresented among the hits exhibiting an increase (Figure 3.7). Tubulin expression fluctuates in relation to cell cycle stage (Spellman et al., 1998). It is likely that in some cases, tubulin expression is altered as a function of cell cycle staging. Indeed, many of the RNA processing mutant alleles tested in this screen have previously published cell cycle delay or arrest phenotypes (Table 3.3). To address this, I repeated the Western blots for the candidate RNA processing hits following synchronization in G1 with α-factor for 2.5 hours. Surprisingly, only 4 of the mutants – hsh155-ts, rrp4-ts, hrp1-ts, and pab1-ts – were restored to wildtype levels of tubulin protein expression (Figure 3.8). This is especially interesting in light of the arrest being less effective on some mutants compared to others (noted in Figure 3.8); while wildtype cells were > 90% arrested at 2.5 hours, some strains only exhibited as little as 50% schmooing at this timepoint; this appeared to be relatedto the sickness of each strain, as the lower levels of arrest correlated, at least visually, with the amount of cell death. It should also be noted that incidence of small buds was near zero for all tested strains, indicating that while the cells may have not schmooed as effectively as wildtype, the strains were likely no longer cycling.Given that tubulin expression peaks in G2 (Spellman et al., 1998), if anything, this would have made the less arrested strains appear to have higher expression than they would when properly arrested – still, the protein levels appear dramatically decreased in comparison to the arrested wildtype control. These data support the hypothesis that tubulin expression is nota consequence of cell cycle defects in these RNA processing mutants.3.4 DiscussionGenome-wide analysis of the dis3E729K mutant reveals synthetic sickness with loss of anaphase-associated components, implicating DIS3 in mitotic processes. This is supported byexpression microarray data of dis3E729K indicating a downregulation of cell cycle-related transcripts. Cell cycle progression in dis3E729K and dis3-ts appears normal, while a significant 61increase can be seen in the proportion of G2/M cells in dis3-EXO at 30°C, and for pWT, dis3-ENDO, and dis3-EXO at 37°C. The notion of DIS3 having influence on anaphase is supported further by an apparent decrease in α-tubulin expression in dis3E729K and dis3-ts; interestingly, this change is not observed at the transcriptional level. Finally, a proteogenomicscreen of a collection of CIN alleles reveals that many mutant alleles of RNA processing genes induce tubulin expression alterations. This effect is observable in asynchronous and synchronized cultures, indicating that the effect is not simply a read-out of growth delay in any particular cell cycle stage. 3.4.1 Differences in expression of key transcripts in the DIS3 mutants My expression microarray of dis3E729K indicates a significant downregulation of diverse cell cycle-related genes. This stands in contrast to published RNA-seq data from a yeast DIS3 temperature sensitive allele, which revealed a substantial enrichment in mitosis-related GO terms among upregulated genes, and this occurs in the context of broad downregulation of RNA transcripts more generally (Smith et al., 2011). This study also reported substantial overlap between the expression changes in the DIS3 mutant, and temperature sensitive mutants of MTR3, a core RNA exosome component, and MTR4, an exosome cofactor. Interestingly, this group further reported an increase in tubulin (TUB1, TUB2, and TUB3) expression in this DIS3 mutant, an effect not seen in my analysis of dis3E729K (Figure 3.6b). 3.4.2 Synthetic genetic array reveals novel interactions between dis3E729K and anaphase-associated proteinsThe SGA datasets for dis3-ts and dis3E729K reveal stark differences in the biological consequences of these two alleles. The dis3-ts dataset is dominated by GO terms surroundingRNA processing and ribosome maturation, whereas dis3E729K is not; this supports the hypothesis that the dis3-ts allele may manifest broad RNA processing defects, while dis3E729K retains much of its processing abilities, at least under the tested conditions (i.e. growth at 30°C). Interestingly, there were 19 genes that appeared as negative interactions in both datasets; while anaphase-related processes were not enriched for dis3-ts, the occurrence of 62these hits in both SGA results suggests that the dis3-ts allele may also influence mitotic progress, however support for this idea in the genetic interaction data is effectively drowned out by its effects on RNA processing.This analysis also identified 89 and 76 candidate positive interactions in dis3-ts and dis3E729K,respectively. While GO term analyses found no significant enrichments among the dis3E729K positive interaction genes, the dis3-ts dataset was enriched for proteasome-related processes, possibly suggesting that the Dis3 protein in this strain is unstable and is degraded by these pathways under normal conditions (Appendix 8). Additionally, enrichment of terms relating to general transcription regulation seem to suggest that relieving transcriptional stress increases the fitness of dis3-ts, a notion further supported by this strain’s increase in P-body formation as assessed by Lsm1-GFP foci accumulation (Figure 2.3a). However, it should be noted that our protocol does not incorporate a counter-selection step against the URA3-marked query strain. By this method, double mutant colonies were compared against colonies that likely contain a mixture of query haploids and diploids; for this reason, true positive interactions cannot be reliably identified and candidate positive hits were not validated for the purposes of this study. However, this dataset could very well contain candidate suppressors of DIS3 mutation, and validation of dis3E729K hits in particular may provide valuable insight into the pathways influencing this allele’s effects on spindle function.Given the suggestion that my dis3-ts and dis3E729K alleles differ in their turnover by the proteasome (evidenced by the positive SGA dataset hit enrichment in dis3-ts only), I hypothesize that the temperature sensitive DIS3 alleles produce unstable Dis3 protein that may or may not interfere with exosome assembly, and that this study captured effects that area broad consequence of RNA exosome perturbation, and not loss of DIS3 activity per se. RNA-seq analysis has revealed cell cycle upregulation in D. melanogaster S2 cells followingDIS3 knockdown, in contrast to the downregulation observed in dis3E729K (Table 3.1). This lends further credence to the idea that loss of the Dis3 protein induces specific effects, and the difference in allele construction may account for the discrepency in these results (Kiss & 63Andrulis, 2010). 3.4.3 Plasmid-borne DIS3 alleles influence budding indexBudding index analysis indicates a cell cycle delay in G2/M for dis3-EXO at 30°C, but no similar delay in dis3E729K . At the very least, this indicates that the enrichment for cell cycle GO terms in the downregulated transcripts in the expression microarray is not simply a reflection of the dis3E729K strain having an overrepresentation of a given cell cycle stage, and concurrent downregulation of transcripts involved in mediating other, less well represented stages. The cell cycle delay in dis3-EXO may be related to the excessive burden of genomic instability borne by this strain (Figure 2.4b), with other strains simply not reaching some threshold of damage where the burden overwhelms response pathways severely enough to induce cell cycle delay. Regardless, we can conclude that most of the DIS3 strains do not delay the cell cycle significantly in standard culture conditions.Interpretation of these results is complicated by the apparent increase in all strains bearing plasmid-borne DIS3 alleles (wildtype or mutant) at 37°C. This delay may broadly be a consequence of the plasmid construct in the context of temperature stress. Without establishment of copy number and Dis3 protein expression, the implications of this result are difficult to determine. As discussed in 2.4.3, there are a number of mechanisms by which high gene dosage of DIS3 could influence these results; in addition to interference with exosome assembly or catalytic function independent of the complex, overexpression of DIS3could influence the cell cycle through stoichiometric imbalance with key interacting proteins.For example, given recent evidence that Dis3 is phosphorylated in a cell-cycle dependent manner, with direct consequences on mitotic progression, it is feasible that excessive Dis3 protein would result in incomplete modification by cell cycle regulatory proteins, inducing a similar G2/M delay as described in mutants carrying phosphomimetic DIS3 (Snee et al., 2016). As well, dominant effects of the Dis3 protein acting independently of the exosome complex would likely involve an increase in Dis3 activity, and may promote Dis3 processingand/or degradation of novel RNA targets; indeed, in vitro biochemical analysis reveals that 64RNA can directly access Dis3 without threading through the exosome, implying that some RNAs may be targetted to Dis3 independently of the non-catalytic core (Zinder, Wasmuth, &Lima, 2016). However, it is notable that studies examining Dis3 RNA targets using plasmid-borne alleles reveal very similar targets to those using genomic mutations (Kiss & Andrulis, 2010; Schneider et al., 2012; Szczepińska et al., 2015). Finally, overexpression of DIS3 in colorectal cancer implies a functional effect of this gene’s overexpression; such overexpression correlates with invasiveness, viability, and migration (de Groen et al., 2014). 3.4.4 Altered tubulin expression is a general feature of CIN-inducing RNA processing mutantsWestern blot analysis indicates that the genomic DIS3 mutant alleles cause a downregulation of α-tubulin (Tub1) protein, but not mRNA. In RNA processing mutants where we have previously observed tubulin downregulation, we typically see a concurrent decrease in mRNA expression; the fact that DIS3 mutation does not influence mRNA abundance indicates that this effect may be more indirect. This defect may reflect a decrease in tubulin translation, resulting from ribosome defects arising from Dis3 activity loss. Conversely, it could represent an increase in tubulin protein turnover. Further, it remains unclear if this downregulation is an effect mediated by DIS3 loss itself, or represents some form of adaptiveregulation that opposes the stability-influencing effects arising from DIS3 mutation. Future work directly modulating tubulin protein levels in these strains could help to resolve how important the Tub1 decrease is in determining CIN.It is peculiar that dis3E729K and dis3-ts cause a decrease in tubulin, while strains that carry their only copy of DIS3 on a plasmid (pWT, dis3-ENDO, and dis3-EXO) do not. As with the cell cycle abnormalities, it is possible that this phenotypic divergence is caused by variation in DIS3 copy number; it is also possible that the cell cycle defects observed in the plasmid strains influence tubulin levels as assessed by Western blot simply because there are more cells in G2/M, when tubulin expression is higher (Spellman et al., 1998).65The proteogenomic screen examined tubulin expression in all RNA processing mutants that were identified by CIN screening experiments (Stirling et al., 2011). Over 30% of the tested RNA processing genes induce a change in expression of α-tubulin when mutated or deleted. This relationship remains correlational, and it is unclear whether tubulin expression changes are a cause or consequence in this case; indeed, the explanation likely varies between strains.Several of these strains also have demonstrated sensitivities to the microtubule-destabilizing drug benomyl, which supports the hypothesis that spindle assembly is defective as a consequence of inadequate tubulin expression (Table 3.3). While my data also supports the claim that these expression changes are not simply a result of cell cycle delays or arrest, the difficulty of performing an α-factor-induced G1 arrest under the test conditions for this assay obscured further interpretation of the data. Finally, this analysis did not include a concurrent assessment of other tubulin proteins; given the importance of balanced expression between α-tubulin (Tub1) and β-tubulin (Tub2) protein levels, future work in this area would do best to begin with assessing a potential stoichiometric imbalance as a probable mechanism of instability induction (Burke et al., 1989). Further, this screen did not involve further inquiry into the nature of strains with apparent tubulin accumulation; it is possible that, while the underlying mechanisms producing the expression defect may differ, many of these strains may experience CIN as a result of a stoichiometric imbalance in one or another direction. Nevertheless, this screen answered our hypothesis (i.e. that RNA processing mutants may generally influence tubulin protein levels), by showing that tubulin depletion is prevalent beyond simply splicing mutants.66Figure 3.1 RNP composition cluster expression changes in microarray of dis3E729K. GeneChIP Yeast Genome 2.0 microarrays were prepared from duplicate cultures using total RNA from mid-log phase cells. Gene level differential analysis was performed for transcriptsthat met a fold change cut-off threshold of -2 (downregulated) or +2 (upregulated). Statisticalsignificance was determined by unpaired one-way between-subject ANOVA. Relative abundances of up- or down-regulated genes meeting our cut-off from the microarray were identified in each of ten ribonucleoprotein (RNP) composition clusters derived from (Tuck &Tollervey, 2013). The percent of all mRNAs clustered is shown in black, and dis3E729K up- and down-regulated genes are shown in blue and grey, respectively.  67Figure 3.2 Genomic profiling of dis3E729K indicates mitotic defects. The dis3-ts and dis3E729K strains were crossed with the MATa non-essential gene deletion collection (Winzeleret al., 1999), a ts-allele collection (Z. Li et al., 2011), and the Decreased Abundance by mRNA Perturbation (DAmP) collection (Breslow et al., 2008) then analyzed by synthetic genetic array (SGA; see Methods section 3.2.4 for details). Output arrays were scanned as plate images and colony size was analyzed using Balony Software (Young & Loewen, 2013).68Candidate negative hits were selected with a spot size difference (control vs experimental) cut-off of -0.2 and p-value < 0.05. ReviGO plots (Supek et al., 2011) were prepared indicating significantly enriched GO biological processes from the (A) dis3-ts SGA, and (B) dis3E729K microarray and SGA datasets. For the right panel, solid circles are enriched terms derived from the expression microarray, and circles with red hatched outlines are derived from negative SGA hits. (C) Venn diagram summarizing unique and overlapping candidate negative hits in both SGA datasets. 69Figure 3.3 Validation of kinetochore component interactions from the dis3E729K SGA. Spot-dilution assay validations of negative genetic interactions between the indicated mutant alleles and dis3E729K. Indicated strains were grown in liquid selective media at 30°C overnight(or 25°C for temperature sensitive strains), prepared to equal optical density (OD), then serially diluted. Liquid was transferred to the indicated media, and plates were incubated at the indicated temperature for 2 days prior to scanning.70Figure 3.4 Expression microarray and SGA datasets contain few overlapping hits. Venn diagram indicates the overlap between downregulated genes in the dis3E729K microarray, versus negative interaction hits in the dis3E729K and dis3-ts synthetic genetic array (SGA) datasets. 7172Figure 3.5 Budding index of DIS3 mutants. Asynchronous cultures were grown at 30°C, diluted, and either (A) returned to 30°C for 2 hours prior to imaging, or (B) returned to 30°C for 1.5 hours then shifted to 37°C for 2 hours. Samples from these actively growing cultures were mounted on concanavalin-coated slides and imaged at 100x magnification. A minimum of 105 cells per replicate, 332 in total across all replicates were counted. Cells were scored by bud size; “large-budded” cells represent those with a bud 1/3 the size of the mother cell orgreater. Error bars indicate SEM. Significance was calculated using the Fisher’s exact test with Bonferroni-Holm p-value correction.7374Figure 3.6 Protein expression of α-tubulin is decreased in DIS3 mutants. (A) Western blot analysis of the indicated DIS3 mutant strains. For each strain, 1 OD of asynchronous culture was pelleted and flash frozen. Lysates were prepared by precipitation with dithiothreitol (DTT), and 20 μL L of each sample was run on a standard SDS-PAGE gel, followed by transfer using a Trans-Blot Turbo system. Blots were incubated with primary antibody (mouse anti-α-tubulin) overnight with rocking at 4°C, then washed and incubated with secondary antibody (goat anti-mouse HRP) for 1 hour at room temperature. Membranes were then washed briefly and developed using Pierce ECL western blotting substrates. Ponceau staining (lower panel) was used as a visual reference for the loading control. (B) Analysis of TUB1 mRNA expression by RT-qPCR. Equal cell numbers were collected from actively growing cultures. RNA was extracted, then reverse transcribed using a standard thermocycler. Analysis of cDNA samples was carried out using a StepOnePlus Real-Time PCR System using Fast Sybr Green master mix. Primers were designed in-house or adapted from literature where noted, and are listed in Table 2.2. Left panel, genomic DIS3 mutations are compared to WT as the control strains. Right panel: plasmid-borne DIS3 mutants are compared to pWT. Statistics were calculated by non-parametric t-test on ΔCt values averagedCt values averagedacross 3 replicates. Error bars indicate SEM.7576Figure 3.7 α-tubulin protein expression in a panel of RNA processing CIN mutants. Western blot analysis of the indicated mutant strains. For the purposes of this experiment, DAmP and deletion strains were grown at 30°C, while temperature sensitive (ts) collection strains were grown at 25°C, then shifted to 37°C for 3 hours. 1 OD of each asynchronous culture was pelleted and flash frozen. Lysates were prepared by precipitation with dithiothreitol (DTT), and 20 μL L of each sample was run on a standard SDS-PAGE gel, followed by transfer using a Trans-Blot Turbo system. Blots were incubated with primary antibody (mouse anti-α-tubulin) overnight with rocking at 4°C, then washed and incubated with secondary antibody (goat anti-mouse HRP) for 1 hour at room temperature. Membranes were then washed briefly and developed using Pierce ECL western blotting substrates. Ponceau staining (lower panel) was used as a visual reference for the loading control. Asterisks indicate where a expression was called to be lower (red) or higher (green) than the wildtype control. Check marks indicate that the result validates the noted expression change from the first round of blots (not shown). 77Figure 3.8 Protein expression of α-tubulin in RNA processing mutant strains synchronized with α-factor. Western blot analysis of the indicated mutant strains. Strains in the left panel were cultured at 30°C throughout; strains in the right panel were grown overnight at 25°C and shifted to 37°C for 3 hours prior to collection. All cultures were arrested in α-factor for the final 2.5 hours prior to lysate preparation. 1 OD of each culture was pelleted and flash frozen. “% shmooing” indicates a visual estimate of the frequency of shmoo formation in each culture at the time of collection, as assessed by morphology under light microscopy. Lysates were prepared by precipitation with dithiothreitol (DTT), and 20 μL L of each sample was run on a standard SDS-PAGE gel, followed by transfer using a Trans-Blot Turbo system. Blots were incubated with primary antibody (mouse anti-α-tubulin) overnight with rocking at 4°C, then washed and incubated with secondary antibody (goat anti-mouse HRP) for 1 hour at room temperature. Membranes were then washed briefly and developed using Pierce ECL western blotting substrates. Ponceau staining (lower panel) was used as a visual reference for the loading control. Ponceau staining (upper panel) was used asa visual reference for the loading control. 78Table 3.1 Enriched GO terms in the dis3E729K microarray.Ten most significantly downregulated terms from the process ontologyGene Ontology term Cluster frequency Genome frequency Corrected p-valuecell cycle 83 of 207 genes, 40.1% 802 of 7166 genes, 11.2% 7.00E-25cell cycle process 74 of 207 genes, 35.7% 663 of 7166 genes, 9.3% 1.43E-23mitotic cell cycle 53 of 207 genes, 25.6% 400 of 7166 genes, 5.6% 4.61E-19mitotic cell cycle process 51 of 207 genes, 24.6% 384 of 7166 genes, 5.4% 2.96E-18cell division 39 of 207 genes, 18.8% 309 of 7166 genes, 4.3% 1.68E-12nucleic acid metabolic process100 of 207 genes, 48.3% 1769 of 7166 genes, 24.7%6.22E-11regulation of cell cycle 34 of 207 genes, 16.4% 287 of 7166 genes, 4.0% 8.76E-10regulation of mitotic cell cycle26 of 207 genes, 12.6% 169 of 7166 genes, 2.4% 1.30E-09regulation of cell cycle process28 of 207 genes, 13.5% 211 of 7166 genes, 2.9% 6.96E-09nucleobase-containing compound metabolic process103 of 207 genes, 49.8% 2028 of 7166 genes, 28.3%2.57E-08Ten most significantly upregulated terms from the process ontologyGene Ontology term Cluster frequency Genome frequency Corrected p-valuecarbohydrate metabolic process39 of 231 genes, 16.9% 296 of 7166 genes, 4.1% 1.65E-11cellular carbohydrate metabolic process30 of 231 genes, 13.0% 191 of 7166 genes, 2.7% 2.21E-10generation of precursor metabolites and energy26 of 231 genes, 11.3% 226 of 7166 genes, 3.2% 1.01E-05monosaccharide metabolic process16 of 231 genes, 6.9% 99 of 7166 genes, 1.4% 6.86E-05hexose metabolic process 15 of 231 genes, 6.5% 90 of 7166 genes, 1.3% 0.00011energy derivation by oxidation of organic compounds20 of 231 genes, 8.7% 165 of 7166 genes, 2.3% 0.00022glucose metabolic process 13 of 231 genes, 5.6% 73 of 7166 genes, 1.0% 0.0003679Ten most significantly upregulated terms from the process ontologyGene Ontology term Cluster frequency Genome frequency Corrected p-valuedisaccharide metabolic process9 of 231 genes, 3.9% 32 of 7166 genes, 0.4% 0.00038phosphate-containing compound metabolic process52 of 231 genes, 22.5% 833 of 7166 genes, 11.6% 0.00113oligosaccharide metabolicprocess9 of 231 genes, 3.9% 36 of 7166 genes, 0.5% 0.0011480Table 3.2 Enriched GO terms in the dis3E729K and dis3-ts synthetic genetic arrays.dis3-ts SGA GO term enrichmentGene Ontology termCluster frequencyGenome frequencyCorrected p-valueFDR False positivesGenes annotated to the termmaturation of 5.8S rRNA15 of 115 genes, 13.0%89 of 7166genes, 1.2%4.31E-09 0.00% 0 YPR143W, YOR294W, YGR095C,YOR004W, YOL010W, YAL025C, YGR158C, YKR081C, YOR048C, YCL054W, YOL077C, YDR457W,YDL111C, YOR310C, YKR063Cmaturation of 5.8S rRNA from tricistronic rRNA transcript (SSU-rRNA, 5.8S rRNA, LSU-rRNA)15 of 115 genes, 13.0%89 of 7166genes, 1.2%4.31E-09 0.00% 0 YPR143W, YOR294W, YGR095C,YOR004W, YOL010W, YAL025C, YGR158C, YKR081C, YOR048C, YCL054W, YOL077C, YDR457W,YDL111C, YOR310C, YKR063CrRNA processing25 of 115 genes, 21.7%355 of 7166 genes, 5.0%1.39E-07 0.00% 0 YKR024C, YDR478W, YOL010W,YAL025C, YGR158C, YCL054W, YOL077C, YDR457W, YDR293C, YOR310C, YOL066C, YOR294W, YPR143W, YGR095C, YOR004W,YOR272W, YKL009W, YOL022C,YOR048C, YKR081C, YNL110C, YIL096C, YDL111C, YMR131C, YKR063C81dis3-ts SGA GO term enrichmentGene Ontology termCluster frequencyGenome frequencyCorrected p-valueFDR False positivesGenes annotated to the termncRNA processing28 of 115 genes, 24.3%473 of 7166 genes, 6.6%5.37E-07 0.00% 0 YKR024C, YBL013W, YDR478W,YOL010W, YAL025C, YGR158C, YCL054W, YOL077C, YDR457W,YDR293C, YOR310C, YOL066C, YOR294W, YPR143W, YGR095C,YOR004W, YOR272W, YKL009W, YOL022C, YOR048C, YKR081C, YOL102C, YNL110C, YIL096C, YDL111C, YMR131C, YNR011C, YKR063Cribosomal large subunit biogenesis15 of 115 genes, 13.0%126 of 7166 genes, 1.8%7.11E-07 0.00% 0 YKR024C, YPR143W, YOR294W,YAL025C, YOR272W, YKL009W, YKR081C, YOR048C, YCL054W, YNL110C, YOL077C, YDR457W, YIL148W, YDR496C, YKR063CrRNA metabolic process25 of 115 genes, 21.7%399 of 7166 genes, 5.6%1.63E-06 0.00% 0 YKR024C, YDR478W, YOL010W,YAL025C, YGR158C, YCL054W, YOL077C, YDR457W, YDR293C, YOR310C, YOL066C, YOR294W, YPR143W, YGR095C, YOR004W,YOR272W, YKL009W, YOL022C,YOR048C, YKR081C, YNL110C, YIL096C, YDL111C, YMR131C, YKR063C82dis3-ts SGA GO term enrichmentGene Ontology termCluster frequencyGenome frequencyCorrected p-valueFDR False positivesGenes annotated to the termribosome biogenesis27 of 115 genes, 23.5%477 of 7166 genes, 6.7%3.08E-06 0.00% 0 YKR024C, YDR478W, YOL010W,YAL025C, YGR158C, YCL054W, YOL077C, YDR457W, YDR293C, YOR310C, YIL148W, YOL066C, YOR294W, YPR143W, YGR095C,YOR004W, YOR272W, YKL009W, YOL022C, YOR048C, YKR081C, YNL110C, YIL096C, YDL111C, YMR131C, YDR496C, YKR063Cribonucleoprotein complex biogenesis30 of 115 genes, 26.1%581 of 7166 genes, 8.1%3.08E-06 0.00% 0 YKR024C, YDR478W, YOL010W,YAL025C, YGR158C, YCL054W, YOL077C, YDR457W, YKR086W,YDR293C, YOR310C, YIL148W, YAL032C, YOL066C, YOR294W, YPR143W, YGR095C, YOR004W,YOR272W, YKL009W, YKR081C,YOL022C, YOR048C, YNL110C, YIL096C, YDL111C, YMR131C, YDR496C, YNR011C, YKR063CRNA processing32 of 115 genes, 27.8%657 of 7166 genes, 9.2%3.47E-06 0.00% 0 YKR024C, YBL013W, YDR478W,YOL077C, YKR086W, YDR293C, YOR310C, YAL032C, YMR061W,YPR143W, YGR095C, YOR272W,YKL009W, YOL022C, YDL111C, YNR011C, YOL010W, YGR158C, YAL025C, YCL054W, YDR457W, YOL066C, YOR294W, YOR004W,YBR236C, YOR048C, YKR081C, YNL110C, YOL102C, YIL096C, YMR131C, YKR063C83dis3-ts SGA GO term enrichmentGene Ontology termCluster frequencyGenome frequencyCorrected p-valueFDR False positivesGenes annotated to the termmaturation of LSU-rRNA from tricistronic rRNA transcript (SSU-rRNA, 5.8S rRNA, LSU-rRNA)9 of 115 genes, 7.8%46 of 7166genes, 0.6%2.20E-05 0.00% 0 YKR024C, YPR143W, YAL025C, YKR081C, YOR048C, YCL054W, YOL077C, YDR457W, YKR063Ccleavage involved in rRNA processing11 of 115 genes, 9.6%82 of 7166genes, 1.1%3.85E-05 0.00% 0 YOR294W, YGR095C, YOR004W,YOL010W, YGR158C, YOR048C, YOL077C, YDR457W, YDL111C, YOR310C, YKR063CncRNA metabolic process28 of 115 genes, 24.3%584 of 7166 genes, 8.1%5.70E-05 0.00% 0 YKR024C, YBL013W, YDR478W,YOL010W, YAL025C, YGR158C, YCL054W, YOL077C, YDR457W,YDR293C, YOR310C, YOL066C, YOR294W, YPR143W, YGR095C,YOR004W, YOR272W, YKL009W, YOL022C, YOR048C, YKR081C, YOL102C, YNL110C, YIL096C, YDL111C, YMR131C, YNR011C, YKR063Cmaturation of LSU-rRNA9 of 115 genes, 7.8%59 of 7166genes, 0.8%0.00021 0.00% 0 YKR024C, YPR143W, YAL025C, YKR081C, YOR048C, YCL054W, YOL077C, YDR457W, YKR063C84dis3-ts SGA GO term enrichmentGene Ontology termCluster frequencyGenome frequencyCorrected p-valueFDR False positivesGenes annotated to the termcellular component biogenesis44 of 115 genes, 38.3%1322 of 7166 genes, 18.4%0.00025 0.00% 0 YKR024C, YDR478W, YOL077C, YML098W, YKR086W, YDR293C, YOR310C, YIL148W, YAL032C, YLL003W, YLR212C, YNL084C, YPR143W, YNR035C, YGR095C, YOR058C, YOR272W,YKL009W, YOL022C, YOR057W,YDL111C, YDR443C, YNR011C, YKL042W, YER177W, YOL010W,YGR158C, YAL025C, YKL192C, YCL054W, YDR457W, YOL030W, YOL066C, YOR294W,YOR004W, YBL034C, YOR048C, YKR081C, YNL110C, YIL096C, YMR131C, YDR496C, YKR063C,YKR037C85dis3-ts SGA GO term enrichmentGene Ontology termCluster frequencyGenome frequencyCorrected p-valueFDR False positivesGenes annotated to the termRNA metabolic process47 of 115 genes, 40.9%1501 of 7166 genes, 20.9%0.00052 0.13% 0.02 YKR024C, YBL013W, YDR478W,YGR122W, YOL077C, YKR086W,YML098W, YDR293C, YOR310C,YAL032C, YMR061W, YPR143W,YGR095C, YPL075W, YOR272W, YKL009W, YOL022C, YOL005C, YDL111C, YDR443C, YNR011C, YPR179C, YER177W, YOL010W, YGR158C, YAL025C, YJR035W, YCL054W, YDR457W, YOL017W, YOL066C, YOR166C, YOR294W, YOL094C, YNL290W,YOR004W, YBR236C, YKL028W,YOR048C, YKR081C, YKL112W, YNL110C, YOL102C, YBR150C, YIL096C, YMR131C, YKR063C86dis3-ts SGA GO term enrichmentGene Ontology termCluster frequencyGenome frequencyCorrected p-valueFDR False positivesGenes annotated to the termnucleic acid metabolic process52 of 115 genes, 45.2%1769 of 7166 genes, 24.7%0.00068 0.12% 0.02 YKR024C, YBL013W, YDR478W,YGR122W, YOL077C, YML098W, YKR086W, YDR293C, YOR310C, YAL032C, YMR061W, YPR143W, YOR060C,YGR095C, YJL090C, YPL075W, YOR272W, YKL009W, YOL005C,YOL022C, YDL111C, YDR443C, YNR011C, YPR179C, YER177W, YOL010W, YAL025C, YGR158C, YOR077W, YJR035W, YCL054W, YDR457W, YOL017W, YOL066C,YKL022C, YOR166C, YOL094C, YOR294W, YOR004W, YNL290W, YBR236C, YKL028W,YOL034W, YOR048C, YKR081C, YKL112W, YOL102C, YNL110C, YBR150C, YIL096C, YMR131C, YKR063Cendonucleolytic cleavage involved in rRNA processing8 of 115 genes, 7.0%59 of 7166genes, 0.8%0.00246 0.35% 0.06 YOR294W, YOR004W, YOL010W, YOR048C, YOL077C, YDR457W, YOR310C, YKR063C87dis3-ts SGA GO term enrichmentGene Ontology termCluster frequencyGenome frequencyCorrected p-valueFDR False positivesGenes annotated to the termendonucleolytic cleavage of tricistronic rRNA transcript (SSU-rRNA, 5.8S rRNA, LSU-rRNA)8 of 115 genes, 7.0%59 of 7166genes, 0.8%0.00246 0.33% 0.06 YOR294W, YOR004W, YOL010W, YOR048C, YOL077C, YDR457W, YOR310C, YKR063Ccellular component organization orbiogenesis62 of 115 genes, 53.9%2452 of 7166 genes, 34.2%0.00627 0.42% 0.08 YKR024C, YKL165C, YHR166C, YDR478W, YOL077C, YML098W, YKR086W, YDR293C, YOR310C, YIL148W, YAL032C, YLL003W, YLR212C, YNL084C, YPR143W, YNR035C, YGR095C, YOR058C, YPL075W, YGR092W, YOR272W, YKL009W, YOL022C, YBR109C, YOR057W, YDL111C, YDR443C, YKL042W, YNR011C, YPR179C, YLR127C, YER177W, YOL010W, YAL025C, YGR158C, YKL192C, YJR035W, YCL054W, YOR046C, YDR457W, YOL030W, YDR498C,YOL017W, YOL066C, YOL094C, YOR294W, YOR004W, YNL290W, YKL028W, YBR091C,YOL034W, YBL034C, YKR081C, YOR048C, YKL112W, YNL110C, YIL096C, YMR131C, YDR496C, YKR063C, YKR037C, YOR195W88dis3-ts SGA GO term enrichmentGene Ontology termCluster frequencyGenome frequencyCorrected p-valueFDR False positivesGenes annotated to the termRNA phosphodiesterbond hydrolysis13 of 115 genes, 11.3%194 of 7166 genes, 2.7%0.00777 0.60% 0.12 YOR294W, YGR095C, YOR004W,YOL010W, YGR158C, YOR048C, YOL077C, YDR457W, YDL111C, YOR310C, YKR063C, YOR166C, YMR061Wdis3E729K SGA GO term enrichmentGene Ontology termCluster frequencyGenome frequencyCorrected p-valueFDR False positivesGenes annotated to the termmicrotubule-based process11 of 105 genes, 10.5%122 of 7166 genes, 1.7%0.0008 0.00% 0 YNL287W, YML031W, YOR257W, YGR113W, YHR005C,YKL089W, YJL018W, YOL069W, YGL075C, YKR037C, YMR117Cestablishment of chromosome localization5 of 105 genes, 4.8%15 of 7166genes, 0.2%0.00092 0.00% 0 YGR113W, YKL089W, YJL018W, YOL069W, YOL104C89Table 3.3 Previously published phenotypes of RNA processing α-tubulin screen hits. Gene Allele Category Drug sensitivities (van Pel, Stirling, Minaker, Sipahimalani, & Hieter, 2013)Cell cycle arrest/delay PRP4 CB-ts 3-I05 Spliceosome MMS G1 and G2 (Eckert et al., 2016)PRP6 CB-ts 1-N14 Spliceosome G2 (S. pombe) (Potashkin, Kim, Fons, Humphrey, & Frendewey, 1998)HSH155 PH-ts 2-E5 SpliceosomeCWC2 PH-ts 1-E3 SpliceosomeSYF1 PH-ts 3-G3 Spliceosome Benomyl G2/M (Russell, Ben-Yehuda, Dix, Kupiec, & Beggs, 2000)HRP1 CB-ts 3-M14 CFI complexPAB1 PH-ts 4-D12 3' end processing, poly(A) tailingG1 (Sachs & Davis, 1989)XRN1 DMA 13D-C11mRNA decayRRP4 CB-ts 2-J08 Exosome (mRNA degradation)Benomyl G2/M (Smith et al., 2011)CDC36 CB-ts 1-F04 CCR4-NOT Benomyl, hydroxyurea G1 (de Barros Lopes et al., 1990)CDC39 CB-ts 1-O17 CCR4-NOT Hydroxyurea G1 (de Barros Lopes et al., 1990)CCR4 DMA 1D-C12CCR4-NOT Benomyl, hydroxyurea, rapamycinG1 (Westmoreland et al., 2004)DCP2 CB-ts 2-L22 Splicing, RNAprocessingRPS23A DMA 5B-F1 Ribosomal core componentG1 (Hoose et al., 2012)GRS1 PH-ts 1-B11 tRNA biogenesis  90Gene Allele Category Drug sensitivities (van Pel, Stirling, Minaker, Sipahimalani, & Hieter, 2013)Cell cycle arrest/delay MES1 CB-ts 1-E21 tRNA biogenesis  MMSTAF1 CB-ts 22-D08 TFIID G1 (H. H. Li, Li, Sheppard, & Liu, 2004)TAF2 CB-ts 25-C10 TFIID G2/M (S. S. Walker, Reese, Apone, & Green, 1996)RPC37 PH-ts 1-G01 RNA pol / TFIIsBenomyl, MMSPOB3 CB-ts 23-E05 RNA pol / TFIIsBenomyl, hydroxyureaSPT5 CB-ts 25-F05 Transcription Control, Factors914 INVESTIGATING THE MECHANISM OF CIN INDUCTION IN DIS3 MUTANTS4.1 IntroductionDIS3 has been linked to spindle function by many research groups and multiple approaches. In Drosophila, DIS3 knockdown in wing imaginal discs completely prevents wing differentiation, and induces various mitotic phenotypes including multipolar spindles, chromatin condensation, and shortened mitotic spindles (Snee et al., 2016; Towler et al., 2015). Experiments using a temperature-sensitive allele of DIS3 revealed a variety of defects including significant elongation of astral microtubules, misorientation of mitotic spindles along the mother-bud axis, and an apparent decoupling of spindle growth from budding reflected by short, pre-anaphase spindles appearing prematurely in small-budded cells (Smithet al., 2011). Further, another major RNA processing and degradation enzyme, Xrn1/Kem1, was previously implicated in microtubule stabilization (Interthal et al., 1995). For these reasons, we hypothesize that Dis3’s role in mitotic regulation influences the cell’s progression through anaphase, particularly by affecting spindle morphology in some way.I demonstrate that the dis3E729K mutation alters the budding index of kinetochore-deficient cells. Hypothesizing that this may reflect a defect in spindle assembly checkpoint (SAC) function, I tested the frequency at which these DIS3 strains are able to escape from a nocodazole-induced arrest. Surprisingly, all the mutant strains remain arrested at 2 hours, in contrast to the mad2Δ control strain. Therefore, DIS3 mutation does not inhibit the SAC, at least in the context of a functional kinetochore.Next, I extend previous analyses of spindle morphology in DIS3 mutants by assaying for additional spindle defects using a plasmid bearing GFP-conjugated TUB1. The dis3E729K appears to delay slightly following bud neck anchoring of the mitotic spindle, but this effect is not present in other mutants. In accordance with the budding index data in the last chapter, 92closer analysis of mitotic spindles reveals that the strains carrying only plasmid-borne DIS3 exhibit a cell cycle delay, while dis3E729K and dis3-ts do not, indicating that this may be an effect more related to DIS3 copy number than mutational effects. Having established that mitotic timing is slightly abnormal in DIS3 mutants, I hypothesized that loss of DIS3 activity influences mitosis through accumulation of Dis3 target RNAs. Activation and relocation of key nucleolar proteins is critical in triggering the final steps of mitosis (Roccuzzo, Visintin, Tili, & Visintin, 2015); given its role in rRNA processing and data demonstrating that dis3-ts accumulates poly(A) RNAs in the nucleolus, we performed RNA fluorescence in situ hybridization (FISH) to examine if this phenomenon is present in our other mutants. However, this phenotype is limited to the temperature sensitive mutant only and likely does not reflect a nucleolar defect that is contributing to CIN.Finally, I demonstrate that the fitness defects exhibited by the DIS3 exonuclease mutants are virtually eliminated when these strains are grown on non-fermentable media. This result was surprising and gives us new insight into the mechanisms that produce CIN in DIS3 mutants.4.2 Methods 4.2.1 Yeast strains and culturingYeast were grown in rich media at 30°C by standard procedures unless otherwise noted.  Strains used in this study are listed in Table 2.1. Additional strains were taken from the collections described below (see Methods: “SGA”).4.2.2 Spindle defect imagingIndicated strains were transformed with a plasmid bearing GFP-tagged TUB1 and the HIS3 nutritional marker (Therizols et al., 2006), and struck to histidine-depleted media. These strains were inoculated in histidine-depleted media and grown overnight at 30°C. The next day, the overnight cultures were diluted 1 in 5 and imaged after 2 hours (once the cultures 93were actively growing). Cultures were mounted on concanavalin-coated slides and imaged at100x magnification on a Leica Dmi8 microscope using Metamorph software (Molecular Devices) and the appropriate fluorescent filter set. Final images were scored using Image J (rsbweb.nih.gov/ij/) as described (Stirling et al., 2011). A minimum of 177 cells per replicate,and 720 cells in total across all replicates were counted, imaged in DIC and GFP channels.Bud neck anchoring was defined as cases where any part of the spindle was positioned directly between the narrowest point of the bud neck, at the cleavage furrow. Measurements are reported as percent of cells counted with mitotic spindles (short or elongated) and not including pre-anaphase spindles – those with astral spindles only, or where the spindle still appeared as a focus and not a bar (immediately following spindle pole body duplication). Forquantification of mitotic spindle frequency, I calculated the ratio of pre-anaphase to mitotic spindles.4.2.3 Nocodazole escape imagingIndicated strains were grown overnight at 30°C in complete media. The next day, the overnight cultures were diluted 1 in 10 for 1.5 hours, and then arrested in S-phase through addition of hydroxyurea to the media (0.2M final concentration). Two hours later – which corresponded to the timepoint where >80% of cells are large-budded – the cultures were washed twice with water and cells were resuspended in media containing either DMSO or nocodazole (15 μL g/ml final), and returned to the 30°C incubator for two hours. Cultures weremounted on concanavalin-coated slides and imaged at 100x magnification on a Leica Dmi8 microscope using Metamorph software for DIC only (Molecular Devices). Final images werescored using Image J (rsbweb.nih.gov/ij/) as described (Stirling et al., 2011). A minimum of 100 cells per replicate, and 320 in total across all replicates were counted.4.2.4 Budding indicesStrains were grown overnight at 30°C in YPD, diluted 1 in 10 in the morning, and returned tothe incubator to grow for 2 hours in order to leave stationary phase. If a temperature shift was94used, cells were diluted 1 in 10 in the morning, allowed to grow for 1.5 hours, then shifted to either 37°C for 2 hours, or 25°C for 4 hours (to account for slower growth at lower temperatures). Cultures were mounted on concanavalin-coated slides and imaged at 100x magnification on a fluorescent microscope (Leica) using Metamorph software (Molecular Devices) and imaged in only the DIC channel. Final images were scored using Image J (rsbweb.nih.gov/ij/) as described (Stirling et al., 2011). A minimum of 120 cells per replicate,and 431 cells in total across all replicates were counted.4.2.5 Fluorescence in-situ hybridizationExperiments were performed as previously described (Paul & Montpetit, 2016). Briefly, indicated strains were grown overnight at permissive temperature in appropriate drop-out selection media. The next day, the overnight cultures were diluted and, once in log phase, shifted to 37°C for 3 hours. Cells were fixed with 5% formaldehyde for 15 min. Hybridization was performed with a fluorescein isothiocyanate–labeled oligo-dT probe (Cole, Heath, Hodge, Hammell, & Amberg, 2002); cultures were then washed and mounted with mounting media/DAPI. Slides were imaged at 100x using Metamorph software.4.2.6 Spotting assayFor spot assays, liquid cultures were grown at 30°C overnight in YPD (or 25°C for temperature sensitive strains), diluted to an optical density at 600nm (OD) of 0.6 in the morning, and serially diluted in YPD in 96-well plates. Liquid was transferred to the indicated media plates using a spot tool and plates were incubated for 2-4 days prior to scanning. For spot assays on glycerol-containing media (YPG), cultures were grown overnight in YPD as before, washed in dH2O, and diluted in phosphate-buffered saline (PBS) instead of YPD tominimize carry-over of dextrose. Plates were then prepared as described above.954.3 Results4.3.1 DIS3 mutants are resistant to the microtubule-destabilizing drug benomylThe interaction of DIS3 mutations with anaphase regulators, in the context of previous studies indicating spindle defects in DIS3 mutants, suggests that Dis3 may alter cell cycle progression through this protein’s influence on mitotic spindle stability. As well, given the common feature of benomyl sensitivity in other RNA processing mutants examined in my proteogenomic screen, I hypothesized that downregulated tubulin expression may sensitize DIS3 mutants to this drug as well. Indeed, sensitivity to both benomyl and nocodazole has been previously published for a different temperature sensitive allele if DIS3 (Smith et al., 2011).Surprisingly, and in contrast to published data, I observed that dis3-ts and dis3E729K both showed notable resistance to the microtubule poison benomyl when tested by spotting assays(Figure 4.1, Table 2.4). This resistance was also evident in dis3-ts, although to a lesser extent,on plates containing nocodazole, which also interferes with the polymerization of microtubules (Table 2.4). This indicates that while spindle regulation in DIS3 mutants may be altered, it is unlikely to be due to spindle instability, as such an effect should be exacerbated by these drugs.4.3.2 DIS3 mutants exhibit abnormal timing of spindle dynamicsDIS3 mutants have been reported to exhibit a variety of microtubule defects, including elongated astral microtubules, mis-oriented spindles, and an increase in pre-anaphase spindles in large-budded cells (Smith et al., 2011). These data seem to indicate that DIS3 mutation causes a decoupling of spindle dynamics from cell growth, and consequently, a mis-timing of spindle-related events. I extended this analysis to my cancer-associated point mutants, in order to establish if mis-timed spindle formation and movement is a general feature of DIS3 mutants. To assess spindle morphology, I transformed the DIS3 mutant strains with a plasmid bearing GFP-tagged TUB1. Visualizing the progression of spindle 96assembly and elongation by counting the frequency of cells in given spindle morphology stages allows us to pinpoint with finer resolution any potential cell cycle aberrations that could feasibly influence chromosome segregation (Figure 4.1). I focused on ascertaining the frequency of cells exhibiting an anchored mitotic spindle, as a previous study of a DIS3 temperature sensitive mutant revealed a decrease in cells at this stage (Smith et al. 2011). Spindle anchoring is critical in mitotic progression, as it positions the mitotic machinery such that spindle elongation will pull the daughter chromosomes into the bud, instead of segregating within the mother cell, resulting in genome duplication and instability. Surprisingly, in asynchronous cultures, I observed an increased proportion of anchored mitotic spindles in the dis3E729K mutant; however, this effect was absent in all other mutants (Figure 4.2a). The dis3-ENDO mutant did exhibit an increase in comparison to WT, yet not in comparison to the pWT control. This analysis also allowed me to take a closer look at cell cycle progression in these mutants,as assessing spindle morphology is a better indicator of cell cycle stage than budding analysis(which relies on visual cues for cell separation which are often difficult to detect). Quantification of the proportion of cells with mitotic spindles revealed that once again, the plasmid-bearing DIS3 alleles, including pWT pile up significantly in G2/M (Figure 4.2b). Unlike the budding index analysis, this quantification strategy demonstrates that the effect is detectable at 30°C, further supporting the hypothesis that the cell cycle delay is a direct effectof the plasmid and not related to the DIS3 mutations in these strains.4.3.3 DIS3 mutation alters cell cycle progression in the context of kinetochore deficiencyWhile dis3E729K itself did not alter the budding index, even at 37°C (Figure 3.5a), our SGA analysis showed strong dependence of this allele on a functional kinetochore. To explore this relationship, I introduced the dam1-1 allele into the dis3E729K bearing strain and retested cell cycle progression by budding index. DAM1 encodes a protein of the Dam1 ring complex which helps to tether microtubules to the outer kinetochore during anaphase (Cheeseman et 97al., 2001). The presence of the dam1-1 allele in otherwise WT cells led to a strong G2/M arrest at 37°C. Remarkably, introduction of the dis3E729K allele into this strain led to a reduction in G2/M cells, suggesting a weakened cell cycle arrest (Figure 4.3). One rationale for this is that mutations in Dis3 could allow arrested dam1-1 cells to slip through the spindleassembly checkpoint inappropriately, creating inviable progeny and manifesting the observedpopulation fitness defect (see discussion section 3.4).Previous research has demonstrated a similar effect when MAD2, a gene coding for a critical SAC protein, was deleted in a dis3-ts strain; mad2Δ impairs SAC activation, and the double mutants proceed through anaphase, producing aneuploid cells (Murakami et al., 2007). Although they did not appear as hits in my SGA analysis (see section 3.3.2), I expanded my analysis and performed spot assays for double mutants of DIS3 and either MAD2, or its interacting partner MAD1. While no interaction was observed with any DIS3 mutant and MAD1, a slight increase in temperature sensitivity was seen when MAD2 was deleted in the context of dis3E729K or dis3-EXO (Figure 4.4). Interestingly, mad2Δ deletion appears to slightly rescue the growth of dis3-ts at 34°C, however this effect is very mild. This confirms that dis3E729K depends upon a functional SAC, but also highlights allele specific differences between dis3 alleles.4.3.4 DIS3 mutants do not escape nocodazole-induced anaphase arrestFailing to arrest at proper mitotic checkpoints in the context of mitotic defects could lead to lethal CIN events, and potentially explain the negative genetic interactions observed with alleles of DIS3 and the mitotic chromosome segregation apparatus (e.g. dam1-1 dis3E729K ). Both benomyl and nocodazole activate the spindle assembly checkpoint (SAC), and resistance to these drugs may indicate that the checkpoint in DIS3 mutants is damaged, allowing them to escape arrest and continue budding, likely at the expense of mitotic fidelity.In order to ascertain if DIS3 mutants have defective SAC function, I assayed for their ability to escape a nocodazole-induced arrest by microscopy. After two hours in nocodazole-containing media, all DIS3 mutants were arrested at levels comparable to control cells; this is98in contrast to mad2Δ cells, which lack the ability to activate the SAC (Figure 4.5). However, again the phenotype appears to be more complex in dis3-ENDO and dis3-EXO. When compared to WT cells, both exhibit a significant increase in the frequency of nocodazole escape; however, this increase is not significant in comparison to the plasmid-borne pWT. This is particularly interesting in light of the differential rate of progression through the cell cycle following release from hydroxyurea into DMSO; again, all plasmid-bearing DIS3 mutant strains exhibit a cell cycle delay, which falls in line with the budding index and mitotic spindle data presented in Chapter 3.4.3.5 MM-associated DIS3 mutations do not induce nucleolar poly(A)-RNA accumulationThe RNA exosome is responsible for several key steps in ribosome production through processing the 7S rRNA into the 5.8S, as well as degradation of the 5’ external transcribed spacer (5’-ETS) region (Allmang, Mitchell, Petfalski, & Tollervey, 2000). Nucleolar functionis intimately tied to cell cycle progression. For example, Cdc14, a master regulator of mitoticprogression, relocates between the nucleolus, nucleus, and cytoplasm when triggered by the Cdc fourteen early anaphase release (FEAR) and mitotic exit network (MEN) pathways; disruption of this system induces a substantial anaphase delay (Stegmeier, Visintin, & Amon, 2002). Therefore, interference with nucleolar maintenance and/or stability could influence not only ribosome production itself, but also cell cycle progression and stability.This hypothesis piqued our interest following a recent publication demonstrating that the same dis3-ts allele used in this project accumulates diverse mRNA species in the nucleolus atthe non-permissive temperature (Paul & Montpetit, 2016). We asked whether this phenotype correlates with the level of genome instability across the DIS3 mutant strains. Fluorescence in situ hybridization (FISH) of total poly(A)-RNA revealed that poly(A)-RNA accumulation after a 37°C temperature shift was specific to dis3-ts and did not occur appreciably in any other mutants (Figure 4.6). Therefore, while interesting, this phenotype does not appear to be99a feature of MM-associated point mutations, and is likely not related to CIN induction.4.3.6 Rescue of mutant fitness under non-fermentative growthThe dis3-EXO mutant exhibits the lowest fitness of the mutants examined in this study (Figure 2.1b). However, literature suggests that this slow growth phenotype can be completely abrogated through culturing on nonfermentable media; dis3-EXO accumulates ROS in fermentative growth and these levels drop under respiratory growth, contradictory to wildtype strains (Tsanova et al., 2014). Although the mechanism for this effect is not entirely understood, I wanted to assess if nonfermentable media would also rescue the growth defectsof the other mutants. Spot assays plated on media containing only glycerol as a carbon sourcerevealed a partial rescue of the growth defects of dis3-EXO and dis3E729K relative to wildtype (Figure 4.7). In order to assess if the fitness rescue on non-fermentable media would also relieve the mechanisms by which these DIS3 mutants gain their drug resistance, I performed a spot assay on media containing both glycerol and benomyl. The metabolic shift does not appear tohave any effect on drug resistance in this case, and again I observed a slight increase in growth of the mutant strains relative to wildtype (Figure 4.8). This indicates that the cellular defects underlying temperature sensitivity of these strains may be uncoupled to those mediating their resistance to microtubule poisons.4.4 DiscussionIn contrast to previously published data, my DIS3 mutant alleles exhibit resistance to microtubule-destabilizing drugs, indicating that they may have different effects on spindle kinetics than previously reported in other, temperature sensitive strains. Spindle stage quantification using a GFP-Tub1 reporter indicates that while the budding indices of DIS3 mutants are altered, this effect is only present in mutants carrying DIS3 on a plasmid, and may reflect a secondary effect of our system. The DIS3 single mutants have a functional 100SAC and arrest fully in nocodazole-containing media, however, the dis3E729K allele decreases the proportion of cells arrested by the dam1-1 allele, indicating that while cell cycle progression is normal in this mutant, it has some effect on anaphase progression that is evident only in the context of a defective kinetochore. While this dis3-ts mutant exhibits a nucleolar poly(A)-RNA accumulation phenotype at 37°C, possibly indicating a loss of nucleolar stability, this effect is not seen in other mutants. Finally, consistent with previous reports, growth on non-fermentable media completely rescues the slow growth phenotypes ofnot only dis3-EXO, but also dis3E729K and to some extent even dis3-ts. 4.4.1 Spindle timing is altered in DIS3 mutantsPrevious studies have examined spindle orientation and assembly in DIS3 mutants (Murakami et al., 2007; Smith et al., 2011). I expanded upon this work by analyzing the delay at bud neck anchoring for this DIS3 mutant set. Surprisingly, only the dis3E729K allele induced a delay at the anchoring stage of spindle assembly; this could be due to an extended time until release from the SAC (which triggers subsequent spindle elongation), or could be the product of more time spent with elongated spindles (which were also counted as anchored). Examination of the raw data reveals that the effect is explained by an increase in short mitotic spindles, pre-elongation, located at the bud neck. This supports the notion that the SAC has not been satisfied, and keeps the cells arrested before chromosome segregation. As this effect did not reflect the findings of previous research, and did not correlate with the prevalence of CIN among these mutant strains, it was not investigated further.The mitotic/nonmitotic analysis of GFP-Tub1 indicates that all the strains with plasmid-borne DIS3 exhibit a G2/M delay at 30°C, while the budding index analysis only identified a cell cycle delay in dis3-EXO. This discrepancy could result from G2/M cells in the budding index analysis having been counted as separated G1 cells when they were in fact still attached; however, in my quantification I applied the assumption that two large cells in directcontact were unseparated mother-daughter pairs, which makes it unlikely that a G2/M delay would be missed. 101The other possibility is that while the number of large-budded cells might have been constantin both experiments, the number of cells with mitotic spindles (that is, spindles appearing as a bar instead of as astral spindles, or a single point) was not directly correlated with the number of large-budded cells. This would suggest an S-phase arrest; indeed, cells that arrest in S-phase – when the spindle would appear as a point, immediately before or after spindle pole body duplication – continue growing a bud, and can reach a large-budded state without ever entering G2/M. A disruption in cell cycle timing could feasibly induce a downstream delay, particularly at the SAC, which is activated during each cycle and only relieved when a number of signals coordinate to dismiss it (Fang, Hongtao, & Kirschner, 1998).4.4.2 DIS3 mutants have a functional SACThe spindle-perturbing drug nocodazole induces activation of the SAC and subsequent arrest at the large-budded stage. My analysis demonstrates that DIS3 mutants arrest as expected in the presence of this drug. It should be noted that I only assayed for escape at the 2 hour timepoint, where pilot experiments demonstrated that wildtype would remain arrested, and mad2Δ would exhibit significant escape; it remains possible that escape may occur at a later timepoint, however we consider this possibility unlikely as the mechanism by which this could occur is not immediately clear.Additionally, this analysis did not include an assessment of rebudding, a phenotype where the cell forms a second bud before completing anaphase to release the first. There were manycases, particularly in the dis3-ts strain, where I noted 3 large cells in close proximity to one another; such a phenotype was extremely rare in the wildtype strain. Although I did not quantify the frequency of such events, they necessarily represent either the presence of G1 cells, or rebudding; in either case this would represent some form of escape. 4.4.3 DIS3 point mutations do not induce nucleolar poly(A)-RNA accumulationGiven DIS3’s role in rRNA processing, we were intrigued by a recent report that dis3-ts 102induces a non-specific accumulation of poly(A)-RNAs in the nucleolus (Paul & Montpetit, 2016). It is feasible that such a profound shift in mRNA localization could have negative consequences on nucleolar stability. The dis3-ts is also the only mutant that exhibits R-loop accumulation (see section 2.3.5); nucleolar poly(A) RNA accumulation could subsequently induce nucleolar R-loop formation, and this hypothesis could be easily tested through analysis by methods such as DNA:RNA hybrid immunoprecipitation with microarray (DRIP-chip) or sequencing (DRIP-seq). However, as I have demonstrated that these phenotypes are specific to dis3-ts, and not induced as a consequence of MM-associated mutations in DIS3, itremains beyond the scope of this project to investigate the nature of these specific defects.Dis3 may have other effects on cell cycle progression through yet unidentified roles in the process of mitotic exit. Recent work in Drosophila cells has identified conserved phosphorylation sites on Dis3 that appear to be targets of the major anaphase regulator Cdk1 (Snee et al., 2016). Dis3 phosphorylation inhibited the protein’s exonuclease activity, and a phosphomimetic Dis3 mutant allele induced a cell cycle delay, as well as overcondensed chromosomes and aneuploidy. This falls in line with the budding index analysis indicating that dis3-EXO delays significantly in G2/M; however, the particular target of DIS3 activity that mediates this process remains elusive.4.4.4 Fitness defects in DIS3 mutants are abrogated by respiratory growthPrevious study of the dis3-EXO mutant has demonstrated a rescue of this strain’s growth defects when cultured on non-fermentable media, where dextrose is substituted with glycerolor ethanol (Tsanova et al., 2014). On such media, yeast must turn to respiratory growth in theabsence of fermentable carbon sources, which utilizes the oxidative phosphorylation pathway. Surprisingly, the rescue of growth deficiencies was notable in most of the tested DIS3 mutant strains during growth on glycerol-containing media. This is especially interested in light of bioinformatic analyses that have revealed a putative mitochondrial targeting sequence in DIS3, and several studies that have identified Dis3p in purified mitochondria in the absence of any other core RNA exosome components (Sickmann et al., 1032003; Turk, Das, Seibert, & Andrulis, 2013).This effect has been noted for dis3-EXO by previous studies; in this case, it appears that dis3-EXO’s fitness defects were caused by an excessive accumulation of reactive oxygen species (ROS) during fermentative growth (Tsanova et al., 2014). It is possible that ROS accumulation causes indiscriminate damage in DIS3 mutant strains that ultimately culminatesin DNA damage and CIN, however given the robust growth of alleles such as dis3-ts and dis3E729K under culturing conditions that induce CIN, this seems unlikely. Moreover, we did not see evidence of spontaneous DNA damage or sensitivity to DNA damaging agents (Chapter 2), suggesting that ROS-driven DNA damage is minimal in DIS3 mutants.An alternative possibility is that the slowing of mitotic progression imposed by respiratory growth is beneficial to cells with DIS3 mutation. Although I was unable to assay for CIN on non-fermentable media for this project, it is exciting to speculate that inhibiting fermentation would similarly rescue stability defects. Indeed, glycerol is a poor carbon source for yeast growth, and growth on glycerol-containing media extends mitotic length (Leitao & Kellogg, 2017). Further, slowing the cell cycle, particularly at G2/M, can rescue genome instability phenotypes, indicating that mitotic fidelity is higher when the cells have more time to coordinate mitotic processes and address damage and errors before they proceed with cell division (Vinton & Weinert, 2017).104Figure 4.1 Benomyl resistance in DIS3 mutants grown at 25°C. Spot dilution assays of the indicated alleles on YPD plates prepared with DMSO or the microtubule depolymerizing drug benomyl. Indicated strains were grown in liquid selective media at 30°C overnight (or 25°C for temperature sensitive strains), prepared to equal optical density (OD), then serially diluted. Liquid was transferred to the indicated media, and plates were incubated at the indicated temperature for 2 days prior to scanning.105106Figure 4.2 Spindle dynamics in DIS3 mutants assessed by fluorescent microscopy. (A) Live cell fluorescent microscopy of Tub1-GFP and DIC channels in asynchronous cultures visualized by fluorescent microscopy. Percent of mitotic spindles that were “anchored” at thebud neck; this was assessed by one end of the spindle being visibly within the bud neck. Samples from actively growing cultures were mounted on concanavalin-coated slides and imaged at 100x magnification. A minimum of 177 cells per replicate, and 720 cells in total across all replicates were counted. Significance was calculated using the Fisher’s exact test with Bonferroni-Holm p-value correction. (B) Quantification of the percent of cells from the described experiment exhibiting pre-anaphase versus mitotic spindles. Significance was calculated using the Fisher’s exact test with Bonferroni-Holm p-value correction.107108Figure 4.3 The dis3E729K allele decreases the proportion of arrested dam1-1 cells. (A) Triplicate budding index measurements of the indicated mutants show suppression of dam1-1 G2/M arrest after a 3 hour temperature shift to 37°C by dis3E729K. Samples from these cultures were mounted on concanavalin-coated slides and imaged at 100x magnification. Cells were scored by bud size; “large-budded” cells represent those with a bud 1/3 the size ofthe mother cell or greater. A minimum of 120 cells per replicate, and 431 cells in total across all replicates were counted. Error bars indicate SEM. Significance was calculated using the Fisher’s exact test with Bonferroni-Holm p-value correction. (B) Representative images of the wildtype and dam1-1 cultures after 3 hour incubation at 37°C.109Figure 4.4 DIS3 mutants do not exacerbate fitness defects of mad1Δ or mad2Δ. Ten-fold serial dilution spots of wildtype controls versus DIS3 mutants, mad1Δ and mad2Δ, and double mutants. Indicated strains were grown in liquid selective media at 30°C overnight (or 25°C for temperature sensitive strains), prepared to equal optical density (OD), then serially diluted. Liquid was transferred to the indicated media, and plates were incubated at the indicated temperature for 2 days prior to scanning.110111Figure 4.5 All DIS3 mutants have a functional SAC as assessed by ability to escape nocodazole arrest. Indicated strains were grown at permissive temperature, then arrested in S-phase with hydroxyurea for 2 hours (until >80% of cells exhibited large buds). Cells were then resuspended in media containing either DMSO or nocodazole (15 μL g/ml final), and returned to the 30°C incubator. Samples from these cultures taken 2 hours post-release were mounted on concanavalin-coated slides and imaged at 100x magnification. Cells were scoredby bud size; “large-budded” cells represent those with a bud 1/3 the size of the mother cell orgreater. A minimum of 100 cells per replicate, and 320 in total across all replicates were counted. Significance was calculated using the Fisher’s exact test with Bonferroni-Holm p-value correction.112Figure 4.6 Representative images of poly(A)-RNA FISH experiments in the indicated DIS3 mutant strains. Cultures were grown at permissive temperature to mid-log phase in selective media, then shifted to 37°C for 3 hours. Cells were fixed with formaldehyde and then co-stained for rDNA (FISH against ITS2) and poly(A) RNA (fluorescein isothiocyanate–labeled oligo-dT prob). Slides were mounted with mounting media/DAPI andimaged at 100x using Metamorph software. Scale bar (lower right) indicates 2μL m.113Figure 4.7 Fitness defects of DIS3 mutants are rescued on nonfermentable media. Ten-fold serial dilution spots of wildtype controls versus DIS3 mutants. Indicated strains were grown in liquid selective media at 30°C overnight (or 25°C for temperature sensitive strains),prepared to equal optical density (OD), then serially diluted in PBS. Liquid was transferred to YPD or YP-glycerol (YPG), and plates were incubated at the indicated temperature for 2 days prior to scanning.114Figure 4.8 Nonfermentable media has no effect on DIS3 mutant benomyl resistance. Ten-fold serial dilution spots of wildtype controls versus DIS3 mutants. Indicated strains were grown in liquid selective media at 30°C overnight (or 25°C for temperature sensitive strains), prepared to equal optical density (OD), then serially diluted in PBS. Liquid was transferred to YPD or YP-glycerol (YPG) containing DMSO or 15 μL g/ml benomyl, and plates were incubated at the indicated temperature for 2 days prior to scanning.1155 CONCLUSIONS AND FUTURE DIRECTIONS5.1 DIS3 separation-of-function alleles reveal specific contributions to genome stability maintenanceThis project aimed to identify not only the mechanism by which CIN is induced as a consequence of MM-associated point mutations, but also to gauge the different contributions (if any) of the two catalytic domains of this protein to its role in stability maintenance. First and foremost, disruption of activity in the exonuclease domain, but not endonuclease domain, induces CIN. This is an interesting result given the broad range of DIS3 mutations identified in cases of MM, which occur throughout the gene in catalytic and non-catalytic domains (Lionetti et al., 2015; Weißbach et al., 2014). It remains possible that it is not (or notonly) loss of DIS3 catalytic activity contributing to CIN, but instead a feature of structural malfunctions that may have influence on exosome assembly; this project did not explicitly explore this possibility but given the roles of Dis3 in the processing of extensive species of RNAs, and given current data indicating that the anchoring of Dis3 within the exosome complex is mediated at the endonuclease domain, we consider it more likely that this is indeed an exonuclease-specific effect (Schneider et al., 2009).The discussion surrounding the contribution of each catalytic domain to the processing of different transcripts is not fruitless speculation. RNA-protein crosslinking analysis following disruption of one or the other domain results in different enrichments of bound targets; in particular, PolIII-transcribed RNAs appeared to be predominantly targets of exonuclease function (Schneider et al., 2012). More recently, X-ray crystallography, electron microscopy, and experiments performed on strains carrying mutations in exosome core components predicted to occlude the primary RNA channel collectively demonstrate that some RNAs candirectly access the Dis3 exonuclease domain without being threaded through the non-catalytic exosome barrel (Delan-Forino, Schneider, & Tollervey, 2017; Han & van Hoof, 2016; Liu et al., 2014). Finally, MM-associated DIS3 exonuclease mutations are synthetic lethal with loss of activity in the endonuclease domain (Tomecki et al., 2014). The 116establishment of exonuclease domain mutations as CIN-inducing further supports the potential for the endonuclease domain as a drug target, and gives us finer resolution on whichtarget transcripts may mediate Dis3’s role in stability maintenance.While plasmid-specific effects were a common theme throughout this project, and while the plasmid-borne DIS3 mutants may exhibit phenotypes relevant to the current inquiry surrounding mechanisms of CIN induction, it is important to note that this cannot fully explain the dramatic genome instability phenotypes described for the dis3-EXO allele. This assertion hinges on the ALF data described in Chapter 2; both genomic DIS3 mutations, as well as dis3-EXO, induce CIN by this assay, while pWT and dis3-ENDO do not. 5.2 A potential role for Dis3 in mitotic exit signalling5.2.1 Expression changes in cell cycle-related transcripts are a general consequence of DIS3 mutationThe microarray analysis of dis3E729K reveals a significant downregulation of cell cycle transcripts (Table 3.1). This stands in contrast to previous RNA-seq analysis of a temperaturesensitive DIS3 mutant, which revealed upregulation of transcripts associated with the spindleorientation checkpoint (Smith et al., 2011). However, the temperature sensitive allele used in that study was isolated in a genetic screen for mutant yeast that accumulate poly(A)-RNA in the nucleus; my data indicates that this phenotype is specific to dis3-ts and does not occur in other DIS3 mutants tested (Figure 4.6). Therefore, differences in these datasets may be attributed to a fundamental difference in the downstream affects of these alleles.Regardless, a complete reversal in the effect on cell cycle regulation in DIS3 temperature sensitive versus point mutants is surprising, and unlikely to be the product of a difference in degree of activity loss between these DIS3 alleles. This seems to support the notion recently put forward by Eynden et al. that the Dis3 point mutants observed in MM datasets are gain offunction mutations, in contrast to a protein-destabilizing temperature sensitive allele which 117would necessarily be loss of function (Van den Eynden et al., 2015). Biochemical analysis of DIS3 MM-associated point mutants has previously indicated that they lose activity on key transcripts as assessed by northern blot; however, this does not preclude the possibility that DIS3 may simultaneously gain activity on other, untested transcripts (Tomecki et al., 2014).5.2.2 Cell cycle control of Dis3 and influence on mitotic spindle organizationRecently, Snee and colleagues identified a CDK1 phosphorylation site on DIS3 in D. melanogaster, and demonstrated that this phosphorylation site is conserved in C. elegans (Snee et al., 2016). This study also demonstrates an accumulation of overcondensed chromosomes and short, multipolar mitotic spindles in dis3 mutants rescued with a phosphomimetic DIS3 transgene; this is an interesting addition to earlier data in D. melanogaster analyzing pre-mitotic spindles, showing they are shorter, but increased in number (Smith et al., 2011). CDK1 carries out phosphorylation of key targets to trigger the initation of mitosis (Holt et al., 2009; McCloy et al., 2014). Dis3’s phosphorylation by CDK1 suggests that deactivation of Dis3’s exonuclease function is a key step in mitotic progression. It is interesting to speculate on the transcriptional consequences of temporary inhibition of much of Dis3’s catalytic activity for a portion of each cell cycle; presumably, this allows for the accumulation of target transcripts, some of which may influence the mitotic process. It is particularly telling that phosphomimetic Dis3 triggers overcondensation of chromosomes; this suggests that Dis3’s temporary inhibition by Cdk1 might promote chromosome condensation in a regulated way, and its reactivation is critical in preventing this process from proceeding to a damaging extent (Snee et al., 2016). It should be noted that the phosphorylation site appears to be conserved in S. cerevisiae, but its functionality has yet to be directly tested.Cdk1 targets are dephosphorylated by PP2A and Cdc14, both of which are active in anaphase(McCloy et al., 2014; Woodbury & Morgan, 2007). If the inactivation of Dis3 is necessary 118for promoting mitotic progression, and re-activation necessary for mitotic exit, this could explain both the apparent growth rate advantage of DIS3 mutant cells in the context of early mitotic disruption (by mutant alleles such as dam1-1, or drugs such as benomyl) yet massively disadvantage the cell at later mitotic stages where Dis3 is unable to be activated.5.3 Rescue on non-fermentable media suggests timing of cell cycle progression is key for production of CIN in DIS3 mutantsMy data demonstrating a rescue of growth for all DIS3 mutant alleles on glycerol further supports earlier data from Tsanova and colleagues revealing the rescue of dis3-EXO during respiratory growth (Tsanova et al., 2014). Previous research has indicated that glycerol slowsthe cell cycle, and further, slower cell cycle progression rescues chromosome segregation defects (Leitao & Kellogg, 2017; Vinton & Weinert, 2017). It may be that Dis3 interferes with pathways responsible for detecting kinetochore or spindle malfunctions; this could explain the disruption of arrest in the dis3E729K dam1-1 double mutant, and the evident increase in growth in the presence of benomyl. A lengthening of the cell cycle may allow for alternative pathways to address such disruptions before they progress to damage and aneuploidy. It is also possible that growth rate and CIN are completely uncoupled in DIS3 mutants. Indeed, dis3E729K and dis3-ts grow robustly at 30°C, yet both exhibit an increase in CIN at thistemperature. Instead, it may be the case that the temperature sensitivity and slow growth phenotypes are a product of other effects of DIS3 mutation. For example, earlier work demonstrated dis3-EXO accumulates ROS during fermentation; it is possible that this hyperaccumulation is the root cause of the slow growth of this strain, yet this study did not go on to analyze if ROS similarly accumulates during growth on glycerol (Tsanova et al., 2014). This accumulation could have substantial effects not only on cellular components broadly (in the form of indiscriminant damage), but also on ROS-sensitive systems that influence gene expression; indeed, the exosome has been identified as a member of one of the decay pathways responsible for turning over ROS-regulated mRNAs, including those that119code for transcription factors, cyclins, and heat shock proteins (Abdelmohsen, Kuwano, Kim,& Gorospe, 2008). Further research is required to fully elucidate the connection of these predicted alterations in the context of DIS3 mutation, and their influence on the promotion ofCIN.5.4 Implications for DIS3 mutation in multiple myelomaMM cells frequently exhibit aneuploidies, GIN, and considerable intra-tumoural diversity (Neri & Bahlis, 2013). DIS3 mutation is highly correlated with the NHDMM subtype; these cancers often carry recurrent IgH translocations, and have a near-diploid or hypodiploid chromosome number (Fonseca 2003). In the study that originally identified the link between IgH translocation and NHDMM, the authors speculate that this subtype may be “permissive” to chromosome loss, moreso than the HDMM subtype, because such translocations so heavily promote growth signalling (Fonseca 2003).It is notable that the hypodiploid subset of NHDMM has a higher rate of monosomies, exhibits upregulation of growth stimulating pathways through CCND2, MMSET, and FGFR3, and has an even more aggressive phenotype than near-diploid NHDMM cases (Van Wier et al., 2013). It is unclear if the frequency of DIS3 mutations differs in near-diploid versus hypodiploid NHDMM; however, chromosome 13 monosomy (and therefore, LOH at DIS3) is more prevalent in hypodiploid cases. If spindle malfunction and resulting aneuploidy is indeed the CIN mechanism induced by DIS3 mutation, it is interesting to speculate that DIS3 mutation itself may contribute to the chromosome loss phenotype in aggressive NHDMM cases; indeed, some researchers have speculated that hypodiploid MM may represent a more advanced stage of NHDMM, having originated from a near-diploid precursor (Van Wier et al., 2013). Further analysis of the mechanism by which DIS3 influences chromosome segregation, in the context of co-occuring genetic lesions influencingchromosome stability, will delineate the possible contribution of loss-of-function mutations to chromosome loss phenotypes in MM cells.1205.5 Limitations to the chosen system 5.5.1 Potential background effects of BY4741 that may influence these data. Strain-specific background effects are an unavoidable feature of model organism research, and in the case of DIS3, there is known variability in allele phenotypes between the most popular budding yeast backgrounds. The protein Ssd1 participates in cytoplasmic RNA regulation and is suspected to be partially redundant with Dis3, as this enzyme is absent in the W303 background and phenotypes of DIS3 mutants have been shown to be more severe in this context compared to our background (BY4741) (Schneider et al., 2009). As well, while DIS3 is essential in yeast, plasmid shuffle experiments have allowed the isolation of strains carrying the catalytically inactive dis3-ENDO-EXO allele, indicating that under some conditions, other enzymes can support viability presumably by complementing its endonucleolytic and/or exonucleolytic activity (Schneider et al., 2009). 5.5.2 System differences in S. cerevisiae vs. H. sapiensThere are key cellular differences that may influence the translational nature of data produced in the budding yeast model. Most relevant to the current project is the nature of the S. cerevisiae centromere; instead of having a regional centromere with a broad pericentromeric region and multiple microtubules contact points, budding yeast have a 150 base pair point centromere that facilitates contact with one spindle (Joglekar et al., 2008). This feature difference is important given the demonstrated role for exosome-mediated silencing of pericentromeric transcripts in other systems, and the necessity of careful expression regulation at these areas for proper kinetochore function and subsequent chromosome segregation (Murakami et al., 2007; Ohkuni & Kitagawa, 2011, 2012). Although centromeric transcription regulation is also a feature of stability maintenance in budding yeast, and deletion of the RNA exosome cofactor Trf4 induces accumulation of cryptic centromeric transcripts, Dis3’s role in degrading these targets has not been examined (Houseley, Kotovic, El Hage, & Tollervey, 2007). Budding yeast are also unique in the sense 121that they lack a functional RNAi pathway. Work done in other systems has demonstrated that the RNA exosome participates in gene silencing by RNAi, either by directly processing miRNAs, or by degrading transcripts that regulate miRNAs (Huntzinger & Izaurralde, 2011; Segalla et al., 2015). While the MM-associated point mutations studied in this research are at conserved sites, there remain many aspects of the cellular context present in B cells that simply cannot be recapitulated in budding yeast. First and foremost, the exosome cooperates with activation-induced cytidine deaminase (AID) to mediate class switch recombination (CSR) and somatic hypermutation at immunoglobulin genes, processes that use controlled DNA damage to produce B cell diversity (Pefanis et al., 2014). Immunoglobulin genes are also the most common site of recurrent translocations in multiple myeloma, and it is generally believed that aberrant targeting of AID is a contributing factor to the production of the widespread genetic damage seen in this disease (Robbiani & Nussenzweig, 2012). Mutation of DIS3 mayvery well interfere with this process; indeed, Cre-mediated loss of the exosome core component EXOSC3 impaires CSR in mice (Pefanis & Basu, 2015).5.6 ConclusionGiven the prevalence of DIS3 plasmid-borne alleles in use for descriptive studies on Dis3’s function, the significant evidence for a plasmid-based effect on cell cycle progression, and bearing in mind that data from our group and others support a role for Dis3 in the coordination of mitotic timing, these data serve as a cautionary note for future research in this area. Development of a reliable antibody against the S. cerevisiae Dis3 protein would be a valuable first step in dissecting whether expression levels vary between these mutants, and if gene dosage variations influence data collected to date. Unfortunately, my efforts to optimize a Western blotting protocol for the quantification of Dis3 protein were unsuccessful,as there are no commercially available antibodies raised against Dis3 from S. cerevisiae, and two antibodies raised against hDIS3 proved to be too nonspecific to yield interpretable data in yeast. 122This project did not address potential epigenetic explanations for the phenotypes presented inthis thesis. For example, silencing loss at the MAT locus can make cells sensitive to pheromones from the same mating type, and could allow for mating that would be detectable by the ALF assay (Pillus & Rine, 1989). Additionally, silencing loss at MAT loci in budding yeast can be induced by a variety of spontaneous aneuploidies, not necessarily just those involving ChrIII (Mulla et al., 2017). The exosome’s activities in degrading noncoding RNAs influence silencing at rDNA spacers and telomeric loci, as well as enhancer activity, which could have downstream consequences on transcription more broadly (Pefanis et al., 2015; Vasiljeva, Kim, Terzi, Soares, & Buratowski, 2008). The diversity of DIS3 targets provides many potential explanations for any given effect; further research dissecting these complex systems is required to pinpoint targets of interest.This project aimed to connect DIS3 point mutations at conserved sites with the induction of CIN using S. cerevisiae as a model system. I have demonstrated that these mutations do promote CIN, although details of the exact mechanism of CIN induction remain subjects for further inquiry. 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Retrieved from http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=56904&tool=pmcentrez&rendertype=abstract150APPENDICESAppendix 1. gBlock sequences used for DIS3 mutant construction.Block Name Block sequence (5’ → 3’)3’ DIS3 + URA3 CAGAAAGCACAGAAACGCCCAATTCGCCGGTAGGGCAAGCATAGAATACTATGTCGGGCAAGTAATGAGGAATAACGAGTCCACAGAAACTGGATATGTTATTAAGGTATTTAATAATGGTATAGTCGTACTGGTTCCCAAGTTTGGCGTGGAAGGCTTGATAAGACTGGATAATTTGACTGAGGATCCTAACTCAGCCGCTTTTGATGAGGTGGAATACAAATTAACCTTTGTGCCTACAAATTCAGATAAACCGAGGGATGTTTACGTTTTCGATAAGGTCGAAGTTCAAGTTAGGTCGGTGATGGATCCAATTACTAGCAAGCGTAAGGCAGAATTATTGTTAAAATAGAAGCTTTTCAATTCATCTTTTTTTTTTTTGTTCTTTTTTTTGATTCCGGTTTCTTTGAAATTTTTTTGATTCGGTAATCTCCGAGCAGAAGGAAGAACGAAGGAAGGAGCACAGACTTAGATTGGTATATATACGCATATGTGGTGTTGAAGAAACATGAAATTGCCCAGTATTCTTAACCCAACTGCACAGAACAAAAACCTGCAGGAAACGAAGATAAATCATGTCGAAAGCTACATATAAGGAACGTGCTGCTACTCATCCTAGTCCTGTTGCTGCCAAGCTATTTAATATCATGCACGAAAAGCAAACAAACTTGTGTGCTTCATTGGATGTTCGTACCACCAAGGAATTACTGGAGTTAGTTGAAGCATTAGGTCCCAAAATTTGTTTACTAAAAACACATGTGGATATCTTGACTGATTTTTCCATGGAGGGCACAGTTAAGCCGCTAAAGGCATTATCCGCCAAGTACAATTTTTTACTCTTCGAAGACAGAAAATTTGCTGACATTGGTAATACAGTCAAATTGCAGTACTCTGCGGGTGTATACAGAATAGCAGAATGGGCAGACATTACGAATGCACACGGTGTGGTGGGCCCAGGTATTGTTAGCGGTTTGAAGCAGGCGGCGGAAGAAGTAACAAAGGAACCTAGAGGCCTTTTGATGTTAGCAGAATTGTCATGCAAGGGCTCCCTAGCTACTGGAGAATATACTAAGGGTACTGTTGACATTGCGAAGAGCGACAAAGATTTTGTTATCGGCTTTATTGCTCAAAGAGACATGGGTGGAAGAGATGAAGGTTACGATTGGTTGATTATGACACCCGGTGTGGGTTTAGATGACAAGGGAGACGCATTGGGTCAACAGTATAGAACCGTGGATGATGTGGTCTCTACAGGATCTGACATTATTATTGTTGGAAGAGGACTATTTGCAAAGGGAAGGGATGCTAAGGTAGAGGGTGAACGTTACAGAAAAGCAGGCTGGGAAGCATATTTGAGAAGATGCGGCCAGCAAAACTAAAAAACTGTATTATAAGTAAATGCATGTATACTAAACTCACAAATTAGAGCTTCAATTTAATTATATCAG151Block Name Block sequence (5’ → 3’)TTATTACCCGGGAATCTCGGTCGTAATGATTTCTATAATGACGAAAAAAAAAAAATTGGAAAGAAAAAGCTTTCGCGAGCCCAGGGTGTATTTAAAACATTTAAATGTATATTCTTTCTTAATCGTATCTT152Block Name Block sequence (5’ → 3’)D551N_g1651a gBlockCTAGAATGTTTGCCCGCAGAAGGCCACGATTGGAAGGCCCCAACAAAACTGGACGATCCTGAGGCTGTTTCAAAGGATCCATTATTGACAAAAAGAAAGGATCTCAGAGATAAACTTATATGTAGTATCGATCCTCCAGGATGTGTTGATATTAACGATGCCCTACATGCGAAAAAGCTTCCAAACGGTAATTGGGAAGTTGGTGTTCATATTGCTGATGTTACTCACTTCGTTAAACCGGGCACTGCCCTGGATGCGGAAGGTGCTGCAAGAGGTACTTCTGTATATTTGGTAGACAAACGTATTGACATGCTGCCCATGCTTCTAGGTACCGACCTGTGTTCTCTAAAACCATACGTTGATAGATTCGCATTCTCTGTCATTTGGGAATTGGATGATAGTGCTAATATTGTAAATGTTAATTTTATGAAATCCGTCATCAGATCTAGAGAAGCTTTCTCATACGAACAAGCACAACTGAGAATTGATGACAAAACCCAAAATGATGAATTAACGATGGGTATGAGGGCTCTCTTGAAATTGTCTGTAAAACTGAAGCAAAAGAGACTAGAGGCAGGTGCCTTGAACTTAGCTTCTCCTGAGGTTAAGGTCCATATGGATAGTGAGACTTCAGATCCAAATGAAGTGGAAATCAAAAAATTACTGGCGACAAATTCTTTAGTTGAAGAATTTATGTTGTTGGCTAATATATCAGTGGCAAGGAAGATATACGATGCCTTCCCTCAAACGGCGATGCTAAGAAGACACGCAGCTCCGCCATCTACCAATTTTGAAATCTTAAATGAAATGTTAAACACAAGAAAGAATATGTCAATTTCGTTGGAATCGTCCAAGGCCTTGGCCGATTCTTTAGACAGGTGTGTGGATCCCGAAGATCCATATTTTAATACATTGGTTCGTATCATGTCGACTCGCTGTATGATGGCAGCCCAATACTTTTATTCTGGAGCTTATTCTTATCCTGACTTTAGACACTATGGTTTAGCCGTTGATATCTACACACATTTCACATCACCTATTAGACGTTACTGTGATGTTGTGGCCCATAGACAATTAGCAGGTGCCATTGGGTATGAACCCCTAAGTTTGACTCATCGTGATAAGAATAAAATGGACATGATTTGCAGAAATATCAACAGAAAGCACAGAAACGCCCAATTCGCCGGTAGGGCAAGCATAGAATACTATGTCGGGCAAGTAATGAGGAATAACGAGTCCACAGAAACTGGATATGTTATTAAGGTATTTAATAATGGTATAGTCGTACTGGTTCCCAA153Block Name Block sequence (5’ → 3’)E729K_g2185a gBlockCTAGAATGTTTGCCCGCAGAAGGCCACGATTGGAAGGCCCCAACAAAACTGGACGATCCTGAGGCTGTTTCAAAGGATCCATTATTGACAAAAAGAAAGGATCTCAGAGATAAACTTATATGTAGTATCGATCCTCCAGGATGTGTTGATATTGACGATGCCCTACATGCGAAAAAGCTTCCAAACGGTAATTGGGAAGTTGGTGTTCATATTGCTGATGTTACTCACTTCGTTAAACCGGGCACTGCCCTGGATGCGGAAGGTGCTGCAAGAGGTACTTCTGTATATTTGGTAGACAAACGTATTGACATGCTGCCCATGCTTCTAGGTACCGACCTGTGTTCTCTAAAACCATACGTTGATAGATTCGCATTCTCTGTCATTTGGGAATTGGATGATAGTGCTAATATTGTAAATGTTAATTTTATGAAATCCGTCATCAGATCTAGAGAAGCTTTCTCATACGAACAAGCACAACTGAGAATTGATGACAAAACCCAAAATGATGAATTAACGATGGGTATGAGGGCTCTCTTGAAATTGTCTGTAAAACTGAAGCAAAAGAGACTAGAGGCAGGTGCCTTGAACTTAGCTTCTCCTGAGGTTAAGGTCCATATGGATAGTGAGACTTCAGATCCAAATGAAGTGGAAATCAAAAAATTACTGGCGACAAATTCTTTAGTTGAAAAATTTATGTTGTTGGCTAATATATCAGTGGCAAGGAAGATATACGATGCCTTCCCTCAAACGGCGATGCTAAGAAGACACGCAGCTCCGCCATCTACCAATTTTGAAATCTTAAATGAAATGTTAAACACAAGAAAGAATATGTCAATTTCGTTGGAATCGTCCAAGGCCTTGGCCGATTCTTTAGACAGGTGTGTGGATCCCGAAGATCCATATTTTAATACATTGGTTCGTATCATGTCGACTCGCTGTATGATGGCAGCCCAATACTTTTATTCTGGAGCTTATTCTTATCCTGACTTTAGACACTATGGTTTAGCCGTTGATATCTACACACATTTCACATCACCTATTAGACGTTACTGTGATGTTGTGGCCCATAGACAATTAGCAGGTGCCATTGGGTATGAACCCCTAAGTTTGACTCATCGTGATAAGAATAAAATGGACATGATTTGCAGAAATATCAACAGAAAGCACAGAAACGCCCAATTCGCCGGTAGGGCAAGCATAGAATACTATGTCGGGCAAGTAATGAGGAATAACGAGTCCACAGAAACTGGATATGTTATTAAGGTATTTAATAATGGTATAGTCGTACTGGTTCCCAA154Block Name Block sequence (5’ → 3’)R847K_g2540a gBlockCTAGAATGTTTGCCCGCAGAAGGCCACGATTGGAAGGCCCCAACAAAACTGGACGATCCTGAGGCTGTTTCAAAGGATCCATTATTGACAAAAAGAAAGGATCTCAGAGATAAACTTATATGTAGTATCGATCCTCCAGGATGTGTTGATATTGACGATGCCCTACATGCGAAAAAGCTTCCAAACGGTAATTGGGAAGTTGGTGTTCATATTGCTGATGTTACTCACTTCGTTAAACCGGGCACTGCCCTGGATGCGGAAGGTGCTGCAAGAGGTACTTCTGTATATTTGGTAGACAAACGTATTGACATGCTGCCCATGCTTCTAGGTACCGACCTGTGTTCTCTAAAACCATACGTTGATAGATTCGCATTCTCTGTCATTTGGGAATTGGATGATAGTGCTAATATTGTAAATGTTAATTTTATGAAATCCGTCATCAGATCTAGAGAAGCTTTCTCATACGAACAAGCACAACTGAGAATTGATGACAAAACCCAAAATGATGAATTAACGATGGGTATGAGGGCTCTCTTGAAATTGTCTGTAAAACTGAAGCAAAAGAGACTAGAGGCAGGTGCCTTGAACTTAGCTTCTCCTGAGGTTAAGGTCCATATGGATAGTGAGACTTCAGATCCAAATGAAGTGGAAATCAAAAAATTACTGGCGACAAATTCTTTAGTTGAAGAATTTATGTTGTTGGCTAATATATCAGTGGCAAGGAAGATATACGATGCCTTCCCTCAAACGGCGATGCTAAGAAGACACGCAGCTCCGCCATCTACCAATTTTGAAATCTTAAATGAAATGTTAAACACAAGAAAGAATATGTCAATTTCGTTGGAATCGTCCAAGGCCTTGGCCGATTCTTTAGACAGGTGTGTGGATCCCGAAGATCCATATTTTAATACATTGGTTCGTATCATGTCGACTCGCTGTATGATGGCAGCCCAATACTTTTATTCTGGAGCTTATTCTTATCCTGACTTTAGACACTATGGTTTAGCCGTTGATATCTACACACATTTCACATCACCTATTAAACGTTACTGTGATGTTGTGGCCCATAGACAATTAGCAGGTGCCATTGGGTATGAACCCCTAAGTTTGACTCATCGTGATAAGAATAAAATGGACATGATTTGCAGAAATATCAACAGAAAGCACAGAAACGCCCAATTCGCCGGTAGGGCAAGCATAGAATACTATGTCGGGCAAGTAATGAGGAATAACGAGTCCACAGAAACTGGATATGTTATTAAGGTATTTAATAATGGTATAGTCGTACTGGTTCCCAA155Appendix 2. Significantly altered genes in microarray comparing “WT” DIS3::URA3 vs. dis3E729K, from greatest downregulation to greatest upregulationTranscript Cluster IDWT Bi-weight Avg Signal (log2)dis3E729K Bi-weight Avg Signal (log2)WT StandardDeviationdis3E729K Standard DeviationFold Change (linear) (WT vs. dis3E729K)ANOVA p-value (WT vs. dis3E729K)FDR p-value (WT vs. dis3E729K)Gene Symbol1774239_at 10.66 7.3 0.1 0.3 -10.26 0.004464 0.270933 YGR079W1774092_at 10.85 7.6 0.08 0.62 -9.52 0.018021 0.275438 RRN111774592_at 8.37 5.13 0.52 0.04 -9.46 0.012615 0.270933 SPS41771495_at 10.64 7.42 0.22 0.54 -9.3 0.015866 0.27356 HLR11773809_at 10.37 7.21 0.59 0.46 -8.94 0.026753 0.288554 AQR11778319_at 10.51 7.55 0.32 0.7 -7.74 0.032512 0.292905 PCL11772275_at 9.64 6.72 0 0.95 -7.57 0.049411 0.310964 JJJ31777207_at 10.22 7.45 0.01 0.69 -6.79 0.029922 0.289797 CLB61775720_at 10.96 8.29 0.3 0.47 -6.37 0.021445 0.277191 YOX11778739_at 10.87 8.2 0.23 0.58 -6.36 0.026326 0.28851 SFG11777214_at 8.32 5.8 0.06 0.63 -5.72 0.030419 0.289797 YNL162W-A1779227_at 9.83 7.43 0.24 0.48 -5.29 0.024025 0.282911 CDC61772612_at 8.22 5.86 0.1 0.35 -5.12 0.011867 0.270933 BUB11779772_at 10.53 8.25 0.4 0.43 -4.86 0.032233 0.292905 YEH11779804_at 10.31 8.03 0.1 0.48 -4.86 0.022732 0.280708 TRF51777796_at 9.83 7.61 0.16 0.2 -4.65 0.006716 0.270933 TEA11773158_at 10.86 8.64 0.08 0.43 -4.65 0.018591 0.275438 VTS1156Transcript Cluster IDWT Bi-weight Avg Signal (log2)dis3E729K Bi-weight Avg Signal (log2)WT StandardDeviationdis3E729K Standard DeviationFold Change (linear) (WT vs. dis3E729K)ANOVA p-value (WT vs. dis3E729K)FDR p-value (WT vs. dis3E729K)Gene Symbol1779541_at 10.63 8.42 0.13 0.29 -4.63 0.010204 0.270933 GFD21775866_at 11.57 9.45 0.09 0.52 -4.33 0.030037 0.289797 BFR21769876_at 8.86 6.76 0.33 0.13 -4.26 0.014283 0.271876 YOR338W1771109_at 10.95 8.87 0.53 0.05 -4.24 0.030959 0.290792 WSC41775495_at 10.88 8.82 0.09 0.27 -4.19 0.009432 0.270933 MCD11774186_at 10.34 8.38 0.03 0.21 -3.88 0.00587 0.270933 SSF11778919_at 12.66 10.7 0.04 0.57 -3.87 0.039835 0.302173 RNR11778085_at 10.61 8.67 0.08 0.43 -3.86 0.024449 0.284229 IFH11779073_at 11.29 9.35 0.1 0.59 -3.83 0.044486 0.306325 UTP181779136_at 11.64 9.72 0.08 0.56 -3.8 0.040063 0.302173 RSA41772631_at 11.05 9.12 0.06 0.47 -3.78 0.029555 0.289797 RFU11779423_at 8.07 6.19 0.12 0.45 -3.69 0.029895 0.289797 SSP21778270_at 11.5 9.66 0.08 0.59 -3.59 0.0486 0.310889 HO1773591_at 10.82 8.98 0.37 0.15 -3.59 0.022798 0.280876 CLN11770790_at 10.49 8.68 0.1 0.42 -3.51 0.027394 0.288554 SKG61779544_at 11.22 9.42 0.13 0.46 -3.49 0.03359 0.296229 LCP51775481_at 9.73 7.93 0.03 0.43 -3.48 0.028124 0.288554 IBD21773118_at 10.16 8.42 0.01 0.5 -3.34 0.038453 0.300492 DUS11775641_at 10.35 8.61 0.18 0.43 -3.33 0.034602 0.297443 SAP1851778857_at 10.65 8.94 0.52 0.08 -3.29 0.043889 0.306071 DUR1,21776554_at 9.02 7.3 0.18 0.03 -3.29 0.005665 0.270933 MSH5157Transcript Cluster IDWT Bi-weight Avg Signal (log2)dis3E729K Bi-weight Avg Signal (log2)WT StandardDeviationdis3E729K Standard DeviationFold Change (linear) (WT vs. dis3E729K)ANOVA p-value (WT vs. dis3E729K)FDR p-value (WT vs. dis3E729K)Gene Symbol1771069_at 9.82 8.11 0.05 0.24 -3.27 0.01044 0.270933 YLR063W1770147_at 11.09 9.39 0.14 0.44 -3.25 0.035655 0.297443 DBP81769863_at 8.96 7.26 0.08 0.32 -3.24 0.018751 0.275438 RRN71772101_at 9.89 8.2 0.1 0.48 -3.23 0.039588 0.302173 OGG11775497_at 10.17 8.49 0.16 0.23 -3.19 0.013396 0.270933 YIL014C-A1772054_at 8.27 6.6 0.09 0.09 -3.17 0.002856 0.270933 BNA21777938_at 9.64 7.99 0.02 0.36 -3.14 0.022943 0.281147 CWC21775116_at 11.09 9.44 0 0.3 -3.14 0.015847 0.27356 GIN41771588_at 9.51 7.87 0.14 0.21 -3.13 0.011911 0.270933 SPT211778296_at 10.18 8.54 0.16 0.41 -3.12 0.033695 0.296229 CSI21779753_at 9.73 8.09 0.05 0.25 -3.11 0.011871 0.270933 KCC41776993_at 10.95 9.32 0.04 0.29 -3.11 0.015319 0.27356 MNN11776157_at 10.67 9.05 0.23 0.09 -3.08 0.011317 0.270933 BAS11771835_at 11.28 9.67 0.15 0.44 -3.06 0.03873 0.301888 UTP251773290_at 9.94 8.33 0.07 0.46 -3.06 0.039463 0.302173 PPR11769973_at 12.67 11.06 0.02 0.12 -3.05 0.002914 0.270933 CLB11770442_at 8.95 7.35 0.06 0.12 -3.04 0.003524 0.270933 BNR11774820_at 10.06 8.46 0.11 0.44 -3.04 0.037106 0.297994 RRP361777823_s_at 9.07 7.49 0.09 0.32 -3.01 0.021453 0.277191 YLR312C-B1771269_at 10.25 8.69 0.01 0.14 -2.94 0.004042 0.270933 CDC451771359_at 10.57 9.02 0.14 0.46 -2.93 0.044127 0.306071 IPI1158Transcript Cluster IDWT Bi-weight Avg Signal (log2)dis3E729K Bi-weight Avg Signal (log2)WT StandardDeviationdis3E729K Standard DeviationFold Change (linear) (WT vs. dis3E729K)ANOVA p-value (WT vs. dis3E729K)FDR p-value (WT vs. dis3E729K)Gene Symbol1773154_at 11.13 9.59 0.04 0.42 -2.93 0.034851 0.297443 RCL11778275_at 11.85 10.32 0.07 0.44 -2.9 0.039112 0.302173 UTP91777513_at 7.05 5.52 0.18 0.38 -2.89 0.035666 0.297443 SPO211769929_at 12.41 10.89 0.01 0.48 -2.88 0.046655 0.308624 RPL22B1779881_at 8.17 6.65 0.14 0.23 -2.87 0.015718 0.27356 EST21769317_at 9.45 7.93 0.09 0.38 -2.87 0.031908 0.292468 DAT11771500_at 9.87 8.35 0.22 0.2 -2.87 0.01839 0.275438 CTF181779856_at 10.8 9.28 0.03 0.13 -2.86 0.004072 0.270933 SMC31775884_at 10.85 9.38 0.14 0.15 -2.78 0.009322 0.270933 RAX21772865_at 8.9 7.42 0.01 0 -2.78 1.5E-05 0.082915 YGK31776623_at 9.88 8.41 0.03 0.01 -2.77 0.000205 0.17589 PTP31774270_at 10.17 8.7 0.01 0.24 -2.77 0.013545 0.270933 TOF11778331_at 8.99 7.53 0.24 0.09 -2.75 0.015193 0.27356 YDL211C1773291_at 5.42 3.96 0.17 0.01 -2.75 0.007042 0.270933 YHL012W1777114_at 9.97 8.53 0.07 0.08 -2.72 0.002585 0.270933 CLB51771565_at 10.64 9.2 0.03 0.36 -2.71 0.030937 0.290792 ATC11772374_at 9.95 8.51 0.14 0.24 -2.71 0.017742 0.275438 YJR054W1777319_at 8.39 6.95 0.04 0.26 -2.7 0.016908 0.275438 SPO161771711_at 10.25 8.82 0.01 0.27 -2.69 0.01773 0.275438 SEN341769860_at 6.94 5.51 0.07 0.3 -2.68 0.023151 0.281147 HTL11776348_at 10.15 8.73 0.17 0.3 -2.68 0.027907 0.288554 FAL1159Transcript Cluster IDWT Bi-weight Avg Signal (log2)dis3E729K Bi-weight Avg Signal (log2)WT StandardDeviationdis3E729K Standard DeviationFold Change (linear) (WT vs. dis3E729K)ANOVA p-value (WT vs. dis3E729K)FDR p-value (WT vs. dis3E729K)Gene Symbol1773124_at 9.68 8.26 0.08 0.22 -2.67 0.013663 0.270933 YDR179W-A1772524_at 10.14 8.72 0.03 0.21 -2.67 0.011231 0.270933 YML108W1772793_at 10.84 9.43 0.13 0.17 -2.66 0.01152 0.270933 HCM11770541_at 10.51 9.1 0.02 0.33 -2.66 0.026758 0.288554 EFG11774467_at 9.35 7.94 0.04 0.28 -2.66 0.019545 0.275438 PZF11777007_at 11.56 10.15 0.15 0.31 -2.65 0.029179 0.289797 HSL11770115_at 8.61 7.2 0.21 0.4 -2.65 0.047312 0.308973 SPH11770607_at 11.27 9.86 0.14 0.37 -2.65 0.036642 0.297443 SGD11769336_at 9.23 7.83 0.09 0.21 -2.65 0.012364 0.270933 SPC981776526_at 11.29 9.89 0.03 0.29 -2.63 0.020744 0.276248 POL11770878_at 10.31 8.93 0.05 0.06 -2.62 0.001521 0.270933 ELG11779549_at 10.43 9.04 0.06 0.29 -2.62 0.022556 0.280582 DFR11772485_at 9.48 8.1 0.04 0.25 -2.61 0.015818 0.27356 SLK191775330_at 10.72 9.35 0.04 0.27 -2.6 0.018406 0.275438 KIN41776685_at 10.17 8.79 0.13 0.17 -2.6 0.012438 0.270933 RLF21769420_at 11.13 9.76 0.03 0.21 -2.59 0.011943 0.270933 PDS51777921_at 10.04 8.67 0.32 0.3 -2.58 0.047057 0.308973 NOP191773476_at 10.38 9.01 0 0.32 -2.58 0.026128 0.28851 YMR185W1770928_at 9.92 8.56 0 0.25 -2.57 0.01653 0.275438 YCG11779249_at 11.31 9.96 0.14 0.41 -2.56 0.047686 0.308973 ECM11777198_at 9.83 8.49 0.04 0.15 -2.53 0.0063 0.270933 YJR030C160Transcript Cluster IDWT Bi-weight Avg Signal (log2)dis3E729K Bi-weight Avg Signal (log2)WT StandardDeviationdis3E729K Standard DeviationFold Change (linear) (WT vs. dis3E729K)ANOVA p-value (WT vs. dis3E729K)FDR p-value (WT vs. dis3E729K)Gene Symbol1770834_at 9.66 8.32 0.02 0.2 -2.53 0.010976 0.270933 MIF21770864_at 8.98 7.65 0.11 0.24 -2.53 0.018556 0.275438 RAD531776151_at 9.52 8.18 0.11 0.27 -2.52 0.022759 0.280708 MTO11770084_at 11.08 9.74 0.32 0.23 -2.52 0.04171 0.304282 FAA31776864_at 9.27 7.95 0.01 0.1 -2.51 0.002796 0.270933 SAS21775835_at 10.11 8.78 0.1 0.23 -2.51 0.016837 0.275438 ACM11770812_at 9.85 8.52 0.37 0.04 -2.5 0.038008 0.299899 ZAP11770227_at 8.13 6.81 0.06 0.3 -2.5 0.026427 0.28851 YPL216W1778903_at 9.26 7.94 0.17 0.02 -2.5 0.007858 0.270933 YPL068C1771552_at 10.14 8.82 0.02 0.41 -2.49 0.044653 0.306469 RAD91776757_at 9.75 8.43 0.21 0.29 -2.49 0.035932 0.297443 CIN21777978_at 11.16 9.85 0.07 0.34 -2.48 0.033176 0.295476 BUD211769717_at 9.61 8.31 0.06 0.19 -2.47 0.011578 0.295476 NTO11777927_at 10.99 9.69 0.15 0.3 -2.46 0.031952 0.292468 DHR21776496_at 10.16 8.86 0.07 0.15 -2.46 0.008609 0.270933 BUL21779398_at 10.02 8.73 0.02 0.39 -2.45 0.043763 0.306071 LTE11770943_at 10.7 9.41 0.22 0.24 -2.45 0.029834 0.289797 RNT11777311_at 10.75 9.46 0.04 0.31 -2.44 0.027464 0.288554 ASG11778806_at 11.76 10.48 0.22 0.15 -2.43 0.020787 0.276248 MSB21778685_at 11.23 9.96 0.03 0.41 -2.41 0.049037 0.310889 UTP61777481_at 9.94 8.68 0.18 0.06 -2.39 0.011673 0.270933 JJJ1161Transcript Cluster IDWT Bi-weight Avg Signal (log2)dis3E729K Bi-weight Avg Signal (log2)WT StandardDeviationdis3E729K Standard DeviationFold Change (linear) (WT vs. dis3E729K)ANOVA p-value (WT vs. dis3E729K)FDR p-value (WT vs. dis3E729K)Gene Symbol1772854_at 9.37 8.12 0.22 0.06 -2.38 0.015787 0.27356 ESC81772209_at 9.76 8.51 0.11 0.32 -2.37 0.034993 0.297443 SHQ11773767_at 9.5 8.25 0.04 0.12 -2.37 0.005429 0.270933 PMS11771326_at 6.84 5.6 0.11 0.12 -2.36 0.008313 0.270933 SPR11769443_at 7.85 6.62 0.1 0.05 -2.35 0.004125 0.270933 PLM21773678_at 10.15 8.91 0.04 0.34 -2.35 0.035411 0.297443 YOR093C1776763_at 11.14 9.91 0.19 0.22 -2.35 0.027148 0.288554 CLN21775962_at 11.05 9.82 0.08 0.31 -2.35 0.031993 0.292468 NOP531780147_at 9.5 8.28 0.06 0.23 -2.34 0.018182 0.275438 ROG11776391_at 10.65 9.42 0.13 0.23 -2.34 0.021981 0.278148 MSB11779284_at 9.12 7.9 0.07 0.35 -2.33 0.041001 0.303671 PET3091779207_at 10.26 9.06 0.34 0.02 -2.31 0.036767 0.297868 YKL068W-A1770257_at 11.28 10.07 0.1 0.23 -2.31 0.021696 0.278148 EMW11778951_at 9.16 7.95 0.01 0.22 -2.31 0.015719 0.27356 AVO11773972_at 10.24 9.04 0.06 0.24 -2.3 0.020341 0.276248 MRC11770409_at 9.49 8.29 0.13 0.2 -2.3 0.018959 0.275438 YER137C1777580_at 10.95 9.75 0.23 0.3 -2.3 0.046393 0.308012 RNH2031774618_at 10.07 8.87 0.03 0.05 -2.29 0.001254 0.270933 DAD41779931_at 10.36 9.17 0.25 0.16 -2.28 0.030275 0.289797 SIR21775635_at 9.88 8.69 0.02 0.1 -2.28 0.00364 0.270933 SMC51779312_at 9.4 8.22 0.02 0.34 -2.27 0.039179 0.302173 MSH3162Transcript Cluster IDWT Bi-weight Avg Signal (log2)dis3E729K Bi-weight Avg Signal (log2)WT StandardDeviationdis3E729K Standard DeviationFold Change (linear) (WT vs. dis3E729K)ANOVA p-value (WT vs. dis3E729K)FDR p-value (WT vs. dis3E729K)Gene Symbol1774012_at 6.91 5.74 0.12 0.2 -2.26 0.019755 0.275438 DAL11772438_at 10.58 9.4 0.03 0.14 -2.26 0.007783 0.270933 TOP11778358_at 6.76 5.58 0.28 0.1 -2.26 0.029785 0.289797 HES11776483_at 10.96 9.8 0.03 0.32 -2.24 0.036417 0.297443 BUD31770941_at 10.06 8.9 0 0.16 -2.24 0.009592 0.270933 ELM11773771_at 10.72 9.56 0.2 0.16 -2.23 0.023709 0.282524 OCA51773073_at 9.51 8.36 0.27 0.23 -2.23 0.042872 0.306071 MCH51770219_at 10.06 8.9 0.01 0.19 -2.22 0.013196 0.270933 CBF21779095_at 7.08 5.93 0.26 0.01 -2.22 0.024339 0.283986 DAL41775593_at 11.38 10.22 0.01 0.14 -2.22 0.007402 0.270933 CDC51774601_at 10.44 9.3 0.15 0.3 -2.21 0.040917 0.303671 MNL21773892_at 10.36 9.21 0.08 0.31 -2.21 0.036426 0.297443 NCS21777910_at 9.97 8.83 0.06 0 -2.2 0.001335 0.270933 ZDS21776407_at 11.31 10.19 0.11 0.14 -2.18 0.012901 0.270933 ALK11774947_at 9.82 8.69 0.22 0.28 -2.18 0.047037 0.308973 TOS41774982_at 11.44 10.33 0.06 0.31 -2.17 0.038228 0.299899 HGH11772730_at 5.98 4.87 0.02 0.04 -2.17 0.000909 0.270933 CRR11773671_at 10.32 9.2 0.11 0.04 -2.17 0.005471 0.270933 YLR407W1773669_at 11.9 10.78 0.09 0.35 -2.17 0.048556 0.310889 UTP231775355_at 10.8 9.69 0.06 0.07 -2.16 0.003445 0.270933 BST11770450_at 5.87 4.76 0.18 0.26 -2.16 0.038184 0.299899 RRT5163Transcript Cluster IDWT Bi-weight Avg Signal (log2)dis3E729K Bi-weight Avg Signal (log2)WT StandardDeviationdis3E729K Standard DeviationFold Change (linear) (WT vs. dis3E729K)ANOVA p-value (WT vs. dis3E729K)FDR p-value (WT vs. dis3E729K)Gene Symbol1776428_at 9.77 8.66 0.06 0.04 -2.16 0.002047 0.270933 SKP21771804_at 9.45 8.35 0.1 0.04 -2.15 0.00482 0.270933 TSR41770645_at 9.83 8.73 0.11 0.15 -2.15 0.013646 0.270933 DPB21778100_at 9.95 8.85 0.16 0.01 -2.14 0.010767 0.270933 IRC81778542_at 9.05 7.96 0.21 0.2 -2.13 0.03391 0.296229 TCA171777041_at 10.62 9.53 0.07 0.29 -2.13 0.036614 0.297443 FIR11772170_at 10.22 9.13 0.04 0.36 -2.13 0.04965 0.311089 CCH11770213_at 10.46 9.37 0.02 0.29 -2.13 0.032472 0.292905 RRN31771067_at 10.79 9.69 0.01 0.11 -2.13 0.005549 0.270933 ABF11780005_at 9.97 8.89 0.13 0.17 -2.12 0.019136 0.275438 PPH31772968_at 10.5 9.42 0.17 0.01 -2.12 0.012028 0.270933 SWE11770036_at 10.14 9.06 0.03 0.22 -2.12 0.019806 0.275438 MSH21775573_at 10.79 9.71 0.02 0.28 -2.11 0.031641 0.292468 YDL073W1779279_at 10.27 9.2 0.1 0.3 -2.11 0.040157 0.302173 MYO11776865_at 7.45 6.37 0.16 0.04 -2.11 0.011537 0.270933 YKL071W1777343_at 8.12 7.04 0.09 0.13 -2.11 0.01047 0.270933 SPS191773706_at 12.16 11.08 0.08 0.32 -2.11 0.043349 0.306071 PNO11775510_at 9.23 8.16 0.04 0.31 -2.1 0.040522 0.302681 TOS21776983_at 10.17 9.1 0.06 0.02 -2.09 0.001577 0.270933 APC11777034_at 10.32 9.25 0.21 0.12 -2.09 0.025292 0.286426 THI801774967_at 10.34 9.28 0.15 0.28 -2.08 0.04356 0.306071 RPC53164Transcript Cluster IDWT Bi-weight Avg Signal (log2)dis3E729K Bi-weight Avg Signal (log2)WT StandardDeviationdis3E729K Standard DeviationFold Change (linear) (WT vs. dis3E729K)ANOVA p-value (WT vs. dis3E729K)FDR p-value (WT vs. dis3E729K)Gene Symbol1777130_at 9.7 8.64 0.04 0.33 -2.08 0.046526 0.308327 FKH11775640_at 11.35 10.3 0.12 0.12 -2.07 0.013019 0.270933 BUD41771479_at 10.8 9.75 0.09 0.04 -2.07 0.004109 0.270933 ATX11771655_at 10.61 9.57 0.01 0.14 -2.05 0.008679 0.270933 SIR41776092_at 10.65 9.61 0.09 0.26 -2.05 0.034868 0.297443 GEA11778802_at 9.87 8.84 0.06 0.2 -2.05 0.019778 0.275438 NNF11772826_at 8.98 7.95 0.08 0.26 -2.05 0.033577 0.296229 LAS11777812_at 9.76 8.73 0.06 0.31 -2.04 0.043875 0.306071 SNU231776413_at 10.84 9.82 0.05 0.18 -2.04 0.01532 0.27356 SPP411770666_at 10.47 9.44 0.11 0.12 -2.04 0.01228 0.270933 BCD11772712_at 10.7 9.67 0.07 0.29 -2.04 0.039891 0.302173 AXL21778823_at 6.37 5.35 0.19 0.08 -2.04 0.019984 0.275846 HOP11770816_at 10.71 9.68 0.03 0.25 -2.04 0.028206 0.288561 ORC11773256_at 9.44 8.41 0.1 0.25 -2.04 0.032486 0.292905 YMR144W1779254_at 10.25 9.22 0.08 0.18 -2.03 0.018357 0.275438 BUD231777988_at 11.89 10.87 0.18 0.26 -2.03 0.045807 0.306727 PXR11773057_at 10.72 9.69 0.08 0.15 -2.03 0.013864 0.270933 SMC61774670_at 9.69 8.67 0.17 0.26 -2.03 0.043427 0.306071 YPL108W1773885_at 9.33 8.31 0.04 0.25 -2.02 0.029801 0.289797 YDL085C-A1775937_at 9.86 8.84 0.13 0.14 -2.02 0.017949 0.275438 YMR030W-A1778433_at 9.36 8.35 0.04 0.28 -2.02 0.038172 0.299899 AFI1165Transcript Cluster IDWT Bi-weight Avg Signal (log2)dis3E729K Bi-weight Avg Signal (log2)WT StandardDeviationdis3E729K Standard DeviationFold Change (linear) (WT vs. dis3E729K)ANOVA p-value (WT vs. dis3E729K)FDR p-value (WT vs. dis3E729K)Gene Symbol1769685_at 11.01 10 0 0.11 -2.01 0.005418 0.270933 EUG11780064_at 9.39 8.38 0.09 0.29 -2.01 0.042271 0.306071 MSH11774409_at 9.79 10.8 0.02 0.22 2.01 0.023119 0.281147 CAD11777455_at 8.17 9.18 0.22 0.25 2.02 0.049785 0.311089 ARG821780194_at 9.32 10.34 0.07 0.31 2.02 0.044281 0.306071 HUA11780085_at 8 9.02 0.02 0.32 2.03 0.045084 0.306565 FAA21774767_at 8.92 9.94 0.01 0.04 2.03 0.000878 0.270933 OTU11775392_at 9.32 10.34 0.19 0.04 2.03 0.017336 0.275438 YPI11774653_at 10.23 11.26 0.13 0.2 2.03 0.027446 0.288554 AIM371779412_at 12.23 13.26 0.14 0.24 2.04 0.034892 0.297443 CIT11771404_at 9.69 10.73 0.14 0.31 2.05 0.049387 0.310964 RTK11769514_at 10.44 11.48 0.04 0.28 2.05 0.036504 0.297443 HAL51777714_at 11.85 12.89 0.14 0.26 2.06 0.03739 0.29868 DIP51772697_at 9.79 10.84 0.02 0.21 2.08 0.018848 0.275438 SDS221779476_at 11.04 12.1 0.08 0.22 2.08 0.023418 0.281845 GLC81769481_at 9.67 10.74 0.22 0.05 2.09 0.021024 0.276248 TWF11770998_at 5.49 6.55 0.29 0.14 2.09 0.044474 0.306325 YNR066C1776719_at 7.18 8.25 0.01 0.11 2.1 0.004829 0.270933 ATP101774526_at 9.25 10.32 0.06 0.13 2.11 0.008606 0.270933 ARE21774485_at 9.48 10.56 0.15 0.18 2.12 0.022102 0.278148 MPM11774287_at 8.89 9.98 0.07 0.28 2.13 0.03377 0.296229 CRD1166Transcript Cluster IDWT Bi-weight Avg Signal (log2)dis3E729K Bi-weight Avg Signal (log2)WT StandardDeviationdis3E729K Standard DeviationFold Change (linear) (WT vs. dis3E729K)ANOVA p-value (WT vs. dis3E729K)FDR p-value (WT vs. dis3E729K)Gene Symbol1773240_at 5.85 6.94 0.2 0.03 2.13 0.016769 0.275438 SPO111776670_at 9.79 10.88 0.08 0.26 2.14 0.030031 0.289797 YFL042C1774613_at 9.23 10.33 0.2 0.12 2.15 0.022042 0.278148 IMP2'1772171_at 9.27 10.37 0.1 0.17 2.15 0.016065 0.275225 YLR152C1772962_at 7.68 8.79 0.2 0.2 2.16 0.03055 0.289797 FAR71780187_at 10.59 11.7 0.01 0.14 2.16 0.007909 0.270933 POM331779968_at 7.83 8.94 0.05 0.26 2.16 0.027211 0.288554 YMR253C1778263_at 9.79 10.91 0.05 0.24 2.17 0.023243 0.281147 AIM191779275_at 10.91 12.04 0.24 0.24 2.19 0.042415 0.306071 GRE31774864_at 10.2 11.33 0.13 0.18 2.19 0.018881 0.275438 VTI11776450_at 11.57 12.71 0.1 0.11 2.2 0.00859 0.270933 SIS11772193_at 9.62 10.76 0.32 0.18 2.21 0.046821 0.308896 YLR297W1773907_at 9.4 10.56 0.16 0.02 2.22 0.009991 0.270933 YCL049C1778956_at 8.6 9.76 0.09 0.15 2.23 0.012033 0.270933 NEM11774835_at 11.06 12.22 0.02 0.23 2.23 0.019777 0.275438 BCY11772343_at 8.12 9.28 0.13 0.26 2.24 0.029581 0.289797 SAP41771999_at 9.24 10.4 0.07 0.22 2.24 0.019463 0.275438 AIM391775509_at 11.33 12.49 0.17 0.07 2.24 0.012899 0.270933 HRK11779589_at 8.65 9.82 0.03 0.13 2.25 0.006415 0.270933 LDB171777223_at 9.86 11.03 0.05 0.32 2.25 0.035372 0.297443 YGR127W1772558_at 12.38 13.56 0.34 0.02 2.26 0.040289 0.302173 TIP1167Transcript Cluster IDWT Bi-weight Avg Signal (log2)dis3E729K Bi-weight Avg Signal (log2)WT StandardDeviationdis3E729K Standard DeviationFold Change (linear) (WT vs. dis3E729K)ANOVA p-value (WT vs. dis3E729K)FDR p-value (WT vs. dis3E729K)Gene Symbol1770859_at 6.28 7.46 0.05 0.29 2.27 0.02911 0.289797 IMA11772873_at 6.95 8.15 0.05 0.36 2.3 0.043705 0.306071 MAL131775837_at 8.34 9.54 0.14 0.1 2.3 0.010067 0.270933 SSN81771519_at 10.7 11.91 0.11 0.17 2.32 0.013891 0.270933 UIP31773748_at 8.11 9.33 0.22 0.05 2.32 0.017385 0.275438 MUP31771013_at 8.88 10.1 0.02 0.21 2.33 0.015176 0.27356 YLR271W1776087_at 5.16 6.4 0.17 0.08 2.35 0.01176 0.270933 ECM121779018_at 9.94 11.18 0.1 0.14 2.37 0.00917 0.270933 URA81775629_at 8.83 10.07 0.06 0.34 2.37 0.036966 0.297868 YPL109C1778272_at 7.75 9 0.3 0.03 2.39 0.027445 0.288554 YGR121W-A1776975_at 8.9 10.15 0.1 0.32 2.39 0.03349 0.296229 ENV71780131_at 7.81 9.07 0.09 0.29 2.4 0.028118 0.288554 YFL041W-A1779936_at 9.41 10.68 0.09 0.23 2.41 0.018417 0.275438 COQ31779921_at 12.07 13.34 0.06 0.26 2.41 0.021157 0.276248 LSP11769804_at 8.58 9.85 0.09 0.28 2.42 0.025523 0.28765 VPS731769313_at 8.33 9.61 0.14 0.36 2.42 0.042633 0.306071 PKP21778769_at 9.67 10.95 0.15 0.28 2.43 0.030071 0.289797 SFK11769958_at 9.88 11.16 0.14 0.27 2.43 0.026113 0.28851 GID81778805_at 4.2 5.49 0.06 0.12 2.45 0.005241 0.270933 YFL051C1777017_at 8.93 10.23 0.06 0.18 2.45 0.010051 0.270933 YGR237C1772540_at 9.49 10.79 0.12 0.39 2.47 0.046208 0.307216 MIG3168Transcript Cluster IDWT Bi-weight Avg Signal (log2)dis3E729K Bi-weight Avg Signal (log2)WT StandardDeviationdis3E729K Standard DeviationFold Change (linear) (WT vs. dis3E729K)ANOVA p-value (WT vs. dis3E729K)FDR p-value (WT vs. dis3E729K)Gene Symbol1779609_at 8.45 9.77 0.01 0.28 2.5 0.021595 0.278148 DDI11770456_at 10.91 12.24 0.16 0.2 2.52 0.018151 0.275438 NTH11773521_at 8.87 10.2 0.21 0.16 2.52 0.018738 0.275438 SHY11776609_at 11.08 12.42 0.26 0.29 2.53 0.039959 0.302173 MRP81778440_at 9.91 11.25 0.19 0.12 2.54 0.013425 0.270933 YDR391C1779236_at 9.64 11 0.23 0.27 2.57 0.032601 0.292978 HAP21779805_at 11.27 12.63 0.13 0.41 2.57 0.04515 0.306565 ORM21773739_at 9.72 11.09 0.14 0.26 2.58 0.022118 0.278148 NVJ11770795_at 8.35 9.72 0.19 0.35 2.58 0.040614 0.303165 YKL162C1778599_at 11.01 12.37 0.04 0.28 2.58 0.020248 0.276248 MCR11769464_at 10.51 11.88 0.06 0.33 2.59 0.028777 0.289251 YGR130C1778655_at 9.4 10.77 0.07 0.26 2.59 0.018367 0.275438 CKI11775201_at 7.2 8.58 0.04 0.2 2.6 0.011186 0.270933 YPL257W1779844_at 7.49 8.88 0.03 0.2 2.62 0.010862 0.270933 YAR023C1776257_at 10.45 11.84 0.16 0.08 2.62 0.008217 0.270933 YGR250C1779962_at 10.2 11.59 0.05 0.36 2.62 0.032272 0.292905 RIM111771072_at 4.78 6.17 0.25 0.14 2.62 0.019858 0.275633 ATG161772073_at 9.62 11.01 0.02 0.17 2.62 0.007575 0.270933 OXR11770191_at 9.17 10.57 0.32 0.15 2.64 0.029722 0.289797 MAG11778746_at 9.4 10.8 0.01 0.19 2.64 0.008852 0.270933 CST61769764_at 8.52 9.92 0.06 0.3 2.64 0.023485 0.282031 YOR223W169Transcript Cluster IDWT Bi-weight Avg Signal (log2)dis3E729K Bi-weight Avg Signal (log2)WT StandardDeviationdis3E729K Standard DeviationFold Change (linear) (WT vs. dis3E729K)ANOVA p-value (WT vs. dis3E729K)FDR p-value (WT vs. dis3E729K)Gene Symbol1771972_at 6.86 8.27 0.05 0.15 2.67 0.005999 0.270933 PTH11770636_at 5.82 7.24 0.15 0.23 2.68 0.018775 0.275438 DOC11775255_at 8.74 10.16 0 0.34 2.69 0.026747 0.288554 PRM81774564_at 11.71 13.14 0.06 0.08 2.69 0.002401 0.270933 HSP1041777109_at 8.37 9.8 0.16 0.33 2.7 0.031772 0.292468 VID301775990_at 10.39 11.83 0.19 0.26 2.71 0.0233 0.281147 YDC11773262_at 9.44 10.88 0.17 0.31 2.72 0.028454 0.289251 SIP51773831_at 7.67 9.12 0.2 0.4 2.73 0.045006 0.306565 YMR114C1773728_at 9.59 11.04 0.22 0.42 2.74 0.049777 0.311089 CMK11774804_at 8.4 9.86 0.26 0.3 2.75 0.034663 0.297443 ATG31779924_at 8.1 9.59 0.23 0.23 2.79 0.022601 0.280582 YER053C-A1775133_at 9.13 10.62 0.26 0.18 2.8 0.021903 0.278148 SNX41773855_at 8.19 9.68 0.02 0.1 2.8 0.00249 0.270933 USB11774404_at 7.13 8.63 0.15 0.05 2.81 0.005795 0.270933 ARP101771165_x_at 3.12 4.62 0.05 0.07 2.82 0.001702 0.270933 HXT131778184_at 8.23 9.73 0.1 0.4 2.83 0.036377 0.297443 YOL114C1773225_at 8.31 9.81 0.19 0.29 2.83 0.025855 0.28851 YOR292C1776402_at 10.05 11.55 0.02 0.3 2.84 0.019805 0.275438 YMR181C1776883_at 10.26 11.77 0.25 0.4 2.85 0.045694 0.30668 BXI11778728_at 9.37 10.89 0.08 0.41 2.87 0.035589 0.297443 RCR21769951_at 9.72 11.25 0.06 0.19 2.88 0.008506 0.270933 IML2170Transcript Cluster IDWT Bi-weight Avg Signal (log2)dis3E729K Bi-weight Avg Signal (log2)WT StandardDeviationdis3E729K Standard DeviationFold Change (linear) (WT vs. dis3E729K)ANOVA p-value (WT vs. dis3E729K)FDR p-value (WT vs. dis3E729K)Gene Symbol1778565_at 3.23 4.77 0.01 0.28 2.9 0.015841 0.27356 YDR169C-A1776204_at 9.5 11.04 0.01 0.48 2.91 0.045703 0.30668 YKL151C1769395_at 11.13 12.67 0.08 0.17 2.92 0.007093 0.270933 CHO11779035_at 8.39 9.94 0.07 0.44 2.92 0.039435 0.302173 MTL11771432_at 9.83 11.39 0.28 0.42 2.93 0.048907 0.310889 YGR149W1769450_at 10.18 11.73 0.19 0.39 2.94 0.036413 0.297443 EDC21779307_at 11.04 12.6 0.3 0.05 2.95 0.018628 0.275438 EHT11773329_at 12 13.57 0.09 0.21 2.97 0.010705 0.270933 OPI31780210_at 11.21 12.79 0.32 0.17 2.99 0.024909 0.285333 YOR052C1775892_at 8.81 10.4 0.02 0.4 3.01 0.029852 0.289797 YIL077C1779061_at 10.9 12.49 0.04 0.2 3.02 0.007894 0.270933 YLR257W1777816_at 7.49 9.1 0.28 0.43 3.06 0.046866 0.308896 GUD11772785_at 8.9 10.51 0.45 0.26 3.06 0.04766 0.308973 PHM81778686_at 9.51 11.12 0.06 0.43 3.06 0.034727 0.297443 TPO41777549_at 12.11 13.72 0.01 0.27 3.06 0.013972 0.270933 YPR036W-A1774353_at 8.89 10.54 0.27 0.26 3.14 0.02435 0.283986 UPS31780130_at 9.82 11.48 0.09 0.41 3.15 0.031162 0.291063 PPM11780047_at 10.21 11.88 0.32 0.43 3.18 0.047719 0.308973 TPK21777476_at 8.34 10.02 0.12 0.05 3.2 0.002949 0.270933 CUR11773457_at 10.83 12.52 0 0.42 3.21 0.029211 0.289797 GDH21773890_at 8.53 10.22 0.12 0.5 3.21 0.043745 0.306071 APJ1171Transcript Cluster IDWT Bi-weight Avg Signal (log2)dis3E729K Bi-weight Avg Signal (log2)WT StandardDeviationdis3E729K Standard DeviationFold Change (linear) (WT vs. dis3E729K)ANOVA p-value (WT vs. dis3E729K)FDR p-value (WT vs. dis3E729K)Gene Symbol1778357_at 8.5 10.19 0.08 0.51 3.22 0.043542 0.306071 PRM41774340_at 9.08 10.77 0.12 0.48 3.23 0.039618 0.302173 FBP261778556_at 6.54 8.23 0.17 0.06 3.23 0.005823 0.270933 YML003W1778006_at 9.33 11.03 0.03 0.43 3.25 0.030426 0.289797 YSC841772907_at 8.13 9.85 0.05 0 3.28 0.00047 0.257081 SOL11776964_at 6.49 8.22 0.06 0.3 3.33 0.014848 0.27356 YPT351774081_at 9.82 11.56 0.09 0.53 3.35 0.045058 0.306565 MDH21780053_at 11.27 13.03 0.18 0.2 3.37 0.011552 0.270933 ICY11772447_at 9.16 10.91 0.25 0.51 3.38 0.048776 0.310889 SYM11773681_at 9.73 11.55 0.35 0.32 3.53 0.031789 0.292468 VID241773998_at 6.36 8.18 0.05 0.39 3.54 0.022497 0.280324 YGR045C1779150_at 11.94 13.77 0.17 0.23 3.55 0.011835 0.270933 GLK11778758_at 8.55 10.39 0.1 0.24 3.56 0.009973 0.270933 RMD51769622_at 9.75 11.61 0.05 0.16 3.63 0.004106 0.270933 YJL047C-A1778604_at 9.3 11.17 0.08 0.43 3.65 0.026844 0.288554 XKS11773607_at 10.39 12.27 0.06 0.43 3.66 0.025421 0.286981 YAK11773255_at 11.12 13.01 0.58 0.19 3.71 0.047867 0.308973 STF21774796_at 6.31 8.2 0.03 0.3 3.72 0.01281 0.270933 ABM11774057_at 9.54 11.46 0.3 0.46 3.77 0.038469 0.300492 YLR345W1778899_at 9.47 11.39 0.58 0.23 3.78 0.048603 0.310889 HSP781778079_at 10.79 12.71 0.26 0.19 3.78 0.013775 0.270933 BTN2172Transcript Cluster IDWT Bi-weight Avg Signal (log2)dis3E729K Bi-weight Avg Signal (log2)WT StandardDeviationdis3E729K Standard DeviationFold Change (linear) (WT vs. dis3E729K)ANOVA p-value (WT vs. dis3E729K)FDR p-value (WT vs. dis3E729K)Gene Symbol1772055_at 8.53 10.46 0.07 0.17 3.8 0.004676 0.270933 VHS11775683_at 9.73 11.66 0.01 0.4 3.81 0.020414 0.276248 NDI11775441_at 10.21 12.15 0.09 0.07 3.83 0.001684 0.270933 HAP41774403_at 10.02 11.96 0.19 0.45 3.83 0.030419 0.289797 YLR177W1772597_at 5.7 7.65 0.44 0.42 3.88 0.045653 0.30668 YCR101C1772007_at 5.81 7.77 0.13 0.37 3.9 0.019795 0.275438 YIL029C1773792_at 8.3 10.29 0.21 0.38 3.99 0.022658 0.280582 FYV101777525_at 9.84 11.84 0.26 0.45 4 0.031967 0.292468 RCN21779784_at 10.4 12.4 0.31 0.3 4.02 0.021806 0.278148 YJL133C-A1771824_at 8.84 10.85 0.05 0.12 4.03 0.002066 0.270933 ICY21774817_at 6.68 8.7 0.33 0.07 4.05 0.013639 0.270933 PHR11769352_at 10.46 12.5 0.26 0.32 4.1 0.020302 0.276248 STP41776624_at 11.49 13.53 0.06 0.47 4.12 0.025559 0.28765 ALD41772848_at 8.41 10.47 0.1 0.58 4.16 0.038194 0.299899 FRT21778569_at 3.44 5.53 0.42 0.01 4.26 0.019811 0.275438 YOR008C-A1776948_at 10.99 13.11 0.26 0.21 4.34 0.012397 0.270933 PNC11778181_at 6.41 8.56 0.27 0.33 4.45 0.018473 0.275438 ATG291779344_at 9.32 11.49 0.18 0.12 4.5 0.004842 0.270933 ADH51775851_at 8.99 11.19 0.51 0.35 4.61 0.037151 0.297994 GPX11776672_at 10.03 12.25 0.47 0.45 4.66 0.040713 0.303279 CMK21773494_at 6.43 8.66 0.05 0.26 4.66 0.007162 0.270933 YOR376W-A173Transcript Cluster IDWT Bi-weight Avg Signal (log2)dis3E729K Bi-weight Avg Signal (log2)WT StandardDeviationdis3E729K Standard DeviationFold Change (linear) (WT vs. dis3E729K)ANOVA p-value (WT vs. dis3E729K)FDR p-value (WT vs. dis3E729K)Gene Symbol1771402_at 10.85 13.08 0.46 0.02 4.71 0.020788 0.276248 SAM21771214_at 9.16 11.42 0.4 0.3 4.81 0.023914 0.282524 PYK21770529_at 8.76 11.06 0.18 0.25 4.91 0.008856 0.270933 OPI101776161_at 8.61 10.91 0.21 0.32 4.93 0.013463 0.270933 GGA11771615_at 5.27 7.59 0.29 0.29 4.99 0.014902 0.27356 YKL183C-A1770230_at 5.48 7.81 0.46 0.59 5 0.047973 0.309133 YGR204C-A1770900_at 7.39 9.72 0.3 0.58 5.06 0.036579 0.297443 KIN821773859_at 9.93 12.27 0.51 0.45 5.07 0.039814 0.302173 AGP21773273_at 10.83 13.18 0.38 0.52 5.1 0.035578 0.297443 ACH11773234_at 8.92 11.29 0.08 0.44 5.17 0.017281 0.275438 YER079W1779620_at 8.49 10.88 0.48 0.11 5.24 0.020995 0.276248 YEL073C1775729_at 6.96 9.35 0.01 0.65 5.24 0.034694 0.297443 MLS11774756_at 10.82 13.23 0.48 0.37 5.31 0.030241 0.289797 TSL11776302_at 8.3 10.72 0.21 0.19 5.34 0.006837 0.270933 YPL247C1773341_at 5.27 7.7 0.13 0.24 5.38 0.006335 0.270933 YMR105W-A1775976_at 11.64 14.07 0.35 0.3 5.39 0.017491 0.275438 HXK11775390_at 8.43 10.86 0.35 0.32 5.4 0.01866 0.275438 YPK21776550_at 10.87 13.31 0.41 0.23 5.46 0.018118 0.275438 HSP421779105_at 11.03 13.48 0.29 0.36 5.46 0.017442 0.275438 GSY21772023_at 9.31 11.77 0.25 0.62 5.5 0.035095 0.297443 YKL091C1776531_at 10.46 12.93 0.21 0.32 5.51 0.012246 0.270933 TPS2174Transcript Cluster IDWT Bi-weight Avg Signal (log2)dis3E729K Bi-weight Avg Signal (log2)WT StandardDeviationdis3E729K Standard DeviationFold Change (linear) (WT vs. dis3E729K)ANOVA p-value (WT vs. dis3E729K)FDR p-value (WT vs. dis3E729K)Gene Symbol1771695_at 6.25 8.74 0.32 0.65 5.59 0.039931 0.302173 CIT31778374_at 8.3 10.79 0.7 0.25 5.6 0.041711 0.304282 YBL086C1780217_at 9.47 11.97 0.4 0.66 5.67 0.044064 0.306071 RTS31769679_at 10.57 13.15 0.31 0.1 5.98 0.007871 0.270933 PIC21773415_at 8.99 11.57 0.22 0.51 5.98 0.022414 0.279874 IGD11776673_at 10.97 13.56 0.12 0.37 6.04 0.011149 0.270933 NCE1031774137_at 7.87 10.49 0.01 0.78 6.12 0.041602 0.304282 CYC71776644_at 7.94 10.57 0.07 0.49 6.18 0.017392 0.275438 GLG11777857_at 9.09 11.73 0.15 0.43 6.23 0.014467 0.272112 YPL014W1771757_at 8.45 11.12 0.32 0.68 6.35 0.03716 0.297994 YAT21773097_at 9.36 12.04 0.41 0.11 6.39 0.012204 0.270933 YPC11770651_at 3.03 5.73 0.26 0.35 6.49 0.013025 0.270933 YBR296C-A1777917_at 8.73 11.45 0.13 0.26 6.61 0.005695 0.270933 MTH11772850_at 9.2 11.99 0.13 0.27 6.88 0.005527 0.270933 MHO11779897_at 9.88 12.67 0.02 0.36 6.93 0.008048 0.270933 YNR034W-A1776944_at 7.43 10.27 0.57 0.57 7.18 0.038138 0.299899 MAL111778907_at 9.83 12.73 0.24 0.52 7.49 0.01916 0.275438 PGM21774177_at 7.27 10.2 0.01 0.21 7.64 0.002585 0.270933 YNL144C1779850_at 10 12.94 0.37 0.69 7.66 0.034029 0.296675 GPH11774778_at 7.06 10.04 0.33 0.61 7.84 0.025917 0.28851 CRC11775556_at 2.96 5.97 0.46 0.33 8.01 0.017487 0.275438 YBR182C-A175Transcript Cluster IDWT Bi-weight Avg Signal (log2)dis3E729K Bi-weight Avg Signal (log2)WT StandardDeviationdis3E729K Standard DeviationFold Change (linear) (WT vs. dis3E729K)ANOVA p-value (WT vs. dis3E729K)FDR p-value (WT vs. dis3E729K)Gene Symbol1779450_at 8.05 11.06 0.08 0.51 8.06 0.014215 0.271336 YNR014W1769426_at 8.18 11.23 0.39 0.52 8.26 0.021927 0.278148 PDH11769626_at 9.25 12.31 0.29 0.2 8.33 0.006498 0.270933 TDA11770001_at 9.74 12.88 0.53 0.37 8.79 0.020438 0.276248 EMI21778380_at 6.63 9.78 0.24 0.44 8.9 0.012247 0.270933 MGA11777575_at 7.48 10.68 0.23 0.75 9.19 0.028501 0.289251 YJR115W1775678_at 8.24 11.48 0.17 1 9.45 0.045499 0.30668 PUT11779905_at 8.47 11.82 0.21 0.54 10.19 0.014603 0.273258 ICL11777587_at 4.85 8.29 0.14 1.03 10.78 0.043333 0.306071 YPR159C-A1773594_at 8.39 11.83 0.35 0.51 10.89 0.015965 0.274308 MAL311770013_at 5.17 8.64 0.47 0.78 11.01 0.033325 0.296229 YFL052W1772051_at 9.89 13.39 0.12 0.58 11.34 0.013929 0.270933 GLC31779568_at 7.28 10.89 0.53 0.82 12.22 0.034489 0.297443 REG21775364_at 9.61 13.22 0.34 0.07 12.25 0.004564 0.270933 HSP301778218_at 9.19 12.81 0.4 0.75 12.35 0.026386 0.28851 TMA101778293_at 8.45 12.14 0.58 0.06 12.91 0.01225 0.270933 YKR075C1776064_at 7.97 11.9 0.07 0.89 15.21 0.024623 0.284647 JEN11777561_at 8.77 12.72 0.31 0.69 15.45 0.017978 0.275438 FMP431775842_at 8.07 12.16 0.12 0.49 16.97 0.00766 0.270933 AIM171774072_at 6.22 10.37 0.33 1.13 17.78 0.037763 0.299379 SFC11777753_at 9.64 13.79 0.14 0.25 17.84 0.002448 0.270933 RGI1176Transcript Cluster IDWT Bi-weight Avg Signal (log2)dis3E729K Bi-weight Avg Signal (log2)WT StandardDeviationdis3E729K Standard DeviationFold Change (linear) (WT vs. dis3E729K)ANOVA p-value (WT vs. dis3E729K)FDR p-value (WT vs. dis3E729K)Gene Symbol1776778_at 7.07 11.46 0.09 1.32 20.97 0.042293 0.306071 ISF11770580_at 6.08 11.2 0.21 1.43 35 0.037489 0.298876 ADY2177Appendix 3. GO term enrichment analysis for the dis3E729K expression microarray.Downregulated Terms from the Process Ontology of gene_association.sgd with p-value <= 0.01Gene Ontology termCluster frequencyGenome frequencyCorrected p-valueFDR False positivesGenes annotated to the termcell cycle 83 of 207 genes, 40.1%802 of 7166 genes, 11.2%7.00E-25 0.00% 0 CWC2, SIR2, MSH2, SPS19, HSL1, SFG1, MCD1, FKH1, ELG1, CLB1, CRR1, CLN2, SSP2, RAX2, SMC6, CDC5, CLB5, PCL1, CDC6, MYO1, MSB2, CTF18, EFG1, MSH3, TRF5, AFI1, POL1, KCC4, ESC8, ELM1, DPB2, CBF2, SMC5, HTL1, BUB1, BNR1, CDC45, PPH3, TOS2, TOP1, PDS5, YOX1, RAD53, HCM1, SPH1, SPS4, YOR338W, ACM1, RAD9, SPR1, SKG6, MIF2, TOF1, SPC98, DAD4, NNF1, BUD4, BUD3, ATC1, MSH5, KIN4, HOP1, PMS1, SMC3, BUD23, GIN4, SPO16, SWE1, SAP185, LTE1, ALK1, APC1, CLB6, ORC1, SPO21, AXL2, CLN1, IPI1, YCG1, ZDS2, MRC1, IBD2, SLK19178Downregulated Terms from the Process Ontology of gene_association.sgd with p-value <= 0.01Gene Ontology termCluster frequencyGenome frequencyCorrected p-valueFDR False positivesGenes annotated to the termcell cycle process 74 of 207 genes, 35.7%663 of 7166 genes, 9.3%1.43E-23 0.00% 0 SIR2, MSH2, SPS19, HSL1, MCD1, FKH1, ELG1, CLB1, CRR1, CLN2, SSP2, RAX2, SMC6, CDC5, CLB5, CDC6, MYO1, MSB2, CTF18, EFG1, MSH3, AFI1, POL1, KCC4, ESC8, ELM1, CBF2, SMC5, BUB1, BNR1, CDC45, PPH3, TOS2, TOP1, PDS5, YOX1, RAD53, HCM1, SPH1, SPS4, YOR338W, RAD9, SPR1, SKG6, MIF2, TOF1, SPC98, DAD4, BUD4, BUD3, ATC1, MSH5, KIN4, HOP1, PMS1, SMC3, BUD23, GIN4, SPO16, SAP185, SWE1, LTE1, APC1, CLB6, ORC1, SPO21, AXL2, CLN1, IPI1, YCG1, ZDS2, MRC1, IBD2, SLK19mitotic cell cycle 53 of 207 genes, 25.6%400 of 7166 genes, 5.6%4.61E-19 0.00% 0 SPH1, RAD9, MIF2, SKG6, TOF1, SPC98, HSL1, SFG1, MCD1, FKH1, ELG1, CLB1, CLN2, BUD4, BUD3, ATC1, RAX2, KIN4, CDC5, CLB5, SMC3, CDC6, BUD23, MSB2,GIN4, CTF18, SWE1, SAP185, LTE1, ALK1, APC1, CLB6, AFI1, ORC1, POL1, KCC4, AXL2, CLN1, ELM1, CBF2, BUB1, YCG1, BNR1, ZDS2, CDC45, MRC1, TOS2, TOP1, YOX1, PDS5, IBD2, RAD53, SLK19179Downregulated Terms from the Process Ontology of gene_association.sgd with p-value <= 0.01Gene Ontology termCluster frequencyGenome frequencyCorrected p-valueFDR False positivesGenes annotated to the termmitotic cell cycle process51 of 207 genes, 24.6%384 of 7166 genes, 5.4%2.96E-18 0.00% 0 SPH1, RAD9, MIF2, SKG6, TOF1, SPC98, HSL1, MCD1, FKH1, ELG1, CLB1, CLN2, BUD4, BUD3, ATC1, RAX2, KIN4, CDC5, CLB5, CDC6, SMC3, BUD23, MSB2, GIN4, CTF18, SWE1, SAP185, LTE1, APC1, CLB6, AFI1, ORC1, POL1, KCC4, AXL2, CLN1, ELM1, CBF2, BUB1, YCG1, BNR1, ZDS2, CDC45, MRC1, TOS2, TOP1, YOX1, PDS5, IBD2, RAD53, SLK19cell division 39 of 207 genes, 18.8%309 of 7166 genes, 4.3%1.68E-12 0.00% 0 SPH1, ACM1, MIF2, SKG6, DAD4, MCD1, CLB1, CLN2, NNF1, BUD4, BUD3, ATC1, RAX2, CDC5, PCL1, CDC6, SMC3, CLB5, BUD23, MYO1, MSB2, GIN4, SWE1, LTE1,TRF5, APC1, CLB6, AFI1, SPO21, KCC4, AXL2, CLN1, ELM1, YCG1, BNR1, TOS2, PDS5, IBD2, SLK19180Downregulated Terms from the Process Ontology of gene_association.sgd with p-value <= 0.01Gene Ontology termCluster frequencyGenome frequencyCorrected p-valueFDR False positivesGenes annotated to the termnucleic acid metabolic process100 of 207 genes, 48.3%1769 of 7166 genes, 24.7%6.22E-11 0.00% 0 PNO1, DAT1, PPR1, CWC2, UTP18, SIR2, MSH2, DUS1, MCD1, FKH1, ELG1, SMC6, CDC5, TSR4, SEN34, CLB5, CDC6, MTO1, CTF18, BUD21, EFG1, MSH3, IRC8, TRF5,RNH203, JJJ1, POL1, PLM2, RNR1, HO, TOS4, TEA1, ESC8, PXR1, FAL1, IFH1, RRN3, ZAP1, DPB2, SMC5, HTL1, LCP5, RPC53, NOP19, CDC45, SIR4, PPH3, LAS1, TOP1, PDS5, YOX1, RAD53, SSF1, YLR063W, HCM1, BAS1, DHR2, YOR338W, RAD9, ASG1, TOF1, NCS2, OGG1, RNT1, NOP53, BCD1, DAL1, FIR1, SNU23, MSH5, PZF1, PMS1, SMC3, BUD23, SPO16, MSH1, SAP185, DBP8, UTP9, VTS1, CLB6, RCL1, ORC1, RRP36,SAS2, BFR2, UTP25, RRN11, UTP23, UTP6, IPI1, YCG1, ABF1, ZDS2, RRN7, YPL216W, MRC1, SPP41, SPT21, EST2regulation of cell cycle34 of 207 genes, 16.4%287 of 7166 genes, 4.0%8.76E-10 0.00% 0 RAD9, MSH2, SKG6, TOF1, HSL1, DAD4, FKH1, CLB1, CLN2, KIN4, HOP1, CDC5, PCL1, CDC6, CLB5, GIN4, SPO16, SWE1, LTE1, APC1, CLB6, ORC1, KCC4, CLN1, BUB1, YCG1, ZDS2, CDC45, MRC1, PPH3, TOS2, IBD2, RAD53, SLK19181Downregulated Terms from the Process Ontology of gene_association.sgd with p-value <= 0.01Gene Ontology termCluster frequencyGenome frequencyCorrected p-valueFDR False positivesGenes annotated to the termregulation of mitoticcell cycle26 of 207 genes, 12.6%169 of 7166 genes, 2.4%1.30E-09 0.00% 0 CLB6, ORC1, RAD9, KCC4, SKG6, HSL1, FKH1, CLN1, CLB1, CLN2, KIN4, CDC5, CDC6, BUB1, CLB5, GIN4, ZDS2, CDC45, SWE1, MRC1, TOS2, LTE1, IBD2, RAD53, APC1, SLK19regulation of cell cycle process28 of 207 genes, 13.5%211 of 7166 genes, 2.9%6.96E-09 0.00% 0 CLB6, ORC1, RAD9, MSH2, SKG6, DAD4, FKH1, CLN1, CLB1, CLN2, KIN4, HOP1, CDC5, CDC6, BUB1, CLB5, YCG1, ZDS2, SPO16, CDC45, SWE1, PPH3, MRC1, TOS2,LTE1, IBD2, APC1, SLK19nucleobase-containing compound metabolic process103 of 207 genes, 49.8%2028 of 7166 genes, 28.3%2.57E-08 0.00% 0 PNO1, DAT1, PPR1, CWC2, UTP18, SIR2, YHL012W, MSH2, DUS1, MCD1, FKH1, ELG1, SMC6, CDC5, TSR4, SEN34, CLB5, CDC6, MTO1, CTF18, BUD21, EFG1, MSH3, IRC8, TRF5, RNH203, JJJ1, POL1, PLM2, RNR1, HO, TOS4, TEA1, BNA2, ESC8, PXR1, FAL1, IFH1, RRN3, ZAP1, DPB2, DAL4, SMC5, HTL1, LCP5, RPC53, NOP19, CDC45, SIR4, PPH3, LAS1, TOP1, PDS5, YOX1, RAD53, SSF1, YLR063W, HCM1, BAS1, DHR2, YOR338W, RAD9, ASG1, TOF1, NCS2, OGG1, RNT1, NOP53, BCD1, DAL1, FIR1, SNU23, MSH5, PZF1, PMS1, SMC3, BUD23, SPO16, MSH1, SAP185, DBP8, UTP9, VTS1, CLB6, RCL1, ORC1, RRP36, SAS2, BFR2, UTP25, RRN11, UTP23, UTP6, IPI1, YCG1, ABF1, ZDS2, RRN7, YPL216W, MRC1, SPP41, SPT21, EST2182Downregulated Terms from the Process Ontology of gene_association.sgd with p-value <= 0.01Gene Ontology termCluster frequencyGenome frequencyCorrected p-valueFDR False positivesGenes annotated to the termorganic cyclic compound metabolic process108 of 207 genes, 52.2%2182 of 7166 genes, 30.4%2.76E-08 0.00% 0 PNO1, DAT1, PPR1, CWC2, UTP18, SIR2, YHL012W, MSH2, DUS1, MCD1, FKH1, ELG1, SMC6, CDC5, YEH1, TSR4, SEN34, CLB5, CDC6, MTO1, CTF18, BUD21, EFG1, MSH3, IRC8, TRF5, RNH203, THI80, JJJ1, POL1, PLM2, RNR1, HO, TOS4, TEA1, BNA2, ESC8, PXR1, FAL1, IFH1, RRN3, ZAP1, DPB2, DAL4, SMC5, HTL1, LCP5, RPC53, NOP19, CDC45, SIR4, PPH3, LAS1, TOP1, PDS5, YOX1, RAD53, SSF1, YLR063W, HCM1, BAS1, DHR2, YOR338W, RAD9, ASG1, TOF1, NCS2, OGG1, RNT1, NOP53, BCD1, DAL1, FIR1, SNU23, HES1, MSH5,PMS1, PZF1, SMC3, BUD23, SPO16, MSH1, SAP185, DBP8, UTP9, VTS1, CLB6, RCL1, DUR1,2, ORC1, RRP36,SAS2, BFR2, UTP25, RRN11, UTP23, UTP6, IPI1, DFR1, YCG1, ABF1, ZDS2, RRN7, YPL216W, MRC1, SPP41, SPT21, EST2nuclear division 31 of 207 genes, 15.0%273 of 7166 genes, 3.8%3.01E-08 0.00% 0 CLB6, MSH2, MIF2, TOF1, SPC98, MCD1, ELG1, CLN1, CLB1, CLN2, MSH5, KIN4, HOP1, CDC5, CBF2, YCG1, BUB1, SMC3, CLB5, CTF18, SPO16, SWE1, PPH3, MSH3,MRC1, TOP1, LTE1, PDS5, IBD2, APC1, SLK19183Downregulated Terms from the Process Ontology of gene_association.sgd with p-value <= 0.01Gene Ontology termCluster frequencyGenome frequencyCorrected p-valueFDR False positivesGenes annotated to the termheterocycle metabolic process106 of 207 genes, 51.2%2126 of 7166 genes, 29.7%3.24E-08 0.00% 0 PNO1, DAT1, PPR1, CWC2, UTP18, SIR2, YHL012W, MSH2, DUS1, MCD1, FKH1, ELG1, SMC6, CDC5, TSR4, SEN34, CLB5, CDC6, MTO1, CTF18, BUD21, EFG1, MSH3, IRC8, TRF5, RNH203, THI80, JJJ1, POL1, PLM2, RNR1, HO, TOS4, TEA1, BNA2, ESC8, PXR1, FAL1, IFH1, RRN3, ZAP1, DPB2, DAL4, SMC5, HTL1, LCP5, RPC53, NOP19, CDC45, SIR4, PPH3, LAS1, TOP1, PDS5, YOX1, RAD53, SSF1, YLR063W, HCM1, BAS1, DHR2, YOR338W, RAD9, ASG1, TOF1, NCS2, OGG1, RNT1, NOP53, BCD1, DAL1, FIR1, SNU23, MSH5, PMS1, PZF1, SMC3, BUD23, SPO16, MSH1, SAP185, DBP8, UTP9, VTS1, CLB6, RCL1, DUR1,2, ORC1, RRP36, SAS2, BFR2,UTP25, RRN11, UTP23, UTP6, IPI1, DFR1, YCG1, ABF1, ZDS2, RRN7, YPL216W, MRC1, SPP41, SPT21, EST2184Downregulated Terms from the Process Ontology of gene_association.sgd with p-value <= 0.01Gene Ontology termCluster frequencyGenome frequencyCorrected p-valueFDR False positivesGenes annotated to the termcellular component organization or biogenesis116 of 207 genes, 56.0%2452 of 7166 genes, 34.2%4.98E-08 0.00% 0 PNO1, EMW1, RSA4, CIN2, CWC2, UTP18, SIR2, MSH2, HLR1, MCD1, FKH1, ELG1, CLB1, CRR1, CLN2, SSP2, RAX2, CDC5, TSR4, CLB5, PCL1, CDC6, MYO1, MSB2, CTF18, BUD21, EFG1, BST1, MSH3, JJJ1, PLM2, KCC4, TOS4, ESC8, PXR1, NTO1, FAL1, IFH1, TCA17, ELM1, DPB2, CBF2, SMC5, HTL1, LCP5, BUB1, NOP19, BNR1, CDC45, SIR4, PPH3, LAS1, TOP1, PDS5, SSF1, YLR063W, WSC4, HCM1, SGD1, BAS1, SPH1, DHR2, SPR1, YOR338W, AVO1, MIF2, TOF1, OGG1, SPC98, DAD4, RNT1, NOP53, BCD1, BUD4, MSH5, KIN4, HOP1,SMC3, BUD23, GIN4, SPO16, RLF2, MSH1, SWE1, LTE1,DBP8, UTP9, ECM1, APC1, CLB6, RCL1, GEA1, ORC1, SPO21, RRP36, SAS2, BFR2, UTP25, CLN1, RRN11, YDR179W-A, UTP23, UTP6, IPI1, YCG1, ABF1, ZDS2, SHQ1, RRN7, YPL216W, MRC1, SPT21, EST2, IBD2, PET309, SLK19185Downregulated Terms from the Process Ontology of gene_association.sgd with p-value <= 0.01Gene Ontology termCluster frequencyGenome frequencyCorrected p-valueFDR False positivesGenes annotated to the termcellular aromatic compound metabolic process105 of 207 genes, 50.7%2116 of 7166 genes, 29.5%6.13E-08 0.00% 0 PNO1, DAT1, PPR1, CWC2, UTP18, SIR2, YHL012W, MSH2, DUS1, MCD1, FKH1, ELG1, SMC6, CDC5, TSR4, SEN34, CLB5, CDC6, MTO1, CTF18, BUD21, EFG1, MSH3, IRC8, TRF5, RNH203, THI80, JJJ1, POL1, PLM2, RNR1, HO, TOS4, TEA1, BNA2, ESC8, PXR1, FAL1, IFH1, RRN3, ZAP1, DPB2, DAL4, SMC5, HTL1, LCP5, RPC53, NOP19, CDC45, SIR4, PPH3, LAS1, TOP1, PDS5, YOX1, RAD53, SSF1, YLR063W, HCM1, BAS1, DHR2, YOR338W, RAD9, ASG1, TOF1, NCS2, OGG1, RNT1, NOP53, BCD1, DAL1, FIR1, SNU23, MSH5, PZF1, PMS1, SMC3, BUD23, SPO16, MSH1, SAP185, DBP8, UTP9, VTS1, CLB6, RCL1, ORC1, RRP36, SAS2, BFR2, UTP25, RRN11, UTP23, UTP6, IPI1, DFR1, YCG1, ABF1, ZDS2, RRN7, YPL216W, MRC1, SPP41, SPT21, EST2organelle fission 31 of 207 genes, 15.0%283 of 7166 genes, 3.9%7.66E-08 0.00% 0 CLB6, MSH2, MIF2, TOF1, SPC98, MCD1, ELG1, CLN1, CLB1, CLN2, MSH5, KIN4, HOP1, CDC5, CBF2, YCG1, BUB1, SMC3, CLB5, CTF18, SPO16, SWE1, PPH3, MSH3,MRC1, TOP1, LTE1, PDS5, IBD2, APC1, SLK19mitotic nuclear division24 of 207 genes, 11.6%179 of 7166 genes, 2.5%1.96E-07 0.00% 0 CLB6, MIF2, TOF1, SPC98, MCD1, ELG1, CLN1, CLB1, CLN2, KIN4, CDC5, CBF2, BUB1, SMC3, CLB5, YCG1, CTF18, MRC1, TOP1, LTE1, PDS5, IBD2, APC1, SLK19186Downregulated Terms from the Process Ontology of gene_association.sgd with p-value <= 0.01Gene Ontology termCluster frequencyGenome frequencyCorrected p-valueFDR False positivesGenes annotated to the termchromosome segregation27 of 207 genes, 13.0%227 of 7166 genes, 3.2%2.20E-07 0.00% 0 SIR2, MIF2, TOF1, ESC8, DAD4, MCD1, ELG1, NNF1, SMC6, MSH5, KIN4, HOP1, CDC5, CBF2, SMC5, BUB1, SMC3, YCG1, CTF18, SPO16, MRC1, TOP1, PDS5, LTE1, IBD2, APC1, SLK19reproduction 42 of 207 genes, 20.3%510 of 7166 genes, 7.1%2.65E-07 0.00% 0 SPH1, SPS4, SPR1, YOR338W, MSH2, MIF2, TOF1, SPS19, SPC98, FKH1, CLB1, CRR1, CLN2, BUD4, BUD3, SSP2, ATC1, MSH5, HOP1, CDC5, PMS1, SMC3, CLB5, GIN4, SPO16, EFG1, SWE1, MSH3, CLB6, POL1, SPO21, HO, KCC4, AXL2, ELM1, YMR144W, BUB1, YCG1, PPH3, PDS5, SSF1, SLK19DNA replication 22 of 207 genes, 10.6%156 of 7166 genes, 2.2%4.35E-07 0.00% 0 CLB6, ORC1, SIR2, RAD9, POL1, MSH2, RNR1, TOF1, FKH1, ELG1, DPB2, IPI1, CDC6, CLB5, ABF1, CTF18, CDC45, MRC1, MSH3, TOP1, RAD53, RNH203nuclear chromosome segregation24 of 207 genes, 11.6%194 of 7166 genes, 2.7%1.05E-06 0.00% 0 SIR2, MIF2, TOF1, ESC8, DAD4, MCD1, ELG1, MSH5, KIN4, HOP1, CDC5, CBF2, SMC5, BUB1, SMC3, YCG1, CTF18, SPO16, MRC1, TOP1, PDS5, LTE1, IBD2, APC1chromosome organization45 of 207 genes, 21.7%610 of 7166 genes, 8.5%1.97E-06 0.00% 0 SIR2, YOR338W, MSH2, MIF2, TOF1, OGG1, RNT1, MCD1, FKH1, ELG1, KIN4, MSH5, HOP1, CDC5, CDC6, SMC3, RLF2, CTF18, SPO16, MSH3, LTE1, APC1, ORC1, ESC8, PXR1, SAS2, IFH1, NTO1, DPB2, CBF2, SMC5, HTL1, BUB1, YCG1, ABF1, ZDS2, CDC45, SIR4, YPL216W, MRC1, TOP1, PDS5, EST2, SPT21, IBD2187Downregulated Terms from the Process Ontology of gene_association.sgd with p-value <= 0.01Gene Ontology termCluster frequencyGenome frequencyCorrected p-valueFDR False positivesGenes annotated to the termnegative regulation of cellular process46 of 207 genes, 22.2%635 of 7166 genes, 8.9%2.26E-06 0.00% 0 DAT1, SIR2, RAD9, ACM1, MSH2, AVO1, SKG6, TOF1, HSL1, FKH1, RFU1, ELG1, KIN4, HOP1, CDC6, GIN4, SWE1, MSH3, LTE1, VTS1, ORC1, KCC4, ESC8, PXR1, PTP3, SAS2, IFH1, DPB2, YDL073W, BUB1, YCG1, ABF1, BNR1, ZDS2, CDC45, SIR4, YPL216W, PPH3, MRC1, TOS2, YOX1, TOP1, SPP41, SPT21, IBD2, RAD53negative regulation of cell cycle20 of 207 genes, 9.7%142 of 7166 genes, 2.0%2.86E-06 0.00% 0 ORC1, RAD9, MSH2, KCC4, SKG6, TOF1, HSL1, KIN4, HOP1, CDC6, BUB1, YCG1, GIN4, MRC1, PPH3, SWE1, TOS2, LTE1, IBD2, RAD53regulation of cellular process82 of 207 genes, 39.6%1569 of 7166 genes, 21.9%3.38E-06 0.00% 0 DAT1, PPR1, SIR2, MSH2, HSL1, FKH1, RFU1, ELG1, CLB1, CLN2, SSP2, RAX2, CDC5, CLB5, PCL1, CDC6, MSB2, EUG1, EFG1, MSH3, KCC4, TEA1, ESC8, PXR1, IFH1, RRN3, ZAP1, ELM1, DPB2, BUB1, JJJ3, BNR1, CDC45, SIR4, SKP2, PPH3, TOS2, TOP1, YOX1, RAD53, HCM1, BAS1, SPH1, DHR2, YOR338W, ACM1, RAD9, ASG1, AVO1, SKG6, TOF1, RNT1, DAD4, BUD3, KIN4, HOP1, GIN4, SPO16, SWE1, LTE1, UTP9, ALK1, APC1, VTS1, CLB6, GEA1, ORC1, PTP3, SAS2, CLN1, IPI1, YDL073W, YCG1, ABF1, ZDS2, YPL216W, MRC1, SPP41,SPT21, IBD2, SLK19, PET309188Downregulated Terms from the Process Ontology of gene_association.sgd with p-value <= 0.01Gene Ontology termCluster frequencyGenome frequencyCorrected p-valueFDR False positivesGenes annotated to the termreproductive process39 of 207 genes, 18.8%493 of 7166 genes, 6.9%4.12E-06 0.00% 0 SPH1, SPS4, SPR1, YOR338W, MSH2, MIF2, TOF1, SPS19, SPC98, FKH1, CLB1, CRR1, CLN2, BUD3, SSP2, MSH5, HOP1, CDC5, PMS1, SMC3, CLB5, GIN4, SPO16, EFG1, SWE1, MSH3, CLB6, POL1, SPO21, HO, KCC4, ELM1, YMR144W, BUB1, YCG1, PPH3, PDS5, SSF1, SLK19regulation of biological process85 of 207 genes, 41.1%1678 of 7166 genes, 23.4%6.90E-06 0.00% 0 DAT1, PPR1, SIR2, MSH2, HSL1, FKH1, RFU1, CCH1, ELG1, CLB1, CLN2, SSP2, RAX2, CDC5, CLB5, PCL1, CDC6, MSB2, EUG1, EFG1, MSH3, TRF5, KCC4, TOS4, TEA1, ESC8, PXR1, IFH1, RRN3, ZAP1, ELM1, DPB2, BUB1, JJJ3, BNR1, CDC45, SIR4, SKP2, PPH3, TOS2, TOP1, YOX1, RAD53, HCM1, BAS1, SPH1, DHR2, YOR338W, ACM1, RAD9, ASG1, AVO1, SKG6, TOF1, RNT1, DAD4, BUD3, KIN4, HOP1, GIN4, SPO16, SWE1, LTE1, UTP9, ALK1, APC1, VTS1, CLB6, GEA1, ORC1, PTP3, SAS2, CLN1, IPI1, YDL073W, YCG1, ABF1, ZDS2, YPL216W, MRC1, SPP41, SPT21, IBD2, SLK19, PET309maturation of SSU-rRNA18 of 207 genes, 8.7%121 of 7166 genes, 1.7%7.51E-06 0.00% 0 PNO1, DHR2, RCL1, UTP18, RRP36, FAL1, BFR2, UTP25,UTP6, UTP23, LCP5, TSR4, BUD23, NOP19, BUD21, EFG1, DBP8, UTP9189Downregulated Terms from the Process Ontology of gene_association.sgd with p-value <= 0.01Gene Ontology termCluster frequencyGenome frequencyCorrected p-valueFDR False positivesGenes annotated to the termDNA metabolic process41 of 207 genes, 19.8%548 of 7166 genes, 7.6%7.96E-06 0.00% 0 SIR2, RAD9, MSH2, TOF1, OGG1, MCD1, FKH1, ELG1, DAL1, SMC6, MSH5, CDC5, PMS1, CDC6, SMC3, CLB5, CTF18, SPO16, MSH1, MSH3, IRC8, RNH203, VTS1, CLB6, ORC1, POL1, HO, RNR1, PXR1, DPB2, IPI1, SMC5, ABF1, CDC45, SIR4, PPH3, MRC1, PDS5, TOP1, EST2, RAD53maturation of SSU-rRNA from tricistronic rRNA transcript (SSU-rRNA, 5.8S rRNA, LSU-rRNA)17 of 207 genes, 8.2%109 of 7166 genes, 1.5%9.53E-06 0.00% 0 PNO1, DHR2, RCL1, UTP18, RRP36, FAL1, BFR2, UTP25,UTP6, UTP23, LCP5, NOP19, BUD23, BUD21, EFG1, DBP8, UTP9DNA-dependent DNA replication19 of 207 genes, 9.2%138 of 7166 genes, 1.9%1.06E-05 0.00% 0 CLB6, ORC1, POL1, MSH2, TOF1, FKH1, ELG1, DPB2, IPI1, CDC6, CLB5, ABF1, CTF18, CDC45, MRC1, MSH3, TOP1, RAD53, RNH203190Downregulated Terms from the Process Ontology of gene_association.sgd with p-value <= 0.01Gene Ontology termCluster frequencyGenome frequencyCorrected p-valueFDR False positivesGenes annotated to the termmacromolecule metabolic process132 of 207 genes, 63.8%3203 of 7166 genes, 44.7%1.44E-05 0.00% 0 DAT1, MNL2, PPR1, UTP18, SIR2, YHL012W, MSH2, DUS1, HSL1, FKH1, RFU1, ELG1, CLB1, CRR1, SSP2, SMC6, TSR4, SEN34, MTO1, CTF18, MSH3, RNH203, PLM2, RNR1, TOS4, ESC8, PXR1, NTO1, DPB2, JJJ3, CDC45, SKP2, LAS1, PDS5, RAD53, BAS1, DHR2, RAD9,ACM1, YOR338W, ASG1, NCS2, RNT1, BCD1, DAL1, FIR1, MSH5, PZF1, GIN4, SPO16, SAP185, UTP9, RRP36, CLN1, UTP25, IPI1, YDL073W, ABF1, ZDS2, YPL216W, MRC1, SPT21, EST2, PET309, PNO1, CWC2, MCD1, CLN2, RPL22B, CDC5, CDC6, PCL1, CLB5, BUD21, EFG1, BST1, IRC8, TRF5, JJJ1, POL1, KCC4, HO, TEA1, IFH1, FAL1, ZAP1, RRN3, ELM1, SMC5, LCP5, HTL1, BUB1, RPC53, NOP19, SIR4, PPH3, YOX1, TOP1, YLR063W, SSF1, HCM1, SPH1, MNN1, SPR1, TOF1, OGG1, NOP53, YGK3, KIN4, SNU23, PMS1, SMC3, BUD23, MSH1, SWE1, DBP8, BUL2, ALK1, APC1, VTS1, CLB6, RCL1, ORC1, PTP3, SAS2, BFR2, RRN11, UTP6, UTP23, YCG1, RRN7, SPP41cell cycle phase transition22 of 207 genes, 10.6%188 of 7166 genes, 2.6%1.54E-05 0.00% 0 CLB6, ORC1, RAD9, HSL1, FKH1, CLN1, CLB1, CLN2, KIN4, CDC5, CDC6, BUB1, CLB5, ZDS2, CDC45, SWE1, SAP185, YOX1, LTE1, IBD2, APC1, SLK19191Downregulated Terms from the Process Ontology of gene_association.sgd with p-value <= 0.01Gene Ontology termCluster frequencyGenome frequencyCorrected p-valueFDR False positivesGenes annotated to the termmitotic cell cycle phase transition22 of 207 genes, 10.6%188 of 7166 genes, 2.6%1.54E-05 0.00% 0 CLB6, ORC1, RAD9, HSL1, FKH1, CLN1, CLB1, CLN2, KIN4, CDC5, CDC6, BUB1, CLB5, ZDS2, CDC45, SWE1, SAP185, YOX1, LTE1, IBD2, APC1, SLK19regulation of DNA metabolic process17 of 207 genes, 8.2%116 of 7166 genes, 1.6%2.49E-05 0.00% 0 VTS1, CLB6, SIR2, RAD9, MSH2, TOF1, PXR1, FKH1, ELG1, IPI1, CDC6, CLB5, SPO16, MRC1, MSH3, PPH3, TOP1rRNA metabolic process33 of 207 genes, 15.9%399 of 7166 genes, 5.6%2.60E-05 0.00% 0 PNO1, DHR2, UTP18, RNT1, NOP53, BCD1, PZF1, TSR4, BUD23, BUD21, EFG1, DBP8, UTP9, TRF5, RCL1, JJJ1, PLM2, TOS4, PXR1, RRP36, BFR2, FAL1, UTP25, RRN11,UTP6, UTP23, IPI1, LCP5, NOP19, RRN7, LAS1, SSF1, YLR063Wnegative regulation of biological process48 of 207 genes, 23.2%740 of 7166 genes, 10.3%3.48E-05 0.00% 0 DAT1, SIR2, RAD9, ACM1, MSH2, AVO1, SKG6, TOF1, HSL1, RNT1, FKH1, RFU1, ELG1, KIN4, HOP1, CDC6, GIN4, SWE1, MSH3, LTE1, TRF5, VTS1, ORC1, KCC4, ESC8, PXR1, PTP3, SAS2, IFH1, DPB2, YDL073W, BUB1,YCG1, ABF1, BNR1, ZDS2, CDC45, SIR4, YPL216W, PPH3, MRC1, TOS2, TOP1, YOX1, SPP41, SPT21, IBD2, RAD53cell cycle checkpoint16 of 207 genes, 7.7%105 of 7166 genes, 1.5%3.68E-05 0.00% 0 ORC1, RAD9, KCC4, TOF1, HSL1, KIN4, HOP1, CDC6, BUB1, GIN4, MRC1, PPH3, SWE1, LTE1, IBD2, RAD53192Downregulated Terms from the Process Ontology of gene_association.sgd with p-value <= 0.01Gene Ontology termCluster frequencyGenome frequencyCorrected p-valueFDR False positivesGenes annotated to the termribosomal small subunit biogenesis19 of 207 genes, 9.2%149 of 7166 genes, 2.1%3.80E-05 0.00% 0 PNO1, SGD1, DHR2, RCL1, UTP18, RRP36, FAL1, BFR2, UTP25, UTP6, UTP23, LCP5, TSR4, BUD23, NOP19, BUD21, EFG1, DBP8, UTP9negative regulation of mitotic cell cycle15 of 207 genes, 7.2%92 of 7166 genes, 1.3%3.89E-05 0.00% 0 KIN4, BUB1, CDC6, ORC1, RAD9, GIN4, KCC4, SKG6, SWE1, MRC1, HSL1, TOS2, LTE1, IBD2, RAD53193Downregulated Terms from the Process Ontology of gene_association.sgd with p-value <= 0.01Gene Ontology termCluster frequencyGenome frequencyCorrected p-valueFDR False positivesGenes annotated to the termcellular process 181 of 207 genes, 87.4%5158 of 7166 genes, 72.0%4.53E-05 0.00% 0 EMW1, RSA4, DAT1, MNL2, PPR1, UTP18, SIR2, YHL012W, MSH2, ROG1, DUS1, HSL1, SFG1, FKH1, RFU1, ELG1, CLB1, CRR1, ATX1, SSP2, SMC6, TSR4, SEN34, MYO1, MTO1, CTF18, EUG1, MSH3, RNH203, PLM2, RNR1, TOS4, BNA2, ESC8, PXR1, NTO1, DPB2, JJJ3, CDC45, SKP2, LAS1, PDS5, RAD53, BAS1, DHR2, RAD9, ACM1, YOR338W, ASG1, SKG6, NCS2, RNT1, BCD1, NNF1, DAL1, FIR1, ATC1, MSH5, PZF1, GIN4, RLF2, SPO16, SAP185, UTP9, GEA1, SPO21, RRP36, CLN1, UTP25, YDR179W-A, IPI1, YDL073W, DFR1, ABF1, ZDS2, SHQ1, YPL216W, MRC1, SPT21, EST2, PET309, SLK19, PNO1, CIN2, CWC2, SPS19, HLR1, MCD1, CLN2, RAX2, CDC5, RPL22B, YEH1, CDC6, PCL1, CLB5, MSB2, BUD21, EFG1, BST1, IRC8, TRF5, THI80, AFI1, JJJ1, POL1, HO, KCC4, TEA1, MSB1, IFH1, FAL1, RRN3, TCA17, ZAP1, ELM1, DAL4, CBF2, SMC5, YMR144W, LCP5, HTL1, RPC53, BUB1, BNR1, NOP19, SIR4, PPH3, TOS2, YOX1, TOP1, FAA3, SSF1, YLR063W, WSC4, HCM1, SPH1, SPS4, MNN1, SPR1, AVO1, MIF2, TOF1, OGG1, SPC98, DAD4, NOP53, BUD4, BUD3, YGK3, SNU23, HES1, KIN4, HOP1, PMS1, SMC3, BUD23, MSH1, SWE1, DBP8, LTE1, ALK1, BUL2, APC1, VTS1, CLB6, RCL1, DUR1,2, ORC1, PTP3, SAS2, BFR2, 194Downregulated Terms from the Process Ontology of gene_association.sgd with p-value <= 0.01Gene Ontology termCluster frequencyGenome frequencyCorrected p-valueFDR False positivesGenes annotated to the termbiological regulation95 of 207 genes, 45.9%2044 of 7166 genes, 28.5%4.66E-05 0.00% 0 CIN2, DAT1, PPR1, SIR2, MSH2, HSL1, FKH1, RFU1, CCH1, ELG1, CLB1, CLN2, ATX1, SSP2, RAX2, CDC5, CLB5, PCL1, CDC6, MSB2, EUG1, EFG1, BST1, MSH3, TRF5, JJJ1, KCC4, TOS4, TEA1, ESC8, PXR1, IFH1, RRN3, ZAP1, ELM1, DPB2, BUB1, JJJ3, BNR1, CDC45, SIR4, SKP2, PPH3, TOS2, TOP1, YOX1, RAD53, SSF1, HCM1, BAS1, SPH1, DHR2, YOR338W, ACM1, RAD9, ASG1, AVO1, SKG6, TOF1, OGG1, RNT1, DAD4, BUD3, ATC1, KIN4, HOP1, GIN4, SPO16, SWE1, LTE1, UTP9, ALK1, APC1, VTS1, CLB6, RCL1, GEA1, ORC1, PTP3, SAS2, CLN1, YDR179W-A, IPI1, YDL073W, YCG1, ABF1,ZDS2, YPL216W, MRC1, SPP41, EST2, SPT21, IBD2, SLK19, PET309G2/M transition of mitotic cell cycle11 of 207 genes, 5.3%48 of 7166 genes, 0.7%6.85E-05 0.00% 0 CLB6, CLB5, CDC6, ORC1, ZDS2, SWE1, HSL1, FKH1, CLN1, CLB1, CLN2cell cycle G2/M phase transition11 of 207 genes, 5.3%48 of 7166 genes, 0.7%6.85E-05 0.00% 0 CLB6, CLB5, CDC6, ORC1, ZDS2, SWE1, HSL1, FKH1, CLN1, CLB1, CLN2sister chromatid segregation19 of 207 genes, 9.2%157 of 7166 genes, 2.2%8.93E-05 0.00% 0 SIR2, MIF2, TOF1, ESC8, MCD1, ELG1, KIN4, CBF2, SMC5, BUB1, SMC3, YCG1, CTF18, MRC1, PDS5, LTE1, TOP1, IBD2, APC1195Downregulated Terms from the Process Ontology of gene_association.sgd with p-value <= 0.01Gene Ontology termCluster frequencyGenome frequencyCorrected p-valueFDR False positivesGenes annotated to the termcytoskeleton-dependent cytokinesis15 of 207 genes, 7.2%98 of 7166 genes, 1.4%9.32E-05 0.00% 0 BUD4, BUD3, ATC1, RAX2, SPH1, CDC5, AFI1, BUD23, MYO1, MSB2, BNR1, SKG6, TOS2, AXL2, ELM1meiotic cell cycle 28 of 207 genes, 13.5%326 of 7166 genes, 4.5%0.00014 0.00% 0 CLB6, SPS4, SPR1, POL1, YOR338W, MSH2, SPO21, MIF2, TOF1, SPS19, SPC98, CLB1, CRR1, SSP2, MSH5, HOP1, CDC5, PMS1, BUB1, SMC3, CLB5, YCG1, SPO16, SWE1, PPH3, MSH3, PDS5, SLK19ncRNA processing 35 of 207 genes, 16.9%473 of 7166 genes, 6.6%0.00015 0.00% 0 PNO1, DHR2, UTP18, DUS1, NCS2, RNT1, NOP53, BCD1, TSR4, SEN34, BUD23, MTO1, BUD21, EFG1, SAP185, DBP8, UTP9, TRF5, RCL1, JJJ1, PLM2, TOS4, PXR1, RRP36, BFR2, FAL1, UTP25, UTP6, UTP23, IPI1, LCP5, NOP19, LAS1, SSF1, YLR063WRNA metabolic process75 of 207 genes, 36.2%1501 of 7166 genes, 20.9%0.00017 0.00% 0 PNO1, DAT1, PPR1, CWC2, UTP18, SIR2, MSH2, DUS1, FKH1, TSR4, SEN34, CDC6, MTO1, BUD21, EFG1, TRF5,RNH203, JJJ1, POL1, PLM2, TOS4, TEA1, ESC8, PXR1, IFH1, FAL1, RRN3, ZAP1, DPB2, LCP5, HTL1, RPC53, NOP19, CDC45, SIR4, LAS1, TOP1, YOX1, YLR063W, SSF1, HCM1, BAS1, DHR2, YOR338W, RAD9, ASG1, NCS2, RNT1, NOP53, BCD1, FIR1, SNU23, PZF1, BUD23,SAP185, DBP8, UTP9, VTS1, RCL1, ORC1, RRP36, SAS2,BFR2, UTP25, RRN11, UTP6, UTP23, IPI1, ABF1, RRN7, ZDS2, YPL216W, MRC1, SPP41, SPT21196Downregulated Terms from the Process Ontology of gene_association.sgd with p-value <= 0.01Gene Ontology termCluster frequencyGenome frequencyCorrected p-valueFDR False positivesGenes annotated to the termmitotic cell cycle checkpoint13 of 207 genes, 6.3%78 of 7166 genes, 1.1%0.00024 0.00% 0 KIN4, BUB1, CDC6, ORC1, RAD9, GIN4, KCC4, SWE1, MRC1, HSL1, LTE1, IBD2, RAD53rRNA processing 29 of 207 genes, 14.0%355 of 7166 genes, 5.0%0.00025 0.00% 0 PNO1, DHR2, RCL1, JJJ1, UTP18, PLM2, TOS4, PXR1, RNT1, RRP36, FAL1, BFR2, UTP25, NOP53, BCD1, UTP23, UTP6, IPI1, LCP5, TSR4, BUD23, NOP19, BUD21,EFG1, LAS1, DBP8, UTP9, YLR063W, SSF1meiotic cell cycle process25 of 207 genes, 12.1%276 of 7166 genes, 3.9%0.00026 0.00% 0 CLB6, SPS4, SPR1, POL1, YOR338W, MSH2, SPO21, MIF2, SPS19, CLB1, CRR1, SSP2, MSH5, HOP1, CDC5, PMS1, BUB1, SMC3, CLB5, YCG1, SPO16, SWE1, PPH3, MSH3, PDS5regulation of DNA replication11 of 207 genes, 5.3%55 of 7166 genes, 0.8%0.0003 0.00% 0 CLB6, IPI1, CLB5, CDC6, SIR2, RAD9, MSH2, TOF1, MSH3, MRC1, FKH1cytokinesis 15 of 207 genes, 7.2%107 of 7166 genes, 1.5%0.0003 0.00% 0 BUD4, BUD3, ATC1, RAX2, SPH1, CDC5, AFI1, BUD23, MYO1, MSB2, BNR1, SKG6, TOS2, AXL2, ELM1mitotic cytokinesis 14 of 207 genes, 6.8%93 of 7166 genes, 1.3%0.00031 0.00% 0 BUD4, BUD3, ATC1, RAX2, SPH1, CDC5, AFI1, BUD23, MSB2, BNR1, SKG6, TOS2, AXL2, ELM1ncRNA metabolic process39 of 207 genes, 18.8%584 of 7166 genes, 8.1%0.00041 0.00% 0 PNO1, DHR2, UTP18, DUS1, NCS2, RNT1, NOP53, BCD1, PZF1, TSR4, SEN34, BUD23, MTO1, BUD21, EFG1, SAP185, DBP8, UTP9, TRF5, RCL1, JJJ1, PLM2, TOS4, PXR1, RRP36, BFR2, FAL1, UTP25, RRN11, UTP6,UTP23, IPI1, LCP5, RPC53, NOP19, RRN7, LAS1, SSF1, YLR063W197Downregulated Terms from the Process Ontology of gene_association.sgd with p-value <= 0.01Gene Ontology termCluster frequencyGenome frequencyCorrected p-valueFDR False positivesGenes annotated to the termendonucleolytic cleavage in ITS1 to separate SSU-rRNAfrom 5.8S rRNA and LSU-rRNA from tricistronic rRNA transcript (SSU-rRNA, 5.8S rRNA, LSU-rRNA)10 of 207 genes, 4.8%46 of 7166 genes, 0.6%0.00046 0.00% 0 PNO1, UTP23, UTP6, RCL1, LCP5, UTP18, BUD23, NOP19, BUD21, DBP8morphogenesis checkpoint4 of 207 genes,1.9%4 of 7166 genes, 0.1%0.00058 0.00% 0 KCC4, SWE1, HSL1, GIN4regulation of nitrogen compound metabolic process57 of 207 genes, 27.5%1045 of 7166 genes, 14.6%0.00059 0.00% 0 HCM1, DAT1, SPH1, BAS1, DHR2, PPR1, SIR2, RAD9, ACM1, YOR338W, MSH2, ASG1, TOF1, FKH1, RFU1, ELG1, CLB1, CLN2, SSP2, CLB5, PCL1, CDC6, SPO16, SWE1, MSH3, UTP9, VTS1, CLB6, ORC1, TEA1, ESC8, PXR1, PTP3, SAS2, IFH1, RRN3, CLN1, ZAP1, ELM1, DPB2, IPI1, YDL073W, JJJ3, YCG1, ABF1, ZDS2, CDC45, SIR4, SKP2, YPL216W, PPH3, MRC1, TOP1, YOX1, SPP41, SPT21, PET309regulation of gene expression, epigenetic18 of 207 genes, 8.7%160 of 7166 genes, 2.2%0.00059 0.00% 0 ORC1, SIR2, MSH2, ESC8, SAS2, RNT1, FKH1, IFH1, DPB2, CDC6, ABF1, ZDS2, CDC45, SIR4, YPL216W, MRC1, TOP1, SPT21198Downregulated Terms from the Process Ontology of gene_association.sgd with p-value <= 0.01Gene Ontology termCluster frequencyGenome frequencyCorrected p-valueFDR False positivesGenes annotated to the termendonucleolytic cleavage involved in rRNA processing11 of 207 genes, 5.3%59 of 7166 genes, 0.8%0.00064 0.00% 0 PNO1, UTP23, UTP6, RCL1, LCP5, UTP18, BUD23, NOP19, BUD21, LAS1, DBP8endonucleolytic cleavage of tricistronic rRNA transcript (SSU-rRNA, 5.8S rRNA, LSU-rRNA)11 of 207 genes, 5.3%59 of 7166 genes, 0.8%0.00064 0.00% 0 PNO1, UTP23, UTP6, RCL1, LCP5, UTP18, BUD23, NOP19, BUD21, LAS1, DBP8cellular component organization93 of 207 genes, 44.9%2089 of 7166 genes, 29.2%0.00065 0.00% 0 PNO1, EMW1, RSA4, CIN2, CWC2, SIR2, MSH2, HLR1, MCD1, FKH1, ELG1, CLB1, CRR1, CLN2, SSP2, RAX2, CDC5, CLB5, PCL1, CDC6, MYO1, MSB2, CTF18, BST1, MSH3, JJJ1, KCC4, ESC8, PXR1, NTO1, IFH1, TCA17, ELM1, DPB2, CBF2, SMC5, HTL1, BUB1, BNR1, CDC45, SIR4, PPH3, TOP1, PDS5, SSF1, WSC4, HCM1, BAS1, SPH1, YOR338W, SPR1, AVO1, MIF2, TOF1, OGG1, SPC98, RNT1, DAD4, NOP53, BCD1, BUD4, MSH5, KIN4, HOP1, SMC3, GIN4, SPO16, RLF2, MSH1, SWE1, LTE1, APC1, CLB6, GEA1, ORC1, SPO21, SAS2, CLN1, RRN11, YDR179W-A, IPI1, YCG1, ABF1, ZDS2, RRN7, SHQ1, YPL216W, MRC1, EST2, SPT21, IBD2, SLK19, PET309199Downregulated Terms from the Process Ontology of gene_association.sgd with p-value <= 0.01Gene Ontology termCluster frequencyGenome frequencyCorrected p-valueFDR False positivesGenes annotated to the termcellular component biogenesis67 of 207 genes, 32.4%1322 of 7166 genes, 18.4%0.00066 0.00% 0 PNO1, RSA4, CIN2, CWC2, UTP18, CRR1, SSP2, CDC5, TSR4, CLB5, CDC6, MYO1, BUD21, EFG1, JJJ1, PLM2, KCC4, TOS4, PXR1, FAL1, TCA17, ELM1, CBF2, LCP5, BUB1, NOP19, BNR1, CDC45, SIR4, LAS1, YLR063W, SSF1, SGD1, BAS1, SPH1, DHR2, MIF2, SPC98, RNT1, DAD4, NOP53, BCD1, MSH5, HOP1, SMC3, BUD23, GIN4, SPO16, RLF2, SWE1, DBP8, UTP9, ECM1, RCL1, ORC1, SPO21, RRP36, BFR2, UTP25, RRN11, UTP6, UTP23, IPI1, YCG1, RRN7, SHQ1, PET309regulation of nuclear division16 of 207 genes, 7.7%130 of 7166 genes, 1.8%0.00075 0.00% 0 KIN4, CLB6, HOP1, CLB5, BUB1, MSH2, SPO16, SWE1, PPH3, LTE1, CLN1, IBD2, CLB1, APC1, CLN2, SLK19sister chromatid cohesion11 of 207 genes, 5.3%60 of 7166 genes, 0.8%0.00076 0.00% 0 SMC5, SMC3, BUB1, SIR2, CTF18, TOF1, ESC8, MRC1, MCD1, PDS5, ELG1gene silencing 18 of 207 genes, 8.7%164 of 7166 genes, 2.3%0.00085 0.00% 0 ORC1, SIR2, MSH2, ESC8, SAS2, RNT1, FKH1, IFH1, DPB2, CDC6, ABF1, ZDS2, CDC45, SIR4, YPL216W, MRC1, TOP1, SPT21cellular response to DNA damage stimulus28 of 207 genes, 13.5%355 of 7166 genes, 5.0%0.00086 0.00% 0 SIR2, RAD9, POL1, MSH2, PLM2, TOS4, TOF1, OGG1, MCD1, ELG1, DPB2, SMC6, MSH5, SMC5, HTL1, PMS1, SMC3, ABF1, CTF18, CDC45, SIR4, MSH1, PPH3, MSH3, MRC1, PDS5, ALK1, RAD53negative regulation of cell cycle process14 of 207 genes, 6.8%101 of 7166 genes, 1.4%0.00087 0.00% 0 KIN4, HOP1, YCG1, BUB1, CDC6, ORC1, RAD9, MSH2, SKG6, PPH3, SWE1, TOS2, LTE1, IBD2200Downregulated Terms from the Process Ontology of gene_association.sgd with p-value <= 0.01Gene Ontology termCluster frequencyGenome frequencyCorrected p-valueFDR False positivesGenes annotated to the termregulation of macromolecule metabolic process59 of 207 genes, 28.5%1116 of 7166 genes, 15.6%0.00101 0.00% 0 HCM1, DAT1, SPH1, BAS1, DHR2, PPR1, SIR2, RAD9, ACM1, YOR338W, MSH2, ASG1, TOF1, RNT1, FKH1, RFU1, ELG1, CLB1, CLN2, SSP2, CLB5, PCL1, CDC6, SPO16, SWE1, MSH3, UTP9, TRF5, VTS1, CLB6, ORC1, TOS4, TEA1, ESC8, PXR1, PTP3, SAS2, IFH1, RRN3, CLN1, ZAP1, ELM1, DPB2, IPI1, YDL073W, JJJ3, YCG1, ABF1, ZDS2, CDC45, SIR4, YPL216W, PPH3, MRC1, TOP1, YOX1, SPP41, SPT21, PET309mitotic sister chromatid segregation16 of 207 genes, 7.7%135 of 7166 genes, 1.9%0.00126 0.00% 0 KIN4, CBF2, YCG1, SMC3, BUB1, CTF18, MIF2, TOF1, MRC1, TOP1, LTE1, PDS5, MCD1, IBD2, ELG1, APC1reproduction of a single-celled organism20 of 207 genes, 9.7%204 of 7166 genes, 2.8%0.00128 0.00% 0 SPH1, SPS4, SPR1, YOR338W, SPO21, HO, KCC4, SPS19,FKH1, AXL2, CRR1, ELM1, SSP2, BUD3, BUD4, ATC1, YMR144W, SMC3, GIN4, SPO16201Downregulated Terms from the Process Ontology of gene_association.sgd with p-value <= 0.01Gene Ontology termCluster frequencyGenome frequencyCorrected p-valueFDR False positivesGenes annotated to the termorganelle organization72 of 207 genes, 34.8%1490 of 7166 genes, 20.8%0.00134 0.00% 0 RSA4, SIR2, MSH2, MCD1, FKH1, ELG1, CLB1, CLN2, CDC5, CLB5, PCL1, CDC6, MYO1, CTF18, BST1, MSH3, KCC4, ESC8, PXR1, NTO1, IFH1, ELM1, DPB2, CBF2, SMC5, HTL1, BUB1, BNR1, CDC45, SIR4, PPH3, TOP1, PDS5, SSF1, HCM1, YOR338W, AVO1, MIF2, TOF1, OGG1, SPC98, RNT1, DAD4, NOP53, BUD4, MSH5, KIN4, HOP1, SMC3, GIN4, SPO16, RLF2, MSH1, SWE1, LTE1, APC1, CLB6, GEA1, ORC1, SAS2, CLN1, IPI1, YCG1, ABF1, ZDS2, YPL216W, MRC1, EST2, SPT21, IBD2, SLK19, PET309regulation of cellular metabolic process58 of 207 genes, 28.0%1102 of 7166 genes, 15.4%0.00151 0.00% 0 HCM1, DAT1, SPH1, BAS1, DHR2, PPR1, SIR2, RAD9, ACM1, YOR338W, MSH2, ASG1, TOF1, FKH1, RFU1, ELG1, CLB1, CLN2, SSP2, CLB5, PCL1, CDC6, SPO16, SWE1, MSH3, UTP9, VTS1, CLB6, ORC1, TEA1, ESC8, PXR1, PTP3, SAS2, IFH1, RRN3, CLN1, ZAP1, ELM1, DPB2, IPI1, YDL073W, JJJ3, YCG1, ABF1, ZDS2, CDC45, SIR4, SKP2, YPL216W, PPH3, MRC1, TOP1, YOX1, SPP41, SPT21, RAD53, PET309202Downregulated Terms from the Process Ontology of gene_association.sgd with p-value <= 0.01Gene Ontology termCluster frequencyGenome frequencyCorrected p-valueFDR False positivesGenes annotated to the termregulation of metabolic process61 of 207 genes, 29.5%1186 of 7166 genes, 16.6%0.0016 0.00% 0 HCM1, DAT1, SPH1, BAS1, DHR2, PPR1, SIR2, RAD9, ACM1, YOR338W, MSH2, ASG1, TOF1, RNT1, FKH1, RFU1, ELG1, CLB1, CLN2, SSP2, CLB5, PCL1, CDC6, SPO16, SWE1, MSH3, UTP9, TRF5, VTS1, CLB6, ORC1, TOS4, TEA1, ESC8, PXR1, PTP3, SAS2, IFH1, RRN3, ZAP1, CLN1, ELM1, DPB2, IPI1, YDL073W, JJJ3, YCG1, ABF1, ZDS2, CDC45, SIR4, SKP2, YPL216W, PPH3, MRC1, TOP1, YOX1, SPP41, SPT21, RAD53, PET309regulation of primary metabolic process57 of 207 genes, 27.5%1080 of 7166 genes, 15.1%0.00176 0.00% 0 HCM1, DAT1, SPH1, BAS1, DHR2, PPR1, SIR2, RAD9, ACM1, YOR338W, MSH2, ASG1, TOF1, FKH1, RFU1, ELG1, CLB1, CLN2, SSP2, CLB5, PCL1, CDC6, SPO16, SWE1, MSH3, UTP9, VTS1, CLB6, ORC1, TEA1, ESC8, PXR1, PTP3, SAS2, IFH1, RRN3, CLN1, ZAP1, ELM1, DPB2, IPI1, YDL073W, JJJ3, YCG1, ABF1, ZDS2, CDC45, SIR4, SKP2, YPL216W, PPH3, MRC1, TOP1, YOX1, SPP41, SPT21, PET309negative regulation of DNA replication6 of 207 genes,2.9%15 of 7166 genes, 0.2%0.00188 0.00% 0 TOF1, MSH3, MRC1, SIR2, RAD9, MSH2chromatin silencing 17 of 207 genes, 8.2%156 of 7166 genes, 2.2%0.00192 0.00% 0 ORC1, SIR2, MSH2, ESC8, SAS2, FKH1, IFH1, DPB2, CDC6, ABF1, ZDS2, CDC45, YPL216W, SIR4, MRC1, TOP1, SPT21203Downregulated Terms from the Process Ontology of gene_association.sgd with p-value <= 0.01Gene Ontology termCluster frequencyGenome frequencyCorrected p-valueFDR False positivesGenes annotated to the termnegative regulation of gene expression, epigenetic17 of 207 genes, 8.2%156 of 7166 genes, 2.2%0.00192 0.00% 0 ORC1, SIR2, MSH2, ESC8, SAS2, FKH1, IFH1, DPB2, CDC6, ABF1, ZDS2, CDC45, YPL216W, SIR4, MRC1, TOP1, SPT21nuclear DNA replication9 of 207 genes,4.3%43 of 7166 genes, 0.6%0.00244 0.00% 0 CLB6, IPI1, CLB5, CDC6, ORC1, POL1, CDC45, MRC1, FKH1negative regulation of nitrogen compound metabolic process31 of 207 genes, 15.0%440 of 7166 genes, 6.1%0.00245 0.00% 0 VTS1, DAT1, ORC1, SIR2, RAD9, ACM1, MSH2, TOF1, ESC8, PXR1, SAS2, PTP3, FKH1, IFH1, RFU1, ELG1, DPB2, YDL073W, CDC6, YCG1, ABF1, ZDS2, CDC45, SIR4, YPL216W, MSH3, MRC1, TOP1, YOX1, SPP41, SPT21cleavage involved in rRNA processing12 of 207 genes, 5.8%82 of 7166 genes, 1.1%0.00296 0.00% 0 PNO1, UTP23, UTP6, RCL1, LCP5, UTP18, BUD23, NOP19, BUD21, LAS1, DBP8, RRP36negative regulation of cellular metabolic process32 of 207 genes, 15.5%468 of 7166 genes, 6.5%0.00315 0.00% 0 DAT1, SIR2, RAD9, ACM1, MSH2, TOF1, FKH1, RFU1, ELG1, CDC6, MSH3, VTS1, ORC1, ESC8, PTP3, SAS2, PXR1, IFH1, DPB2, YDL073W, YCG1, ABF1, ZDS2, CDC45, YPL216W, SIR4, MRC1, YOX1, TOP1, SPT21, SPP41, RAD53cellular bud site selection9 of 207 genes,4.3%45 of 7166 genes, 0.6%0.00365 0.00% 0 BUD4, BUD3, ATC1, RAX2, SPH1, AFI1, BUD23, MSB2, AXL2cell cycle DNA replication9 of 207 genes,4.3%45 of 7166 genes, 0.6%0.00365 0.00% 0 CLB6, IPI1, CLB5, CDC6, ORC1, POL1, CDC45, MRC1, FKH1204Downregulated Terms from the Process Ontology of gene_association.sgd with p-value <= 0.01Gene Ontology termCluster frequencyGenome frequencyCorrected p-valueFDR False positivesGenes annotated to the termnegative regulation of nucleobase-containing compound metabolic process26 of 207 genes, 12.6%340 of 7166 genes, 4.7%0.00388 0.00% 0 DAT1, ORC1, SIR2, RAD9, MSH2, TOF1, ESC8, PXR1, SAS2, FKH1, IFH1, ELG1, DPB2, CDC6, YCG1, ABF1, ZDS2, CDC45, SIR4, YPL216W, MRC1, MSH3, TOP1, YOX1, SPP41, SPT21endonucleolytic cleavage to generatemature 5'-end of SSU-rRNA from (SSU-rRNA, 5.8S rRNA, LSU-rRNA)8 of 207 genes,3.9%35 of 7166 genes, 0.5%0.00439 0.00% 0 PNO1, BUD21, UTP23, UTP6, RCL1, DBP8, UTP18, NOP19DNA repair 24 of 207 genes, 11.6%301 of 7166 genes, 4.2%0.00456 0.00% 0 SIR2, RAD9, POL1, MSH2, TOF1, OGG1, MCD1, ELG1, DPB2, SMC6, MSH5, SMC5, PMS1, SMC3, ABF1, CTF18, CDC45, SIR4, MSH1, PPH3, MRC1, MSH3, PDS5, RAD53ribosome biogenesis 32 of 207 genes, 15.5%477 of 7166 genes, 6.7%0.00472 0.00% 0 PNO1, RSA4, SGD1, DHR2, UTP18, RNT1, NOP53, BCD1, TSR4, BUD23, BUD21, EFG1, DBP8, UTP9, ECM1, RCL1, JJJ1, PLM2, TOS4, RRP36, PXR1, BFR2, FAL1, UTP25, UTP6, UTP23, IPI1, LCP5, NOP19, LAS1, SSF1, YLR063Wpositive regulation of cell cycle12 of 207 genes, 5.8%86 of 7166 genes, 1.2%0.00494 0.00% 0 CLB6, CDC5, CLB5, ZDS2, CDC45, PPH3, DAD4, FKH1, CLN1, CLB1, SLK19, CLN2205Downregulated Terms from the Process Ontology of gene_association.sgd with p-value <= 0.01Gene Ontology termCluster frequencyGenome frequencyCorrected p-valueFDR False positivesGenes annotated to the termprotein phosphorylation21 of 207 genes, 10.1%244 of 7166 genes, 3.4%0.00567 0.00% 0 SPH1, CLB6, KCC4, HSL1, PTP3, CLN1, CLB1, ELM1, CLN2, SSP2, YGK3, KIN4, CDC5, YDL073W, PCL1, BUB1, CLB5, GIN4, SWE1, ALK1, RAD53cell proliferation 5 of 207 genes,2.4%11 of 7166 genes, 0.2%0.00664 0.00% 0 CLB6, CLB5, CLB1, CLN1, CLN2positive regulation of cell proliferation5 of 207 genes,2.4%11 of 7166 genes, 0.2%0.00664 0.00% 0 CLB6, CLB5, CLB1, CLN1, CLN2regulation of cell proliferation5 of 207 genes,2.4%11 of 7166 genes, 0.2%0.00664 0.00% 0 CLB6, CLB5, CLB1, CLN1, CLN2rRNA 5'-end processing8 of 207 genes,3.9%37 of 7166 genes, 0.5%0.00686 0.00% 0 PNO1, BUD21, UTP23, UTP6, RCL1, DBP8, UTP18, NOP19regulation of organelle organization25 of 207 genes, 12.1%330 of 7166 genes, 4.6%0.0071 0.00% 0 CLB6, YOR338W, MSH2, PXR1, DAD4, FKH1, CLN1, CLB1, CLN2, KIN4, HOP1, CDC5, CDC6, BUB1, CLB5, BNR1, SPO16, CDC45, SIR4, SWE1, PPH3, LTE1, IBD2, APC1, SLK19RNA processing 39 of 207 genes, 18.8%657 of 7166 genes, 9.2%0.00767 0.00% 0 PNO1, DHR2, CWC2, UTP18, DUS1, NCS2, RNT1, FKH1,NOP53, BCD1, FIR1, SNU23, TSR4, SEN34, BUD23, MTO1, BUD21, EFG1, SAP185, DBP8, UTP9, TRF5, RCL1, JJJ1, PLM2, TOS4, PXR1, RRP36, BFR2, FAL1, UTP25, UTP6, UTP23, IPI1, LCP5, NOP19, LAS1, SSF1, YLR063W206Downregulated Terms from the Process Ontology of gene_association.sgd with p-value <= 0.01Gene Ontology termCluster frequencyGenome frequencyCorrected p-valueFDR False positivesGenes annotated to the termnitrogen compound metabolic process136 of 207 genes, 65.7%3657 of 7166 genes, 51.0%0.00927 0.00% 0 DAT1, MNL2, PPR1, UTP18, SIR2, YHL012W, MSH2, DUS1, HSL1, FKH1, RFU1, ELG1, CLB1, CRR1, SSP2, SMC6, TSR4, SEN34, MTO1, CTF18, MSH3, RNH203, PLM2, RNR1, TOS4, BNA2, ESC8, PXR1, NTO1, DPB2, JJJ3, CDC45, SKP2, LAS1, PDS5, RAD53, BAS1, DHR2, RAD9, ACM1, YOR338W, ASG1, NCS2, RNT1, BCD1, DAL1, FIR1, MSH5, PZF1, GIN4, SPO16, SAP185, UTP9, RRP36, CLN1, UTP25, IPI1, YDL073W, DFR1, ABF1, ZDS2, YPL216W, MRC1, SPT21, EST2, PET309, PNO1, CWC2, MCD1, CLN2, RPL22B, CDC5, CDC6, PCL1, CLB5, BUD21, EFG1, BST1, IRC8, TRF5, THI80, JJJ1, POL1, HO, KCC4, TEA1, IFH1, FAL1, ZAP1, RRN3, ELM1, DAL4, SMC5, LCP5, HTL1, BUB1, RPC53, NOP19, SIR4, PPH3, YOX1, TOP1, YLR063W, SSF1, HCM1, SPH1, MNN1, TOF1, OGG1, NOP53, YGK3, SNU23, KIN4, PMS1, SMC3, BUD23, MSH1, SWE1, DBP8, BUL2, ALK1, APC1, VTS1, CLB6, RCL1, DUR1,2, ORC1, PTP3, SAS2, BFR2, RRN11, UTP6, UTP23, YCG1, RRN7, SPP41207Downregulated Terms from the Process Ontology of gene_association.sgd with p-value <= 0.01Gene Ontology termCluster frequencyGenome frequencyCorrected p-valueFDR False positivesGenes annotated to the termprimary metabolic process141 of 207 genes, 68.1%3838 of 7166 genes, 53.6%0.0094 0.00% 0 DAT1, MNL2, PPR1, UTP18, SIR2, YHL012W, MSH2, ROG1, DUS1, HSL1, FKH1, RFU1, ELG1, CLB1, CRR1, SSP2, SMC6, TSR4, SEN34, MTO1, CTF18, MSH3, RNH203, PLM2, RNR1, TOS4, BNA2, ESC8, PXR1, NTO1, DPB2, JJJ3, CDC45, SKP2, LAS1, PDS5, RAD53, BAS1, DHR2, RAD9, ACM1, YOR338W, ASG1, NCS2, RNT1, BCD1, DAL1, FIR1, MSH5, PZF1, GIN4, SPO16, SAP185, UTP9, RRP36, CLN1, UTP25, IPI1, YDL073W, ABF1, ZDS2, YPL216W, MRC1, SPT21, EST2, PET309, PNO1, CWC2, SPS19, MCD1, CLN2, RPL22B, CDC5, YEH1, CDC6, PCL1, CLB5, BUD21, EFG1, BST1, IRC8, TRF5, JJJ1, POL1, HO, KCC4, TEA1, IFH1, FAL1, ZAP1, RRN3, ELM1, DAL4, SMC5, LCP5, HTL1, BUB1, RPC53, NOP19, SIR4, PPH3, YOX1, TOP1, FAA3, YLR063W, SSF1, HCM1, SPH1, MNN1, SPR1, TOF1, OGG1, YJR030C, NOP53, YGK3, SNU23, KIN4, HES1, PMS1, SMC3, BUD23, MSH1, SWE1, DBP8, BUL2, ALK1, APC1,VTS1, CLB6, RCL1, DUR1,2, ORC1, PTP3, SAS2, BFR2, RRN11, UTP6, UTP23, YCG1, RRN7, SPP41208Upregulated Terms from the Process Ontology of gene_association.sgd with p-value <= 0.01Gene Ontology termCluster frequencyGenome frequencyCorrected p-valueFDR False positivesGenes annotated to the termcarbohydrate metabolic process39 of 231 genes, 16.9%296 of 7166 genes, 4.1%1.65E-11 0.00% 0 PGM2, VID24, GID8, VID30, GLC8, GSY2, YPI1, EMI2, GLC3, CIT1, SOL1, GRE3, OPI10, GLG1, ADH5, MLS1, HSP104, FBP26, YKR075C, IMA1, PYK2, MDH2, FYV10, RMD5, XKS1, TPS2, ICL1, MAL31, GPH1, NTH1, MAL13,YLR345W, TSL1, HXK1, IGD1, MAL11, GLK1, PKP2, CIT3cellular carbohydrate metabolic process30 of 231 genes, 13.0%191 of 7166 genes, 2.7%2.21E-10 0.00% 0 PGM2, VID24, GID8, VID30, GLC8, GSY2, XKS1, RMD5, YPI1, EMI2, GLC3, TPS2, ICL1, MAL31, GPH1, MAL13, NTH1, OPI10, GLG1, YLR345W, TSL1, MLS1, HXK1, HSP104, FBP26, MAL11, IGD1, IMA1, GLK1, FYV10generation of precursor metabolites and energy26 of 231 genes, 11.3%226 of 7166 genes, 3.2%1.01E-05 0.00% 0 PGM2, GLC8, GSY2, YPI1, HAP4, EMI2, GLC3, ICL1, CIT1, GPH1, ISF1, RGI1, NDI1, GLG1, ADH5, YLR345W, CYC7, MLS1, PRM4, HXK1, IGD1, HAP2, GLK1, MDH2, PYK2, CIT3monosaccharide metabolic process16 of 231 genes, 6.9%99 of 7166 genes, 1.4%6.86E-05 0.00% 0 PGM2, VID24, GID8, VID30, XKS1, RMD5, GRE3, ADH5, YLR345W, HXK1, FBP26, IGD1, GLK1, PKP2, MDH2, FYV10hexose metabolic process15 of 231 genes, 6.5%90 of 7166 genes, 1.3%0.00011 0.00% 0 PGM2, ADH5, VID24, GID8, YLR345W, VID30, RMD5, HXK1, FBP26, IGD1, PKP2, GLK1, GRE3, MDH2, FYV10209Upregulated Terms from the Process Ontology of gene_association.sgd with p-value <= 0.01Gene Ontology termCluster frequencyGenome frequencyCorrected p-valueFDR False positivesGenes annotated to the termenergy derivation byoxidation of organic compounds20 of 231 genes, 8.7%165 of 7166 genes, 2.3%0.00022 0.00% 0 PGM2, GLC8, GSY2, YPI1, HAP4, GLC3, ICL1, CIT1, GPH1, ISF1, RGI1, NDI1, ADH5, GLG1, CYC7, MLS1, IGD1, HAP2, MDH2, CIT3glucose metabolic process13 of 231 genes, 5.6%73 of 7166 genes, 1.0%0.00036 0.00% 0 PGM2, ADH5, VID24, GID8, VID30, RMD5, HXK1, FBP26,IGD1, PKP2, GLK1, MDH2, FYV10disaccharide metabolic process9 of 231 genes, 3.9%32 of 7166 genes, 0.4%0.00038 0.00% 0 PGM2, TSL1, HSP104, TPS2, MAL11, MAL31, IMA1, MAL13, NTH1phosphate-containing compound metabolic process52 of 231 genes, 22.5%833 of 7166 genes, 11.6%0.00113 0.00% 0 PGM2, GLC8, HRK1, YPI1, EMI2, YAK1, SAP4, CIT1, SOL1, VHS1, OPI10, ARG82, ADH5, RIM11, ACH1, CMK2, YPK2, SSN8, ENV7, FBP26, TPK2, ALD4, HAL5, PYK2, REG2, URA8, CMK1, YKL151C, KIN82, RTK1, SDS22, CHO1, XKS1, YGR149W, TPS2, BCY1, CRD1, TDA1, NDI1, CKI1, YLR345W, CYC7, NEM1, OPI3, PHM8, TSL1, HXK1, PNC1, LSP1, YPL014W, PKP2, GLK1oligosaccharide metabolic process9 of 231 genes, 3.9%36 of 7166 genes, 0.5%0.00114 0.00% 0 PGM2, TSL1, HSP104, TPS2, MAL11, MAL31, IMA1, MAL13, NTH1energy reserve metabolic process9 of 231 genes, 3.9%38 of 7166 genes, 0.5%0.00188 0.00% 0 PGM2, GLG1, GLC8, GSY2, YPI1, GLC3, IGD1, GPH1, RGI1210Upregulated Terms from the Process Ontology of gene_association.sgd with p-value <= 0.01Gene Ontology termCluster frequencyGenome frequencyCorrected p-valueFDR False positivesGenes annotated to the termphosphorus metabolic process52 of 231 genes, 22.5%852 of 7166 genes, 11.9%0.00225 0.00% 0 PGM2, GLC8, HRK1, YPI1, EMI2, YAK1, SAP4, CIT1, SOL1, VHS1, OPI10, ARG82, ADH5, RIM11, ACH1, CMK2, YPK2, SSN8, ENV7, FBP26, TPK2, ALD4, HAL5, PYK2, REG2, URA8, CMK1, YKL151C, KIN82, RTK1, SDS22, CHO1, XKS1, YGR149W, TPS2, BCY1, CRD1, TDA1, NDI1, CKI1, YLR345W, CYC7, NEM1, OPI3, PHM8, TSL1, HXK1, PNC1, LSP1, YPL014W, PKP2, GLK1carbohydrate phosphorylation6 of 231 genes, 2.6%15 of 7166 genes, 0.2%0.00334 0.00% 0 FBP26, YLR345W, XKS1, GLK1, EMI2, HXK1negative regulation of gluconeogenesis5 of 231 genes, 2.2%10 of 7166 genes, 0.1%0.00597 0.00% 0 VID24, GID8, VID30, RMD5, FYV10211Appendix 4. Synthetic genetic array hits dis3-ts x DMARemoved: genes located on the YOL chromosome arm (where DIS3 is located), and uracil-biosynthesis genes# Plate Row Col ORF Gene Ctrl Ctrl SD Exp Exp SD Ratio  Ratio SDRatio < pRatio > qDiff p-valueHit?110 1 22 43 YOR058C ASE1 1.034589764317360.0258129202463980.05 0 0.0483584373345080.0012065386003312/2 0/2 -0.984589764317360.016686393262343 4 19 44 YOL019W-A_15false 1.20381689215720.0370997734952330.4321946469958310.0894522313156930.3581749732062080.0702898249646693/3 0/3 -0.771622245161370.004916007493036Yes5 2 22 6 YKL009WMRT4 1.099743479488820.0122675465257050.4079263508072850.0501666281959340.3706052843162510.0423850666074753/3 0/3 -0.6918171286815320.001838709906783Yes6 2 17 25 YKR024C DBP7 0.8494917751962630.0696389322642690.2517543859649120.1866298934890560.2827988209061090.1908993910333453/3 0/3 -0.5977373892313510.0217981402827Yes212# Plate Row Col ORF Gene Ctrl Ctrl SD Exp Exp SD Ratio  Ratio SDRatio < pRatio > qDiff p-valueHit?8 3 11 2 YIL148W RPL40A0.9392917171143540.0432344524127070.3896099472787470.0382373687948670.4142374081945910.030264866806953/3 0/3 -0.5496817698356080.001431702161459Yes9 3 7 43 YDR457WTOM1 0.8059172823591830.0283765785132680.2797853084495660.0267718264065360.3466279432351230.0236465829600523/3 0/3 -0.5261319739096160.00043718375758Yes10 2 1 21 YNL171C YNL171C0.7399949569490150.1020928393247340.225987279893530.1335694988836820.3050736425636710.1944843958746713/3 0/3 -0.5140076770554850.039464825814112Yes11 2 24 10 YGR122WYGR122W0.9132887566240740.1537120416382450.4159078734585620.1259521865607310.4477976795765040.0990056192759873/3 0/3 -0.4973808831655110.015312939305413Yes12 4 19 40 YOL013W-B_15false 1.082378253110330.0712448703710220.6387887428935730.1954776882654570.5806313673133970.14803497036293/3 0/3 -0.4435895102167530.037645337997622Yes213# Plate Row Col ORF Gene Ctrl Ctrl SD Exp Exp SD Ratio  Ratio SDRatio < pRatio > qDiff p-valueHit?13 2 3 44 YGL042C YGL042C0.8094517405908510.0118180032832910.3664159891815830.0970912463056630.4522203705888780.1169759827744873/3 0/3 -0.4430357514092680.021816174350467Yes14 1 4 35 YOL029C YOL029C0.9554752849282490.1527490822180860.5198962754327270.1158082126091310.538124956040250.0394840080935793/3 0/3 -0.4355790094955220.004312955006909Yes15 4 28 30 YNL084C_14false 1.05511688744580.0267869661594240.6404975477348060.1101088081901080.6092559436180080.1172085471590083/3 0/3 -0.4146193397109920.045739253219475Yes16 2 31 15 YOL013W-AYOL013W-A1.198239114962260.0407424956875110.7933701225199170.0178240365262620.6626137799155650.0194700612685833/3 0/3 -0.4048689924423390.003582056637804Yes17 3 19 11 YDR496C PUF6 0.8364619499411850.0721264177995520.4419333226958760.0678248060055220.5367450486354970.1195305282651413/3 0/3 -0.3945286272453090.048075530629161Yes214# Plate Row Col ORF Gene Ctrl Ctrl SD Exp Exp SD Ratio  Ratio SDRatio < pRatio > qDiff p-valueHit?18 4 28 21 YNL003C_14false 1.094609488523280.0353850996888870.7056282497467810.1416835179055580.6415450119462890.1110364893702043/3 0/3 -0.3889812387764940.038575779692966Yes19 2 2 45 YJL207C LAA1 0.8916275990236680.2085320017403310.5028360705596110.3218806665829770.4958757061224090.2932348327129623/3 0/3 -0.3887915284640570.042382927299152Yes20 2 1 36 YPR179C HDA3 0.8978147997095930.0903581017351680.5201155511848490.0370925431154650.5852841082303080.0696217469686323/3 0/3 -0.3776992485247450.032550698294994Yes21 3 7 3 YDR443C SSN2 0.6917309979166760.1198532039171240.3326385968378180.1253689765533190.4630679227536760.1031401944210053/3 0/3 -0.3590924010788570.00014712379154Yes22 4 28 46 YPL268W_14false 1.051229193359090.0201155825504150.6925222061726340.1136786816823590.6585802639964030.1051774191539193/3 0/3 -0.3587069871864580.044958022361426Yes215# Plate Row Col ORF Gene Ctrl Ctrl SD Exp Exp SD Ratio  Ratio SDRatio < pRatio > qDiff p-valueHit?23 1 4 43 YOL031C SIL1 0.9449930195631790.0777190465107380.5897576815488180.0608228830363110.6229850231224490.0151140220309753/3 0/3 -0.3552353380143620.001384498139726Yes24 4 23 32 YOR034C-A_15false 1.086172006781380.1074469421679030.7385749779098770.0960840582077370.6812692348358530.076155713440333/3 0/3 -0.3475970288715050.031788892575361Yes25 3 25 37 YNL140C YNL140C0.8012896975114770.0130230235946290.4556915959011710.1095167410066940.5687747789106460.1380877535984953/3 0/3 -0.3455981016103060.04705257517177Yes26 1 32 41 YOL017WESC8 1.080590637076360.2043281782955320.7385792408469490.2423372885049970.665867508831360.1285215011441653/3 0/3 -0.3420113962294070.042996771525064Yes27 4 28 22 YNL003C_14false 1.067255593057390.0297275620146210.7327033273741230.1282437472568120.6840265260912150.1029921062613613/3 0/3 -0.3345522656832670.043695063183393Yes216# Plate Row Col ORF Gene Ctrl Ctrl SD Exp Exp SD Ratio  Ratio SDRatio < pRatio > qDiff p-valueHit?28 1 6 39 YOR003WYSP3 1.013046624780820.1017808866593660.680283299030890.0774704688081670.6715071742834970.0320020025320083/3 0/3 -0.3327633257499290.009997823956628Yes29 3 7 44 YGR092WDBF2 0.7441690124386780.0711456528466430.4195434291248810.0841770623181130.5584678500330780.0569351844595543/3 0/3 -0.3246255833137980.00109468811986Yes30 4 32 45 YOR008C-A_14false 1.286921645217680.0258530755981250.9694747118702350.0986015175444060.7531082636278580.0719160443568913/3 0/3 -0.317446933347440.040398908014987Yes31 3 17 11 YNL109WYNL109W1.01510199502330.0564428763657190.7026792868850270.0636177763082690.6920795973494840.0488032746634973/3 0/3 -0.3124227081382690.013757177770243Yes32 3 16 48 YOL150C YOL150C1.317397108074710.068225927385341.006091380147490.1012114539022210.7619712857866310.0435939845872473/3 0/3 -0.3113057279272220.01059268012605Yes217# Plate Row Col ORF Gene Ctrl Ctrl SD Exp Exp SD Ratio  Ratio SDRatio < pRatio > qDiff p-valueHit?33 3 8 15 YJR056C YJR056C1.119502173661810.1116488861876470.8087177692995220.0813875307700690.7264150187224890.0740911867049153/3 0/3 -0.3107844043622910.047001927033797Yes34 4 16 48 YNL277W_14false 0.8478113687102530.124294906814460.5482034732532540.2025750541424370.6262491731301880.1447753306312783/3 0/3 -0.2996078954569980.034155000883453Yes35 4 25 40 YGR122C-A_15false 1.281041633433940.0372229473283120.9843880363115520.1018579650728120.7673543837638470.0658535710251463/3 0/3 -0.2966535971223870.033068575664937Yes36 2 3 42 YBL013W FMT1 1.045505113976070.0490185804986940.7667064760395860.0420246188153470.7348567272455290.052989056130323/3 0/3 -0.2787986379364860.024548034743532Yes37 3 4 19 YJR035W RAD26 1.11674488878920.044955444513340.8412079845611920.0595204041988070.7536398669639060.0508221027801313/3 0/3 -0.2755369042280080.021559260578954Yes218# Plate Row Col ORF Gene Ctrl Ctrl SD Exp Exp SD Ratio  Ratio SDRatio < pRatio > qDiff p-valueHit?38 1 20 26 YML013C-AYML013C-A0.704939110774030.1091073801044140.4305902390797240.129104217470850.598193484206850.0816990940424323/3 0/3 -0.2743488716943070.002724420158366Yes39 4 32 46 YOR008C-A_14false 1.310235118991230.0272838409332821.04340485262340.0187346308675910.7969318989566280.0291190922668963/3 0/3 -0.2668302663678320.01320443236699Yes361 1 14 39 YOR029WYOR029W1.1775258856160.0490797418505910.9133991612896740.1112430502660630.7741883965636710.0753975675895192/3 0/3 -0.2641267243263290.04736012536419440 2 8 20 YOR166C SWT1 1.021300873798170.0524342874705010.7589745864710080.0798777754453040.7429319402291560.0656914930266093/3 0/3 -0.2623262873271570.030361325547636Yes41 1 4 39 YOL030WGAS5 0.9527733855325620.0727312615335230.7050408039510440.0478431380424380.7417881505128060.0420568648809743/3 0/3 -0.2477325815815180.021566993249229Yes219# Plate Row Col ORF Gene Ctrl Ctrl SD Exp Exp SD Ratio  Ratio SDRatio < pRatio > qDiff p-valueHit?397 3 31 45 YDL086WYDL086W1.048415875849260.0347512795759640.8043646236143990.025293414097330.7672623532587480.001306670835912/2 0/2 -0.2440512522348570.02465897059578242 3 14 8 YML107C PML39 1.005997414411090.0765963125772610.7638333036140930.0741344819910940.7588227272995610.040510202595793/3 0/3 -0.2421641107969930.015539739209739Yes404 4 8 3 YDR417C_14false 0.3023913951545530.0135025062656640.0650098749177090.0150098749177090.2131945151622570.0401175920853342/2 0/2 -0.2373815202368440.00404247048995343 1 30 46 YLL039C UBI4 0.8481613373846580.0656233344856030.6116032875164780.1006966014375380.7173843281609970.070447390165473/3 0/3 -0.2365580498681810.0235968483238Yes406 3 26 41 YJR074W MOG1 0.873890519640870.1351873590022260.6381362315975220.1299628129763430.724557739884680.0366313227540982/2 0/2 -0.2357542880433480.0141058090838220# Plate Row Col ORF Gene Ctrl Ctrl SD Exp Exp SD Ratio  Ratio SDRatio < pRatio > qDiff p-valueHit?414 2 21 4 YFR044C DUG1 1.206468824532480.0471864539357880.9759291024371350.044728402559550.8093642890035930.0341936997246692/3 0/3 -0.2305397220953420.01845676793060544 2 16 12 YOR195WSLK19 1.089212335331120.0759386313931220.8599065326602870.0512073050679580.7903668080910290.0235354204290493/3 0/3 -0.2293058026708360.013259255745853Yes45 2 32 33 YGL195WGCN1 0.7420101501847530.0068054496692540.5150835318938530.0357078026856040.6946354342055470.0542568933515443/3 0/3 -0.22692661829090.016687001613769Yes420 3 31 4 YBR150C TBS1 1.256927965287010.0709240500399151.030553356078380.0987270831683830.8185071967451950.0417044468876522/3 0/3 -0.2263746092086310.018982023666701434 2 9 15 YDR293C SSD1 1.085014527239090.1003470940020230.8645367276038170.0935307403289120.7975257432440060.0619123453724712/3 0/3 -0.2204777996352770.046986289269693221# Plate Row Col ORF Gene Ctrl Ctrl SD Exp Exp SD Ratio  Ratio SDRatio < pRatio > qDiff p-valueHit?46 3 6 31 YJR139C HOM6 0.8125294376073470.0903231121283690.5938518627045560.0460826094502390.7345158925675770.0425179911031413/3 0/3 -0.2186775749027910.027859390636832Yes462 4 20 19 YNL014WHEF3 1.243215074220440.0641590142452741.033293259382970.1277287360883710.8281990500984240.0636398592396191/3 0/3 -0.209921814837470.048104890763842478 2 3 41 YIL096C YIL096C1.011315452812240.0786073018307430.805917567390690.0861812184990510.7964389555914660.0566778127722362/3 0/3 -0.2053978854215460.03668885008254447 4 2 11 YER177W_15false 1.018954765432010.0436340337465880.8164823336041610.0332811110931770.8019743825151790.0310532030589613/3 0/3 -0.2024724318278460.016964302559377Yes222Appendix 5. Synthetic genetic array hits dis3-ts x CB-ts, DAmPRemoved: genes located on the YOL chromosome arm (where DIS3 is located), and uracil-biosynthesis genes# Plate Row Col ORF Gene Ctrl Ctrl SDExp Exp SDRatio  Ratio SDRatio < pRatio > qDiff p-valueHit?2338 2 11 27 YKL112W abf1-102 2.051786692487820.2072902201345150.7402629531854260.1820433029111980.3557407103369510.05891827579053/3 0/3 -1.311523739302390.001244995325541Yes2436 2 29 5 YHR166C cdc23-1 1.717092134168850.2836678106538740.4208946784321610.0391172720170970.2564678561100820.0687799088869243/3 0/3 -1.296197455736690.029563578104791Yes3043 2 29 43 YKL210W uba1-1 2.002034242074650.0237115354577330.7522606496824370.1194625533192570.3764980107846590.0639091933483753/3 0/3 -1.249773592392210.006476693946703Yes2951 2 22 41 YKR037C spc34-ts 1.571441243475860.0883638473536990.3963262477253370.1591379527399450.2582255893855450.1126239140629013/3 0/3 -1.175114995750520.020974290511373Yes223# Plate Row Col ORF Gene Ctrl Ctrl SDExp Exp SDRatio  Ratio SDRatio < pRatio > qDiff p-valueHit?2950 2 30 17 YKR037C spc34 41-1 1.655202078190150.1062775792072630.5069121269661550.2062027769840050.300071629629740.1021647572236153/3 0/3 -1.1482899512240.004524433573284Yes2631 2 10 9 YKL165C mcd4-174 1.504307178855090.0603514126973890.3957361070537710.2057277912314730.2598132971907190.1336088633009683/3 0/3 -1.108571071801320.011801032174464Yes2868 2 29 36 YKL193C sds22-6 1.478078967903830.1200755665978840.445877937238780.136087726801370.2996114452825260.0768406602191223/3 0/3 -1.032201030665050.006936517227029Yes2337 2 22 33 YKL112W abf1-101 1.438348332726890.1293017245852690.4286873287726830.2753734714107630.3040881005007070.2077058439815013/3 0/3 -1.009661003954210.047113457495424Yes2770 2 23 30 YKR086W prp16-ts 1.447674599896390.0542191171357350.4903333674879990.0555177218942370.3387635928223270.0359183117808753/3 0/3 -0.957341232408390.002263130094076Yes224# Plate Row Col ORF Gene Ctrl Ctrl SDExp Exp SDRatio  Ratio SDRatio < pRatio > qDiff p-valueHit?2952 2 21 26 YKL042W spc42-10 1.349558029320190.0865960014176980.5254576336473190.08563176218190.3937996642294640.0823987971917633/3 0/3 -0.8241003956728720.018495836184308Yes2550 2 5 5 YHR007C erg11-td 1.070503071080860.0875464038172910.3467566273326850.1109397252833190.3275763186309850.1154860579412253/3 0/3 -0.7237464437481760.0206075740165Yes2806 2 7 20 YPL010W ret3-1 1.587071977326360.2872282607132460.8644507269798240.2722227827694330.5292036089065340.0864386750186523/3 0/3 -0.7226212503465390.000861004896693Yes1021 2 22 46 YOR046C::DAMPDBP5 1.228356699421760.1514998759828520.5129584941159340.1048954787847790.4287725291898670.1266767644788363/3 0/3 -0.7153982053058260.043069196572462Yes7 1 7 6 YKL192C ACP1 0.9492997133274010.0582357637471570.2634397003025620.0289852645060780.2799179758643270.0438497913704413/3 0/3 -0.6858600130248390.007228781635707Yes225# Plate Row Col ORF Gene Ctrl Ctrl SDExp Exp SDRatio  Ratio SDRatio < pRatio > qDiff p-valueHit?1800 2 8 20 YGR095C::DAMPRRP46 0.9048240641458940.0094459892854880.2469267782618040.1464874440912860.2716837729811350.1609946921899833/3 0/3 -0.657897285884090.021819281161776Yes1823 1 31 32 YOR077W RTS2 0.8804566041073960.0403704603562260.235883013825860.0188996476427950.2682309736250570.021928555900513/3 0/3 -0.6445735902815360.001873728121579Yes8 1 5 6 YKL192C ACP1 0.9683300021348560.0333575490406530.3409779250329690.0161435929274310.3519994830649330.0058626551053383/3 0/3 -0.6273520771018870.000427462226227Yes1270 1 9 2 YKR063C LAS1 1.056273432310840.0392086208012030.4551495346027020.0563728814709670.4334364473980710.0692020975721923/3 0/3 -0.6011238977081330.012231300384971Yes1875 2 20 2 YDR498C::DAMPSEC20 1.02391035910360.0251393233221950.4375179827819390.1309492578529350.4280923707768850.1290071384244353/3 0/3 -0.5863923763216620.026275575720257Yes226# Plate Row Col ORF Gene Ctrl Ctrl SDExp Exp SDRatio  Ratio SDRatio < pRatio > qDiff p-valueHit?2164 1 25 4 YOL022C TSR4 1.024737075438080.0223023990906460.4530989949347490.0303829562706320.4419955581941740.0248852601623223/3 0/3 -0.5716380805033340.000960900444321Yes3021 2 11 12 YKL028W tfa1-21 1.355113056266490.037744253256540.8103575075893360.0964489870338860.5977190529418160.065424946513143/3 0/3 -0.5447555486771520.013186228383674Yes1918 2 26 2 YOR057W::DAMPSGT1 1.331648427683690.0568818271928030.7871119701885740.0786059359858310.5939225009134310.0790420881150213/3 0/3 -0.5445364574951180.024932516702527Yes1569 1 23 28 YNR011C PRP2 1.024237310188590.0337585146915110.4845887543541540.1024290416365390.4769004589841440.1156200864455973/3 0/3 -0.5396485558344410.030230513472404Yes1146 1 2 39 YPL075W GCR1 0.9042670631575770.0159292902786080.36767614378610.0325185981807940.4060938115266410.0288076532232382/2 0/2 -0.5365909193714770.019675544599849227# Plate Row Col ORF Gene Ctrl Ctrl SDExp Exp SDRatio  Ratio SDRatio < pRatio > qDiff p-valueHit?2059 1 17 9 YML098W TAF13 1.136222683605720.0866002664238580.6162161486434140.1300027217168740.539016121538360.0947672864177113/3 0/3 -0.5200065349623020.014936997331238Yes2579 2 21 32 YGR216C gpi1-1 1.180665579535890.1081934400109520.67000523920760.0588267435942310.5709625143965290.0596007028499813/3 0/3 -0.5106603403282870.022676963567028Yes1919 1 25 1 YOR057W SGT1 1.357353722723340.0223957519662880.8537508221290280.0599881115309840.6298717348987250.0544118437161113/3 0/3 -0.503602900594310.013037638254385Yes1627 1 24 15 YOL010W RCL1 1.083265881122020.0371800166970770.5802171730947940.0956056598839740.5335866464488950.0710423043074493/3 0/3 -0.5030487080272210.008086564265412Yes1801 1 7 19 YGR095C RRP46 0.8438740048198060.0986716161598680.34661707371540.0438507778830750.421446803250890.0948060391103413/3 0/3 -0.4972569311044070.037560399237145Yes228# Plate Row Col ORF Gene Ctrl Ctrl SDExp Exp SDRatio  Ratio SDRatio < pRatio > qDiff p-valueHit?1797 2 22 44 YDL111C::DAMPRRP42 0.9486553605022520.1156477578856070.4516731792275420.0463577372535720.4840142029310230.0851031987002523/3 0/3 -0.496982181274710.030892242183956Yes1824 1 29 32 YOR077W RTS2 0.8075522721652990.0280258700480180.3117027985123650.009834863057550.3868021748077040.0242733067976933/3 0/3 -0.4958494736529340.002735969399824Yes2335 2 25 9 YBR236C abd1-5 0.9289819669526160.0991898247162650.4452745211168470.1184541218307920.4850530136147370.1487422812237663/3 0/3 -0.4837074458357690.047742911520198Yes2302 1 31 28 YOR060C YOR060C 1.076725107589320.0176430717913360.5985608420237620.0930320089885190.5547549521246190.0782743327496983/3 0/3 -0.4781642655655580.012736415380675Yes2538 2 7 7 YJL090C dpb11-1 1.749203884951240.1100414187770491.284504703166470.23126726648410.7295271717199230.0962814608519943/3 0/3 -0.4646991817847770.043547824315009Yes229# Plate Row Col ORF Gene Ctrl Ctrl SDExp Exp SDRatio  Ratio SDRatio < pRatio > qDiff p-valueHit?2197 1 29 20 YOR004W UTP23 0.9207799646512510.0196560983371760.456247266111810.1468369949185280.4929012674834920.1525006051585083/3 0/3 -0.4645326985394410.037557588938027Yes2801 2 15 11 YDL090C ram1-119 1.098319404358730.2166666790188920.6469459153929630.0758437574031910.6002700507975060.0581067022405443/3 0/3 -0.4513734889657650.047681788697422Yes1643 1 17 48 YNL290W RFC3 1.039889025239020.0151563842925270.6207362060278610.1298862129734930.5957777821636940.1201509801496083/3 0/3 -0.4191528192111620.038511954280519Yes2137 2 2 22 YDR050C::DAMPTPI1 1.163744566066460.1027483398186310.7571317233188940.0865733956157470.6542983472037790.0868533134805873/3 0/3 -0.4066128427475660.04356266028595Yes1698 1 21 44 YOL005C RPB11 0.923536653825590.0993574220953610.5170087115213330.033835282086370.5623276736504630.0238981221598743/3 0/3 -0.4065279423042570.012821483636419Yes230# Plate Row Col ORF Gene Ctrl Ctrl SDExp Exp SDRatio  Ratio SDRatio < pRatio > qDiff p-valueHit?1645 1 27 32 YOL094C RFC4 0.7913227459220160.0629620708408220.3944567774508460.0813948996630830.4972553307948940.0828447417551323/3 0/3 -0.396865968471170.015004167904118Yes2852 2 7 16 YOR294W rrs1-84 0.8518232282741730.0773664371759710.4558654785979220.0252114523818230.541783010577650.0737576588628733/3 0/3 -0.3959577496762510.031355167148679Yes985 1 9 27 YBR109C CMD1 0.4786695344271630.0399853739019950.0914762051587340.058656211851250.1856470773795220.1081071474510093/3 0/3 -0.3871933292684290.006481846692939Yes1348 2 10 20 YBR091C::DAMPMRS5 1.239048240902880.0279725308042560.855723130631210.1029389193827140.6917916591347750.0908732881679323/3 0/3 -0.3833251102716740.043817176813648Yes2371 2 29 6 YNR035C arc35-5 1.192741123252270.0574489004621830.8170884562204120.0820088569263210.6865087105770140.0749557773323673/3 0/3 -0.3756526670318550.0313825721516Yes231# Plate Row Col ORF Gene Ctrl Ctrl SDExp Exp SDRatio  Ratio SDRatio < pRatio > qDiff p-valueHit?2303 1 29 28 YOR060C YOR060C 0.9514049568296410.0877722462132170.5818112396083230.0212271004083850.615139097919720.040161415146353/3 0/3 -0.3695937172213180.017450380932397Yes1954 2 16 42 YDR478W::DAMPSNM1 0.9569618749109410.0766110949115140.5886086612992760.043298746681460.6158868062856820.0271725255831343/3 0/3 -0.3683532136116640.008059397499194Yes1022 1 21 45 YOR046C DBP5 1.069965608858840.0238100547728210.7023260840100530.068728954952770.6567710327818540.0670361302627273/3 0/3 -0.367639524848790.019238371113232Yes88 1 27 24 YOL077C BRX1 0.6288134353157960.1244401712583650.2639762510441480.0449177776080980.4228137189699640.0179928346549683/3 0/3 -0.3648371842716470.02339892347767Yes1646 1 25 32 YOL094C RFC4 0.8333004609553190.0718067664888020.4690432273388180.0148194192124930.5656446831365890.0325816435829243/3 0/3 -0.3642572336165010.012167184020801Yes232# Plate Row Col ORF Gene Ctrl Ctrl SDExp Exp SDRatio  Ratio SDRatio < pRatio > qDiff p-valueHit?1808 1 30 37 YOR294W RRS1 0.4774121638174960.0868881130651450.1182894341410190.0308817320252570.2549447316459470.0847725772525983/3 0/3 -0.3591227296764770.030248366278758Yes2981 2 30 7 YBL034C stu1-7 1.212018141628520.0734953859888250.8576467212294870.1321267592875330.7046893053589880.08087952262113/3 0/3 -0.3543714203990380.027700745251091Yes1793 1 14 27 YPR143W RRP15 0.7947506329531530.0281077419447480.4468779849840140.0383130441421970.5627208288892090.0479968970234173/3 0/3 -0.3478726479691390.007831513436438Yes2198 1 31 20 YOR004W UTP23 1.036109200912310.0555692464768690.7024528004604440.0637320813143040.6816571556707980.0880995149306533/3 0/3 -0.3336564004518690.043988030929335Yes1945 1 25 8 YOL034W SMC5 1.100795201063150.0537459151470530.778685385684970.054158562736070.7075104104582290.0388469619114993/3 0/3 -0.3221098153781750.010412513590082Yes233# Plate Row Col ORF Gene Ctrl Ctrl SDExp Exp SDRatio  Ratio SDRatio < pRatio > qDiff p-valueHit?1655 1 27 16 YOL066C RIB2 0.9569907541551990.0427636111335450.6430633760387320.1039060961913780.6699801690435980.0922301584898863/3 0/3 -0.3139273781164670.031219526113098Yes1594 1 30 19 YAL032C PRP45 0.911246006539750.118244485528950.6049600893411490.1365188255786010.6611304218539070.0949249649455843/3 0/3 -0.3062859171986010.039375854144694Yes1809 1 6 29 YOR294W RRS1 0.5471027943767770.0714386497635430.2411590595661510.0608154531438890.447732454023930.1154674615255843/3 0/3 -0.3059437348106260.044278318104651Yes1422 1 30 41 YOR310C NOP58 1.018376653370990.0607238507932430.713601793947460.0682947958318210.7018876944993390.0688350988855333/3 0/3 -0.3047748594235260.029990085550162Yes1360 1 9 1 YGR158C MTR3 0.7590846476356330.0425251443710230.4627056530467460.0417903838195640.614202308039330.0891836395410013/3 0/3 -0.2963789945888860.035019876277354Yes234# Plate Row Col ORF Gene Ctrl Ctrl SDExp Exp SDRatio  Ratio SDRatio < pRatio > qDiff p-valueHit?1624 1 31 24 YOR048C RAT1 1.025979532146990.027517870296390.7396133275314250.0348665241507190.7209412132566570.0288307568156123/3 0/3 -0.286366204615560.006047057785479Yes1794 1 22 13 YPR143W RRP15 0.7219791880386070.0713196150739910.4456993971804620.0483994895093150.6172937441310280.0299537015206433/3 0/3 -0.2762797908581450.008427604746567Yes1727 1 9 14 YKR081C RPF2 1.028493004516330.0573246503673220.7542563977923730.0752231122655540.7318176677412880.0353458771236253/3 0/3 -0.2742366067239520.004996791688521Yes2889 2 19 4 YDR238C sec26-F856AW860A0.8607652299151190.1374604361429770.5888858949803130.08029154131890.6879444726761340.0492617546221243/3 0/3 -0.2718793349348060.033064173696958Yes2272 1 8 27 YKL083W YKL083W 0.5203312944495710.0812351570746290.24892256089760.026594514274020.4834390312721790.0472210938525633/3 0/3 -0.2714087335519710.024653592990365Yes235# Plate Row Col ORF Gene Ctrl Ctrl SDExp Exp SDRatio  Ratio SDRatio < pRatio > qDiff p-valueHit?1699 1 23 44 YOL005C RPB11 0.8643377396905690.0611595906789370.5938688033658270.1202312068559790.6831315070955540.1151116187404343/3 0/3 -0.2704689363247410.048517008098577Yes894 2 20 44 YJL008C::DAMPCCT8 1.303235647390960.1598013563469651.03507210734460.2393344945173240.7835380329598880.0967287099691322/3 0/3 -0.268163540046360.0492432271289571414 1 9 40 YNL110C NOP15 0.6937851785287960.0558071342523260.4352730366170950.0224866202298950.6289716361453880.0202442321202943/3 0/3 -0.2585121419117010.008399555863148Yes2367 2 23 37 YLR127C apc2-8 1.073351125658380.1643540872853190.8191681263284530.1493090134875060.7599000823795980.0475748289826283/3 0/3 -0.2541829993299280.01760895659231Yes909 1 31 35 YKL022C CDC16 1.069918524482880.0691917440319290.8178096682083460.0327876056115510.765953903992620.0305038780521053/3 0/3 -0.2521088562745380.017703091413005Yes236# Plate Row Col ORF Gene Ctrl Ctrl SDExp Exp SDRatio  Ratio SDRatio < pRatio > qDiff p-valueHit?3041 2 15 36 YLR212C tub4-Y445D0.6623765221419150.1805237597068690.4123375167704270.1422409634642860.6059125557582080.0609364570834483/3 0/3 -0.2500390053714880.011620899073113Yes1683 2 18 22 YMR061W::DAMPRNA14 1.229763903861560.0775655688626850.9801209628358620.0096264119632190.8001383419103310.0500863161217382/3 0/3 -0.2496429410257020.0453563806795592910 2 29 26 YLL003W sfi1-3 1.291680860942490.0907734653077691.042129359300630.0312042716157760.8090633935033090.0330091928418373/3 0/3 -0.2495515016418650.029287228585396Yes2139 1 27 40 YOL102C TPT1 0.6001227648353140.0381509241671670.353382242204650.0342805856677170.5876228306791670.0198250932250443/3 0/3 -0.2467405226306630.000218748481391Yes1728 1 11 14 YKR081C RPF2 1.005920488989150.0588285511290310.7593434672622310.0195723475610250.7570660639503620.0411570403568773/3 0/3 -0.2465770217269190.022631469452449Yes237# Plate Row Col ORF Gene Ctrl Ctrl SDExp Exp SDRatio  Ratio SDRatio < pRatio > qDiff p-valueHit?2238 1 20 21 YDR526C YDR526C 0.3773085274395380.0331131927108870.1315140608947060.0611584697532570.3364690444388320.1381164065633663/3 0/3 -0.2457944665448320.006610049693137Yes2851 2 7 12 YOR294W rrs1-124 0.6778779952605430.1322715451592570.4364915359287490.0721969653302860.6508108381067610.0579228662548883/3 0/3 -0.2413864593317930.041108940346939Yes2329 1 30 25 YOR272W YTM1 0.7420420260090950.0515708490539340.5036733365518960.0362335354449850.6789055053457560.0164951617825943/3 0/3 -0.2383686894571990.004071407317697Yes1798 1 21 43 YDL111C RRP42 0.6835189255710530.03548985944990.4574946731440550.0355440282090930.6718991781607880.0704919838289733/3 0/3 -0.2260242524269970.031296401052697Yes1619 1 31 27 YKL019W RAM2 0.8834287163623390.0561850093595380.6767972205511330.045724822805540.7679502837816250.05563261050933/3 0/3 -0.2066314958112060.033847543491165Yes238# Plate Row Col ORF Gene Ctrl Ctrl SDExp Exp SDRatio  Ratio SDRatio < pRatio > qDiff p-valueHit?1773 1 3 16 YMR131C RRB1 0.9052535967897010.1239293187807180.700457595976540.1860568136554220.7584124471769150.1129275603288782/3 0/3 -0.204796000813160.0441065329086171293 1 18 23 YAL025C MAK16 1.20543429064820.0192179655686821.003219364278840.038107603197740.8328091918525910.0416225230258391/3 0/3 -0.2022149263693550.0330903036659241969 2 18 20 YCL054W::DAMPSPB1 1.350304110622480.0637031022413131.150016311106790.0165102212285370.853046627386370.0297327073078311/3 0/3 -0.2002877995156920.030384526115439239Appendix 6. Synthetic genetic array hits dis3E729K x DMARemoved: genes located on the YOL chromosome arm (where DIS3 is located), and uracil-biosynthesis genes# Plate Row Col ORF Gene Ctrl Ctrl SDExp Exp SDRatio  Ratio SDRatio < pRatio > qDiff p-valueHit?5283 4 15 3 YNL059C ARP5 0.9386740946928760.1141547406592410.05 6.93889390390723E-180.0540675989380230.0066107536745213/3 0/3 -0.8886740946928760.008149640740734Yes5284 4 15 4 YNL059C ARP5 0.9180721858072290.1797220075414930.1937894983797420.1238212011235910.2225370224684230.1298914460833883/3 0/3 -0.7242826874274870.047575259752668Yes5139 4 12 3 YBL093C ROX3 0.6931796815745360.0180253605868820.05 0 0.0721801782338650.0018769646232782/2 0/2 -0.6431796815745360.017836847739135742 4 24 30 YJR032W CPR7 0.7865009922340070.3530053523534590.2257452574525750.2485413266121820.2205954427387950.173657410005953/3 0/3 -0.5607557347814320.037872618827542Yes240# Plate Row Col ORF Gene Ctrl Ctrl SDExp Exp SDRatio  Ratio SDRatio < pRatio > qDiff p-valueHit?3726 3 14 30 YML041C VPS71 0.8881119136539010.1027629367085380.3561528271805110.176657074520070.3926243010163980.1610653811457473/3 0/3 -0.531959086473390.032175808638952Yes5277 4 14 45 YER110C KAP123 0.8514027893393750.2887803348656160.3724946712091570.3248681416372870.3684246199969920.2256149085073533/3 0/3 -0.4789081181302170.009537707757676Yes3655 3 13 7 YML107C PML39 1.069799329274110.0149284479155920.628708234603760.0698356745576740.5886145553882720.0727870134998693/3 0/3 -0.4410910946703520.017434254329224Yes400 1 9 16 YOR010C TIR2 1.202350268452750.0148718280439560.7822886447609960.1004401445881450.650475816364350.0816230054386343/3 0/3 -0.4200616236917580.025989725786096Yes3999 3 20 15 YJL206C YJL206C 1.055030928836020.0710311515867580.6518783128566510.0932571178502140.6222055421546560.1082549565304453/3 0/3 -0.4031526159793740.046747164944106Yes241# Plate Row Col ORF Gene Ctrl Ctrl SDExp Exp SDRatio  Ratio SDRatio < pRatio > qDiff p-valueHit?600 1 13 24 YOR025W HST3 1.014698632686120.0163525661436380.6136596117674370.0320412887604030.6047122487730110.028720620352123/3 0/3 -0.4010390209186810.00265915614106Yes3651 3 13 3 YML106W URA5 0.917562911170140.016509561412210.5448551502725510.0686010190505750.595205555672440.0851540274976683/3 0/3 -0.3727077608975890.024283237996596Yes3917 3 18 29 YNR024W YNR024W 1.02216103677650.0233154046964430.6556403338982980.0590144131228160.6405116709242120.0440202643615673/3 0/3 -0.3665207028782030.005189404801118Yes4167 3 23 39 YJR128W YJR128W 0.9633961435604160.0651493509200260.5974721235795460.0908331909379490.6219708489590090.1012377679354853/3 0/3 -0.365924019980870.036935671652766Yes412 1 9 28 YOR013W YOR013W 1.170151114281280.0234452805650310.8220557516197310.0837332772186110.7029580692515330.0753759759584973/3 0/3 -0.348095362661550.031310572528737Yes242# Plate Row Col ORF Gene Ctrl Ctrl SDExp Exp SDRatio  Ratio SDRatio < pRatio > qDiff p-valueHit?2050 2 11 34 YDR156W RPA14 0.603623482339570.0823976289087750.256916922492760.0483112351793570.423000119402460.0289011266926613/3 0/3 -0.3467065598468090.006332709680664Yes3601 3 12 1 YIL148W RPL40A 0.9582297106947540.0245552472234760.6312265134068690.0421725050595150.659714651915190.0540157021226093/3 0/3 -0.3270031972878850.015596233271745Yes4310 3 26 38 YNL140C YNL140C 0.8460528450582030.0145814927528530.519758509468160.0684336625489460.6133157737696650.0710241318355723/3 0/3 -0.3262943355900430.01452269740616Yes3639 3 12 39 YJL136C RPS21B 0.9640787161175140.0369131480405590.6390798068030430.0221243080687370.6638252594123320.0328662827693813/3 0/3 -0.3249989093144710.008331128233394Yes3627 3 12 27 YGR250C YGR250C 1.149585436033020.062867106554850.8364598588587520.0224385631892570.7292476186809850.034072518367333/3 0/3 -0.3131255771742670.014114573700062Yes243# Plate Row Col ORF Gene Ctrl Ctrl SDExp Exp SDRatio  Ratio SDRatio < pRatio > qDiff p-valueHit?5925 4 28 21 YNL003C PET8 1.200252009017750.0668243559099060.8921886063842750.0467240604393080.7457707571111360.057668745562933/3 0/3 -0.3080634026334760.033614470659269Yes232 1 5 40 YOR003W YSP3 1.201533915410990.0168485067851780.9253817032606450.0187392340853260.7704601119990820.0241111660469243/3 0/3 -0.276152212150340.006802569847974Yes5886 4 27 30 YNL084C END3 1.19412223431490.0167217388245490.9213496129869580.0191274014868780.7715102592678810.0069548608035493/3 0/3 -0.2727726213279460.000290210893683Yes3662 3 13 14 YMR174C PAI3 1.017009213082430.0452368679320680.744305460128360.0682632092545780.7304072713506470.0371514417546433/3 0/3 -0.2727037529540660.00518569266045Yes1172 1 25 20 YOR066W YOR066W 1.147399414379620.0212832832325680.8751882537899370.0701104242704130.7630217882759950.0628674523072473/3 0/3 -0.2722111605896780.03414479331585Yes244# Plate Row Col ORF Gene Ctrl Ctrl SDExp Exp SDRatio  Ratio SDRatio < pRatio > qDiff p-valueHit?1619 2 2 35 YPR179C HDA3 0.9046897126073610.1024406581727740.6370321520163760.0295842686102650.7094939042976260.0474039428646563/3 0/3 -0.2676575605909860.035107398030542Yes2131 2 13 19 YKL113C RAD27 0.6373315105946690.0457353943030480.3799657488256640.1285844564542690.5852581451481520.1556507625806973/3 0/3 -0.2573657617690050.04958175577585Yes780 1 17 12 YOR034C AKR2 1.146986269632230.0181787035635050.8898073404417160.0090873016660550.7758607409685390.0061691316171933/3 0/3 -0.2571789291905150.000858216919058Yes424 1 9 40 YOR016C ERP4 1.191886923540120.0258292292852640.9362784433897840.0376174383399740.7852755955628440.0165340643681493/3 0/3 -0.2556084801503370.001980107416387Yes4738 4 3 34 YLR244C MAP1 0.8826057834726270.1352448858595830.6291439927057080.1012856065893920.7129849305013830.0279000606549213/3 0/3 -0.2534617907669190.015232717599758Yes245# Plate Row Col ORF Gene Ctrl Ctrl SDExp Exp SDRatio  Ratio SDRatio < pRatio > qDiff p-valueHit?772 1 17 4 YOR032C HMS1 1.222610374114610.0444732491737320.9747157841477670.0444994218705610.7974702921325610.0287871216233083/3 0/3 -0.2478945899668440.012206132732068Yes3534 3 10 30 YLR334C YLR334C 1.075857736180550.0259616373055920.8304991740257080.0525027634803420.7733160992300510.0644288969324333/3 0/3 -0.2453585621548410.043030933208459Yes2416 2 19 16 YGL261C YGL261C 0.3127965367965370.0191980833985270.0711340206185570.0298880185862360.224912664487470.0858654765371463/3 0/3 -0.241662516177980.005259845647278Yes5412 4 17 36 YHR033W YHR033W 1.22072536920610.0895709443329380.9794044162052240.0712825330355460.802653070097310.0248219702091053/3 0/3 -0.2413209530008760.011790320769683Yes3615 3 12 15 YGR238C KEL2 1.078280482288480.0297859136731990.8389529567519480.008852169343920.7784464393401370.0151854603711823/3 0/3 -0.2393275255365270.004498125112988Yes246# Plate Row Col ORF Gene Ctrl Ctrl SDExp Exp SDRatio  Ratio SDRatio < pRatio > qDiff p-valueHit?3398 3 7 38 YBR278W DPB3 1.154240238549940.0163105068159890.916721872040720.0399962363475770.7944008517826610.036544406541563/3 0/3 -0.2375183665092210.016634333358487Yes3389 3 7 29 YPR060C ARO7 0.9995176353660850.04511777424330.7641129965666450.0111005341616120.7664875065161490.044723521648333/3 0/3 -0.2354046387994390.025871026795135Yes3635 3 12 35 YJL132W YJL132W 1.126314713630140.0362689206433550.8946746015454780.107178399707850.7922778167614550.0735448797664573/3 0/3 -0.2316401120846650.048182851073547Yes3734 3 14 38 YML042W CAT2 1.131466618477110.0271316733944130.9023104974997220.0865006600963850.7962805854074220.0588450872456782/3 0/3 -0.2291561209773890.0357933334389124563 3 32 3 YBR150C TBS1 1.495072699556320.0271214051300641.266921991277380.0349832544027570.8472697699323750.0096776404769451/3 0/3 -0.2281507082789420.001302999109151247# Plate Row Col ORF Gene Ctrl Ctrl SDExp Exp SDRatio  Ratio SDRatio < pRatio > qDiff p-valueHit?1646 2 3 14 YLR296W YLR296W 1.146748065072270.0671012546770950.920066669022410.0324412953825780.8043463792376810.0438185390769522/3 0/3 -0.2266813960498620.0331023111000763497 3 9 41 YOL138C YOL138C 1.170576191878590.0106664109769950.9445980377449040.0810630631206780.8063941753061270.0615954129309722/3 0/3 -0.2259781541336810.0453356707635773090 3 1 18 YLR426W TDA5 0.9661564712344110.0425513601172780.7419616420021990.0086417207786780.7696910039787280.0398523343201753/3 0/3 -0.2241948292322120.023387819179119Yes3879 3 17 39 YMR100W MUB1 1.053970527292350.0467239600357440.8298115720717480.0300561116021640.7898206773712840.0598213099686512/3 0/3 -0.2241589552205980.0465429793690643529 3 10 25 YNL043C YNL043C 1.067302566576870.0477447540408720.8492121372114410.0315524934397950.7963661020285840.0278946557786643/3 0/3 -0.2180904293654270.013319261094393Yes248# Plate Row Col ORF Gene Ctrl Ctrl SDExp Exp SDRatio  Ratio SDRatio < pRatio > qDiff p-valueHit?428 1 9 44 YOR017W PET127 1.17897352126060.0433227776042210.9614309506506760.0583743613141290.8149168732275160.025296007718663/3 0/3 -0.2175425706099230.006634545502258Yes1803 2 6 27 YPR196W YPR196W 0.9622281967545130.0526268125463010.744727157472990.0525832408633150.7748581686663680.0495989914594683/3 0/3 -0.2175010392815230.030176840241524Yes564 1 12 36 YCL032W STE50 0.8284438352837270.1005784489440360.6165558090380130.0724969622051240.7465207060100130.0487314241095853/3 0/3 -0.2118880262457140.029186796372892Yes3108 3 1 36 YJR118C ILM1 0.8404144481128230.0241709253918010.6292371068499590.0218149030547040.7489130489835310.0226986792796913/3 0/3 -0.2111773412628630.005055381352536Yes3641 3 12 41 YIL161W YIL161W 1.237378862988830.014339746365081.028430317054050.0298719154329060.830977812160980.0152206455449063/3 0/3 -0.2089485459347890.003122526892079Yes249# Plate Row Col ORF Gene Ctrl Ctrl SDExp Exp SDRatio  Ratio SDRatio < pRatio > qDiff p-valueHit?4792 4 4 40 YFL016C MDJ1 0.8054515925805330.0725156995850070.5966144435160010.0381108691182620.7435381698264830.0415095630148373/3 0/3 -0.2088371490645320.024814557247438Yes338 1 8 2 YHR049C-AYHR049C-A1.280866437672310.0637067993341891.072757450242810.0367787233767750.8383539140613040.0217571138159341/3 0/3 -0.2081089874295030.0155890221944263101 3 1 29 YOL104C NDJ1 1.151975369035530.0210622023745760.9449989837666830.0217652916231250.8206418482445980.025530699769042/3 0/3 -0.2069763852688490.0118265612937221765 2 5 37 YLR182W SWI6 0.8056492747019060.019502906303540.6001128823083010.0372714206959090.7448369587820330.041100327259563/3 0/3 -0.2055363923936050.013105062321138Yes4744 4 3 40 YFL016C MDJ1 0.7912821947246380.1405069690770090.5862135220993020.0951819491232620.7440244525326450.0402179098093023/3 0/3 -0.2050686726253360.033633544589284Yes250# Plate Row Col ORF Gene Ctrl Ctrl SDExp Exp SDRatio  Ratio SDRatio < pRatio > qDiff p-valueHit?734 1 16 14 YHR103W SBE22 1.012072233537660.0618024401360590.8074913345924230.0414102906332540.7986145723159750.0235817690113833/3 0/3 -0.2045808989452420.011812020408925Yes3898 3 18 10 YMR048W CSM3 0.9506326487083160.0261419056714310.746641591963950.0396808591756090.7867887906047220.0578161918446133/3 0/3 -0.2039910567443660.041720513528332Yes1613 2 2 29 YPL057C SUR1 0.7453649949007760.013391162344170.5432917492820680.0788882432341680.7272453463353170.0933947726615293/3 0/3 -0.2020732456187080.04906502352178Yes251Appendix 7. Synthetic genetic array hits dis3E729K x CB-ts, DAmPRemoved: genes located on the YOL chromosome arm (where DIS3 is located), and uracil-biosynthesis genes# Plate Row Col ORF Gene Ctrl Ctrl SDExp Exp SDRatio  Ratio SDRatio < pRatio > qDiff p-valueHit?2892 2 29 12 YBR155W cns1-1 1.261467897910170.0992750530080540.1544911035728680.1477727358200810.1308402355548770.1312273280560013/3 0/3 -1.10697679433730.02180838746986Yes2346 2 17 42 YGL075C mps2-1 0.8014640109944490.1224945202820480.0574070572950750.010475160883970.0719775181237220.0088086763630813/3 0/3 -0.7440569536993740.011740756607457Yes2923 2 29 43 YKL210W UBA1 1.712872916167920.1743555678113790.9892155585731120.0631596318834710.5863928064625960.0909200500565293/3 0/3 -0.723657357594810.046911203511566Yes2741 2 26 5 YLR298C YHC1 0.9445060136847850.1349859038986460.2719809280884640.2715040622611930.2551919173363960.2296975425303683/3 0/3 -0.6725250855963210.020259867099734Yes252# Plate Row Col ORF Gene Ctrl Ctrl SDExp Exp SDRatio  Ratio SDRatio < pRatio > qDiff p-valueHit?2331 2 17 27 YOR257W cdc31-2 0.7164356991249470.0979721007769950.05 6.93889390390723E-180.071154516815570.0100225931381243/3 0/3 -0.6664356991249470.010633781955216Yes1747 2 5 19 YKL089W MIF2 1.414952683841620.115811987139370.7956278134679850.0361214106049560.5679246312571570.070213544589583/3 0/3 -0.6193248703736360.026263965902618Yes1180 1 25 28 YOL078W AVO1 0.7122225457710260.06958830060610.1214587357859060.0783030152359090.1664164964179790.1022261313660983/3 0/3 -0.590763809985120.008190923677518Yes714 1 15 42 YLR127C APC2 0.707805782024860.1366232742077050.1235294117647060.1039862913509630.1812864216051130.1535090110373583/3 0/3 -0.5842763702601540.045681384441468Yes1384 1 29 40 YOR103C OST2 0.6490398505034850.096242500250980.0852364475201850.0498318619728930.1469885849082770.1087832255691193/3 0/3 -0.56380340298330.031486455806364Yes253# Plate Row Col ORF Gene Ctrl Ctrl SDExp Exp SDRatio  Ratio SDRatio < pRatio > qDiff p-valueHit?484 1 11 4 YMR309C NIP1 0.653983634602740.0433002313196120.1059125346927580.0661643843591680.1604643132935790.0983538769914413/3 0/3 -0.5480710999099820.007620269752207Yes383 1 8 47 YLL037W YLL037W 0.6800611321646450.0775530649142110.137205807687070.0841879367587360.2104366711949170.1318181375615113/3 0/3 -0.5428553244775750.031865194458414Yes1252 1 27 4 YOL022C TSR4 1.045310223560420.0099795292491980.5071456291537660.0248964471603090.4852860713485670.0259269497966093/3 0/3 -0.5381645944066510.001538381663737Yes2945 2 30 17 YKR037C SPC34 1.396636069289390.1163720295086210.8679186479546370.0970076596666720.6199992747527230.0182148269402653/3 0/3 -0.5287174213347570.000872464954181Yes1156 1 25 4 YOL022C TSR4 1.071114389414940.0442031990611730.5497685256959380.0342889029212950.514382814577940.0413191900409813/3 0/3 -0.5213458637189990.006903816579195Yes254# Plate Row Col ORF Gene Ctrl Ctrl SDExp Exp SDRatio  Ratio SDRatio < pRatio > qDiff p-valueHit?793 1 17 25 YMR146C TIF34 0.5746244546485930.1479242468988350.0555973349165510.0079158269521310.1049673182730560.03566230554413/3 0/3 -0.5190271197320420.040830122453033Yes2577 2 22 33 YKL112W ABF1 1.199461401318290.0363626772051430.7409626424658330.1148627253022580.6184964148283580.1005453286606953/3 0/3 -0.4584987588524550.03413297489799Yes1190 1 25 38 YML031W NDC1 0.4987155066907130.0749314217035140.05 6.93889390390723E-180.1023721832309860.0140930672325693/3 0/3 -0.4487155066907130.013657991008588Yes2738 2 26 2 YOR057W::DAMPSGT1 1.663610929228590.0438584338760741.222994434419140.0275262120852360.7354578785891920.0188370735878763/3 0/3 -0.4406164948094520.004150597341777Yes1733 2 5 5 YHR007C erg11-td 1.072163118108450.0533213101277350.6712618206558660.0605787020052690.6303454360836390.0866664957127923/3 0/3 -0.4009012974525880.037360272098084Yes255# Plate Row Col ORF Gene Ctrl Ctrl SDExp Exp SDRatio  Ratio SDRatio < pRatio > qDiff p-valueHit?2769 2 26 33 YOR149C smp3-1 1.269455201481290.0608816780988080.8959188456244030.0357792119927390.7060756911663640.0112493366003713/3 0/3 -0.3735363558568850.003063413953274Yes1276 1 27 28 YOL078W AVO1 0.536183286382860.1478925473626510.1926663888229130.1166390885121650.3233315528670840.1446096733511673/3 0/3 -0.3435168975599470.01495167122496Yes525 1 11 45 YDR381W YRA1 1.042366263492390.0437379958945330.7121182208353530.0508100945670880.682962149946780.0360288077361113/3 0/3 -0.3302480426570420.006245146391141Yes1003 1 21 43 YDL111C RRP42 0.9927797286441760.0164113926552180.6642442214203620.0205823878048290.6689302187156210.0104892200311463/3 0/3 -0.3285355072238140.000208448981082Yes1172 1 25 20 YOL069W NUF2 1.015838693510090.0107840236779840.697046323351670.0604480059427290.6862705077105250.0605302886495043/3 0/3 -0.318792370158420.018172577052487Yes256# Plate Row Col ORF Gene Ctrl Ctrl SDExp Exp SDRatio  Ratio SDRatio < pRatio > qDiff p-valueHit?1651 2 3 19 YMR117C spc24 4-2 1.190283881476050.0786792720658310.8783902286859440.0563009637038760.7388374304081270.0360022903671973/3 0/3 -0.3118936527901080.014361049631796Yes2315 2 17 11 YOR074C cdc21-ts 1.626381085067250.1502562920889471.327559742889390.1277420203342430.8170395587356040.0430449902533532/3 0/3 -0.298821342177860.0305655508692711243 1 26 43 YOR056C NOB1 1.051060087675490.0342114613402140.7536041213107570.0536471555770580.718447284607930.0651174425149613/3 0/3 -0.2974559663647310.030356635470225Yes2417 2 19 17 YGR113W dam1-1 1.501214625686410.0484780451899971.205272709421230.0179827167945370.8033232048493230.0141918704308373/3 0/3 -0.2959419162651790.005267405614016Yes1004 1 21 44 YOL005C RPB11 1.01517139622010.0402938803203380.7287762805389930.0445652178611990.7181182205851540.0374404926519533/3 0/3 -0.2863951156811110.010785905642692Yes257# Plate Row Col ORF Gene Ctrl Ctrl SDExp Exp SDRatio  Ratio SDRatio < pRatio > qDiff p-valueHit?198 1 5 6 YKL192C ACP1 0.9551962741749780.0165634517856110.6843347922685050.0377429936970590.7165107265440530.0384864279575283/3 0/3 -0.2708614819064740.009715683986875Yes1533 1 32 45 YJL018W YJL018W 1.28268800113950.0513231378097121.017273313962240.0474142441125070.7951208513193970.0604890326396252/3 0/3 -0.2654146871772680.047407347139323908 1 19 44 YNL287W SEC21 0.852883420622770.0458124704767490.5891901291874210.1030697887156760.6872531366012620.0957156008636073/3 0/3 -0.2636932914353490.033633161537724Yes2789 2 27 5 YLR397C AFG2 1.00351371230630.0265315804141170.7401187380651240.0456111983138320.7384221266696070.0552518624178143/3 0/3 -0.2633949742411770.024867995632071Yes671 1 14 47 YPR176C BET2 0.9718633282588370.0585285188423130.7104778796821860.0131749704087030.7338849926661310.0495417667487983/3 0/3 -0.2613854485766520.026853700565051Yes258# Plate Row Col ORF Gene Ctrl Ctrl SDExp Exp SDRatio  Ratio SDRatio < pRatio > qDiff p-valueHit?1119 1 24 15 YOL010W RCL1 1.03777416137970.0243255524284560.7786724567745230.0547190378628210.7517686077103610.068953608099793/3 0/3 -0.2591017046051730.040278902406511Yes2080 2 12 16 YHR005C::DAMPGPA1 1.105579227989960.0295053521742070.8540873747331820.0424836719821860.7725238614151840.0317021683559253/3 0/3 -0.2514918532567740.010214380967736Yes1844 2 7 20 YPL010W ret3-1 1.078383334129560.0428282750346410.8285602523934560.0563481788848830.7675262952134270.02496295731273/3 0/3 -0.2498230817361080.002850547322223Yes1273 1 27 25 YFR005C SAD1 0.3599729699795410.0245011215659580.1159365874009180.0932484161589770.3093524744704810.232568872515433/3 0/3 -0.2440363825786230.043621697717296Yes2051 2 11 35 YFL008W smc1-2 0.7233089849341720.1027861267337780.4850069806577240.0506829539915190.676525865820280.0569080249825713/3 0/3 -0.2383020042764480.03565498243535Yes259# Plate Row Col ORF Gene Ctrl Ctrl SDExp Exp SDRatio  Ratio SDRatio < pRatio > qDiff p-valueHit?1372 1 29 28 YOR060C YOR060C 1.062717865258820.0577556418348180.8270102906546790.0935100136264030.7758618408271420.0493471692964043/3 0/3 -0.2357075746041360.014328608446259Yes1653 2 3 21 YLR026C SED5 0.9985760038395580.0601313997478030.7641827145395860.0608432143862340.765217245114120.0414773929240913/3 0/3 -0.2343932892999720.016074423088112Yes2780 2 26 44 YDL212W::DAMPSHR3 1.432557235101980.1035239244340761.204153993838280.0724810455926540.8412641203028670.0097157907093013/3 0/3 -0.2284032412636980.009112887686668Yes2406 2 19 6 YNL061W nop2-5 1.140504308547910.0269041045810850.9139160183358760.0473341171592260.8008051316921180.022367945841743/3 0/3 -0.226588290212030.004131464639029Yes1256 1 27 8 YOL034W SMC5 1.058845569252020.0504555067553440.8371009353571650.0654564991880010.7894380131790090.0247809076781443/3 0/3 -0.2217446338948590.002735777837925Yes260# Plate Row Col ORF Gene Ctrl Ctrl SDExp Exp SDRatio  Ratio SDRatio < pRatio > qDiff p-valueHit?1472 1 31 32 YOR077W RTS2 0.8375855694502960.042890524122150.6166742902869910.0089147992088980.7382235846937360.0395883257291393/3 0/3 -0.2209112791633040.019375931458137Yes847 1 18 31 YDR303C RSC3 1.069096884639270.024093311890110.8482557100560360.0170471729524880.7938246548815430.0237841466199553/3 0/3 -0.2208411745832320.008431536246841Yes2590 2 22 46 YOR046C::DAMPDBP5 1.090184139876090.0568605900173330.8703415418713690.0154613160762190.800002549688180.0330419802409723/3 0/3 -0.2198425980047210.020970593420594Yes1813 2 6 37 YGL022W stt3-1 0.8156416226304020.0109664345114940.5958959964687890.0518628514838970.7311346272876250.0685785604501053/3 0/3 -0.2197456261616130.033069634177939Yes1977 2 10 9 YKL165C MCD4 1.263629404154650.0387637843015621.048326676372010.0576976701093620.8293369381566530.0316412474943232/3 0/3 -0.2153027277826410.015076881527001261# Plate Row Col ORF Gene Ctrl Ctrl SDExp Exp SDRatio  Ratio SDRatio < pRatio > qDiff p-valueHit?2909 2 29 29 YDR054C cdc34-1 0.9319555681051720.0376261167838540.7168008220135620.0297646089260050.7691186403511560.0059019753495623/3 0/3 -0.215154746091610.00109709168039Yes424 1 9 40 YNL110C NOP15 0.8853846996687460.0288679133831490.6720220034694970.0270706805860840.7590497541597710.0193553353149493/3 0/3 -0.2133626961992490.003712448684394Yes1656 2 3 24 YPL217C bms1-1 0.9273580124681230.0928726148081350.7264987915820380.096961583555080.7813697497754880.0342963385659723/3 0/3 -0.2008592208860850.009002164104524Yes262Appendix 8. GO term enrichment of dis3-ts positive interactions identified by synthetic genetic arrayGene Ontology term Cluster frequencyGenome frequencyCorrected p-valueFDR False positivesGenes annotated to the termproteasome assembly 6 of 86 genes, 7.0%35 of 7166 genes, 0.5%0.00168 0.00% 0 YDL097C, YGL048C, YOR259C, YKL145W, YOR117W, YPR103Wpositive regulation of RNA polymerase II transcriptional preinitiation complex assembly4 of 86 genes, 4.7%11 of 7166 genes, 0.2%0.00328 1.00% 0.02 YGL048C, YOR259C, YKL145W, YOR117Wproteasome regulatory particle assembly 4 of 86 genes, 4.7%11 of 7166 genes, 0.2%0.00328 0.67% 0.02 YGL048C, YOR259C, YKL145W, YOR117WDNA-templated transcription, initiation 8 of 86 genes, 9.3%91 of 7166 genes, 1.3%0.00642 0.50% 0.02 YJL011C, YGL048C, YDR362C, YBR198C, YDR145W, YOR117W, YKL145W, YOR259Cregulation of RNA polymerase II transcriptional preinitiation complex assembly4 of 86 genes, 4.7%13 of 7166 genes, 0.2%0.00699 0.40% 0.02 YGL048C, YOR259C, YKL145W, YOR117Wpositive regulation of transcription initiation from RNA polymerase II promoter4 of 86 genes, 4.7%14 of 7166 genes, 0.2%0.00969 0.33% 0.02 YGL048C, YOR259C, YKL145W, YOR117W263Gene Ontology term Cluster frequencyGenome frequencyCorrected p-valueFDR False positivesGenes annotated to the termpositive regulation of DNA-templated transcription, initiation4 of 86 genes, 4.7%14 of 7166 genes, 0.2%0.00969 0.29% 0.02 YGL048C, YOR259C, YKL145W, YOR117Wprotein-DNA complex subunit organization11 of 86 genes, 12.8%194 of 7166 genes, 2.7%0.00983 0.25% 0.02 YGR002C, YLL004W, YGL048C, YDR362C, YBR198C, YDL182W, YNL261W, YOR259C, YKL145W, YDR145W, YOR117W264

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