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The regulatory landscape of the glioma-associated transcription factor Capicua Firme, Juan Marlo R. 2014

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 THE REGULATORY LANDSCAPE OF THE GLIOMA-ASSOCIATED TRANSCRIPTION FACTOR CAPICUA by Juan Marlo R. Firme B.Sc., The University of British Columbia, 2010  A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in The Faculty of Graduate and Postdoctoral Studies (Genome Science and Technology)  THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) December 2014 © Juan Marlo R. Firme, 2014  ii  Abstract  The metazoan developmental gene capicua transcriptional repressor (CIC) encodes a transcription factor that transduces receptor tyrosine kinase signaling into gene expression changes. Aberrant CIC function is implicated in oligodendroglioma (ODG) development since one CIC allele is lost while the other is mutated in ~70% of ODGs. We therefore investigated how CIC can affect gene expression at a genome-wide level by inactivating CIC in HEK293a cells and subsequently measuring gene expression changes using microarrays. From this, gene expression changes spanning entire chromosomes were detected. Additionally, 24 candidate CIC-regulated genes were identified in HEK293a cells that also have evidence of CIC-dependent regulation in ODGs sequenced by The Cancer Genome Atlas (TCGA). Of these 24 genes, 5 genes (CNTFR, DUSP6, GPR3, SHC3, and SPRY4) with reported functions in mitogen-activated protein kinase (MAPK) signaling and central nervous system (CNS) development were further validated to undergo CIC-dependent regulation in HeLa cells. Finally, investigating how different CIC mutations affect gene expression revealed that different types of ODG-associated CIC mutations either abrogated or potentially preserved CIC’s transcriptionally repressive activity. These findings shed insight into possible roles for CIC in regulating gene expression at a chromosome-wide scale, MAPK signaling, CNS development, and ODG development.   iii  Preface   Chapter 1. Data for Figure 1 was gathered from The Cancer Genome Atlas (TCGA) though the Cancer Genomics cBioPortal1,2 and from other applicable sources3–7.  Chapter 2. The data presented are primarily based on work performed at the BC Cancer Agency by Marlo Firme, Dr. Suganthi Chittaranjan, Susanna Chan, and Jeungeun Song in the Marco Marra laboratory at Canada’s Michael Smith Genome Sciences Centre, by Emma Laks in the Sam Aparicio laboratory at the Department of Molecular Oncology, and by Amy Lum at the Centre for Translational and Applied Genomics (CTAG). Sections 2.1.2, 2.1.3, and 2.1.10 of the Materials and Methods section have been directly quoted from previously published material of which I am a coauthor8. Data on Figure 2b were generated by Jeungeun Song. Data on Figure 3a, 3b, and 3c were generated by Emma Laks and Marlo Firme. Data on Figure 3d were generated by Amy Lum. Data from Figures 4b and 8 were gathered from TCGA through the Cancer Genomics cBioPortal1,2 and the Cancer Browser from the University of California, Santa Cruz9.  The Flag-CIC constructs indicated in Figure 9 were designed by Dr. Suganthi Chittaranjan and generated by Susanna Chan and Marlo Firme. The luciferase reporter construct depicted in Figure 9a was a gift from Dr. Takuro Nakamura10. The rest of the experiments were designed and performed by Marlo Firme under the counsel of Dr. Marco Marra.  iv  Table of Contents  Abstract ......................................................................................................................................................... ii Preface .......................................................................................................................................................... iii Table of Contents ......................................................................................................................................... iv List of Tables ................................................................................................................................................. v List of Figures ............................................................................................................................................... vi List of Abbreviations ..................................................................................................................................... vii Acknowledgements ...................................................................................................................................... ix Chapter 1: Introduction .................................................................................................................................. 1 1.1 Traditional Histological Classification of Adult Diffuse Gliomas .......................................................... 1 1.2 Genetics of Adult Diffuse Gliomas ...................................................................................................... 3 1.3 CIC in Cell Signaling, Development, and Disease .............................................................................. 8 1.4 Thesis Investigation Overview .......................................................................................................... 11 Chapter 2: Investigation of CIC Mutations on Gene Expression ................................................................ 15 2.1 Materials and Methods ...................................................................................................................... 15 2.1.1 Cell Culture and Conditions ....................................................................................................... 15 2.1.2 Whole Cell Lysate Protein Extraction ......................................................................................... 15 2.1.3 Western Blot Protein Detection .................................................................................................. 16 2.1.4 Zinc Finger Nuclease-mediated CIC Inactivation ...................................................................... 16 2.1.5 siRNA-mediated Knockdown of CIC Expression ....................................................................... 17 2.1.6 mRNA Quantification by RT-qPCR ............................................................................................ 18 2.1.7 Sequencing of the ZFN Target Locus ........................................................................................ 18 2.1.8 Fluorescence in situ Hybridization (FISH) .................................................................................. 19 2.1.9 Microarray Expression Profiling ................................................................................................. 20 2.1.10 Flag-CIC Construct Generation ............................................................................................... 20 2.1.11 Luciferase Assay ...................................................................................................................... 21 2.1.12 Statistical Analysis ................................................................................................................... 22 2.2 Results .............................................................................................................................................. 23 2.3 Discussion ......................................................................................................................................... 31 References .................................................................................................................................................. 49 Appendix 1 .................................................................................................................................................. 56 Appendix 2 .................................................................................................................................................. 64   v  List of Tables  Table 1. Molecular subtypes of adult diffuse glioma ........................................................................... 13 Table 2. RT-qPCR primers used. .......................................................................................................... 38 Table 3. Consistently identified candidate CIC-regulated genes ...................................................... 39      vi  List of Figures  Figure 1. ODG-associated mutations mapped to the predicted CIC short isoform protein. ......... 14 Figure 2. Zinc finger nuclease-mediated mutation of endogenous CIC produces a model for hypomorphic CIC function. ..................................................................................................................... 41 Figure 3. All sequenced CIC alleles of cicZFN1 and cicZFN2 cells harbour frameshifting insertions. .................................................................................................................................................................... 42 Figure 4. Microarray expression analysis of cicWT and cicZFN2 cells identifies candidate CIC-regulated genes. ....................................................................................................................................... 43 Figure 5. CIC inactivation possibly mediates chromosome-wide gene expression changes in HEK293a cells. ......................................................................................................................................... 44 Figure 6. RT-qPCR verifies gene expression changes detected from microarrays. ...................... 45 Figure 7. siRNA-mediated CIC knockdown validates genes as CIC-regulated. ............................ 46 Figure 8. CIC-regulated genes exhibit CIC mutation type-specific expression. ............................. 47 Figure 9.  Representative missense mutations preserve CIC’s repressive activity while a CIC truncation does not. ................................................................................................................................. 48     vii  List of Abbreviations  1p/19q codeletion deletion of chromosomal arms 1p and 19q 2HG 2-hydroxyglutarate αKG alpha-ketoglutarate ADG adult diffuse glioma C1 CIC’s highly conserved C-terminal motif ChIP-seq chromatin immunoprecipitation followed by next-generation sequencing CIC capicua transcriptional repressor CIC inact 1p/19q-codeleted ADGs with predicted CIC-inactivating mutations CIC C1 1p/19q-codeleted ADGs with single amino acid mutations targeting the C1 motif CIC HMG 1p/19q-codeleted ADGs with predicted CIC-inactivating mutations targeting the HMG box domain cicWT parental HEK293a clone cicZFN1 cicWT-derived clone with reduced CIC expression cicZFN2 cicZFN1-derived clone with essentially undetectable CIC expression  CIC-L long CIC isoform CIC-S short CIC isoform EGFR epidermal growth factor receptor ETS E-twenty-six ETV1/4/5 ETV1, ETV4, and ETV5 FDR false discovery rate FISH fluorescence in situ hybridization  viii  FUBP1 far upstream element binding protein 1 GBM glioblastoma HMG high mobility group IDH1/2 isocitrate dehydrogenase 1 or 2 MAPK mitogen-activated protein kinase ODG oligodendroglioma Q564X Gln564* nonsense mutation R1515H Arg1515His missense mutation R201W Arg201Trp missense mutation RTK receptor tyrosine kinase SCA1 spinocerebellar ataxia type I TBP TATA-binding protein TCGA The Cancer Genome Atlas WHO World Health Organization ZFN zinc finger nuclease     ix  Acknowledgements   Thank you to Ms. Donna Anderson for your generosity and support of the work in this thesis. Thank you to Dr. Takuro Nakamura and Dr. Carol MacKintosh, who graciously provided us with DNA constructs. Thank you to Emma Laks and Amy Lum for performing experiments in this study. Thank you to Dr. Suganthi Chittaranjan and Susanna Chan for assistance in the lab and for guiding and supporting me. Thank you to Diane Trinh, Julia Pon, Dr. Alessia Gagliardi, Ryan Huff, Veronique LeBlanc, Jeungeun Song, Angelica Lee, and Dr. Isabel Serrano for your assistance with reagents and helpful wet lab advice. Thank you to Dr. Jill Mwenifumbo, Olena Morozova, Emilia Lim, Dr. Farah Zahir, Rodrigo Goya, and Elizabeth Chun for your assistance in bioinformatics. Thank you to Lulu Crisostomo for always helping out with administrative tasks. Thank you to the faculty and staff of the Genome Sciences and Technology Program at the University of British Columbia, especially Sharon Ruschkowski, Dr. Stephen Withers, Dr. Rosie Redfield, and Dr. Phil Hieter for helping to further my learning. Thank you to my committee members Dr. Stephen Yip and Dr. Gregory Cairncross for your enthusiasm and support in this research. Finally, thank you to Dr. Marco Marra for leading by example to teach students like me to become better and wiser.    1  Chapter 1: Introduction  1.1 Traditional Histological Classification of Adult Diffuse Gliomas   Adult Diffuse Gliomas (ADGs), accounting for ~85% of all central nervous tumours, are the most common type of primary brain tumour11. To date, ADGs are considered malignant and incurable. This is largely due to their infiltrative and migratory nature, making them difficult to manage surgically12. Less aggressive or lower-grade ADGs also typically progress to higher-grade lesions over time13.  ADGs can be highly heterogeneous with respect to the clinical courses that they follow13,14. The clinical courses of ADGs, however, generally correlate with certain microscopic characteristics. For this reason, the World Health Organization (WHO) has classified ADGs according to their histology (resemblance to specific cell types) and their grade, determined by characteristics such as the presence of anaplastic changes (loss of structural differentiation) and necrosis13. Classifying ADGs this way allows doctors to better predict patient survival and aids in decision-making for choosing between different treatment modalities13–15. ADGs range in grade from II to IV and the three main histological types of ADG are oligodendroglioma, astrocytoma, and oligoastrocytoma13.   2  Oligodendrogliomas (ODGs) are slow-growing neoplasms that comprise ~5-6% of central nervous system gliomas11,16. ODGs get their name from their resemblance to oligodendrocytes, non-neuronal brain cells that myelinate or insulate the axons of neurons17. With overall survival rates of ~70-80% over 5 years, ODGs generally have the most favourable prognosis of the three ADG types13,18,19. ODGs are also characteristically responsive to chemotherapy but can still recur and progress to higher grades12,18,20.  Astrocytomas, comprising ~75% of central nervous system gliomas, are the most common and generally most aggressive histological type of ADG11. Astrocytoma cells resemble astrocytes, highly abundant star-shaped glial cells that are important in maintaining brain structure, nutrition and homeostasis17. 5 year overall survival remains at ~47% and ~27% for WHO grade II and III astrocytomas, respectively11. Grade IV astrocytomas, more commonly known as glioblastomas (GBMs), have an overall survival rate of just ~5% over 5 years11. GBMs can either arise spontaneously (primary GBM) or from the progression of a lower-grade glioma (secondary GBM)13. Relative to secondary GBMs, primary GBMs have a overall higher age of onset21, indicating that primary and secondary GBMs are distinct biological entities.  Oligoastrocytomas are classified as having cells of both oligodendrocytic and astrocytic histologies13. Oligoastrocytomas comprise ~3% of central nervous system gliomas diagnosed in the United States11 but have also been diagnosed at frequencies  3  of up to 9.2% of intracranial gliomas22 and 19% of supratentorial low-grade gliomas23. This apparent inconsistency suggests that the oligoastrocytomas are difficult to distinguish between other ADG histological types. As a group, oligoastrocytomas have an intermediate prognosis (~61% overall survival over 5 years) relative to ODGs and astrocytomas11. However, inconsistent diagnosis of oligoastrocytoma may limit the utility of this classification group in predicting clinical outcomes.  While the histological features of ADGs are generally able to predict clinical outcomes, they may mask the true biological heterogeneity that underlies this group of tumours. In addition, the lack of effective therapies for ADGs prompts us to better understand these tumours at the molecular level. In the recent years, genetic profiling of ADGs has proven useful in refining their classification into clinically and biologically meaningful groups, with the added benefit of providing insight into the molecular underpinnings of ADGs18,24–29.  1.2 Genetics of Adult Diffuse Gliomas  It is widely accepted that cancer is a genetic disease. That is, changes in the genome and in the epigenome are able to cause gene expression changes that deregulate normal cellular pathways to promote uncontrolled cell growth30. Through next-generation sequencing technologies, we are now able to sequence the genome of a tumour within days and for only a few thousand dollars, with costs continuing to  4  decrease31. This cost decrease has increased the feasibility of whole-genome studies, allowing us to uncover the complex landscapes of genomic and epigenomic aberrations that underpin tumour development. Whole-genome and transcriptome profiling techniques are also allowing for the classification of tumours into molecular subtypes, which can often predict clinical outcomes and uncover molecular heterogeneity that we cannot detect using histology alone6,25,27,29,32–35.  ADGs can now be broadly classified into 3 molecular subtypes according to a specific set of genetic alterations, summarized in Table 1. The different ADG molecular subtypes (IDH1/2-wild type, ATRX/TP53-mutated, and 1p/19q-codeleted) correlate well with different clinical outcomes, indicating they are biologically distinct groups6,27,28. The different subtypes also correlate well, albeit not perfectly, with the different ADG histologies, and especially highlight molecular heterogeneity within tumours classified as oligoastrocytomas and GBMs6,27,28.   Notably, some of the genetic alterations that characterize the ADG molecular subtypes can be shared between subtypes6,27,28, alluding to shared mechanisms in ADG development. In addition, some of these genetic alterations exhibit distinct patterns of anticorrelation or even mutual exclusivity between subtypes, suggesting redundant mechanisms in ADG development. Also, some of these genetic alterations often co-occur within the same tumour6,27,28,36, indicating important interactions between  5  genetic alterations. In the following paragraphs, the nature of these genetic alterations and their possible contributions to promoting ADG development will be discussed.  Isocitrate dehydrogenase 1 or 2 (IDH1/2) mutations are common to both the ATRX/TP53-mutated and 1p/19q-codeleted subtypes. IDH1 and IDH2 encode for a cytosolic form and the mitochondrial form, respectively, of enzymes that normally produce alpha-ketoglutarate (αKG) in the citric acid cycle37,38. ADG-associated IDH1/2 mutations are highly recurrent point mutations that substitute a single amino acid within the enzymes’ catalytic binding cleft. These mutations change their enzymatic activity to instead catalyze the production of 2-hydroxyglutarate (2HG) with αKG as a substrate39. The resulting shift in metabolic equilibrium within the cell interferes with the normal functioning of DNA and histone methylation enzymes, resulting in widespread changes in the epigenome40–42.   The observation that IDH1/2 mutations are present in both the ATRX/TP53-mutated and 1p/19q-codeleted ADG subtypes6,27,28 suggests that IDH1/2 mutations are initiating mutations that arise early on in the tumourigenic process, with successive mutations further contributing to malignancy. Notably, IDH1/2 mutations have also been observed in acute myeloid leukemia, chondrosarcoma, cholangiocarcinoma, and angioimmunoblastic T-cell lymphoma37.   6  ATRX and TP53 mutations characterize the ATRX/TP53-mutated subtype, which is characteristic of the majority of oligoastrocytomas, grade II and III astrocytomas, and secondary glioblastomas6,27,28. TP53 is a well-studied tumour suppressor gene that is mutated in many cancer types and has been termed the “guardian of the genome43.” Its gene product, p53, is a DNA-binding protein that can arrest cell cycle progression if DNA is damaged, initiate DNA repair, and initiate apoptosis if the damage is not repaired44–46. Meanwhile, ATRX encodes a chromatin remodeling protein whose inactivation is linked to a mechanism of maintaining telomere length termed alternative lengthening of telomeres or ALT47–49.  Maintaining telomere length is an important hallmark of cancers because telomere shortening from successive replications eventually induces replicative senescence50.   TERT promoter mutations are common to most IDH1/2-wild type and 1p/19q-codeleted ADGs24,26–28,36. These mutations can generate a motif within the TERT promoter that may be recognized by members of the E-twenty-six (ETS) family of transcription factors36,51,52. These mutations therefore likely activate TERT expression by allowing members of the ETS transcription factor family to bind to the TERT promoter and promote TERT transcription. TERT encodes the catalytic subunit of the telomerase enzyme, with a canonical function of maintaining telomere length53,54. Therefore, like ATRX mutations, TERT promoter mutations can constitute an important mechanism in a tumour’s escape from replicative senescence induced by telomere shortening54. Notably, mutations in the TERT promoter are present in a number of cancer types that arise from tissues that typically do not self-renew36.  7   Currently, one of the most routinely used molecular markers for the prognosis of ADGs is a deletion of the chromosomal arms 1p and 19q (1p/19q codeletion)55. 1p/19q codeletions correlate well with increased survival and chemosensitivity and characterize the 1p/19q-codeleted subtype, considered to be “classical” ODG18. However, until next-generation sequencing, specific gene targets of these chromosomal arm deletions had remained enigmatic. In recent years, several sequencing studies have unveiled capicua transcriptional repressor (CIC), located on 19q, and far upstream element binding protein 1 (FUBP1), located on 1p, as being mutated in ~70% and 25-40% of 1p/19q-codeleted ADGs, respectively3–5. This implicates tumour suppressive roles for both CIC and FUBP1 since one allele is lost from the 1p/19q codeletion while the other allele is often mutated in these ADGs.    Both CIC and FUBP1 encode transcription factors for which several target genes have been identified. The FUBP1 protein is required for maximal expression of the well-known proto-oncogene MYC, whose gene product also functions as a transcription factor that can regulate hundreds of cellular genes56. FUBP1 can also bind several mRNA species, both viral and endogenous, to alter the translation or splicing of these mRNA species57.  Meanwhile, the established target genes for the CIC protein are the 3 members of an oncogenic subfamily of ETS transcription factors ETV1, ETV4, and ETV5 (ETV1/4/5)10,58. Overexpression of ETV1/4/5 have been associated with melanoma, breast, and prostate cancers59. To our knowledge, however, no genome- 8  wide studies to comprehensively identify genes regulated by endogenous CIC and FUBP1 in human cells have been reported. How FUBP1 and CIC affect gene expression in human cells has therefore remained largely unexplored, making the roles of CIC and FUBP1 mutations in ADG development unclear. Since CIC is more frequently mutated than FUBP1 in ADG, the focus of this thesis is on CIC and the consequences of CIC mutations on gene expression in human cells.    1.3 CIC in Cell Signaling, Development, and Disease  The gene CIC encodes a transcription factor that transduces receptor tyrosine kinase (RTK) signaling into changes in gene expression to direct developmental processes such as differentiation and proliferation60–62. The functional domains of CIC in different metazoan species are highly conserved63, implying evolutionary conservation of CIC’s biochemical mechanisms. Consistent with this, CIC has invariably been observed in Drosophila, mice, and human cells to mediate RTK signaling through a mechanism of default repression10,60,64–67. That is, instead of directly activating target gene transcription upon the input of a RTK signal, CIC represses transcription until a RTK signal inhibits CIC's repressive activity58,60,68. This mechanism of default repression can facilitate the establishment of sharp boundaries in which genes are turned "off" or "on" in a spatial context in the developing Drososphila embryo69,70. Notably, Cic functions repeatedly throughout Drosophila development to regulate the expression of different target genes through a RTK-MAPK-Cic signaling axis60,61,64,71.   9   The RTK-MAPK-CIC signaling axis is a conserved mechanism of gene regulation in human cells58. Using human melanoma and HEK293 cell line models, Kumara Dissanayake et al. described two biochemical mechanisms linking MAPK activation to the inhibition of CIC’s transcriptionally repressive activity58. First, activated MAPK can promote an interaction between CIC and 14-3-3 chaperone proteins. This CIC-14-3-3 interaction inhibits CIC binding to an octameric DNA motif (5’-TGAATGAA-3’). CIC normally binds this motif at the promoters or enhancers of CIC target genes10 to repress transcription when MAPK is not activated68. The second potential mechanism of CIC regulation by MAPK is through an interaction of CIC with the nuclear import protein importin α4/karyopherin α3. This interaction is inhibited by the activation of MAPK, thus potentially providing a partial mechanism for compartmentalizing CIC within the cytosol (and out of the nucleus) upon MAPK activation.  CIC has also been studied in several mammalian development and disease contexts. In a rare and aggressive subtype of Ewing family tumours, chimeric forms of CIC have been found to be fused to either DUX4, DUX4L, or FOXO410,72–74. The tumour-associated CIC-DUX4 fusion protein retains CIC’s known functional domains while acquiring a relatively small portion of the DUX4 C-terminal end10. This chimeric form of CIC activates ETV1/4/5 transcription whereas the wild type form of CIC normally represses ETV1/4/5 transcription10,75. Aberrant CIC function is also implicated in spinocerebellar ataxia type I (SCA1), in which an aberrant, polyglutamine-expanded  10  form of the ATAXIN-1 protein causes neurodegeneration66,67. Polyglutamine-expanded ATAXIN-1 modulates the transcriptionally repressive activity of CIC, and reduced CIC expression can mitigate the disease phenotypes of SCA166,67. Finally, the transient expression of murine Cic in developing cerebellar granule neurons has also implicated CIC in neurogenesis63.  There are two known main isoforms of CIC, the short (CIC-S) and long (CIC-L) form3. CIC-S and CIC-L differ in their N-terminal portions but share two highly conserved domains: a DNA-binding high mobility group (HMG) box domain and a C-terminal motif (C1) that is necessary for repression60,63. While the functional differences between these isoforms remain to be elucidated, our group has previously reported that CIC-L and CIC-S predominantly localize within the nucleus and cytoplasm, respectively, with the short isoform also in close proximity to the mitochondria8.  In 1p/19q-codeleted ADGs, roughly half of CIC mutations are frameshifting, nonsense, and splice site mutations that are spread throughout the CIC protein (Figure 1)3–6. These mutations are predicted to delete at least a portion of CIC to confer loss-of-function. This pattern of mutations typically characterizes classic tumour suppressor genes such as retinoblastoma 176,77, in which inactivation of both copies of the gene promotes malignancy76. However, the other half of CIC mutations are missense mutations and single, in-frame amino acid deletions that localize within and around the HMG domain and C1 motif and can be recurrent (Figure 1)3–6. This pattern, in contrast,  11  is more reminiscent of gain-of-function mutations such as the aforementioned IDH1/2 mutations, which keep the protein product intact but alter its function37. Overall, the mutational spectrum of CIC therefore confounds its role in ODGs since there seems to be selection for both mutations that disrupt the CIC protein structure as well as specific, single amino acid mutations that may fundamentally retain CIC’s protein structure.  1.4 Thesis Investigation Overview  A mechanistic understanding of the role of CIC mutations in ODGs may shed insight into ODG development. This may lead to the identification of molecular targets for the effective treatment of ODGs. Therefore, the goal for this thesis was to study how CIC mutations can affect gene expression in an experimentally tractable human cell system.   We hypothesized that ODG-associated CIC mutations confer a loss of CIC’s repressive activity and deregulate the expression of CIC target genes other than ETV1/4/5. To test this, we inactivated CIC in HEK293a cells and subsequently measured resulting gene expression changes using microarrays. From this, gene expression changes spanning entire chromosomes were detected. Additionally, 24 candidate CIC-regulated genes were identified in HEK293a cells that also have evidence of CIC-dependent regulation in 1p/19q-codeleted gliomas of The Cancer Genome Atlas (TCGA). Of these 24 genes, 5 genes (CNTFR, DUSP6, GPR3, SHC3,  12  and SPRY4) with reported functions in mitogen-activated protein kinase (MAPK) signaling and central nervous system (CNS) development were further validated to undergo CIC-dependent regulation in HeLa cells. Finally, investigating how different CIC mutations affect gene expression revealed that different types of ODG-associated CIC mutations either abrogated or potentially preserved CIC’s transcriptionally repressive activity. These findings shed insight into possible roles for CIC in regulating gene expression at a chromosome-wide scale, MAPK signaling, CNS development, and ODG development.  13   Figure 1. ODG-associated mutations mapped to the predicted CIC short isoform protein. CIC-S: short isoform of CIC. HMG: highrepressive c-terminal domain. Frequencies of different mutation typesgathered from references 1-7.14 -mobility group. C1 motif: transcriptionally Recurrently detected mutations are directly  are given in parentheses. Mutational data were   stacked.  15  Chapter 2: Investigation of CIC Mutations on Gene Expression  2.1 Materials and Methods   2.1.1 Cell Culture and Conditions   All cells used in this study were incubated at 37°C with 5% CO2 in DMEM (Gibco) supplemented with 10% FBS (Gibco). Unless otherwise stated, at ~70-90% confluency, cells were washed with PBS, trypsinized, and either passaged or harvested by pelleting. Pellet storage was at -80°C. All cell lines and their derived clones were passaged from between 2 to 8 times from their initial storage in liquid nitrogen before transfection or harvesting.   2.1.2 Whole Cell Lysate Protein Extraction  Cells were thawed on ice and resuspended in 5X packed‐cell volume of ice‐cold EDTA-free RIPA lysis buffer (20mM Tris‐HCl pH 7.5, 150mM NaCl, 0.1% NP‐40, and 0.25% sodium deoxycholate freshly supplemented with 1mM sodium orthovanadate, 1mM NaF, and 1X EDTA-free protease inhibitor from Roche). Cell pellets were homogenized by passing 5-10 times through a 21‐gauge needle then mixed for 20 minutes at 4ºC on an automatic rotator. Insoluble cellular debris was pelleted using centrifugation at 13000 x g for 10 minutes at 4ºC.  16    2.1.3 Western Blot Protein Detection  Extracted protein samples were subjected to gel‐electrophoresis on NuPage 3‐8% Tris Acetate pre‐cast mini‐gels (Invitrogen) with 1X MOPs buffer (Invitrogen) for 55 min at 150V. Separated proteins were transferred onto a methanol‐activated PVDF membrane (Bio-Rad) for 60 minutes at 100V in 1X transfer buffer (Invitrogen) with 20% (v/v) methanol. Membranes were then incubated with anti‐CIC (A301-204A, Bethyl Laboratories), anti-FLAG (F3165, Sigma), anti-tubulin (sc-9104, Santa Cruz), or anti-beta actin (ab8227, Abcam) at a 1:1000 dilution at 4oC overnight. Membranes were then incubated with either goat anti‐mouse HRP‐IgG (Santa Cruz) or goat anti‐rabbit IgG-HRP (dilution 1:5000, Santa Cruz) for 1 hour at room temperature, followed by three PBST washes before application of either ECL substrate (GE Healthcare or Bio-Rad) or SuperSignal West Femto substrate (Thermo Scientific). Images were captured using a LAS-4000 imager (FujiFilm) or ChemiDoc™ MP Imager (Bio-Rad).    2.1.4 Zinc Finger Nuclease-mediated CIC Inactivation   HEK293a (cicWT) cells were co-transfected with 5 µL of custom-designed CIC specific CompoZrTM custom zinc finger nuclease (ZFN) construct mRNA (Sigma-Aldrich) with a target site of GCCTCCAACCAGAGCaaaggtGAGGGCTGGTGGGGACTG (with the two ZFN-binding half sites capitalized), along with 250 ng of a Hygro RS reporter  17  construct (Toolgen) harbouring the same ZFN target site to enrich for cells in which ZFNs are active78. Transfection was performed by seeding 4 x 105 cells in a 6-well plate ~24 hours prior to transfection and performing lipid-based transfection using the Trans-IT-mRNA transfection reagent and Trans-IT Boost reagent (MIR 2225, Mirius Bio) according to Sigma’s recommendations for CompoZrTM custom ZFN transfection. Enrichment for cells with active ZFNs was carried out by treating cells with 0.5 mg/mL hygromycin at ~72 - 96 hours post-transfection. From the resulting enriched cell population, single clones were isolated using a limiting dilution method. These clones were then screened for reduced CIC expression using Western blots. A clone with reduced CIC expression (cicZFN1) was selected and brought through an additional round of transfection, enrichment, limiting dilution, and screening to obtain a clone with essentially absent CIC expression (cicZFN2).   2.1.5 siRNA-mediated Knockdown of CIC Expression  Cells were plated to ~80 % confluency and transfected with CIC-specific Stealth siRNA (HSS118258, Life Technologies) or nonspecific negative control siRNA (12935-200, Life Technologies). Transfection was carried out using Lipofectamine® RNAiMAX Transfection Reagent (13778030, Life Technologies) according to the manufacturer’s recommendations. Cells were harvested at ~72 hours post-transfection.   18   2.1.6 mRNA Quantification by RT-qPCR  RNA extraction was performed using the RNeasy Plus Mini Kit (74136, Qiagen) according to the manufacturer’s recommendations. RT-qPCR was carried out using 50 ng of template RNA with the Power SYBR® Green RNA-to-CtTM1-Step Kit (4389986, Life Technologies) according to the manufacturer’s recommended reaction component amounts and cycling conditions. A 7900 HT Sequence Detection System with SDS 2.2 software was used for temperature cycling and the generation of CT values. Analysis of relative mRNA expression was performed using the 2-∆∆CT method with TATA-box binding protein (TBP) expression as an endogenous control. Sequences of the RT-qPCR primers used are listed in Table 2.    2.1.7 Sequencing of the ZFN Target Locus   Genomic DNA extraction from cicWT, cicZFN1, and cicZFN2 cells was performed using the DNeasy Blood & Tissue Kit (69506, Qiagen) according to the manufacturer’s recommendations. Amplicons to be sequenced were assigned unique molecular barcodes and adapted for MiSeq flow-cell NGS sequencing chemistry using PCR. The PCR step was performed on 200 ng of template genomic DNA with Jumpstart Taq Polymerase (D9307, Sigma), a forward primer with sequence5’-TCGTCGGCAGCGTCAGATGTGTATAAGAGACAGCTCCTTAGTCCCCTTCCTGG-3’, and a reverse primer with sequence 5’- 19  GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAGAGGTTCTGGGGACACAGAGG-3’. Cycling conditions for the PCR amplification were (1) an initial denaturation at 95 °C for 1 min, (2) 35 cycles of denaturation at 95 °C for 30 sec, annealing at 58°C for 30 sec, and extension at 72°C for 1 min, and (3) a final extension at 72 °C for 1 min.  The barcoded amplicon libraries were pooled and purified using conventional preparative agarose gel electrophoresis. Library quality and quantitation was performed using a 2100 Bioanalyzer with DNA 1000 chips (Agilent Technologies) and a Qubit 2.0 Fluorometer (Life Technologies). High-throughput DNA sequencing was conducted using a MiSeq sequencer according to the manufacturer's recommendations (Illumina).   2.1.8 Fluorescence in situ Hybridization (FISH)   Fresh HEK293a cells were fixed onto slides using methanol and acetic acid in a 3 to 1 ratio. Slides were then aged in 2X SSC at 37 °C for 30 minutes followed by dehydration through an ethanol series.  Vysis 1p36/1q25 and 19q13/19p13 FISH probes were applied to the cells and co-denatured at 73 °C for 5 minutes and hybridized for 18 hours at 37 °C. Post-hybridization, cells were washed in 0.4X SSC/0.3% NP-40 for 2 minutes at 73 °C and air dried prior to adding DAPI counterstain.   20  2.1.9 Microarray Expression Profiling  Genome-wide mRNA expression profiling on 3 consecutive passages of cicWT, cicZFN1, and cicZFN2 cells was carried out using the GeneChip® Human Gene 2.0 ST array (Affymetrix) at The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, Canada. The resulting chp files were analyzed using the RMA algorithm and differential gene expression analysis was carried out using the Transcriptome Analysis Console (Affymetrix) in which Tukey’s bi-weight average is calculated for each group.  2.1.10 Flag-CIC Construct Generation  A tandem 3x FLAG sequence was PCR-amplified from plasmid pAFW1111 (Drososphila Genomics Resources Centre, Indiana, USA) using KAPA HiFi DNA polymerase (KAPA Biosystems). A forward primer with sequence 5’-ATCGAAGCTTACCATGGACTACAAAGACCATGACG-3’ and reverse primer with sequence 5’-ATCGGGATCCCTTGTCATCGTCATCCTTGTA-3’ were used generate tandem FLAG amplicons with HindIII and BamHI restriction sites.  A pcDNA™4/TO vector (Invitrogen) was modified by inserting the 3x FLAG sequence at HindIII/BamHI sites to create N-terminus 3xFLAG expression vector (pcDNA™4/TO/N-FLAG).   A pcDNA5 FRT/TO GFP-CIC construct (wild type) was obtained from University of Dundee, Scotland58 .  Site-directed mutagenesis was performed to create mutant  21  constructs pcDNA5 FRT/TO GFP-CIC_R1515H and pcDNA5 FRT/TO GFP-CIC_R201W using the QuikChange II XL Kit (Agilent).  Mutant constructs were sequence-verified.   Using a forward primer with the sequence 5’-ATCGGAATTCAAGATCTATGTATTCGGCCCACAGGCCC-3’ and reverse primer with the sequence 5’-AAGGCCAGGTCGTGGTACTTCT-3’, and TaKaRa LA Taq (Clontech), the first 1496 bp of CIC-S (referred to as 5’ CIC-S), including a BglII restriction site just before the start codon, was amplified from pcDNA5 FRT/TO GFP-CIC. The 5’ CIC-S amplicon was sequence-verified and restriction digestion was performed using BglII (NEB).  A 4436 bp region of CIC from pcDNA5 FRT/TO GFP-CIC was obtained using StuI (NEB) and NotI (NEB) enzymes (referred to as 3’ CIC).  This 3’ CIC fragment was ligated to the 5’ CIC-S amplicon using Quick T4 DNA ligase (NEB) to yield full length CIC-S.  CIC-S was cloned into BamHI/NotI sites of pcDNA™4/TO/N-FLAG to create the pcDNA4/TO/FLAG-CIC-S (referred to as Flag-CIC) plasmid construct.  The pcDNA4/TO/FLAG-CIC_R1515H and pcDNA4/TO/FLAG-CIC_R201W constructs were created as described for FLAG-CIC-S.  2.1.11 Luciferase Assay  ~24 hrs prior to transfection, 1.4 x 105 cells per transfection were seeded in 24-well plates. Transfection was carried out using the Turbofect transfection reagent  22  (R0531, Thermo Scientific) according to the manufacturer’s recommendations. The following DNA amounts were transfected into each well: 0.6 µg of a pGL3 reporter vector with a cloned promoter sequence of ETV5 (99 to 996 base pairs upstream of the transcription start site10), 40 ng of the indicated flag-CIC construct or corresponding flag vector-only control, and 0.1 µg of a pRL-CMV vector (E2261, Promega) as a transfection control. At ~72 hours post-transfection, luciferase expression was measured using the Dual Glo luciferase assay system (E2920, Promega) according to the manufacturer’s recommendations and with a Perkin Elmer Wallac 1420 Victor2 microplate reader.  2.1.12 Statistical Analysis  2 sample t-test was used to compare the means of relative mRNA expression, as measured by RT-qPCR and microarrays, between the HEK293a clones. Wilcoxon rank sum test was used to compare transcript abundance of the different genes, as measured by RNA-seq and given in RSEM, between the different groups of 1p/19q-codeleted TCGA gliomas. 1-sided Fisher’s exact test was used to assess the positive association between the number of candidate CIC-regulated genes and the number of measured genes within a chromosome for each chromosome. For CIC-specific siRNA-treated HeLa cells, 1-sample t-test was used to compare the mean of relative mRNA expression (normalized to nonspecific siRNA-treated conditions) to a mean of 1.0. Luciferase expression was normalized to expression in cicWT cells transfected with the flag only vector control. 1 sample t-test was used to compare the mean of luciferase  23  expression in cicZFN2 cells transfected with a vector-only control to a mean of 1.0. 2 sample t-test was used for all other comparisons between means of luciferase expression. The Benjamini-Hochberg procedure was used to calculate all false discovery rates to correct for multiple hypothesis testing.  2.2 Results   Zinc finger nuclease treatment of HEK293a cells produces isogenic clones with CIC loss-of-function phenotypes.   In order to investigate CIC’s effects on gene expression in cells, CIC was first inactivated in HEK293a cells (cicWT) with a zinc finger nuclease (ZFN), an engineered protein that can produce insertions and deletions at unique target sites within the genome. The ZFN used was specific for a unique genomic sequence within CIC that is common to both CIC isoforms and maps N-terminal to CIC’s DNA-binding domain and repressive C-terminal motif (Figure 2a). This insures that frameshifting insertions and deletions introduced by the ZFN could abrogate CIC function.   After treating cicWT cells with the CIC-specific ZFN, a clone was isolated (cicZFN1) with reduced CIC-L and CIC-S expression, as detected using Western blots (Figure 2b). cicZFN1 cells were subjected to another round of ZFN treatment and monoclonal isolation from which an additional clone (cicZFN2) with essentially undetectable levels of CIC-L  24  and CIC-S was obtained (Figure 2b). The specificity of the antibody used in the Western blot detection of CIC was confirmed using siRNA-mediated knockdown of CIC (Figure 2b). Finally, mRNA expression of CIC’s known target genes ETV1/4/5, as measured by RT-qPCR, all increased by ~2-fold in cicZFN1 cells and by at least 10-fold in cicZFN2 cells relative to cicWT cells (Figure 2c).   In cicZFN1 and cicZFN2 cells, mutations were likely introduced that abrogate the expression of functional CIC. Furthermore, the observed ETV1/4/5 expression levels in cicZFN1 and especially in cicZFN2 cells are consistent with a CIC loss-of-function phenotype that would be predicted from the literature. The data therefore indicate the utility of this CIC loss-of-function system in characterizing CIC function and identifying additional CIC target genes.  Frameshifting insertions and deletions were observed in all detected CIC alleles of cicZFN1 and cicZFN2 cells.  The locus containing the CIC-specific ZFN target site was then amplified and sequenced in cicWT, cicZFN1, and cicZFN2 cells to identify the nature of the ZFN-induced frameshifting mutations. As expected, all detected alleles of cicZFN2 cells harboured frameshifting mutations while cicWT cells had no detected frameshifting mutations (Figure 3a and 3b). The ratio of the 3 mutant alleles were also detected at roughly a  25  2:1:2 ratio (Figure 3b), which is consistent with the observation that the HEK293a cells used in this study have up to 5 CIC loci (Figure 3d). Finally, all 3 frameshifting mutations were predicted to add either three or four out-of-frame codons following the mutation before introducing a stop codon to truncate the CIC polypeptide (Figure 3c).    Surprisingly, all sequenced CIC alleles of cicZFN1 cells also harboured the same frameshifting insertions as cicZFN2 cells (Figure 3a and 3b), despite cicZFN1 cells having detectable CIC-L and CIC-S protein expression (Figure 2b). Since the observed frameshifting insertions mutations lie close to the intron-exon boundary (Figure 3a), I speculate that a noncanonical splice site upstream of the frameshifting insertions maybe preferentially used in cicZFN1 cells relative to cicZFN2 cells. This hypothetical splice site, when used instead of the canonical exon 2 splice site in the processing of CIC mRNA, can result in the splicing out the ZFN-induced mutations as intronic sequence. This type of splicing could therefore generate functional transcript in the cicZFN1 cells. However, this phenomenon has not yet been investigated further.     26  Identification of candidate CIC-regulated genes in HEK293a cells and 1p/19q-codeleted ADGs.  To identify genes potentially regulated by CIC, microarray expression profiling was performed to compare gene expression at genome-wide levels between cicWT and cicZFN2 cells. Consistent with their expression patterns observed from RT-qPCR, ETV1/4/5 were observed to have increased expression in cicZFN2 relative to cicWT cells within a calculated false discovery rate (FDR) value of 0.1 or 10% (Figure 3a). For this reason, the 598 genes with differential expression between cicWT and cicZFN2 cells within a FDR threshold of 0.1 were considered candidate CIC-regulated genes in HEK293a cells (Figure 4a).   24 of the 598 candidate CIC-regulated genes in HEK293a cells also had differential expression (FDR < 0.1) in a data set obtained and derived from the Cancer Genome Atlas (TCGA)1,2,9. This data set compared gene expression, as measured by RNA-sequencing, between 21 CIC-inactivated and 43 CIC-wild type 1p/19q-codeleted ADGs (Figure 4b and 4c, and Table 3). These 24 genes included ETV1/4/5 and were therefore considered to be strong candidates for CIC-regulated genes in both HEK293a cells and 1p/19q-codeleted ADGs.   27   Detection of possible CIC-mediated chromosome-wide changes in gene expression.   Unexpectedly, a significant enrichment of candidate CIC-regulated genes in HEK293a cells was observed in chromosomes 2, 6, 19, and 20 (FDR < 0.05, Figures 5a and 5b). Most if not all the candidate CIC-regulated genes in these chromosomes span either several Giemsa bands (chromosomes 2 and 6) or the entire length of the chromosome (chromosomes 19 and 20) (Figure 5a). These results suggest that CIC inactivation can mediate changes in gene expression at a chromosome-wide scale.  Assuming that CIC only functions to directly repress transcription, the widespread decreased expression of genes within chromosomes 2, 19, and 20 upon CIC inactivation is suggestive of an indirect mechanism of regulation by CIC. Furthermore, the vast majority of candidate CIC-regulated genes in these chromosomes exhibited either increased expression (chromosome 6) or decreased expression (chromosomes 2, 19, and 20) upon CIC inactivation (Figure 5b). I therefore speculate that CIC may mediate large-scale changes in chromosomal architecture to either limit or enhance the accessibility of genes to transcriptional machinery. Consistent with this speculation, we note several genes implicated in chromatin remodeling through the alteration of DNA methylation or nucleosome occupancy (histone cluster 1, HAT1, SMARCB1, SMARCA4, MBD3, UHRF1, and DNMT1) were among the candidate CIC-regulated genes in HEK293a cells (Appendix 1 and 2).  28  Verification and Validation of CIC-regulated genes.   Of the 24 consistently detected candidate CIC-regulated genes, CNTFR, DUSP6, GPR3, SHC3, and SPRY4, were among the genes with the highest expression in cicZFN2 relative to cicWT cells. These 5 genes also had increased expression in CIC-inactivated relative to CIC-wild type 1p/19q-codeleted ADGs (Table 3). Interestingly, all 5 genes also have reported roles in neuronal cell development and MAPK signaling regulation (Table 3), possibly indicating that CIC regulates these processes by regulating the expression of these 5 genes. Consistent with their observed expression changes in the microarray data, the expression of DUSP6, GPR3, SHC3, and SPRY4 was verified using RT-qPCR to be increased in cicZFN2 relative to cicWT cells (p < 0.01, Figure 6). The same trend was also apparent for CNTFR (p = 0.11, Figure 6). For all 5 genes, there was also a trend of increased expression in cicZFN1 cells relative to cicWT cells (Figure 6).  To further assess CIC-dependent regulation of CNTFR, DUSP6, GPR3, SHC3, and SPRY4, expression of these genes was quantified using RT-qPCR upon siRNA-mediated knockdown of CIC in HeLa cells (Figure 7). As expected, CIC-S and CIC-L protein expression decreased (Figure 7a) and ETV1/4/5 mRNA expression increased (Figure 7b) in these cells upon treatment with CIC-specific siRNA. There was also a significant increase in mRNA expression of DUSP6 and SHC3 (p < 0.05) and a trend of increased expression of SPRY4 (p = 0.13), GPR3 (p = 0.06), and CNTFR (p = 0.15)  29  upon treatment with CIC-specific siRNA (Figure 7c). These results, taken together with all the heretofore presented evidence, strongly implicate that CNTFR, DUSP6, GPR3, SHC3, and SPRY4 are CIC-regulated genes.  Different CIC mutation types confer different effects on the expression of CIC-regulated genes.   ODG-associated CIC mutations not only consist of mutations predicted to disrupt the CIC protein (e.g. frameshifting mutations), but also single amino acid mutations targeting CIC’s HMG box domain and C1 motif that may preserve CIC’s protein structure. We therefore investigated whether different CIC mutation types confer different effects on the expression of CIC-regulated genes by grouping 82 TCGA 1p/19q-codeleted ADGs into 4 groups according to their CIC status (Figure 8a): (1) those that harbour no detectable CIC mutations, (2) frameshifting, nonsense or splice site mutations (CIC inact), (3) HMG box-targeting single amino acid mutations (CIC HMG), and (4) C1 motif-targeting single amino acid mutations (CIC C1). mRNA expression of the 8 CIC-regulated genes (ETV1/4/5, CNTFR, DUSP6, GPR3, SHC3, and SPRY4), as measured by RNA-sequencing, was then compared between these 4 groups. From this analysis, it was observed that the CIC inact group generally had the highest expression of all 8 genes (Figure 8c). For ETV4, ETV5, GPR3, and DUSP6, however, expression was significantly lower in the CIC C1 group relative to the CIC inact group. Additionally, For ETV4 and GPR3, expression was also significantly lower  30  in the CIC HMG group relative to CIC inact group. These results indicate ODG-associated CIC mutations targeting the HMG box domain and C1 motif may retain CIC’s transcriptionally repressive activity on some genes.  To further assess the extent to which types of CIC mutations could repress target gene expression, we reintroduced wild type and representative mutant forms of CIC-S into cicZFN2 cells (Figure 9a). At the same time, a reporter construct harbouring a luciferase cassette under the control of the ETV5 promoter (Figure 9b) was also introduced into these cells. In this system, luciferase expression hence served as an indicator of the repressive activity of different forms of CIC on the ETV5 promoter. From this assay, we observed that Q564X CIC, a truncating nonsense mutation, had no significant repressive activity (p = 0.48, Figure 9c). Meanwhile, wild type CIC, R201W CIC (a recurrent HMG box domain missense mutation), and R1515H CIC (a recurrent C1 motif missense mutation) could repress luciferase expression (p < 0.05).      31  2.3 Discussion   Summary and Comparison to other Studies   In investigating the effects of CIC on gene expression, it was observed that CIC inactivation possibly mediates chromosome-wide gene expression changes. This investigation has also shown that the expression of CNTFR, DUSP6, GPR3, SPRY4, and SHC3 can be deregulated by CIC inactivation in multiple cell contexts. Finally, we observe that ODG-associated single amino acid mutations targeting CIC’s highly conserved domains have the potential to preserve at least some of CIC’s repressive activity while CIC-inactivating mutations such as the Q564X mutation can completely abrogate CIC’s repressive function.     To my knowledge, there are two other studies in which CIC-regulated genes were identified in mammalian cells. One was in investigating how expression of the oncogenic CIC-DUX4 fusion protein affects gene expression10. LBH, a consistently identified candidate CIC-regulated gene in this study, was also among the genes reported to be activated by CIC-DUX4. In a study of the neurodegenerative disease SCA1 (in which aberrant CIC function is implicated), 16 genes, including another consistently identified candidate CIC-regulated gene in this study (DUSP4), were reported as targets of Cic repression in mice67.    32  Collectively, there are now 10 genes with reported evidence of CIC-dependent regulation in at least two mammalian cell contexts (ETV1/4/5, CNTFR, DUSP6, GPR3, SHC3, SPRY4, LBH, and DUSP4). Consistent with CIC’s known function as a transcriptional repressor, all 10 genes were consistently observed to have increased expression in CIC-inactivated relative to CIC-wild type conditions in this study. However, we also observed that other candidate CIC-regulated genes can have decreased expression upon CIC inactivation, indicating that CIC also directly or indirectly positively regulates gene expression.   Limitations of Study    One potential limitation and simultaneous strength of this investigation is that the overall impact of CIC inactivation on gene expression was measured regardless of whether or not these gene expression changes were directly or indirectly due to a loss of CIC’s repressive activity. For example, while the identified CIC-regulated gene DUSP6 increased in expression upon CIC inactivation, this change could be due to either DUSP6 being a direct target of CIC-mediated repression or to DUSP6 being positively regulated by other CIC targets ETV1/4/5, as has been reported in zebrafish79. To better understand the transcriptional network of CIC, the DNA elements in the genome that CIC binds can potentially be identified in future work using chromatin precipitation followed by next-generation sequencing (ChIP-seq). In ChIP-seq, CIC and CIC-bound DNA regions can be isolated using a CIC-specific antibody. The isolated  33  CIC-bound DNA regions would then be sequenced and mapped to the genome to identify possible genes directly regulated by CIC. This would shed insight into how CIC directly or indirectly influences the transcription of CIC-regulated genes.  We observed that CIC may mediate chromosome-wide gene expression changes. However, there is an important caveat to this argument. This caveat arises from the observation that CIC was nearly undetectable in cicZFN2 cells while consistently detectable in cicZFN1 cells, despite both these clones harbouring the exact same frameshifting CIC mutations at similar frequencies. This suggests that between cicZFN2 and cicZFN1 cells, there is change in the regulation of CIC, perhaps at the epigenetic or mRNA splicing level. This change in CIC regulation could also be causing the chromosome-wide gene expression changes observed between cicZFN2 and cicWT cells. In future work, we can address whether the chromosome-wide gene expression changes are CIC-mediated by ectopically reintroducing CIC into cicZFN2 cells. If this ectopic reintroduction of CIC reverses the chromosome-wide gene expression changes observed between cicZFN2 and cicWT cells, then these changes would be considered CIC-mediated.       34  Possible Tumourigenic Roles of CIC  Tumours such as ADGs develop from the deregulation of normal cellular growth and proliferation pathways50. Examples of such pathways include RTK signaling pathways, which interpret growth factor signaling into a wide variety of cellular responses80,81. Since CIC is a downstream, negatively-regulated component of RTK signaling58,62, deregulation of CIC target genes may recapitulate some effects of increased RTK signaling. The identification of novel CIC-regulated genes may therefore provide us with insight into how CIC mutations can contribute to ADG development.  Interestingly, the 5 identified CIC-regulated genes in this study, along with the consistently identified CIC-regulated gene DUSP4, have all been reported to be involved in regulating MAPK signaling. These genes either promote (CNTFR82, GPR383, and SHC384) or inhibit (DUSP485,86, DUSP687 and SPRY488) MAPK activation. Notably, CIC itself is negatively regulated by MAPK through RTK58. Taken together, these observations suggest that CIC may be positioned in regulatory feedback loops within the MAPK signaling network. CIC may therefore normally function to keep MAPK-mediated RTK signaling from becoming deregulated.     CNTFR, DUSP6, GPR3, SHC3, and SPRY4 have also been reported to either function in neuronal cell development and/or have brain specific expression82,84,89–92.  35  This indicates CIC may be important in the proliferation or differentiation of cells of the CNS. Consistent with this, several reports implicate CIC in CNS development. First, the murine Cic protein has been found to be predominantly expressed in the brain, with expression in the hippocampus and olfactory bulb and transient expression in the developing cerebellum63,93. Second, Drosophila Cic directly represses the transcription factor intermediate neuroblasts defective, a gene essential in the development of part of the Drosophila CNS94. Third, CIC is implicated in glioma and spinocerebellar ataxia type I, two pathologies of the CNS3,4,67. Finally, CIC is negatively regulated by EGFR signaling58, an essential signaling pathway in regulating the proliferation and differentiation of neural stem cells95–97. CIC may therefore normally function to somehow regulate the proliferation or differentiation of cells along the neural stem cell lineage to contribute to CNS development. An aberrant regulation of this process through CIC mutations may contribute to the transformation of normal cells to ODG.   This investigation may also provide insight into the biology of CIC as a cancer-associated gene. Cancer-associated genes can typically be classified as either tumour suppressive (i.e. loss of activity drives malignancy) or oncogenic (i.e. increased activity drives malignancy)30,77. For CIC in ODGs, the loss of one allele through the 1p/19q codeletion and mutation of the other allele in 70% of cases3,4,6 suggest a tumour suppressive role. However, we observed that different CIC mutations likely preserve some of CIC’s transcriptionally repressive activity on some genes while other mutations likely do not. This observation, taken together with the observation that about half of CIC mutations are single amino acid mutations that target CIC’s HMG box domain and  36  C1 motif3–6, indicates selective advantage for CIC mutations that can preserve repressive activity in some ODGs.  Possible Synergistic Interactions of CIC Mutations   CIC mutations may not only act individually but also synergistically with other co-occurring mutations in ODG. One possible interaction of CIC mutations is with IDH1/2 mutations, which cause widespread gene expression changes through the epigenetic alteration of chromatin architecture41,42. In this study, it was observed that CIC inactivation possibly mediates chromosome-wide gene expression changes, possibly by altering chromatin architecture as well. It would therefore be unsurprising if IDH1/2 mutations and CIC mutations, when co-occurring in the same cell, had synergistic effects in altering gene expression through the alteration of chromatin architecture.   Another possible synergistic interaction of CIC mutations is with TERT promoter mutations. As mentioned earlier, TERT promoter mutations likely activate TERT transcription by allowing members of the ETS family of transcription factors to bind to the TERT promoter51,52. In a TERT promoter-mutated context, CIC mutations may potentiate TERT transcription by derepressing the expression of ETV1/4/5, members of the ETS family of transcription factors10,58.    37  TERT promoter mutations are also common in IDH1/2-wild type ADGs28,36. In addition to TERT promoter mutations, RTK signaling is also commonly upregulated in this ADG subtype through aberrations such as EGFR amplifications6,98 and the overexpression of RTK genes99. This upregulation of RTK signaling may in turn inactivate CIC’s transcriptionally repressive activity to derepress ETV1/4/5 expression. Therefore, CIC may also play a key role in a synergistic interaction between upregulated RTK signaling and TERT promoter mutations to potentiate TERT transcription. In support of this, it has been observed that  92% of EGFR amplifications have been observed to co-occur with TERT promoter mutations in ADG98.    Conclusion   The CIC loss-of-function system generated in this study has revealed aspects of CIC’s biology that seem to be conserved in ODGs. Future work with this system may therefore provide further insight into the mechanisms of ODG-associated CIC mutations. In the future, comprehensive knowledge of the mechanisms of CIC and other ODG-associated mutations may give us an unprecedented understanding of the molecular biology of ODGs. Powered with this understanding, we may one day be able to rationalize effective treatments for ODGs.    38  Table 1. RT-qPCR primers used. Gene Forward Primer (5’ to 3’) Reverse Primer (5’ to 3’) ETV1 TGTCCTCCTCGTTGATGTGACG TGGGGCATTCAGAAAAACAGG ETV4 CAGGCGGAGGTTGAAGAAAGG AAGCGCAGAAGAAAGGCAAAGG ETV5 AGGGAAATCTCGATCTGAGGAATG GCTAACCAAGCCTCTTGAAGTTGAC CNTFR GAGGAGGAGGAGGACATTGA AGGAGCAGCCATCTCTTCAC GPR3 CTCCACGGTTCCAGAATGT (Figure 6) TGAGCGGTACCATGATGTG (Figure 7 GGGAGAAGGCTCTGGTTTCT (Figure 6) GATGATGGCCACCACTAGC (Figure 7) DUSP6 GCAACAGACTCGGATGGTAG TGCGTTCTCAAAGAGATTCG SHC3 ATTACCAGGGAAGCCATCAG CGTGGAGATGGTCAGAGAGA SPRY4 GTGACCAGGATGTCACCCAC GACCACCTTGGGCTGGATG TBP CAGCTCTTCCACTCACAGACT GTGCAATGGTCTTTAGGTCAA      39  Table 2. Consistently identified candidate CIC-regulated genes    Gene Symbol cicZFN2 vs. cicWT HEK293a cells CIC-inactivated vs. CIC-wild type 1p/19q-codeleted ADGs   Description Rank by fold change Log2 fold change FDR q-value Log2 fold change FDR q-value ETV4 1 0.644 0.0621 0.882 1.28E-05 ets variant 4 SPRY4* 2 0.517 0.0427 0.217 0.0073 sprouty homolog 4 (Drosophila) ETV5 3 0.504 0.0641 0.245 0.0011 ets variant 5 GPR3* 4 0.400 0.0427 0.320 0.0138 G protein-coupled receptor 3 ETV1 5 0.358 0.0524 0.171 0.0462 ets variant 1 DUSP6* 6 0.355 0.0631 0.151 0.0030 dual specificity phosphatase 6 SHC3* 7 0.208 0.0666 0.276 0.0194 SHC (Src homology 2 domain containing) transforming protein 3 DUSP4 8 0.183 0.0852 0.543 0.0011 dual specificity phosphatase 4 CNTFR* 9 0.145 0.0441 0.060 0.0820 ciliary neurotrophic factor receptor BACH2 10 0.122 0.0822 0.093 0.0073 BTB and CNC homology 1, basic leucine zipper transcription factor 2 LBH 11 0.089 0.0727 0.129 0.0227 limb bud and heart development homolog (mouse) HSF2BP 12 0.082 0.0793 0.223 0.0021 heat shock transcription factor 2 binding protein TJAP1 13 0.044 0.0648 -0.068 0.0226 tight junction associated protein 1 (peripheral) PTPN9 14 0.043 0.0842 0.055 0.0837 protein tyrosine phosphatase, non-receptor type 9 Asterisk: genes involved in MAPK regulation and neuronal cell development or have brain-specific expression. Red and green values: evidence of increased expression and decreased expression, respectively, when CIC is inactivated.    40     cicZFN2 vs. cicWT HEK293a cells CIC-inactivated vs. CIC-wild type 1p/19q-codeleted ADGs   Gene Symbol Rank by fold change Log2 fold change FDR q-value Log2 fold change FDR q-value Description PAQR4 15 -0.045 0.0228 -0.070 0.0826 progestin and adipoQ receptor family member IV UHRF1 16 -0.061 0.0841 0.128 0.0495 ubiquitin-like with PHD and ring finger domains 1 MRI1 17 -0.068 0.0822 -0.150 0.0436 methylthioribose-1-phosphate isomerase homolog (S. cerevisiae) CIC 18 -0.071 0.0375 -0.066 0.0073 capicua homolog (Drosophila) GNG7 19 -0.076 0.0470 -0.064 0.0842 guanine nucleotide binding protein (G protein), gamma 7 SIX1 20 -0.083 0.0736 0.406 0.0490 SIX homeobox 1 SLC35F1 21 -0.197 0.0641 0.117 0.0073 solute carrier family 35, member F1 GPRIN3 22 -0.219 0.0736 0.232 0.0366 GPRIN family member 3 GALC 23 -0.297 0.0899 -0.143 0.0366 galactosylceramidase ITGA4 24 -0.309 0.0441 0.231 0.0523 integrin, alpha 4 (antigen CD49D, alpha 4 subunit of VLA-4 receptor) Asterisk: genes involved in MAPK regulation and neuronal cell development or have brain-specific expression. Red and green values: evidence of increased expression and decreased expression, respectively, when CIC is inactivated.     Figure 2. Zinc finger nucleasemodel for hypomorphic CIC function.(a) Protein structure of long (CIChighly conserved between metazoan species nuclease. aa: amino acids. HMG: DNArepressive C-terminal motif. (bendogenous control, in parental (clones. Cells were treated with either CICconfirm antibody specificity. (cknown CIC target genes ETV1/4/5indicate standard deviations over 3 separate passages   41 -mediated mutation of endogenous CIC -L) and short (CIC-S) CIC isoforms. CIC domainsare shaded in gray. ZFN: zinc finger -binding high mobility group box domain. C1: ) Western blot detection of CIC, with actin as an cicWT) and ZFN-treated (cicZFN1 and cicZFN2-specific siRNA or nonspecific siRNA to ) Relative mRNA expression, measured by RT in HEK293a clones specified in (b). Error bars .   produces a  ) HEK293a -qPCR, of    Figure 3. All sequenced CIC frameshifting insertions. (a) Upper panel: exon structure ofconserved DNA-binding high mobility group (HMG) box domC1 motif (exon 20) are identified. panel. Lower panel: detected zinc finger nuclease (ZFN)alleles of cicZFN1 and cicZFN2 clones. indicated in (a) in the HEK293a clonesreads from a representative 100 mapped readsamino acid sequences from the observed alleles in (hybridization (FISH) detection of chromosome 19 locito determine CIC copy number. Out of 100 counted cells, 4 or 5 probestypically counted for 19q13, where 42 alleles of cicZFN1 and cicZFN2 cells harbour  CIC short isoform. Exons that encode the highly ain (exon 5) The red box indicates the zoomed-in region in lower -mediated insertions(b) Frequency of wild type and variant alleles. Bar labels indicate the number of observed . (c) Predicted CIC short isoform (CICb). (d) Fluorescence  in parental (cicWT) HEK293a clone per cell CIC is located.  and repressive  (Ins) in  -S) in situ  were   Figure 4. Microarray expression analysis candidate CIC-regulated genes.(a) Comparison of gene expression betweendata points indicate the 598 candidatedecreased expression, respectively, upon CIC inactivation. expression changes of the candidateCIC-wild type TCGA 1p/19q-codeleted gliomas24 consistently observed CIC-expression, respectively, uponHEK293a cells(c) Schematic foin HEK293a cells and in 1p/19qmutations is summarized in Figure 8b.  43 of cicWT and cicZFN2 cells identifies   cicZFN2 and cicWT cells. Red and gree CIC-regulated genes with increased and (b) Comparison of  CIC-regulated genes between CIC-. Red and green data points indicate the regulated genes with increased and decreased  CIC inactivation in 1p/19q-codeleted gliomar the identification of the candidate CIC-regulate-codeleted ADGs. The nature of the CIC-inactivating  n gene inactivated and s and d genes   44  a   b                                                                                                                                 Chromosome Figure 5. CIC inactivation possibly mediates chromosome-wide gene expression changes in HEK293a cells.  (a) Genomic location of candidate CIC-regulated genes in HEK293a cells (see Figure 4a). Green and red lines or rectangles: genes with decreased and increased expression, respectively, upon CIC inactivation. (b) Red and green bars: proportion of differentially expressed genes (given along left y-axis) with increased and decreased expression, respectively, relative to the total number of measured genes in each chromosome. Blue points: False discovery rate (FDR)-corrected p values (given along right y-axis) for the positive association between the number of differentially expressed genes and the number of measured genes within each chromosome. Dashed line: FDR threshold of 0.05.    Figure 6. RT-qPCR verifies gene expression changes detected from microarraysRelative mRNA expression (yCIC target genes in parental (clones. Error bars indicate standard deviations over 3 separate passages.**: p < 0.01, ***: p < 0.001 when compared to   45 -axes), measured using RT-qPCR, of indicated potentiacicWT) and ZFN-treated (cicZFN1 and cicZFN2) cicWT cells.  . l HEK293a  *: p < 0.05,   Figure 7. siRNA-mediated CIC knockdown (a) Representative Western blot expression of long (CICisoforms, with tubulin as an endogenous control, (CIC siRNA 1) or nonspecific siRNA (control siRNA). expression, measured using RTknown CIC-regulated genes (b) treated HeLa cells. Error bars: standard deviations between 3 < 0.05, **: p < 0.01. 46 validates genes as CIC-regulated.-L) and short (CICin HeLa cells treated with CIC(b) and (c) Relative mRNA -qPCR and normalized to control siRNA treatment, and novel CIC-regulated genes (c) in CIC biological replicates.    -S) CIC -specific of siRNA 1-*: p   Figure 8. CIC-regulated genes exhibit CIC mutation type(a) Frequency of 1p/19q-codeleted TCGA LGGs with CIC wild type predicted inactivating mutations (CIC inact) and CIC’s DNA-binding HMG domain (Observed CIC mutations in 39 Distributions of transcript abundanceaxes), of CIC-regulated genes in the horizontal lines above the x-axis labels correspond to comparisonsdifferent CIC mutation groups, with the line colours indicating statistical significance the differences between these groups.  47 -specific expressionstatus (CIC wt), single amino acid mutations targetingCIC HMG) and C1 motif (CIC C1) as shown in (CIC-mutated 1p/19q-codeleted TCGA gliomas, measured using RNA-seq and given in RSEMdifferent CIC mutation groups shown in ( made between th  .  b). (b) . (c)  (y-a). The e of   Figure 9.  Representative missense while a CIC truncation does not(a) Representative Western blotas an endogenous control, in tagged forms of CIC or flag vectorluciferase reporter vector used in all conditions of the luciferase assay. luciferase expression in the conditions indicated in (deviations over 3 biological replic     48 mutations preserve CIC’s repressive activity .   detection of ectopically introduced CIC, with DNAcicWT and cicZFN2 cells transfected with the indicated flag-only controls. (b) Diagram of relevant portion of (ca). Error bars indicate standard ates. *: p < 0.05, **: p < 0.01.   -PK -) Normalized  49  References 1. Cerami, E. et al. The cBio Cancer Genomics Portal: An Open Platform for Exploring Multidimensional Cancer Genomics Data. Cancer Discov. 2, 401–404 (2012). 2. Gao, J. et al. Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal. Sci. Signal. 6, pl1 (2013). 3. Yip, S. et al. 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Biol. 986, 143–70 (2013).      56  Appendix 1  Candidate CIC-regulated genes in HEK-293a cells with increased expression in cicZFN2 cells relative to cicWT cells. Gene Symbol Transcript Cluster ID Fold Change P value Adjusted P Value Chromosome GPR3 16661429 5.19 4.10E-05 0.042743 1 HIST2H2BC 16692624 2.19 0.001547 0.083881 1 S100A16 16693474 2.17 0.001212 0.081541 1 HIST2H2AA4, HIST2H2AA3 16692620 1.91 0.001727 0.088225 1 RN5S46 16663446 1.9 0.000789 0.070737 1 PLK3 16664005 1.81 0.000698 0.066595 1 TNFRSF9 16681288 1.46 0.001503 0.082641 1 LOC100132999 16669626 1.43 0.000458 0.063141 1 LOC646626 16666730 1.23 0.000657 0.06624 1 LOC646471 16683703 1.23 0.000816 0.071158 1 CDC14A 16667662 1.22 8.10E-05 0.044115 1 TPM3 16693722 1.16 0.000111 0.044115 1 ADIPOR1 16698122 1.07 0.000931 0.073565 1 FOXJ3 16685958 1.05 2.10E-05 0.033825 1 IAH1 16876907 2.08 7.90E-05 0.044115 2 NOSTRIN 16887194 1.56 0.001627 0.085229 2 LBH 16878676 1.42 0.00089 0.072746 2 TMBIM1 16908338 1.29 0.000684 0.066568 2 ETV5 16962380 7.04 0.000526 0.064093 3 TIMP4 16950825 1.55 0.000248 0.056937 3 PHLDB2, PLCXD2 16943819 1.49 0.001241 0.081882 3 PLXND1 16959007 1.26 0.001376 0.082201 3 DCBLD2 16956714 1.23 0.001139 0.079304 3 TBC1D5 16951357 1.18 0.00136 0.082201 3 SNX4 16958487 1.1 0.000796 0.070737 3 PVRL3 16943763 1.1 0.001062 0.077753 3 NME6 16953303 1.07 5.40E-05 0.042743 3 USP17, USP17L6P, USP17L2, LOC728419, LOC100287205, LOC100287441, LOC100287478, LOC100287178, LOC100287364, LOC100287404, LOC100287513, LOC100288520, LOC100287238, LOC100287327, LOC100287144, LOC649352, USP17L5, LOC728405, LOC728400, LOC728393, LOC728379, LOC728373, LOC728369 16965021 2.19 0.000472 0.063141 4 USP17, USP17L6P, USP17L2, LOC728419, LOC100287205, LOC100287441, LOC100287478, LOC100287178, LOC100287364, LOC100287404, LOC100287513, LOC100288520, LOC100287238, LOC100287327, LOC100287144, LOC649352, USP17L5, LOC728405, LOC728400, LOC728393, LOC728379, LOC728373, LOC728369 16965023 2.19 0.000472 0.063141 4 USP17, USP17L6P, USP17L2, LOC728419, LOC100287205, LOC100287441, LOC100287478, LOC100287178, LOC100287364, LOC100287404, LOC100287513, LOC100288520, LOC100287238, LOC100287327, LOC100287144, LOC649352, USP17L5, LOC728405, LOC728400, LOC728393, LOC728379, LOC728373, LOC728369 16965025 2.19 0.000472 0.063141 4 USP17, USP17L6P, USP17L2, LOC728419, LOC100287205, LOC100287441, LOC100287478, LOC100287178, LOC100287364, LOC100287404, LOC100287513, 16965029 2.19 0.000472 0.063141 4  57  Gene Symbol Transcript Cluster ID Fold Change P value Adjusted P Value Chromosome LOC100288520, LOC100287238, LOC100287327, LOC100287144, LOC649352, USP17L5, LOC728405, LOC728400, LOC728393, LOC728379, LOC728373, LOC728369 USP17, USP17L6P, USP17L2, LOC728419, LOC100287205, LOC100287441, LOC100287478, LOC100287178, LOC100287364, LOC100287404, LOC100287513, LOC100288520, LOC100287238, LOC100287327, LOC100287144, LOC649352, USP17L5, LOC728405, LOC728400, LOC728393, LOC728379, LOC728373, LOC728369 16965031 2.19 0.000472 0.063141 4 USP17, USP17L6P, USP17L2, LOC728419, LOC100287205, LOC100287441, LOC100287478, LOC100287178, LOC100287364, LOC100287404, LOC100287513, LOC100288520, LOC100287238, LOC100287327, LOC100287144, LOC649352, USP17L5, LOC728405, LOC728400, LOC728393, LOC728379, LOC728373, LOC728369 16965033 2.19 0.000472 0.063141 4 USP17, USP17L6P, USP17L2, LOC728419, LOC100287205, LOC100287441, LOC100287478, LOC100287178, LOC100287364, LOC100287404, LOC100287513, LOC100288520, LOC100287238, LOC100287327, LOC100287144, LOC649352, USP17L5, LOC728405, LOC728400, LOC728393, LOC728379, LOC728373, LOC728369 16965037 2.19 0.000472 0.063141 4 USP17, USP17L2, LOC100287404, LOC100287364, LOC100287178, LOC100287205, LOC100287478, LOC100287441, LOC100287513, LOC100288520, LOC728419, USP17L5, LOC728405, LOC728400, LOC728393, LOC728379, LOC728373, LOC728369 16965011 2.13 0.000911 0.073368 4 USP17, USP17L6P, USP17L2, LOC100287364, LOC100287178, LOC100287404, LOC100287441, LOC100287513, LOC100287205, LOC100287478, LOC100288520, LOC728419, LOC100287327, LOC100287144, USP17L5, LOC728405, LOC728400, LOC728393, LOC728379, LOC728373, LOC728369, LOC100287238 16965009 2.08 0.000688 0.066568 4 LOC100287205, LOC100287478, LOC100287441, LOC100287178, LOC100287404, LOC100287513, LOC100287364, LOC100288520 16965002 2.03 0.000864 0.072128 4 USP17, LOC100287205, LOC100287478, LOC100287441, LOC100287178, LOC100287404, LOC100287513, LOC100287364, LOC100288520, LOC728419, USP17L5, LOC728405, LOC728400, LOC728393, LOC728379, LOC728373, LOC728369 16965015 2.03 0.000864 0.072128 4 USP17, USP17L6P, USP17L2, LOC100287513, LOC100287178, LOC100287441, LOC100287205, LOC100287364, LOC100287478, LOC100288520, LOC100287404, LOC728419, LOC100287327, LOC100287238, LOC100287144, LOC649352, USP17L5, LOC728405, LOC728400, LOC728393, LOC728379, LOC728373, LOC728369 16965017 1.94 0.00039 0.062854 4 USP17, USP17L6P, USP17L2, LOC100287441, LOC100287178, LOC100287205, LOC100287478, LOC100287513, LOC100287364, LOC100288520, LOC100287404, LOC728419, LOC100287327, LOC100287238, LOC100287144, LOC649352, USP17L5, LOC728405, LOC728400, LOC728393, LOC728379, LOC728373, LOC728369 16965013 1.92 0.000435 0.063141 4 USP17, USP17L6P, USP17L2, LOC100287178, LOC100287364, LOC100287441, LOC100287513, LOC100287205, LOC100287404, LOC100287478, LOC100288520, LOC728419, LOC100287327, LOC100287238, LOC100287144, USP17L5, LOC728405, LOC728400, LOC728393, LOC728379, LOC728373, LOC728369 16965000 1.87 0.000324 0.061185 4 USP17L6P, LOC649352 16965039 1.83 0.000373 0.062854 4 USP17, USP17L6P, USP17L2, USP17L8, USP17L3, USP17L4, USP17L1P, USP17L7, LOC100287327, LOC100287238, LOC100287513, LOC100287478, LOC728419, LOC100287144, LOC649352, USP17L5, LOC728405, LOC728400, LOC728393, LOC728379, LOC728373, LOC728369 16965007 1.82 0.000548 0.064753 4 CTBP1-AS1 16963913 1.44 0.001528 0.083346 4 FLJ45340 16970094 1.33 0.001663 0.085756 4 SPRY4 17001063 7.58 6.30E-05 0.042743 5 ROPN1L 16983236 2.26 0.000137 0.046989 5 OSMR 16984244 1.55 0.001439 0.082201 5 PCDH1 17001005 1.53 0.00152 0.083075 5 TCF7 16989202 1.38 0.001463 0.082201 5 ARL10 16992796 1.27 0.001345 0.082201 5 FAM105B 16983388 1.26 0.001446 0.082201 5 DNAJC18 17000618 1.21 0.001494 0.082311 5 CXXC5 16989897 1.14 0.001349 0.082201 5 CYFIP2 16991527 1.11 0.001379 0.082201 5 C5orf65 17000605 1.09 0.001007 0.075338 5 MIR4458, LOC100505738 16983117 1.08 0.000315 0.061173 5 RN5S206 17017695 2.22 0.001287 0.082201 6 GPSM3 17017805 1.78 1.10E-05 0.023731 6  58  Gene Symbol Transcript Cluster ID Fold Change P value Adjusted P Value Chromosome NRN1 17015324 1.7 0.001448 0.082201 6 HIST1H2BC, HIST1H2BI, HIST1H2BE, HIST1H2BF, HIST1H2BG 17005582 1.63 0.000168 0.052357 6 BACH2 17021738 1.62 0.001386 0.082201 6 BVES 17022139 1.55 0.000231 0.056937 6 FUCA2 17024374 1.51 0.000436 0.063141 6 TRAF3IP2-AS1 17011735 1.46 5.00E-06 0.022818 6 TAP1 17017979 1.46 0.002053 0.093692 6 MAPK13 17007910 1.44 0.000139 0.046989 6 TEAD3 17018459 1.43 0.001326 0.082201 6 GMPR 17005094 1.38 1.30E-05 0.023731 6 NEU1 17017495 1.38 0.002049 0.093692 6 RRAGD 17021596 1.34 0.000493 0.063141 6 PHF1 17007475 1.34 0.00126 0.082201 6 PLAGL1 17024394 1.33 0.001511 0.082748 6 GPR126 17013126 1.31 0.000313 0.061173 6 MDC1 17016966 1.29 0.000197 0.055038 6 LEMD2 17018309 1.28 0.000429 0.063141 6 ZFAND3 17008196 1.28 0.000601 0.065859 6 MTO1 17010316 1.25 0.000293 0.058961 6 LOC100289495 17014622 1.25 0.001182 0.080511 6 SLC35D3 17012904 1.24 0.000806 0.070737 6 C6orf62 17016205 1.23 0.001176 0.080511 6 PPP1R10 17016888 1.23 0.001412 0.082201 6 GRM4 17018347 1.23 0.001814 0.090974 6 MRPS18B 17006324 1.22 0.001912 0.092499 6 ASCC3 17022035 1.22 0.001953 0.093309 6 TJAP1 17009008 1.21 0.00054 0.064753 6 ICK 17020118 1.21 0.001118 0.079104 6 RDBP, MIR1236 17017575 1.21 0.001539 0.083613 6 TAB2 17013567 1.2 0.00013 0.046585 6 PFDN6 17007446 1.2 0.000138 0.046989 6 DOPEY1 17010639 1.19 0.00077 0.070722 6 BAG6 17017244 1.17 0.001328 0.082201 6 TRMT11 17012350 1.16 0.000358 0.062438 6 PGM3 17021188 1.16 0.000715 0.067744 6 IGF2R 17014364 1.14 0.000763 0.070722 6 OGFRL1 17010175 1.14 0.001231 0.081748 6 HCG25 17007417 1.13 0.001458 0.082201 6 ETV1 17055354 3.4 0.000173 0.052357 7 PARP12 17063480 1.81 4.20E-05 0.042743 7  59  Gene Symbol Transcript Cluster ID Fold Change P value Adjusted P Value Chromosome ELFN1 17042925 1.77 0.000505 0.063141 7 ARHGEF35 17063996 1.71 0.001435 0.082201 7 LOC644794 17118262 1.59 0.000282 0.058913 7 KCNH2 17064299 1.39 0.001899 0.092499 7 SPDYE2, SPDYE2L, SPDYE5, SPDYE1, SPDYE6, LOC100509023 17049852 1.32 0.00089 0.072746 7 SPDYE2L, SPDYE2, SPDYE5, SPDYE1, SPDYE7P, SPDYE6, LOC100509023 17049869 1.31 0.000636 0.065859 7 C7orf57 17045904 1.27 0.000962 0.074411 7 PMS2P1 17060545 1.12 0.000364 0.062636 7 LOC729852 17043573 1.12 0.000459 0.063141 7 TECPR1 17060098 1.08 0.000896 0.072802 7 ZSCAN21 17049090 1.05 0.000915 0.073474 7 REXO1L2P, REXO1L1, LOC100288562 17070480 2.2 0.000106 0.044115 8 REXO1L2P 17078754 2.2 0.000106 0.044115 8 DUSP4 17075973 2 0.001631 0.085229 8 REXO1L2P, REXO1L1, LOC100288562 17070478 1.93 6.00E-05 0.042743 8 REXO1L2P 17078758 1.93 6.00E-05 0.042743 8 REXO1L2P 17078760 1.93 6.00E-05 0.042743 8 REXO1L2P 17078762 1.93 6.00E-05 0.042743 8 REXO1L2P 17078764 1.93 6.00E-05 0.042743 8 ESRP1 17070949 1.89 0.001099 0.078786 8 REXO1L2P 17078756 1.76 0.000402 0.062854 8 RHOBTB2 17066791 1.72 0.00175 0.089068 8 NIPAL2 17079448 1.5 0.000295 0.058961 8 EPPK1 17082362 1.39 0.00027 0.057502 8 XKR6 17074589 1.19 0.000835 0.071674 8 MAF1 17073577 1.13 2.90E-05 0.037813 8 SHC3 17095566 2.05 0.000666 0.066556 9 CNTFR 17093463 1.86 0.000104 0.044115 9 PTGER4P2 17085429 1.42 0.001397 0.082201 9 LHX2 17088916 1.3 0.00143 0.082201 9 KIAA2026 17092233 1.25 1.70E-05 0.029093 9 ANXA1 17085901 1.24 0.00115 0.079318 9 KIAA1161 17093417 1.19 0.000258 0.056937 9 KDM4C 17083492 1.16 0.001113 0.079104 9 DUSP5 16709128 2.23 0.001653 0.085401 10 AFAP1L2 16718592 1.45 0.001934 0.093214 10 BBIP1, LOC100130175 16718395 1.17 0.000294 0.058961 10 NDST2 16715642 1.17 0.000422 0.063141 10 WAC 16703520 1.17 0.001956 0.093309 10 CHST15 16719217 1.11 0.001233 0.081748 10  60  Gene Symbol Transcript Cluster ID Fold Change P value Adjusted P Value Chromosome FOSL1 16740630 3.12 0.001937 0.093214 11 MDK 16724346 1.85 0.00078 0.070722 11 CCKBR 16721355 1.49 0.000563 0.065003 11 PAMR1 16737344 1.43 0.000827 0.07121 11 INS-IGF2, IGF2, INS 16734371 1.37 0.001492 0.082311 11 BACE1 16744822 1.32 0.00089 0.072746 11 CHST1 16737614 1.3 0.001704 0.087376 11 CAPN5 16729336 1.29 0.001108 0.079008 11 TP53I11 16737543 1.22 0.001239 0.081882 11 SLC25A45 16740378 1.2 0.001623 0.085229 11 LRP4-AS1 16724432 1.18 0.00139 0.082201 11 GDPD5 16742244 1.16 0.00198 0.093692 11 DUSP6 16768297 2.93 0.000502 0.063141 12 LPAR5 16760516 2.15 0.000249 0.056937 12 RHEBL1 16764220 2.05 0.000144 0.048085 12 COX6A1 16757886 1.44 0.000489 0.063141 12 LOC100509976 16747257 1.42 0.000397 0.062854 12 CLEC1A 16761259 1.41 0.001991 0.093692 12 RN5S379 16772702 1.4 0.001118 0.079104 12 TAS2R31, TAS2R45 16761518 1.28 0.002047 0.093692 12 C12orf66 16767009 1.21 0.000943 0.073565 12 ANKRD13A 16756865 1.14 0.000816 0.071158 12 SPRY2 16780069 1.64 5.00E-05 0.042743 13 IRS2 16780917 1.47 0.000882 0.072744 13 LMO7 16775434 1.25 0.000242 0.056937 13 LINC00564 16780082 1.08 0.001872 0.092359 13 LRP10 16782207 1.3 0.000677 0.066568 14 CBLN3 16791393 1.2 0.001312 0.082201 14 RBPMS2 16810572 1.85 3.30E-05 0.038791 15 PTPN9 16811816 1.23 0.001568 0.084186 15 MMP2 16819064 2.27 0.000464 0.063141 16 SYT17 16816424 1.75 0.001473 0.082201 16 IL4R 16817254 1.49 0.000341 0.06215 16 LOC100505865 16819813 1.45 0.001532 0.083398 16 KIAA0895L 16827255 1.44 0.001639 0.085401 16 ATP6V0D1 16827366 1.22 0.000559 0.064974 16 MIR3180-4, MIR3180-5 16824191 1.08 0.001483 0.082201 16 SULT1A1 16825391 1.04 0.000114 0.044115 16 ETV4 16845410 16.23 0.000342 0.06215 17 CD68 16830577 2.07 0.000468 0.063141 17  61  Gene Symbol Transcript Cluster ID Fold Change P value Adjusted P Value Chromosome SLC43A2 16839425 1.73 0.001073 0.078141 17 MRC2 16836824 1.53 0.000957 0.074234 17 GPRC5C 16837571 1.5 0.000209 0.055562 17 FAM100B 16838049 1.47 5.00E-06 0.022818 17 NTN1 16831013 1.41 0.000504 0.063141 17 FMNL1 16834931 1.39 0.000498 0.063141 17 MFSD11 16838116 1.35 0.001993 0.093692 17 PGS1 16838392 1.34 0.000482 0.063141 17 ARSG 16837308 1.3 0.001399 0.082201 17 ARL17A, ARL17B, LOC100294341 16846006 1.27 1.30E-05 0.023731 17 TMEM132E 16833246 1.27 0.001247 0.081883 17 LOC100505873 17117728 1.26 0.00199 0.093692 17 ARL17A, ARL17B, LOC100294341 16845996 1.25 0.000323 0.061185 17 SLC16A13 16830295 1.25 0.00129 0.082201 17 G6PC3 16834700 1.25 0.001382 0.082201 17 KRT37 16844684 1.22 0.000821 0.07121 17 SHBG 16830607 1.19 0.000461 0.063141 17 UBE2Z 16835497 1.18 0.000431 0.063141 17 WBP2 16848938 1.18 0.00042 0.063141 17 NKIRAS2 16834252 1.15 0.000618 0.065859 17 HGS 16838855 1.15 0.001448 0.082201 17 PCGF2 16843987 1.07 0.00161 0.084995 17 HSBP1L1 16853325 1.54 0.001338 0.082201 18 KATNAL2 16852241 1.46 0.000503 0.063141 18 ZNF236 16853171 1.23 0.00093 0.073565 18 NFATC1 16853277 1.21 0.001952 0.093309 18 OR7C1 16869710 4.44 0.000634 0.065859 19 LOC386758 16865886 1.4 0.000967 0.074587 19 LOC100653348, LOC100506347 16866389 1.35 0.002016 0.093692 19 LOC284751 16914830 1.37 0.000995 0.075206 20 SNAI1 16914791 1.22 0.001833 0.091091 20 DNAJC5 16916146 1.1 0.001416 0.082201 20 HSF2BP 16926241 1.36 0.001128 0.079304 21 C21orf58 16926725 1.25 0.001292 0.082201 21 MCM3AP 16926679 1.09 0.001061 0.077753 21 LIF 16933760 1.48 0.000201 0.055038 22 SLC2A11 16928064 1.23 0.00095 0.0739 22 C22orf26 16936070 1.11 0.000379 0.062854 22 IL2RG 17111895 1.92 0.001224 0.081613 X GYG2 17101231 1.85 0.001371 0.082201 X  62  Gene Symbol Transcript Cluster ID Fold Change P value Adjusted P Value Chromosome L1CAM 17115271 1.77 0.001032 0.076522 X RN5S514 17114190 1.62 0.000857 0.072128 X CA5BP1 17101732 1.51 0.000608 0.065859 X MAP7D2 17109680 1.35 0.000779 0.070722 X CA5BP1 17101726 1.26 0.001378 0.082201 X TFE3 17110745 1.14 0.000218 0.05685 X TAB3 17109901 1.12 0.000594 0.065859 X TAP1 17027144 1.46 0.002053 0.093692 6_apd_hap1 NEU1 17026875 1.38 0.002049 0.093692 6_apd_hap1 MDC1 17026706 1.28 8.10E-05 0.044115 6_apd_hap1 TAP1 17029788 1.46 0.002053 0.093692 6_cox_hap2 MDC1 17028857 1.27 9.20E-05 0.044115 6_cox_hap2 PPP1R10 17028781 1.24 0.001363 0.082201 6_cox_hap2 MRPS18B 17027506 1.22 0.001912 0.092499 6_cox_hap2 PFDN6 17028495 1.18 0.000262 0.056937 6_cox_hap2 VPS52 17028466 1.13 0.001458 0.082201 6_cox_hap2 RNF5 17028297 1.1 0.000622 0.065859 6_cox_hap2 TAP1 17032476 1.46 0.002053 0.093692 6_dbb_hap3 NEU1 17032134 1.38 0.002049 0.093692 6_dbb_hap3 MDC1 17031635 1.28 8.10E-05 0.044115 6_dbb_hap3 PPP1R10 17031560 1.24 0.001363 0.082201 6_dbb_hap3 MRPS18B 17030351 1.22 0.001912 0.092499 6_dbb_hap3 PFDN6 17031309 1.18 0.000262 0.056937 6_dbb_hap3 VPS52 17031280 1.13 0.001458 0.082201 6_dbb_hap3 TAP1 17034791 1.46 0.002053 0.093692 6_mann_hap4 NEU1 17034509 1.38 0.002049 0.093692 6_mann_hap4 MDC1 17034090 1.27 0.000446 0.063141 6_mann_hap4 PPP1R10 17034014 1.23 0.001412 0.082201 6_mann_hap4 MRPS18B 17033056 1.22 0.001912 0.092499 6_mann_hap4 VPS52 17033765 1.13 0.001458 0.082201 6_mann_hap4 TAP1 17037271 1.46 0.002053 0.093692 6_mcf_hap5 NEU1 17036841 1.38 0.002049 0.093692 6_mcf_hap5 MDC1 17036357 1.27 9.20E-05 0.044115 6_mcf_hap5 PPP1R10 17036281 1.23 0.001412 0.082201 6_mcf_hap5 MRPS18B 17035176 1.22 0.001912 0.092499 6_mcf_hap5 PFDN6 17036058 1.18 0.000262 0.056937 6_mcf_hap5 BRD2 17035950 1.15 0.00191 0.092499 6_mcf_hap5 VPS52 17036029 1.13 0.001458 0.082201 6_mcf_hap5 TAP1 17039977 1.46 0.002053 0.093692 6_qbl_hap6 NEU1 17039585 1.38 0.002049 0.093692 6_qbl_hap6  63  Gene Symbol Transcript Cluster ID Fold Change P value Adjusted P Value Chromosome MDC1 17039133 1.27 0.000121 0.044176 6_qbl_hap6 PPP1R10 17039057 1.24 0.001363 0.082201 6_qbl_hap6 MRPS18B 17037835 1.22 0.001912 0.092499 6_qbl_hap6 PFDN6 17038779 1.18 0.000262 0.056937 6_qbl_hap6 VPS52 17038750 1.14 0.000736 0.069255 6_qbl_hap6 PHF1 17041368 1.35 0.000569 0.06519 6_ssto_hap7 MDC1 17041700 1.27 9.00E-05 0.044115 6_ssto_hap7 PPP1R10 17041641 1.24 0.001363 0.082201 6_ssto_hap7 MRPS18B 17040549 1.22 0.001912 0.092499 6_ssto_hap7 VPS52 17041336 1.13 0.001458 0.082201 6_ssto_hap7 ARL17B, ARL17A, LOC100294341 16850322 1.29 0.001817 0.090974 17_ctg5_hap1     64  Appendix 2  Candidate CIC-regulated genes in HEK-293a cells with decreased expression in cicZFN2 cells relative to cicWT cells. Gene Symbol Transcript Cluster ID Fold Change P value Adjusted P Value Chromosome PLA2G4A 16675197 -4.14 0.000417 0.063141 1 IFI16 16672390 -2.55 0.001142 0.079304 1 DDR2 16673075 -2.12 0.00023 0.056937 1 RYR2 16679142 -1.78 0.000387 0.062854 1 TDRD5 16674414 -1.54 0.001097 0.078786 1 TSPAN2 16691314 -1.44 0.000521 0.064093 1 OPN3 16701092 -1.39 0.001331 0.082201 1 RCC1, SNHG3, SNORA73A 16661589 -1.25 0.001143 0.079304 1 ORC1 16687188 -1.24 0.00085 0.072128 1 UAP1 16673056 -1.19 0.000328 0.061516 1 EFHD2 16659605 -1.19 0.001144 0.079304 1 UBE4B 16658758 -1.16 0.001651 0.085401 1 FH 16701077 -1.12 0.001341 0.082201 1 GNAI3 16668272 -1.06 0.000234 0.056937 1 FAM40A 16668464 -1.06 0.001395 0.082201 1 LOC440894 16884280 -8.04 1.00E-06 0.022818 2 IGFBP5 16908197 -3.84 0.001452 0.082201 2 LOC151009, LOC440894 16901683 -3.3 0.001648 0.085401 2 ITGA4 16888270 -2.49 9.70E-05 0.044115 2 ERBB4 16907863 -2.46 0.000161 0.051262 2 HOXD13 16887917 -2.33 0.000565 0.065003 2 SNAR-H 16899476 -2.2 0.000428 0.063141 2 DLX2 16905108 -2.06 0.000651 0.066021 2 IGFBP2 16890675 -1.74 0.000867 0.072159 2 GLS 16888865 -1.72 0.000493 0.063141 2 MAP2 16890207 -1.7 0.00056 0.064974 2 RPRM 16903863 -1.69 4.90E-05 0.042743 2 IFIH1 16904365 -1.59 8.90E-05 0.044115 2 B3GALT1 16887171 -1.56 8.10E-05 0.044115 2 GRB14 16904425 -1.55 0.000933 0.073565 2 MTX2 16887993 -1.48 0.000146 0.048166 2 ZAK 16887810 -1.48 0.001149 0.079318 2 ASNSD1 16888708 -1.48 0.001764 0.089614 2 NHEJ1, SLC23A3 16908557 -1.45 0.000295 0.058961 2 BCS1L 16890970 -1.45 0.001365 0.082201 2  65  Gene Symbol Transcript Cluster ID Fold Change P value Adjusted P Value Chromosome MGAT5 16885874 -1.44 0.000529 0.064093 2 HECW2 16906749 -1.43 0.001452 0.082201 2 EEF1B2, SNORA41 16889938 -1.42 0.00182 0.090974 2 RAB3GAP1 16885939 -1.41 0.000802 0.070737 2 GMPPA 16891349 -1.39 7.00E-05 0.044115 2 CREB1 16890067 -1.39 0.001823 0.090974 2 BARD1 16907960 -1.38 0.000547 0.064753 2 RAMP1 16892975 -1.38 0.000595 0.065859 2 CNPPD1 16908604 -1.38 0.000639 0.065859 2 HOXD11 16887927 -1.36 0.000907 0.073261 2 SGOL2 16889251 -1.35 0.000323 0.061185 2 HSPE1-MOB4, MOB4, HSPE1 16889126 -1.33 5.00E-04 0.063141 2 HOXD9 16887945 -1.33 0.000647 0.065859 2 ACVR1C 16903953 -1.33 0.000985 0.075206 2 MMADHC 16903461 -1.32 0.000113 0.044115 2 DNPEP 16908782 -1.29 0.000184 0.053053 2 HAT1 16887635 -1.29 0.000641 0.065859 2 NOP58 16889602 -1.29 0.000632 0.065859 2 CUL3 16909049 -1.29 0.000773 0.070722 2 RND3 16903491 -1.29 0.00113 0.079304 2 PELI1 16898326 -1.29 0.001944 0.093309 2 RQCD1 16890915 -1.28 0.001101 0.078786 2 PECR 16908154 -1.27 0.001332 0.082201 2 SPATS2L 16889218 -1.26 0.000775 0.070722 2 SF3B1 16906921 -1.24 0.000627 0.065859 2 NCL 16909491 -1.24 0.000635 0.065859 2 FBXO11 16897349 -1.23 0.001581 0.084224 2 HDLBP 16910375 -1.22 0.000749 0.070237 2 TWIST2 16893143 -1.2 0.000345 0.06215 2 MFF 16891723 -1.19 0.00122 0.081613 2 NIF3L1 16889375 -1.18 3.40E-05 0.038791 2 NDUFA10 16910081 -1.18 0.00121 0.081541 2 GCFC2 16899429 -1.15 0.000226 0.056937 2 ZFAND2B 16891152 -1.13 0.001828 0.091008 2 YEATS2 16948589 -1.35 0.00182 0.090974 3 SLC6A11 16937626 -1.32 0.000508 0.063228 3 RNF7 16946439 -1.32 0.001588 0.084432 3 XYLB 16939203 -1.28 0.000779 0.070722 3 THRB 16951567 -1.22 0.001397 0.082201 3 PDZRN3 16956285 -1.21 0.000388 0.062854 3  66  Gene Symbol Transcript Cluster ID Fold Change P value Adjusted P Value Chromosome DBR1 16959628 -1.19 0.0019 0.092499 3 SFRP2 16980762 -2.51 0.000491 0.063141 4 GPRIN3 16977970 -2.27 0.000936 0.073565 4 QRFPR 16979468 -1.85 0.000551 0.064753 4 VEGFC 16981730 -1.55 0.000251 0.056937 4 GUCY1B3 16971737 -1.38 0.001558 0.084086 4 SCD5 16977396 -1.21 0.000995 0.075206 4 PITX2 16979024 -1.18 0.001837 0.091125 4 LOC100507053 16969157 -1.06 0.001592 0.084481 4 ISL1 16984612 -2.36 6.40E-05 0.042743 5 LOX 16999180 -1.59 0.000111 0.044115 5 FABP6 16991729 -1.51 0.000284 0.058913 5 NR2F1, NR2F2 16987287 -1.26 0.001644 0.085401 5 SLC35F1 17012087 -2.02 0.000524 0.064093 6 C6orf132 17019190 -1.48 0.001458 0.082201 6 HIST1H2AE, HIST1H2AB 17005589 -1.34 0.000489 0.063141 6 LRRC16A 17005420 -1.13 0.000826 0.07121 6 CADPS2 17062321 -3.02 0.001783 0.090244 7 MYC 17072669 -2.78 0.000204 0.055306 8 NDRG1 17081401 -1.71 0.000626 0.065859 8 THEM6 17073234 -1.41 0.000872 0.072355 8 TUBBP5 17091877 -1.85 7.50E-05 0.044115 9 SYK 17086708 -1.34 0.000697 0.066595 9 MRPL50 17096631 -1.34 0.001102 0.078786 9 NCBP1 17087343 -1.32 0.000116 0.044115 9 ANKS6 17096516 -1.32 0.002019 0.093692 9 AUH 17095686 -1.31 7.10E-05 0.044115 9 MGC21881 17085432 -1.26 0.000937 0.073565 9 SEC61B 17087498 -1.24 0.000527 0.064093 9 LOC554249, MGC21881 17085187 -1.24 0.000854 0.072128 9 ZCCHC6 17095461 -1.22 0.000454 0.063141 9 SUSD3 17086845 -1.17 0.000312 0.061173 9 LRSAM1 17089324 -1.13 0.000399 0.062854 9 NACC2 17099816 -1.09 0.001034 0.076522 9 PLXDC2 16703036 -12.14 6.00E-06 0.02347 10 INA 16708796 -1.93 0.001956 0.093309 10 LOC84856 16704107 -1.18 0.001803 0.090971 10 SFMBT2 16711562 -1.13 0.001272 0.082201 10 ELP4 16723228 -1.45 0.000798 0.070737 11 OR4D11 16725097 -1.38 0.001962 0.093317 11  67  Gene Symbol Transcript Cluster ID Fold Change P value Adjusted P Value Chromosome TMEM216 16725608 -1.36 0.000363 0.062636 11 RAB38 16743104 -1.36 0.000805 0.070737 11 CTSC 16743111 -1.3 4.50E-05 0.042743 11 UNC93B1 16741173 -1.24 0.000937 0.073565 11 NDUFC2-KCTD14, KCTD14, NDUFC2 16742594 -1.2 0.001015 0.07573 11 PRSS23 16729789 -1.2 0.001225 0.081613 11 DRAP1 16727168 -1.16 1.30E-05 0.023731 11 OTUB1 16726188 -1.04 0.000786 0.070737 11 PLBD1 16761726 -4.09 8.50E-05 0.044115 12 MGST1 16748788 -3.58 6.00E-04 0.065859 12 LGR5 16754134 -3.09 1.10E-05 0.023731 12 LOC400027 16763479 -1.55 0.000557 0.064974 12 LOC100130776 16753158 -1.43 0.001432 0.082201 12 LOC727803 17117588 -1.34 5.80E-05 0.042743 12 PKP2 16763032 -1.17 0.000208 0.055562 12 LRIG3 16766822 -1.17 0.001288 0.082201 12 PTMS 16747394 -1.13 0.000679 0.066568 12 AEBP2 16748939 -1.08 0.001577 0.084224 12 LPCAT3 16760668 -1.04 0.000691 0.066595 12 MLEC 16757969 -1.02 0.00118 0.080511 12 PCDH9 16779667 -2.26 0.000806 0.070737 13 GPC5 16775785 -1.49 0.000402 0.062854 13 DACH1 16779701 -1.32 0.000647 0.065859 13 SPATA13-AS1 16777448 -1.07 0.000188 0.05307 13 GALC 16795508 -2.22 0.001772 0.089854 14 MLH3 16794864 -2.12 0.000845 0.072128 14 SIX1 16793613 -1.27 0.000937 0.073565 14 ALPK3 16804251 -1.82 0.000771 0.070722 15 SORD 16800506 -1.66 0.000153 0.049288 15 CKMT1B, CKMT1A 16800242 -1.58 0.000646 0.065859 15 LPCAT4 16806920 -1.54 0.00076 0.070722 15 OIP5 16807605 -1.27 0.001804 0.090971 15 TM2D3 16813974 -1.24 0.000458 0.063141 15 TYRO3 16799852 -1.24 0.000718 0.067794 15 C15orf41 16799170 -1.16 0.001193 0.081059 15 WDR76 16800355 -1.15 0.001304 0.082201 15 ACSM3 16816604 -1.58 0.00156 0.084086 16 TRAP1 16823413 -1.44 9.00E-06 0.023731 16 TFAP4 16823512 -1.4 0.000574 0.06533 16 PLCG2 16821330 -1.33 0.000238 0.056937 16  68  Gene Symbol Transcript Cluster ID Fold Change P value Adjusted P Value Chromosome TOX3 16826510 -1.29 8.50E-05 0.044115 16 MSRB1 16822868 -1.29 0.000859 0.072128 16 DNAJA3 16815513 -1.29 0.001624 0.085229 16 HMOX2 16815528 -1.28 2.60E-05 0.03747 16 THOC6 16815316 -1.27 0.000863 0.072128 16 PAQR4 16815289 -1.25 3.00E-06 0.022818 16 TBL3 16814872 -1.25 0.000487 0.063141 16 CPPED1 16824046 -1.22 0.000266 0.057351 16 NDUFB10 16814854 -1.2 0.000183 0.053053 16 C16orf13 16822466 -1.12 0.000695 0.066595 16 HAGHL 16814510 -1.09 0.001568 0.084186 16 GEMIN4 16839254 -1.26 0.000979 0.075206 17 GDPD1 16836511 -1.23 0.001484 0.082201 17 DSEL 16855781 -2.46 0.001346 0.082201 18 ZNF544 16866232 -4.23 0.001602 0.084847 19 ZNF257 16860221 -2.17 0.000119 0.044176 19 SYT3 16874591 -2.02 7.60E-05 0.044115 19 SNAR-C1, SNAR-C2, SNAR-C5, SNAR-C3, SNAR-C4 16863705 -1.94 0.000356 0.062438 19 SNAR-C1, SNAR-C2, SNAR-C5, SNAR-C3, SNAR-C4 16863711 -1.94 0.000356 0.062438 19 SNAR-C1, SNAR-C2, SNAR-C5, SNAR-C3, SNAR-C4 16863721 -1.94 0.000356 0.062438 19 SNAR-C1, SNAR-C2, SNAR-C3, SNAR-C4, SNAR-C5, SNAR-B1, SNAR-B2 16863715 -1.89 0.000391 0.062854 19 SNAR-C1, SNAR-C2, SNAR-C3, SNAR-C4, SNAR-C5, SNAR-B1, SNAR-B2 16863719 -1.89 0.000391 0.062854 19 SNAR-E 16873645 -1.89 0.000436 0.063141 19 SNAR-B1, SNAR-B2, SNAR-C1, SNAR-C2, SNAR-C3, SNAR-C4, SNAR-C5 16874508 -1.82 0.000404 0.062854 19 SNAR-B1, SNAR-B2, SNAR-C1, SNAR-C2, SNAR-C3, SNAR-C4, SNAR-C5 16874510 -1.82 0.000404 0.062854 19 JUND 16870384 -1.69 0.000262 0.056937 19 ZNF260 16871680 -1.64 0.001718 0.087929 19 QTRT1 16858263 -1.61 4.00E-06 0.022818 19 BCAT2 16874082 -1.58 0.002001 0.093692 19 ZNF529 16871688 -1.56 0.000575 0.06533 19 LONP1 16867511 -1.49 0.000366 0.062636 19 GNG7 16866974 -1.46 0.000136 0.046989 19 GCDH 16858756 -1.45 0.000683 0.066568 19 MRI1 16858849 -1.41 0.001257 0.082201 19 MEGF8 16862721 -1.4 6.30E-05 0.042743 19 LOC100506469 16871411 -1.4 0.000611 0.065859 19 PKN1 16858991 -1.4 0.001002 0.075338 19 LOC728485 16861454 -1.4 0.001326 0.082201 19 ZNF562 16868443 -1.4 0.001867 0.092278 19 ECSIT 16869006 -1.39 0.000112 0.044115 19  69  Gene Symbol Transcript Cluster ID Fold Change P value Adjusted P Value Chromosome UHRF1 16857258 -1.39 0.001554 0.084086 19 BCL2L12 16864234 -1.38 0.000248 0.056937 19 PLEKHJ1 16866912 -1.38 0.000543 0.064753 19 NOSIP 16874327 -1.38 0.00059 0.065859 19 CARM1 16858321 -1.38 0.001084 0.078669 19 CIC 16862677 -1.37 2.50E-05 0.03747 19 NDUFA11, FUT5 16867583 -1.37 0.000604 0.065859 19 MARCH2 16857905 -1.36 0.001144 0.079304 19 NRTN 16857389 -1.36 0.001675 0.086212 19 RUVBL2 16863946 -1.35 2.80E-05 0.037813 19 KANK2 16868847 -1.35 0.000273 0.057502 19 ERCC1 16873313 -1.35 0.000941 0.073565 19 QPCTL 16863344 -1.35 0.001207 0.081541 19 PNPLA6 16857630 -1.35 0.001322 0.082201 19 LSM14A 16860678 -1.35 0.001353 0.082201 19 LSM4 16870387 -1.34 0.001434 0.082201 19 USE1 16859437 -1.33 0.000239 0.056937 19 MED25 16864331 -1.33 0.001469 0.082201 19 PEPD 16871239 -1.33 0.001611 0.084995 19 ERF 16872760 -1.33 0.00185 0.091603 19 SMARCA4 16858344 -1.32 0.000152 0.049288 19 AP2A1 16864304 -1.32 0.00017 0.052357 19 FSD1 16857163 -1.32 0.00049 0.063141 19 NR1H2 16864472 -1.32 0.001461 0.082201 19 NR2C2AP 16870581 -1.31 0.000287 0.058961 19 FBL 16872267 -1.31 0.000384 0.062854 19 CDC37 16868732 -1.3 0.001444 0.082201 19 ZNF296 16873221 -1.3 0.001466 0.082201 19 DDX39A 16869624 -1.29 0.000997 0.075206 19 EIF3K 16861841 -1.28 0.000444 0.063141 19 PRMT1 16864244 -1.28 0.000534 0.064414 19 SERTAD3 16872447 -1.27 0.000271 0.057502 19 TBC1D17, MIR4750 16864373 -1.27 0.000591 0.065859 19 TIMM13 16866946 -1.27 0.000612 0.065859 19 PIK3R2 16859740 -1.27 0.001408 0.082201 19 DNMT1 16868576 -1.26 0.000511 0.063313 19 HOOK2 16869299 -1.25 0.000115 0.044115 19 NUMBL, LOC100130713 16872460 -1.25 9.50E-05 0.044115 19 ILVBL 16869740 -1.24 0.00094 0.073565 19 ZNF317 16857950 -1.23 1.20E-05 0.023731 19  70  Gene Symbol Transcript Cluster ID Fold Change P value Adjusted P Value Chromosome DAZAP1 16856567 -1.23 0.000377 0.062854 19 MRPL34 16859481 -1.23 0.000824 0.07121 19 ARHGEF18 16857567 -1.23 0.001072 0.078141 19 URI1 16860430 -1.22 7.00E-06 0.023731 19 NAPA 16873751 -1.22 0.000185 0.053053 19 ZNF180 16873183 -1.22 0.000401 0.062854 19 USF2 16860959 -1.21 0.000314 0.061173 19 SUPT5H 16862033 -1.2 0.001741 0.088775 19 NUDT19 16860545 -1.19 5.00E-06 0.022818 19 ZNF791 16858654 -1.19 0.000344 0.06215 19 MBD3 16866709 -1.18 0.000338 0.06215 19 ATG4D 16858195 -1.18 0.000686 0.066568 19 MED16 16866514 -1.18 0.000796 0.070737 19 MAU2 16859990 -1.18 0.001202 0.081468 19 R3HDM4 16866539 -1.18 0.001459 0.082201 19 ZNF57 16856848 -1.16 0.000644 0.065859 19 INSR 16867915 -1.16 0.001086 0.078669 19 XAB2 16867948 -1.15 0.000658 0.06624 19 ILF3 16858235 -1.15 0.001404 0.082201 19 TBXA2R 16867088 -1.14 0.000457 0.063141 19 CLPTM1 16863148 -1.13 0.000101 0.044115 19 KXD1 16859817 -1.13 0.000993 0.075206 19 PPP2R1A 16864778 -1.09 0.001645 0.085401 19 SNORD17 16917529 -2.1 0.000186 0.053053 20 LINC00493 16911780 -2.06 0.000779 0.070722 20 RBBP9 16917602 -1.98 0.000121 0.044176 20 NANP 16918132 -1.86 0.000351 0.062438 20 C20orf3 16918011 -1.86 0.001141 0.079304 20 SNX5 16917504 -1.78 0.000471 0.063141 20 ADA 16919466 -1.76 0.001246 0.081883 20 EYA2 16914478 -1.74 0.000258 0.056937 20 DSTN 16911651 -1.71 0.001511 0.082748 20 PLK1S1 16911923 -1.62 0.001577 0.084224 20 RALGAPA2 16917689 -1.61 5.50E-05 0.042743 20 BTBD3 16911463 -1.61 0.000183 0.053053 20 NAA20 16911853 -1.6 0.001937 0.093214 20 DTD1 16911783 -1.57 0.000551 0.064753 20 CRNKL1 16917655 -1.57 0.001026 0.076342 20 SOX12 16910597 -1.57 0.001092 0.078786 20 ENTPD6 16912140 -1.53 0.000228 0.056937 20  71  Gene Symbol Transcript Cluster ID Fold Change P value Adjusted P Value Chromosome SEC23B 16911754 -1.51 0.000318 0.061185 20 NCOA5 16919769 -1.41 0.000875 0.072384 20 CTNNBL1 16913456 -1.41 0.002051 0.093692 20 SNRPB2 16911605 -1.39 0.000663 0.066499 20 DNMT3B 16912597 -1.39 0.001472 0.082201 20 NFS1 16918832 -1.37 3.30E-05 0.038791 20 ABHD12 16918077 -1.37 0.000987 0.075206 20 FAM83D 16913681 -1.36 0.000173 0.052357 20 DHX35 16913689 -1.33 0.001482 0.082201 20 GINS1 16912192 -1.31 0.000131 0.046585 20 POFUT1 16912520 -1.29 0.000212 0.055817 20 ITCH 16912905 -1.28 0.000582 0.065853 20 TRPC4AP 16918609 -1.27 0.001343 0.082201 20 JAG1 16917183 -1.26 0.000894 0.072802 20 DBNDD2, SYS1-DBNDD2, SYS1 16914213 -1.26 0.000983 0.075206 20 SLC35C2 16919804 -1.25 0.001692 0.086924 20 TOX2 16913985 -1.24 0.000854 0.072128 20 SPTLC3 16911493 -1.23 0.001181 0.080511 20 FOXA2 16917822 -1.21 4.40E-05 0.042743 20 TM9SF4 16912492 -1.2 0.000112 0.044115 20 DDRGK1 16916667 -1.19 0.000795 0.070737 20 CDS2 16911151 -1.16 0.001631 0.085229 20 SOGA1 16918996 -1.15 0.00117 0.080495 20 CEP250 16913095 -1.13 0.001824 0.090974 20 C20orf4 16913305 -1.09 0.000607 0.065859 20 BMP7 16920585 -1.08 8.60E-05 0.044115 20 CECR5 16931942 -1.32 0.000337 0.06215 22 SELO 16931662 -1.32 0.001047 0.077141 22 LARGE 16934308 -1.25 0.001006 0.075338 22 MCAT 16935767 -1.22 0.001048 0.077141 22 RANBP1 16927198 -1.21 0.000499 0.063141 22 SHANK3 16931815 -1.21 0.000416 0.063141 22 ZC3H7B 16930598 -1.21 0.000907 0.073261 22 SMARCB1 16928046 -1.21 0.001581 0.084224 22 BCR 16927907 -1.19 0.000103 0.044115 22 ALG12 16936255 -1.14 0.001432 0.082201 22 BCL2L13 16926893 -1.12 0.001363 0.082201 22 JOSD1 16935130 -1.09 0.000711 0.067599 22 DRG1 16929203 -1.08 0.001477 0.082201 22 LOC100130899 16930381 -1.08 0.001486 0.082201 22  72  Gene Symbol Transcript Cluster ID Fold Change P value Adjusted P Value Chromosome GABRA3 17115014 -2.63 0.000246 0.056937 X F8A1, F8A3, F8A2 17108528 -2.45 0.00137 0.082201 X GABRQ 17107855 -2.34 0.000201 0.055038 X CAPN6 17113362 -2.33 0.001963 0.093317 X RPS6KA6 17112439 -1.7 0.00122 0.081613 X SRPX 17110071 -1.48 0.0019 0.092499 X NUDT11 17111008 -1.37 0.000174 0.052357 X MIR1184-1, MIR1184-2, MIR1184-3 17108585 -1.35 0.000684 0.066568 X MIR1184-1, MIR1184-2, MIR1184-3 17115763 -1.35 0.000684 0.066568 X MIR1184-1, MIR1184-2, MIR1184-3 17115796 -1.35 0.000684 0.066568 X LOC286467 17114177 -1.26 0.000235 0.056937 X HLA-DPB1 17026444 -1.06 0.000644 0.065859 6_apd_hap1 HLA-DPB1 17035971 -1.06 0.000644 0.065859 6_mcf_hap5   

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