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Schimke immuno-osseous dysplasia : association of SMARCAL1 mutations with genetic and environmental disturbances… Baradaran-Heravi, Alireza 2013

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SCHIMKE IMMUNO-OSSEOUS DYSPLASIA: ASSOCIATION OF SMARCAL1 MUTATIONS WITH GENETIC AND ENVIRONMENTAL DISTURBANCES OF GENE EXPRESSION  by  Alireza Baradaran-Heravi M.D., MASHHAD UNIVERSITY OF MEDICAL SCIENCES, 2004 	
   A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF  DOCTOR OF PHILOSOPHY in The Faculty of Graduate Studies (Medical Genetics)  THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) May 2013  © Alireza Baradaran-Heravi, 2013  Abstract Schimke immuno-osseous dysplasia (SIOD, MIM 242900) is an incompletely penetrant autosomal recessive multisystem disorder characterized by dysmorphic facies, short stature, renal failure, and T-cell immunodeficiency. Biallelic loss-of-function mutations in SMARCAL1 (SWI/SNF-related matrix-associated actin-dependent regulator of chromatin, subfamily a-like 1), which encodes a DNA stress response enzyme with annealing helicase activity, are associated with SIOD. My studies focused on further delineation of the molecular basis of SIOD by assessing the contribution of defective DNA repair to the pathophysiology of SIOD and a mechanism by which SMARCAL1 can modulate trait penetrance. Through collaborative analyses of the clinical data and molecular studies of SIOD patients, my coworkers and I observed that SIOD patients have a high frequency of nonHodgkin lymphoma and showed that despite similarities among SIOD and other DNA repair diseases, SMARCAL1-deficient cells do not have increased baseline DNA breaks detectable by comet assay. Additionally, SIOD patients do not have a detectable defect of nucleotide excision repair (NER), homologous recombination (HR) or nonhomologous end joining (NHEJ) to explain their ectodermal or immunological features, although Smarcal1del/del mice are hypersensitive to several DNA damaging agents. Furthermore, my colleagues and I found that SMARCAL1 orthologues localize to transcriptionally active chromatin and modulate gene expression, that deficiency of the SMARCAL1 orthologues alone is insufficient to cause disease in fruit flies and mice, that SMARCAL1 deficiency causes modest diffuse alterations in gene expression, and that SMARCAL1 deficiency causes disease via interaction with genetic and environmental factors that further alter gene expression. ii  In summary, our findings provide guidance for clinical management of SIOD and suggest that alterations in the variance of gene expression levels contribute to the penetrance of SIOD.  iii  Preface Collaborators: Anja Raams, Dr. Nicolaas G. J. Jaspers Department of Genetics, Erasmus Medical Center, Rotterdam, The Netherlands Contribution: Analysis of cell survival assays in SIOD cells following UV or illudin S exposures.  Dr. Kyoung Sang Cho Department of Biological Sciences, Konkuk University, Seoul, Republic of Korea Contribution: Drosophila genetic studies and experiments.  Dr. Bas Tolhuis, Dr. Maarten van Lohuizen Division of Molecular Genetics and the Centre for Biomedical Genetics, The Netherlands Cancer Institute, Amsterdam, The Netherlands Contribution: DNA adenine methyltransferase analysis of Marcal1 binding.  Dr. Mrinmoy Sanyal, Dr. David B. Lewis, Kira Y. Dionis Department of Pediatrics and Institute for Immunology, Transplantation, and Infectious Disease, Stanford University School of Medicine, Stanford, CA, USA Contribution: Immunological studies in Smarcal1-deficient mice.  Dr. Olena Morozova, Dr. Marco A. Marra  iv  Michael Smith Genome Sciences Centre, British Columbia Cancer Agency and University of British Columbia, Vancouver, British Columbia, Canada Contribution: Data analysis of mouse RNA sequencing.  Dr. Darren Bridgewater Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Ontario, Canada Contribution: Urinary protein analysis in Smarcal1-deficient mice.  Dr. Thomas Lücke Department of Neuropediatrics, University Children's Hospital, Ruhr University Bochum, Bochum, Germany Contribution: Clinical analysis of SIOD patients.  Dr. Arend Bokenkamp Department of Pediatrics, VU University Medical Center, Amsterdam, The Netherlands Contribution: Clinical analysis of SIOD patients.  Dr. Chad Shaw Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA Contribution: Data analysis of mouse RNA sequencing and of human cell and Drosophila microarray gene expression data. v  Marie Morimoto, Dr. Leah I. Elizondo, Dr. Joanna Lubieniecka Department of Medical Genetics, Child and Family Research Institute, University of British Columbia, Vancouver, British Columbia, Canada Contribution: Marie Morimoto, Drosophila genetic studies and experiments; Leah Elizondo, analysis of ATPase activity of SMARCAL1; Joanna Lubieniecka, heat stress experiment in Drosophila.  Portions of chapter 1 have been published in: - Baradaran-Heravi A, Elizondo LI, Boerkoel CF: Gene clusters, molecular evolution and disease: a speculation. In Advances in Genome Science: Changing Views on Living Organisms (Volume 1). Bentham Science (ebook) 2013: 101-145. and - Baradaran-Heravi A, Morimoto M, Lücke T, Boerkoel CF: Schimke Immunoosseous Dysplasia (March 2011) in: GeneReviews at GeneTests: Medical Genetics Information Resource [database online]. Copyright, University of Washington, Seattle, 1997-2013. Available at http://www.genetests.org. I updated these two reviews under the guidance of Dr. Cornelius Boerkoel.  Portions of chapter 2 have been published in: - Baradaran-Heravi A, Raams A, Lubieniecka J, Cho KS, Dehaai KA, Basiratnia M, Mari PO, Xue Y, Rauth M, Olney AH, et al: SMARCAL1 deficiency predisposes to non-Hodgkin lymphoma and hypersensitivity to genotoxic agents in vivo. American Journal of Medical Genetics Part A 2012, 158A:2204-2213.  vi  I conducted the majority of the experiments and wrote most of the manuscript. These experiments included the comet assay, analysis of immunoglobulin switch junctions, treatment of mice with genotoxic agents, urinary protein analysis in mice, cell culture, and histopathology. Analysis of sister chromatid exchange was performed by Mary Shago (Hospital for Sick Children). Culturing of normal human fibroblasts and Cockayne syndrome B fibroblasts as well as cell survival assays following UV or illudin S were performed by Anja Raams (Jaspers Lab, Erasmus Medical Center, the Netherlands).  Portions of chapter 3 and 4 have been published in: - Baradaran-Heravi A, Cho KS, Tolhuis B, Sanyal M, Morozova O, Morimoto M, Elizondo LI, Bridgewater D, Lubieniecka J, Beirnes K, et al: Penetrance of biallelic SMARCAL1 mutations is associated with environmental and genetic disturbances of gene expression. Human Molecular Genetics 2012, 21:2572-2587. I conducted most of the experiments on human cells and mice and wrote most of the manuscript. These experiments include ATPase activity of Smarcal1, cell culture, heat stress of human fibroblasts and mice, α-amanitin treatment of human fibroblasts and mice, phenotypic and histopathological analyses of mice, RpII knock-down analysis, and gene ontology analysis. Most of the Drosophila genetic studies and experiments were performed by Kyoung Sang Cho and Marie Morimoto. Heat stress experiments in Drosophila were performed by Kyoung Sang Cho, Joanna Lubieniecka, and Marie Morimoto. DNA adenine methyltransferase analysis of Marcal1 binding was performed by Bas Tolhuis (the Netherlands Cancer Institute). Analyses of ATPase activity of Marcal1 and SMARCAL1 were performed by Kyoung Sang Cho and Leah Elizondo. High-dimensional flow cytometry  vii  on mouse lymphocytes was performed by Mrinmoy Sanyal (Lewis Lab, Stanford University). Urinary protein analysis in mice was performed by Darren Bridgewater (McMaster University). Data analysis of RNA sequencing, microarray gene expression of human cells and Drosophila was performed by Chad Shaw (Baylor College of Medicine).  Patients referred to this study gave informed consent approved by the Institutional Review Board of Baylor College of Medicine (H-9669, Houston, TX, USA), the Hospital for Sick Children (REB-0019970093, Toronto, ON, Canada), or the University of British Columbia (H06-70283, Vancouver, BC, Canada). Also, the institutional review board of Stanford University School of Medicine (IRB-419, Stanford, CA, USA) approved the use of human tissue. The clinical data for patients were obtained from questionnaires completed by the attending physician as well as from the medical records.  Mice used in this study were housed, bred, and euthanized in accordance with accepted ethical guidelines. These procedures were approved by the Institutional Review Board of Baylor College of Medicine (Houston, TX, USA, IRB protocol: AN-2983) or the University of British Columbia (Vancouver, BC, Canada, Animal Care Certificate: A100296).  viii  Table of Contents  Abstract.................................................................................................................................... ii	
   Preface ..................................................................................................................................... iv	
   Table of Contents ................................................................................................................... ix	
   List of Tables ........................................................................................................................ xvi	
   List of Figures...................................................................................................................... xvii	
   List of Abbreviations ............................................................................................................ xx	
   Acknowledgements ........................................................................................................... xxvii	
   Dedication ......................................................................................................................... xxviii	
   1.	
   Introduction ...................................................................................................................... 1	
   1.1	
   Higher order regulation of gene expression ................................................................. 2	
   1.1.1	
   Three-dimensional nuclear organization and regulation of gene expression........ 3	
   1.1.1.1	
   Chromosomal spatial orientation ................................................................... 4	
   1.1.1.2	
   Nuclear envelope ........................................................................................... 5	
   1.1.1.3	
   Boundary elements......................................................................................... 6	
   1.1.2	
   DNA methylation .................................................................................................. 8	
   1.1.3	
   Histone modifications ........................................................................................... 9	
   1.1.4	
   Chromatin remodeling ........................................................................................ 11	
   1.2	
   SMARCAL1 .............................................................................................................. 12	
   1.3	
   Schimke immuno-osseous dysplasia (SIOD)............................................................. 14	
   1.3.1	
   Characteristics and clinical features.................................................................... 15	
   1.3.2	
   Clinical course and outcome ............................................................................... 21	
   ix  1.3.3	
   Management and treatment of manifestations .................................................... 22	
   1.4	
   Thesis objectives and significance ............................................................................. 25	
   2.	
   Contribution of DNA repair defects to pathophysiology of SIOD ............................ 26	
   2.1	
   Introduction ................................................................................................................ 26	
   2.2	
   Materials and methods ............................................................................................... 27	
   2.2.1	
   Comet assay ........................................................................................................ 27	
   2.2.2	
   Analysis of sister chromatid exchange ............................................................... 27	
   2.2.3	
   Immunoglobulin switch junction amplification and sequencing ........................ 28	
   2.2.4	
   Smarcal1del/del mice and treatment with CPT-11, etoposide, and HU................. 29	
   2.2.5	
   Urinary creatinine and albumin assays ............................................................... 30	
   2.2.6	
   Histopathology and TUNEL assay ..................................................................... 30	
   2.2.7	
   Cell culture .......................................................................................................... 31	
   2.2.8	
   Cell survival assays ............................................................................................. 31	
   2.3	
   Results ........................................................................................................................ 32	
   2.3.1	
   SIOD patients have features observed in other disorders of DNA repair ........... 32	
   2.3.2	
   SIOD patient dermal fibroblasts and Smarcal1-deficient mouse embryonic fibroblasts do not have increased DNA breaks detectable by comet assay .................... 34	
   2.3.3	
   SMARCAL1 and DNA nucleotide excision repair .............................................. 35	
   2.3.4	
   SMARCAL1 and DNA repair by homologous recombination ............................ 36	
   2.3.5	
   SMARCAL1 and DNA repair by non-homologous end joining .......................... 36	
   2.3.6	
   Smarcal1-deficient mice are hypersensitive to genotoxic agents ....................... 40	
   2.3.7	
   Irinotecan, etoposide, and hydroxyurea exposure partially recapitulate the bone phenotype of SIOD in Smarcal1-deficient mice ............................................................. 44	
    x  2.3.8	
   Irinotecan, etoposide, and hydroxyurea exposure do not recapitulate the renal phenotype of SIOD in Smarcal1-deficient mice ............................................................. 46	
   2.4	
   Discussion .................................................................................................................. 47	
   3.	
   Contribution of gene expression alterations to the penetrance of SMARCAL1 mutations ............................................................................................................................... 51	
   3.1	
   Introduction ................................................................................................................ 51	
   3.2	
   Materials and methods ............................................................................................... 53	
   3.2.1	
   Drosophila genetic studies.................................................................................. 53	
   3.2.2	
   ATPase activity assay ......................................................................................... 54	
   3.2.3	
   Immunofluorescence ........................................................................................... 55	
   3.2.4	
   High-dimensional (11-Color) flow cytometry .................................................... 55	
   3.2.5	
   Cell cultures ........................................................................................................ 56	
   3.2.6	
   Heat stress ........................................................................................................... 57	
   3.2.7	
   α-amanitin treatment........................................................................................... 57	
   3.2.8	
   RNA extraction ................................................................................................... 58	
   3.2.9	
   RT-PCR .............................................................................................................. 58	
   3.2.10	
   Urinary protein and creatinine measurement .................................................... 61	
   3.2.11	
   Histopathology .................................................................................................. 62	
   3.2.12	
   Apoptotic analysis............................................................................................. 62	
   3.2.13	
   RpII knock-down .............................................................................................. 63	
   3.2.14	
   RNA sequencing and data analysis ................................................................... 64	
   3.2.15	
   Microarray gene expression analysis in human cells ........................................ 65	
   3.2.16	
   Microarray gene expression analysis in flies .................................................... 66	
    xi  3.2.17	
   Gene Ontology (GO) analysis ........................................................................... 67	
   3.2.18	
   DNA adenine methyltransferase analysis of Marcal1 binding ......................... 67	
   3.3	
   Results ........................................................................................................................ 69	
   3.3.1	
   Deficiency of Marcal1 is insufficient for disease manifestations in Drosophila .................................................................................................................. 69	
   3.3.2	
   Deficiency of murine Smarcal1 is insufficient to cause disease......................... 73	
   3.3.3	
   SMARCAL1 and Marcal1 bind open chromatin ................................................ 75	
   3.3.4	
   Marcal1 and SMARCAL1 genetically interact with transcriptional components ..................................................................................................................... 79	
   3.3.5	
   SMARCAL1 deficiency alters gene expression in SIOD skin fibroblasts ........... 80	
   3.3.6	
   Marcal1 contributes to heat tolerance and modulates heat stress gene expression in Drosophila .................................................................................................................. 83	
   3.3.7	
   Smarcal1 contributes to heat tolerance and modulates heat stress gene expression in mice............................................................................................................................. 88 3.3.8	
   RpII inhibition decreases proliferation in SMARCAL1-deficient human fibroblasts........................................................................................................................ 90	
   3.3.9	
   RpII mutations decrease the viability and increase gene expression changes in Marcal1del/del flies............................................................................................................ 94	
   3.3.10	
   RpII inhibition decreases proliferation in Smarcal1-deficient mouse embryonic fibroblasts........................................................................................................................ 95	
   3.3.11	
   RpII inhibition modifies the penetrance of Smarcal1 deficiency and partially recapitulates SIOD in Smarcal1-deficient mice ............................................................. 96	
   3.4	
   Discussion ................................................................................................................ 100	
    xii  4.	
   Discussion and concluding remarks ........................................................................... 102	
   4.1	
   Improved molecular understanding of SIOD ........................................................... 102	
   4.1.1	
   SMARCAL1 is a multifunctional protein facilitating the cross-talk among DNA repair, replication, recombination and transcription ..................................................... 103	
   4.1.2	
   SIOD does not arise from defective DNA replication, repair or recombination ............................................................................................................... 105	
   4.1.3	
   SIOD is associated with transcriptional alterations beyond a threshold ........... 106	
   4.1.4	
   Possible mechanisms by which SMARCAL1 modulates gene expression ...... 111	
   4.2	
   Overall significance ................................................................................................. 113	
   4.3	
   Future directions ...................................................................................................... 113	
   Bibliography ........................................................................................................................ 115	
   Appendices ........................................................................................................................... 133	
   Appendix 1- Figure showing microhomology usage at Sµ-Sα1 junctions in the immunoglobulins of SIOD patients. ................................................................................. 134	
   Appendix 2- Figure showing microhomology usage at Sµ-Sγ1 junctions in the immunoglobulins of SIOD patients. ................................................................................. 136	
   Appendix 3- Table showing suppressors and enhancers of ectopic wing veins induced by the overexpression of Drosophila Marcal1 and human SMARCAL1.............................. 138	
   Appendix 4- Table showing enrichment in biological process GO-terms (all levels) of upregulated expressed genes (q<0.05 and fold change >2) in SIOD compared to control human skin fibroblasts. ..................................................................................................... 141	
    xiii  Appendix 5- Table showing enrichment in biological process GO-terms (all levels) of downregulated expressed genes (q<0.05 and fold change >2) in SIOD compared to control human skin fibroblasts. ..................................................................................................... 146	
   Appendix 6- Table showing qRT-PCR measurement of mRNA levels of stress response genes in skin fibroblasts of three SIOD patients (SD31, SD120, and SD123) compared to control fibroblasts after 1 hour incubation at 43°C followed by 1 hour of recovery at 37°C. ........................................................................................................................................... 152	
   Appendix 7- Table showing enrichment in biological process GO-terms (all levels) of upregulated expressed genes (fold change >2) between Smarcal1del/del and Smarcal1+/+ mouse livers at 20°C. ........................................................................................................ 154	
   Appendix 8- Table showing enrichment in biological process GO-terms (all levels) of downregulated expressed genes (fold change >2) between Smarcal1del/del and Smarcal1+/+ mouse livers at 20°C. ........................................................................................................ 158	
   Appendix 9- Table showing enrichment in biological process GO-terms (all levels) of upregulated expressed genes (fold change >2) between Smarcal1del/del and Smarcal1+/+ mouse livers at 39.5°C. ..................................................................................................... 162	
   Appendix 10- Table showing enrichment in biological process GO-terms (all levels) of downregulated expressed genes (fold change >2) between Smarcal1del/del and Smarcal1+/+ mouse livers at 39.5°C. ..................................................................................................... 163	
   Appendix 11- Table showing enrichment in biological process GO-terms (all levels) of differentially expressed genes (q<0.05) between RpII2154/FM7;Marcal1del/del and yw fly ovaries. .............................................................................................................................. 169	
    xiv  Appendix 12- Table showing enrichment in biological process GO-terms (all levels) of differentially expressed genes (q<0.05) between RpII2154/FM7 and yw fly ovaries. ...... 175	
    xv  List of Tables Table 1-1- Frequency of disease features in individuals with SIOD with biallelic SMARCAL1 mutations. ........................................................................................................................ 19	
   Table 2-1- Oligonucleotides used for amplification and sequencing of immunoglobulin switch regions. ................................................................................................................ 29	
   Table 2-2- Comparison of the prominent clinical features of SIOD to those of some DNA repair disorders................................................................................................................ 33	
   Table 2-3- Response of Smarcal1+/+ and Smarcal1del/del mice to exposure to CPT-11, etoposide and hydroxyurea. ............................................................................................ 40	
   Table 3-1- Antibodies used for flowcytometry. ..................................................................... 56	
   Table 3-2- Oligonucleotide primers. ...................................................................................... 60	
   Table 3-3- Enrichment in biological process GO-terms (all levels) of differentially expressed genes (q<0.05) between Marcal1del/del and yw ovaries at 20oC. ..................................... 87	
   Table 3-4- Enrichment in biological process GO-terms (all levels) of differentially expressed genes (q<0.05) between Marcal1del/del and yw ovaries at 25oC. ...................................... 87	
   Table 3-5- qRT-PCR measurement of mRNA levels of stress genes in the brain and liver of mice following 3 hours of heat shock at 39.5ºC. ............................................................ 89	
    xvi  List of Figures Figure 1-1- Processes involved in higher order regulation of gene expression. ...................... 3	
   Figure 1-2- Distribution of CpG islands and their contribution to gene expression. ............... 9	
   Figure 1-3- Schematic representation of covalent histone modifications. ............................. 10	
   Figure 1-4- Diagram of the structure of the SMARCAL1 gene and SMARCAL1 protein..... 14	
   Figure 1-5- Typical bony features of SIOD. .......................................................................... 20	
   Figure 2-1- Analyses of DNA breaks in cultured SMARCAL1-deficient skin fibroblasts (N859) and Smarcal1-deficient mouse embryonic fibroblasts (MEFs) by alkaline comet assay. ............................................................................................................................... 34	
   Figure 2-2- Analysis of SMARCAL1 participation in nucleotide excision repair. ............... 35	
   Figure 2-3- SMARCAL1 participation in homologous recombination. ................................ 36	
   Figure 2-4- Examples of microhomology usage at Sµ-Sα1 and Sµ-Sγ1 junctions in the immunoglobulins of SIOD patients. ............................................................................... 39	
   Figure 2-5- Hypersensitivity of Smarcal1del/del mice to CPT-11............................................ 42	
   Figure 2-6- Hypersensitivity of Smarcal1del/del mice to etoposide and HU. .......................... 44	
   Figure 2-7- CPT-11, etoposide and HU exposure partially recapitulate SIOD phenotypes in Smarcal1del/del mice. ........................................................................................................ 46	
   Figure 3-1- DNA specificity and chromatin binding of Marcal1, SMARCAL1 and Smarcal1. ......................................................................................................................................... 71	
   Figure 3-2- Temporospatial expression of Marcal1 in Drosophila cells and tissues............. 72	
   Figure 3-3- Generation of a fly model for the study of Marcal1 function. ............................ 72	
   Figure 3-4- Phenotypic comparison of Smarcal1+/+ and Smarcal1del/del mice. ...................... 74	
    xvii  Figure 3-5- Photographs showing immunofluorescent co-localization of Marcal1 (green) with panacetyl-histone H4 (AcH4; red) on Drosophila polytene chromosomes. ........... 76	
   Figure 3-6- Expression of Marcal1 tagged with DNA adenine methyltransferase (Dam) on its amino terminus methylates adenine in genomic regions of Kc167 cells with hallmarks of active transcription. ......................................................................................................... 77	
   Figure 3-7- Photographs of Drosophila wings showing the extra wing veins induced by expression of Marcal1 and SMARCAL1. ........................................................................ 78	
   Figure 3-8- SMARCAL1 deficiency alters gene expression. .................................................. 81	
   Figure 3-9- SMARCAL1 deficiency causes abnormal expression of heat stress genes. ......... 82	
   Figure 3-10- Marcal1 and Smarcal1 deficiency increase susceptibility to heat stress. ......... 85	
   Figure 3-11- Effect of Marcal1 deficiency on expression of heat stress genes and proteins in 1-3 day old Drosophila females. ..................................................................................... 86	
   Figure 3-12- Inhibition of RpII function causes penetrance of SMARCAL1, Marcal1 and Smarcal1 deficiency........................................................................................................ 92	
   Figure 3-13- Effect of knocking down RpII components in SMARCAL1 and Smarcal1 deficient fibroblasts......................................................................................................... 93	
   Figure 3-14- Treatment of Smarcal1del/del mice with α-amanitin does not recapitulate T-cell deficiency in SIOD. ........................................................................................................ 98	
   Figure 3-15- Treatment of Smarcal1del/del mice with α-amanitin partially recapitulates SIOD. ......................................................................................................................................... 99	
   Figure 4-1- Schematic model showing cross-talk between basic DNA metabolic functions and maintenance of genomic structure. ........................................................................ 105	
    xviii  Figure 4-2- Polygenic model for SIOD depicting the contribution of many dysregulated genes each with small effect size to the penetrance of SIOD. ...................................... 109	
   Figure 4-3- Oligogenic model for SIOD depicting the contribution of a few dysregulated genes to the penetrance of SIOD. ................................................................................. 110	
    xix  List of Abbreviations AcH4  Panacetyl-histone H4  ANOVA  Analysis of variance  AT  Ataxia telangiectasia  ATM  Ataxia-telangiectasia mutated  ATR  ATM and Rad3-related  ATRX  α-thalassemia X-linked mental retardation;  BER  Base excision repair  BMT  Bone marrow transplantation  BrdU  Bromo-deoxyuridine  BRG1  Brahma-related gene 1  BRM  Brahma  BS  Bloom syndrome  C. elegans  Caenorhabditis elegans  CDK9  Cyclin-dependent kinase 9  CFTR  Cystic fibrosis transmembrane conductance regulator  CHD7  Chromodomain helicase DNA binding protein 7  CMV  Cytomegalovirus  CNS  Central nervous system  CPT-11  Camptothecin-11  CS  Cockayne syndrome  CsA  Cyclosporine A  CTCF  CCCTC-binding factor xx  CyO  Curly of Oster  DamID  DNA adenine methyltransferase identification  DAVID  Database for annotation, visualization and integrated discovery  DFNB26  Deafness, autosomal recessive 26  DFNM1  Deafness (recessive, nonsyndromic) modifier 1  DMEM  Dulbecco's modified eagle media  DNA  Deoxyribonucleic acid  DNA-PK  DNA-dependent protein kinase  ds  Double-stranded  DSB  Double-strand break  dTopors  Drosophila Topoisomerase I-interacting RS proteins  EBV  Epstein-Barr virus  EdU  5-ethynyl-2´-deoxyuridine  ELISA  Enzyme-linked immunosorbent assay  ELN  Elastin  ERCC2  Excision repair cross-complementing rodent repair deficiency, complementation group 2  ERCC3  Excision repair cross-complementing rodent repair deficiency, complementation group 3  ERCC6  Excision repair cross-complementing rodent repair deficiency, complementation group 6  ESRD  End stage renal disease  F  Female  xxi  FA  Fanconi anemia  FACS  Fluorescence activated cell sorting  FBP  FUSE binding protein  FBS  Fetal bovine serum  FCS  Fetal calf serum  FDR  False discovery rate  FIR  FBP-interacting repressor  FSGS  Focal segmental glomerulosclerosis  FUSE  Far upstream element  GC  Guanosine-cytosine  G-CSF  Granulocyte-colony stimulating factor  GDP  Guanosine diphosphate  GEO  Gene expression omnibus  GFP  Green fluorescent protein  GI  Gastrointestinal  GMP  Guanosine monophosphate  GO  Gene ontology  GTF2H5  General transcription factor IIH, polypeptide 5  GTP  Guanosine triphosphate  GVHD  Graft versus host disease  H3K27me3  Histone 3 lysine 27 tri-methylation  H3K4me3  Histone 3 lysine 4 tri-methylation  HARP  HepA related protein  xxii  HCT-CI  Hematopoietic cell transplant-comorbidity index  HEPES  4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid  HFE  Hemochromatosis  HLA  Human leukocyte antigen  HR  Homologous recombination  HU  Hydroxyurea  HZ  Hypertrophic zone  ICL  Interstrand crosslink  IL7RA  Interleukin 7 receptor  ip  Intra-peritoneal  IUGR  Intrauterine growth retardation  IVIG  Intravenous immunoglobulin  LIMMA  Linear models for microarray data  M  Male  MEFs  Mouse embryonic fibroblasts  MEM  Minimum essential media  mg HA/ccm  Milligrams hydroxyapatite per cubic centimeter  MMF  Mycophenolate mofetil  MMR  Mismatch repair  MRA  Magnetic resonance angiography  mRNA  Messenger ribonucleic acid  NBS  Nijmegen breakage syndrome  NER  Nucleotide excision repair  xxiii  NHEJ  Non-homologous end joining  NHL  Non-Hodgkin lymphoma  NLS  Nuclear localization signal  NR  Not reported  PAH  Phenylalanine hydroxylase  PBS  Phosphate buffered saline  Pc  Polycomb  PCR  polymerase chain reaction  PFA  Paraformaldehyde  PZ  Proliferative zone  qRT-PCR  Quantitative reverse-transcriptase PCR  R-CHOP  Rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisolone  RMA  Robust multi-array average  RMRP  RNase mitochondrial RNA processing  RNA  Ribonucleic acid  RPA  Replication protein A  RpII  RNA polymerase II  RPMI medium  Roswell Park Memorial Institute medium  RS  Rapadilino syndrome  RTS  Rothmund-Thomson syndrome  SCE  Sister chromatid exchange  SED  Spondyloepiphyseal dysplasia  xxiv  SF2  Super family 2  shRNA  Short hairpin RNA  SIOD  Schimke immuno-osseous dysplasia  siRNA  Small interfering RNA  SMARCA4  SWI/SNF-related, matrix-associated, actin-dependent regulator of chromatin, subfamily a, member 4  SMARCAL1  SWI/SNF-related, matrix-associated, actin-dependent regulator of chromatin, subfamily a-like 1  SMARCB1  SWI/SNF-related, matrix-associated, actin-dependent regulator of chromatin, subfamily b, member 1  SMARCC1  SWI/SNF-related, matrix-associated, actin-dependent regulator of chromatin, subfamily c, member 1  SMARCC2  SWI/SNF-related, matrix-associated, actin-dependent regulator of chromatin, subfamily c, member 2  ss  Single-stranded  SWI2/SNF2  SWItching defective 2 or sucrose non-fermenting 2  T3  Triiodothyronine  T4  Thyroxine  TC-NER  Transcription-coupled nucleotide excision repair  TCR  T cell receptor  TIA  Transient ischemic attack  TNA  Transient neurological attack  TSH  Thyroid stimulating hormone  xxv  TUNEL  Terminal deoxynucleotidyl transferase dUTP nick end labeling  UAS  Upstream activating sequence  Ubx  Ultrabithorax  UV  Ultraviolet light  WS  Werner syndrome  XP  Xeroderma pigmentosum  xxvi  Acknowledgements My sincere thanks to my supervisor, Dr. Cornelius Boerkoel, from whom I learned thoughtful thinking in science. I am so grateful for his guidance, encouragement, and friendship throughout my graduate training over the past 6 years. He gave me the opportunity to get involved in a myriad of experiences focused on improving patient care as the ultimate goal. His generosity in teaching, his commitment to rare disorders and translational research, and his curiosity for learning have been a great source of inspiration for me. Neal! Thank you for all your help! This dissertation is the culmination of a collaborative endeavor of many talented and dedicated individuals from around the world and I would like to express my gratitude to all of them. I am thankful to my supervisory committee members, Drs. Jan Friedman, Lorne Clarke, and Millan Patel for their valuable advice and support. In particular, I am very grateful to Millan Patel for many fascinating and fruitful discussions over the years. I would also like to express my gratitude to all current and previous Boerkoel Lab members particularly Kunho Choi, Marie Morimoto, Andrew Fam, Miraj Kobad Chowdhury, and Chris Dias for their friendship, help, and discussions. I am also very grateful to Cheryl Bishop for her valuable advice and help. I thank my parents and sisters for their encouragement and support. Lastly, I would like to express my gratitude to my loving wife Sara for her unending support, motivation, patience and devotion. I am greatly indebted to her and words cannot describe my gratitude.  xxvii  Dedication  To Mitchell, Wouter, Ashley, Liana, Emily, Ali, Tasin, Robert, Maria and all other SIOD patients.  xxviii  1. Introduction One objective of medical genetics is understanding the correlation between genotype and phenotype. Traditionally, genetics has done this by segregation of abnormal phenotypes to uncover their genetic basis. While this approach has been highly successful, the reverse process of predicting phenotype from genotype has been rather unsatisfying. This challenge is quite intriguing for Mendelian disorders since the phenotype is often fully explained by mutations at a single locus 1-3. As illustrated by phenylketonuria and the ciliopathies, however, prediction of disease severity is frequently the exception rather than the norm 3,4. The spectrum of clinical differences in Mendelian disorders ranges from no expression of disease in genetically predisposed individuals (a property known as incomplete penetrance) to variations in the severity of clinical symptoms (variable expressivity). Variations in expressivity as well as incomplete penetrance have been attributed to genetic and environmental factors as well as to developmental stochastics 5-8. Although incomplete penetrance has been described in a few autosomal recessive conditions 5,9-12, the underlying molecular mechanism for this in most autosomal recessive disorders has yet to be discovered. One hypothesis is that the variable expressivity and incomplete penetrance observed in Mendelian disorders arise from the impingement of environmental and genetic factors on a biological process sensitive to quantitative modulation 13. Gene expression (transcription) is a quantitative trait, and recently it has been shown that variations in mRNA expression contribute to the incomplete penetrance of mutant alleles in model organisms 8. Whether dysregulation of gene expression would also lead to variability in trait penetrance in human  1  diseases is not well understood. Testing this hypothesis requires not only a suitable disease model but also a good understanding of mechanisms modulating gene expression. Processes involved in the regulation of gene expression include basal and genespecific transcription factors, as well as genetic and epigenetic mechanisms. Examples of epigenetic regulators of gene expression include three dimensional nuclear organization, DNA methylation, histone modifications, and chromatin remodeling 14-19. Understanding these mechanisms and the diseases associated with them gives us insight into how mutations in a single gene lead to pleiotropy. To this end, therefore, I review higher order regulatory mechanisms of gene expression in this chapter and then focus on the pleiotropic disorder Schimke immuno-osseous dysplasia (SIOD), which is associated with mutations of the chromatin remodeling ATPase SMARCAL1 (SWI/SNF-related, matrix-associated, actin-dependent regulator of chromatin, subfamily a-like 1). Finally, I lay out the objectives of my dissertation and their significance.  1.1 Higher order regulation of gene expression Processes involved in the regulation of gene expression beyond the transcription factors include three-dimensional nuclear organization, DNA methylation, covalent histone modifications, and chromatin remodeling 15,20-25 (Figure 1-1). Through alteration in chromatin structure these processes modify the accessibility of promoter regions to transcription factors and regulate gene expression. I review in this section the mechanisms contributing to higher order regulation of gene expression in order to place the function of SMARCAL1 in context.  2  Figure 1-1- Processes involved in higher order regulation of gene expression. Adapted and modified by permission from Elsevier: Biochimica et Biophysica Acta (BBA), 1819, 401-410, copyright 2012, and Macmillan Publishers Ltd: Nature Reviews Cancer, 4, 133-142, copyright 2004.  1.1.1 Three-dimensional nuclear organization and regulation of gene expression Gene expression at the highest level is regulated by three-dimensional nuclear organization. Consequently gene expression is associated with location of chromosome territories within the nucleus and with interaction of chromatin with the nuclear envelope as well as with boundary elements. In this section I will further discuss these and reported contributions to the regulation of gene expression.  3  1.1.1.1  Chromosomal spatial orientation Rabl first proposed a territorial organization of interphase chromosomes in 1885 26  and in 1909 Boveri introduced the term “chromosome territory” 27. Within the interphase nucleus, the DNA from the various chromosomes is not randomly intertwined, rather chromosomes occupy non-overlapping territories of irregular shape 28-32. Of note, chromatin from separate territories minimally intermingles 30,33-35. Electron microscopy and polymerization of probes such as vimentin clearly define an interchromosomal domain or space between chromosomal territories 36-40. Additionally, supporting separation of the chromosomal territories, higher resolution analysis of nuclear genomic organization using chromosome conformation capture techniques has identified a predominance of intrachromosomal physical interactions compared to inter-chromosomal interactions 41,42. A model for the distribution of chromosome territories suggests that within the nucleus, gene-dense chromosomes are located more internally than gene-poor ones 25,43,44 and that this localization also correlates with transcriptional activity, replication timing, and GC content 45-48. Although not consistently observed 49, this arrangement has been frequently reported for mammalian and chicken cells 30,50-54 as well as for homologous chromosomes in higher primates 55 and syntenic chromosomes in humans and mice 56-58. Furthermore, genes are generally distributed along the periphery of chromosome territories and invaginating channels where they can loop out into interchromosomal domains upon the induction of expression 56,57,59-67. Thus, transcription may predominate along the periphery of a chromosome territory to allow access for transcription factors and to facilitate processing and transport of mRNA 30,39,40,60.  4  1.1.1.2  Nuclear envelope One mechanism by which chromosome territories could be fixed within the nucleus is  by specific attachment of chromatin to the nuclear matrix. The best-characterized component of the nuclear matrix is the nuclear envelope that consists of the outer and inner nuclear membranes, nuclear pore complexes and the nuclear lamina. The lamins and associated proteins are the major components of the nuclear lamina that underlie the inner membrane of the nuclear envelope. At lower concentrations, lamins are also distributed throughout the nucleoplasm. Lamins and their associated proteins maintain the integrity of the nuclear envelope 68, provide a structural attachment point for chromatin 69, help define DNA replication sites 68,70-72, localize nuclear bodies 73, regulate epigenetic modifications of chromatin 74, and facilitate DNA repair and transcription 75-81. Suggesting that the nuclear matrix and in particular nuclear lamina are key to intranuclear chromosomal positions and gene expression, profiling of gene expression changes in cells with a dominant LMNA mutation showed alterations in both of these properties 81. The nuclear matrix also modulates gene expression directly and not only by maintenance of chromatin territories. This is substantiated by interaction of lamin-associated proteins with the transcriptional apparatus. For example, emerin, an inner nuclear envelope protein, not only binds lamins A and B but also interacts with the transcriptional factors GCL, Btf, Lmo7, BAF, and YT521-B 75,78,82-85. Interactions between the nuclear lamina and chromatin have been mapped by DNA adenine methyltransferase identification (DamID) in Drosophila, mouse and human cell lines 86-88  . The lamina-associated domains are generally gene-poor and transcriptionally inactive,  5  and when those domains dissociate from the lamina, the genes within them often become transcriptionally active or poised for transcription 86-88.  1.1.1.3  Boundary elements Observations from yeast, Drosophila, chicken, mouse and human studies show that  insulators compartmentalize the genome into separate regions of gene expression through interactions with DNA, the nuclear matrix, and other protein components 89-91. Insulator complexes are defined by two activities: 1) they can inhibit the spread of heterochromatin, and/or 2) they can block a transcriptional enhancer from activating a promoter when located between the two 91. One of the best-studied insulators is the gypsy element found in the Drosophila gypsy retrotransposon. Proteins that directly or indirectly bind the gypsy insulator include suppressor of hairy wing, modifier of mdg4, Centrosomal protein 190 kD, Trithorax-like, and dTopors (Drosophila Topoisomerase I-interacting RS proteins); the last binds the gypsy insulator to the nuclear lamina 92-96. Modulation of the interaction between these proteins and the gypsy insulator sequences defines higher order chromatin structures, such as chromatin loops, and the functionality of each gypsy sequence 92,93,95. In vertebrates, our understanding of insulator function primarily comes from studies of imprinted genomic domains such as 11p15.5 and the beta-globin gene cluster 97,98. CCCTC-binding factor (CTCF), which binds the insulator sequences in these regions as well as many other sites, is the best-characterized vertebrate insulator-binding protein. The 5ʹ′ chicken HS4 insulator sequence, which is located upstream of the beta-globin cluster, has two separable functions: 1) it inhibits the adjacent heterochromatin from spreading into the 6  beta-globin locus, and 2) it blocks enhancer-promoter interactions 99. In addition to binding sequences such as HS4, CTCF binds nucleophosmin, a nucleolar protein and a component of the nuclear matrix 100-102. Binding of CTCF to the HS4 and other insulators is proposed to facilitate the formation of chromatin loops and to tether these loops to subnuclear structures, such as the nucleolus and the nuclear matrix 102. In cultured human lung fibroblasts the lamin B1-associated domains are flanked by CTCF 87, and association of CTCF with lamin A is required for localization of telomeres to the nuclear periphery 103. Lastly, CTCF is not only involved in chromosome-matrix interactions but also in intra- and inter-chromosomal interactions 104-107. Therefore, by maintaining three-dimensional nuclear organization, insulators modulate various basic cellular functions including transcription (for a review see 108,109  ). Another chromatin structural motif that is involved in higher order regulation of gene  expression is the cohesin complex. Cohesin complexes were originally identified for their role in maintaining sister chromatid cohesion prior to their separation during anaphase 110. The Drosophila protein Nipped-B loads the cohesin complex onto the chromosomes and is also required for facilitating enhancer-promoter communication 111-113 and regulating gene expression 111,114. These findings as well as the association of cohesin complexes with CTCF target sequences in mammalian cells suggest that cohesin complexes are structural elements defining and regulating gene expression. Indeed, impaired or errant localization of cohesin complexes affect RNA transcription and putatively do so across large genomic regions 115-124.  7  1.1.2 DNA methylation DNA methylation is one of the major epigenetic modifications present in organisms from bacteria to human. In eukaryotes DNA methylation occurs at cytosine residues through transferring of the methyl groups by DNA methyltransferases 125; however, this covalent modification is absent or rare in some of the commonly used model organisms including yeast (Saccharomyces cerevisiae, Saccharomyces pombe), fly (Drosophila melanogaster) and nematode (Caenorhabditis elegans). Based on the position along the transcriptional unit DNA methylation modifies gene expression (Figure 1-2) 24. In mammals, DNA methylation of CpG dinucleotide sequences at the promoters is generally associated with gene expression suppression while DNA methylation in the gene body might even stimulate transcription elongation and affect splicing 24. Whether DNA methylation at CpG islands of the promoters precedes transcriptional silencing or functions as a reinforcing lock for previously silenced genes is yet to be fully delineated 24,126.  8  Figure 1-2- Distribution of CpG islands and their contribution to gene expression. More than half of human gene promoters have CpG islands. Methylation of these sequences are associated with gene expression silencing. Gene bodies and repetitive elements are mostly CpG-depleted and are predominantly methylated. Enhancers are also CpG-poor and have variable CpG methylation. At insulator regions DNA methylation can block the binding of CTCF and alter gene expression. LMR, low-methylated region; NDR, nucleosomedepleted region; TET, ten-eleven translocation; TSS, transcription start site. Adapted by permission from Macmillan Publishers Ltd: Nature Reviews Genetics, 13, 484-492, copyright 2012.  1.1.3 Histone modifications Another major epigenetic modification that has a key role in regulating gene expression is the covalent modification of histones (Figure 1-3). These modifications modulate transcription either by directly changing chromatin structure or by altering the binding of other proteins 22. Examples of modifications that directly change DNA structure 9  include histone acetylation and phosphorylation. These modifications reduce the positive charge of histones and thereby their affinity for DNA and in turn allow the DNA to assume a more open conformation that facilitates transcription factor binding. An example of a modification that alters the binding of other proteins to DNA is tri-methylation of H3K4 (H3K4me3), a histone mark associated with active transcription. This modification leads to the recruitment of chromatin modifying enzymes such as CHD1 to reposition nucleosomes 22,127,128  .  Figure 1-3- Schematic representation of covalent histone modifications. The major modifications include acetylation, ubiquitylation, methylation, and phosphorylation. Positions of the modified amino acids are labeled. Adapted by permission from Macmillan Publishers Ltd: Nature, 421(6921):448-53, copyright 2003.  10  1.1.4 Chromatin remodeling In addition to three-dimensional nuclear organization and covalent modifications of DNA and histones, gene expression is modulated by ATP-dependent chromatin remodeling complexes. These proteins bind DNA and expend energy from ATP hydrolysis to reorganize nucleosomes or DNA structures 129-131. SWI2/SNF2 (SWItching defective 2 or Sucrose NonFermenting 2) or SNF2 family of ATP-dependent chromatin remodeling proteins belongs to the SF2 (Super Family 2) class of helicases 23. Subunits of this family share a SNF2 domain containing seven motifs (I, Ia, II, III, IV, V, VI) that form the nucleotide binding site and participate in nucleotide triphosphate hydrolysis and coupling of DNA binding with nucleotide triphosphate hydrolysis 132. However, these enzymes do not have helicase activity but remodel chromatin by rearranging nucleosomes 133,134, translocating along DNA 135,136, disrupting protein-DNA interactions 137, generating superhelical torsions 133,134, or annealing helicase activity 130,131. Through chromatin remodeling SNF2 proteins contribute to a variety of cellular processes including DNA replication (e.g. SWI/SNF, INO80, ISWI, SMARCAL1 subfamilies), DNA repair and recombination (e.g. SWI/SNF, INO80, SWR1, and SMARCAL1 subfamilies), gene expression (e.g. SWI/SNF, ERCC6, and CHD7 subfamilies), and chromosome segregation (e.g. ATRX subfamily) 138-144. Focusing on their role in transcription, genome-wide mapping of the interactions of several members of the SWI/SNF subfamily including Ini1 (SMARCB1), Brg1 (SMARCA4), BAF155 (SMARCC1) and BAF170 (SMARCC2) showed that they associate with nuclear matrix proteins and transcription factors and frequently occupy transcription start sites and enhancers, CTCFbinding domains and regions occupied by RNA polymerase II 145. SMARCAL1, the enzyme defective in SIOD, is involved in DNA replication, recombination, repair and transcription.  11  1.2 SMARCAL1 Human SMARCAL1 (OMIM 606622) consists of 18 exons, 2 non-coding and 16 coding exons, and encodes a 954- amino acid nuclear protein, SMARCAL1 or HARP (HepA related protein) that is a distinct member of the SNF2 subfamily of chromatin remodeling ATPases 146. In addition to a SNF2 domain at the C-terminus, SMARCAL1 contains an Nterminal Replication Protein A (RPA) binding site, two nuclear localization signals (NLS1 at N-terminus and NLS2 within SNF2 domain), and two tandem HARP motifs (HARP1 and HARP2) at the N-terminal site with sequence similarity to regions of prokaryotic HepA (Figure 1-4). SMARCAL1 recognizes DNA structures that contain single-stranded (ss)-todouble-stranded (ds) transitions including fork DNA, DNA bubbles, DNA substrates with either a 5′ or 3′ recessed end, three- and four-way DNA junctions, and gapped DNA substrates 130,140,147. Binding of ss-to-ds transitions stimulates ATP hydrolysis by SMARCAL1 as it rewinds ss-DNA 130,140,147. This annealing helicase activity and in part the DNA binding and ATPase activity of SMARCAL1 are mediated by the HARP2 domain but not by the HARP1 domain 140,148. In contrast to several previous reports that did not detect any helicase activity for SMARCAL1 130,147, Ciccia et al. showed that SMARCAL1 disrupts D loop structures in the presence of magnesium but not calcium containing buffers 149. At the cellular level SMARCAL1 is localized to its target DNA structures through an interaction with the ssDNA-binding protein RPA 139,141-144. Through this interaction, which is critical for SMARCAL1 in vivo function, SMARCAL1 travels with elongating replication forks and also localizes to stalled replication forks and sites of DNA ds-breaks 139-144. In response to replication stress SMARCAL1 becomes phosphorylated at multiple sites by ATM (Ataxia-telangiectasia mutated), ATR (ATM and Rad3-related), and DNA-PK (DNA12  dependent protein kinase) 139. Therefore, SMARCAL1 is a DNA stress response protein and both silencing and overexpression of this enzyme activates the DNA damage response during S phase 139. Consistently, interaction of SMARCAL1 with replication forks prevents MUS81 endonuclease-dependent ds-breaks 140. Moreover, SMARCAL1-deficient cells are hypersensitive to DNA damaging agents and produce more γH2AX foci compared to control cells 139,141-144,150. Localizing to stalled replication forks, SMARCAL1 is involved in replication fork restart 141. This can be attributed to the newly discovered role of SMARCAL1 in remodeling replication forks by catalyzing branch migration 140. Although cell cycle analyses have shown slightly delayed transition from G2 to M phase in SMARCAL1 deficient cells, the overall proliferation rate of SMARCAL1-deficient cells is not detectably perturbed relative to control cells 139,141. In contrast to SMARCAL1 deficiency in human cells, morpholino knockdown of smarcal1 in zebrafish has shown a defect in cell cycle progression, namely cell cycle arrest at the G0/G1 stage, which was associated with minor dysregulation of expression of several cell cycle genes 151. Furthermore, SMARCAL1 can bind four-way Holliday junctions and promote branch migration of these structures 140. Since these structures frequently occur during homologous recombination, the ability to remodel Holliday junctions suggests a role for SMARCAL1 in homologous recombination. In summary, SMARCAL1 is a chromatin remodeling enzyme with annealing helicase activity that remodels DNA structures at ss-to-ds transitions. Its roles in the DNA stress response, cell cycle progression, and remodeling of stalled replication forks and of Holliday junctions indicate that this enzyme is involved in several basic cellular functions.  13  Figure 1-4- Diagram of the structure of the SMARCAL1 gene and SMARCAL1 protein. The top panel represents the SMARCAL1 gene with its 18 exons in which the first two exons (blue bars) are noncoding and the rest of the exons are coding (purple bars). The lower panel represents the SMARCAL1 protein with its functional domains: RPA binding domain (yellow box), two HARP domains (blue boxes), SNF2 domain (purple box), and two nuclear localization signals (NLS1 and NLS2).  1.3 Schimke immuno-osseous dysplasia (SIOD) Biallelic mutations of SMARCAL1 gene are associated with a fatal childhood disorder called Schimke immuno-osseous dysplasia (SIOD, MIM 242900). SIOD was first described in 1971 by Dr. R. Neil Schimke. He reported a new disease with the cardinal signs of nephritic syndrome, defective cellular immunity, and possibly chondroitin-6-sulphaturia 152. About twenty years later Ehrich et al. (1990) contributed to the clinical description of the disease and Spranger et al. (1991) designated the co-occurrence of growth retardation, immunopathy, and nephritic syndrome as “Schimke immuno-osseous dysplasia”153,154. About ten years later Boerkoel et al. (2002) discovered that 50-60% of SIOD patients have biallelic mutations in their SMARCAL1 gene 155. Mutations are distributed across SMARCAL1 and include deletions, insertions, splice site mutations, and missense and nonsense point mutations, suggesting loss of function 155. Biallelic mutations of SMARCAL1 cell autonomously lead to SIOD disease features 156-158. So far, mutations in other genes have not been associated with SIOD. 14  1.3.1 Characteristics and clinical features Schimke immuno-osseous dysplasia (SIOD) is a panethnic, autosomal recessive, highly pleiotropic, multisystem childhood disorder with variable expressivity and incomplete penetrance 13,130,155,157,159. The most prominent features of the disease are growth failure from spondyloepiphyseal dysplasia, renal failure from focal segmental glomerulosclerosis (FSGS), and T-cell immunodeficiency (Table 1-1). Combined with the facial dysmorphism, these form a diagnostic triad unique to SIOD 152,154,160-162. The prevalence of SIOD is unknown. However, based on referrals and published birth rates, the incidence in North America is estimated to be one in 1-3 million live births. The clinical features of SIOD are described as follows, and their frequencies are summarized in Table 1-1: •  Physical features. Most SIOD patients have facial dysmorphism including a broad, low nasal bridge and bulbous nasal tip. They also have disproportionate short stature with a short neck and trunk as well as lumbar lordosis and protruding abdomen. They also commonly have hyperpigmented macules on the trunk and occasionally on the extremities, neck, and face. Less common ectodermal abnormalities include fine or sparse hair, microdontia or adontia, and corneal opacities.  •  Development. Most individuals with SIOD have normal intellectual and neurologic development until the onset of cerebral ischemic events. Although a few have had developmental delay, the delay can be ascribed for most to the deleterious consequences of chronic illness.  •  Growth and endocrine findings. Most affected children have prenatal and postnatal disproportionate growth failure. A few have normal intrauterine growth followed by  15  postnatal growth failure. The observed disproportionate growth deficiency is not a result of renal failure. Comparison of the anthropometric measurements of persons with SIOD to persons with non-SIOD chronic kidney disease found that in nearly all parameters, persons with SIOD differed significantly from those with non-SIOD chronic renal disease. The most marked difference is that in non-SIOD chronic kidney disease, the median leg length is significantly more reduced than trunk length, while in SIOD, the reduction in trunk length was significantly more than that for leg length. Therefore, a sitting height/leg-length ratio of less than 0.83 is suggestive of SIOD in persons with chronic kidney disease 163. The mean age of diagnosis with growth failure was two years (range: age 0-13 years) 13. Generally, affected individuals have a normal growth hormone axis and no response to growth hormone supplementation. Heights of those who have survived to adulthood are 136-157 cm for men and 98.5-143 cm for women. Nearly half of affected individuals have subclinical hypothyroidism that persists after renal transplantation. The concentration of thyroid stimulating hormone (TSH) is increased, and free and total T3 and T4 concentrations are reduced. •  Skeletal findings. SIOD is characterized by prominent spondyloepiphyseal dysplasia (SED) of the spine, pelvis and capital femoral epiphyses 164. Less frequent skeletal problems include a widened sella turcica, thoracic kyphosis, scoliosis, and osteopenia (Figure 1-5). Affected individuals do not usually have joint pain until they develop degenerative hip disease.  •  Hematologic findings and infection. T-cell deficiency causes lymphopenia in approximately 80% of affected individuals. The B-cell count is usually normal to  16  slightly elevated. In addition to T-cell deficiency, several individuals with SIOD have had deficiencies of other blood cell lineages. See Table 1 for types and frequency. Because of immunodeficiency, affected individuals have an increased risk for opportunistic infections such as Pneumocystis carinii pneumonia and more than half have recurrent infections with various bacteria, viruses (including Herpes simplex, Herpes zoster, cytomegalovirus), and fungi (oral and/or cutaneous candida) 155,161. Infection is a common cause of death. •  Autoimmune findings. About 20% of SIOD patients have features of autoimmune disease. These manifestations include thrombocytopenia, hemolytic anemia, enteropathy, pericarditis with anti-cardiolipin antibodies, and Evans syndrome. In one patient with thrombocytopenia, the autoimmune features resolved spontaneously; in one they resolved after steroid and IVIG treatments, and in one they cleared after splenectomy. All other patients excluding the one with Evans syndrome, were successfully treated with immunosuppressive therapy such as steroids, cyclophosphamide or IVIG. The patient with Evans syndrome was resistant to treatment with steroids, cyclosporine A and rituximab 165.  •  Renal findings. Nephropathy usually develops before age 12 years and progresses to end stage renal disease (ESRD) within the subsequent one to 11 years. Usually the diagnosis of nephropathy is made concurrent with or within the five years following the diagnosis of growth failure. Focal segmental glomerulosclerosis (FSGS) is the predominant renal pathology among individuals with SIOD.  •  Gastrointestinal findings. A few individuals with SIOD have enteropathy. For most of these individuals, the enteropathy results from infection, e.g., Heliobacter pylori.  17  However, one individual without evidence of infection had gastrointestinal villous atrophy that improved with corticosteroid therapy 166. •  Atherosclerosis and hypertension. Half of individuals with SIOD have symptoms suggestive of atherosclerosis. Vascular changes observed on postmortem tissue from three individuals included focal intimal lipid deposition, focal myointimal proliferation, macrophage invasion, foam cells, fibrous transformation, and calcium deposits 154,156,167. The pulmonary and systemic hypertension that persisted despite renal transplantation described by Lücke et al. (2004) could be explained by myointimal hyperplasia 156. Also, gene expression studies have identified a significant decrease in the expression of ELN in individuals with SIOD 168. This gene encodes for elastin protein, which is critical for maintaining the integrity of the arterial wall. Histopathologic analysis of postmortem arterial tissue from three individuals with SIOD showed splitting and fragmentation of elastin fibers 156,168. Reduction in the elastin protein results in the increased proliferation of smooth muscle cells in arterial walls and leads to intimal hyperplasia 169.  •  Central nervous system (CNS) symptoms. Nearly half of affected individuals have severe migraine-like headaches, transient neurological attacks (TNAs), or strokes 162. Frequently, the cerebral ischemic events are precipitated by hypertension. The TNAs are usually focal and are frequently assumed to be transient ischemic attacks (TIAs). Interestingly, however, using magnetic resonance angiography (MRA), these TIAs are often not associated with vascular abnormalities and can be precipitated by fatigue or stress conditions such as hot weather. The cause of the severe migraine-like headaches is unknown.  18  Table 1-1- Frequency of disease features in individuals with SIOD with biallelic SMARCAL1 mutations. Feature Physical features Broad and low nasal bridge Bulbous nasal tip Microdontia Pigmented macules Unusual hair Short neck Short trunk Lumbar lordosis Protruded abdomen Corneal opacities Development Schooling delay Developmental delay Growth IUGR Decreased postnatal growth rate/short stature Endocrine Abnormal TFTs Skeleton Ovoid flat vertebrae Hypoplastic pelvis Abnormal femoral heads Hematology T-cell deficiency Lymphopenia Neutropenia Thrombocytopenia Anemia Kidney Proteinuria or nephropathy FSGS Vasculature Headaches TIAs Strokes Miscellaneous Autoimmune disease Non-Hodgkin lymphoma 1  Number of Affected Individuals with Feature (%)  Total Individuals with SIOD2  37 (65) 43 (80) 11 (39) 44 (76) 30 (63) 45 (83) 47 (82) 41 (75) 44 (80) 9 (16)  57 54 28 58 48 54 57 55 55 57  6 (23) 14 (26)  26 54  31 (72) 59 (98)  43 60  21 (44)  48  42 (79) 34 (68) 43 (84)  53 50 51  38 (83) 46 (81) 21 (41) 17 (31) 30 (59)  46 57 51 55 51  57 (98) 34 (79)  58 43  22 (49) 24 (45) 22 (45)  45 53 49  8 (20) 3 (5)  41 60  IUGR, intrauterine growth retardation; TFT, thyroid function test; FSGS, focal segmental glomerulosclerosis; TIA, transient ischemic attack. 1 EBV-positive and negative non-Hodgkin lymphoma 2 Each row represents the total number of SIOD patients with biallelic SMARCAL1 mutations in whom the specific clinical feature has been reported. The data for this table was compiled from SIOD patient registry maintained by Cornelius F. Boerkoel (C.F.B., SIOD patient registry).  19  Figure 1-5- Typical bony features of SIOD. (A) Lateral spine radiograph of a 5-year-old child showing dorsally flattened, pear-shaped vertebral bodies. (B) Lateral skull radiograph of a 5-year-old child showing widening of the sella. (C) Posteroanterior hand radiograph of a 13-year-old adolescent showing the absence of bony abnormalities. (D) Anteroposterior hip radiograph of a 4-year-old child showing the small, laterally displaced capital femoral epiphyses, hypoplastic basilar ilia, and upslanting and poorly formed acetabula. Adapted with kind permission from Springer Sceince and Business Media: Eur J Pediatr (2010) 169:801–811, Schimke immunoosseous dysplasia: defining skeletal features, Hunter KB et al., figure 1.  20  1.3.2 Clinical course and outcome SIOD varies in severity, ranging from in utero onset of growth retardation with death in the first few years of life to a slowly progressive course with survival into adulthood. Classically, SIOD has been divided into an infantile- or severe early-onset form and a juvenile- or milder later-onset form. SIOD follows a continuum such that affected individuals with early-onset and severe symptoms usually die early in life, whereas those with mild symptoms survive into adulthood if ESRD is treated with renal dialysis and/or renal transplantation. Severity and age of onset of symptoms do not, however, invariably predict survival; a few individuals have survived beyond age 20 years despite having relatively severe early-onset disease 167,170. Growth failure is usually the primary clinical feature of SIOD and most affected individuals develop other symptoms within one to five years of the diagnosis of growth failure. Those with severe symptoms usually die within four to eight years. The mean age of death is 10.8 years. Causes of death include stroke (17%), renal failure (15%), infection (23%), pulmonary hypertension and congestive heart failure (15%), bone marrow failure (3%), complications of organ transplantation (9%), gastrointestinal bleeding (6%), complications of lymphoproliferative disease (9%), and unspecified acute restrictive lung disease (3%) (C.F.B., SIOD patient registry). Ongoing correlations of genotype to phenotype have shown that genotype does not predict disease severity or outcome, either within or among families 13,159,171,172. In five multiplex families, the phenotype of siblings has been variable:  21  •  A boy succumbed to a stroke at age 3.7 years after developing ESRD; his sister succumbed to bone marrow failure at age 2.75 years before developing renal failure and without symptoms of cerebral ischemia 170.  •  Of two brothers, one had severe disease and the other had relatively mild disease 172.  •  Of two brothers with homozygous SMARCAL1 mutations, one presented with growth failure at age six years and the other had no symptoms at age seven years 159.  •  Of three siblings reported by Lama et al. (1995), one died as a child, one died at 43 years and the other survived into her fourth decade 173.  •  Of three siblings reported by Dekel et al. (2008) the elder brother had severe disease beginning at age 3.5 years and two younger non-identical twin brothers had relatively mild disease 171. Among those who have survived beyond puberty, none has reproduced yet. Women  and men develop secondary sexual characteristics. Women have menses, although the menstrual cycle is usually irregular. Men have small testes with histopathologically identified azoospermia 156.  1.3.3 Management and treatment of manifestations To establish the extent of disease in an individual diagnosed with SIOD, the following evaluations are considered: •  Detailed history for headaches or neurologic abnormalities  •  Assessment of developmental status with referral for formal evaluation if significant developmental delays or schooling delays are identified 22  •  Measurement of growth and assessment of body proportions, with plotting on ageappropriate growth charts  •  Evaluation of renal function by measurement of serum concentrations of creatinine and urea, protein excretion in urine, and creatinine clearance and referral to a nephrologist for evaluation  •  Hematology evaluations to assess lymphopenia, anemia, neutropenia, and thrombocytopenia  •  Orthopedic evaluation for symptoms of joint pain or evidence of scoliosis or kyphosis  •  Assessment for osteopenia  •  Thyroid function studies  •  Ophthalmologic evaluation  •  Dental evaluation after teeth are present  Although there is no curative therapy available for SIOD, patients benefit from symptomatic treatments: •  Renal transplantation effectively treats the nephropathy, and neither nephropathy nor arteriosclerosis recurs in the graft 156,158,167. Immunosuppressive monotherapy seems to improve the outcome after renal transplantation 174.  •  Some affected individuals who have survived beyond childhood have required hip replacement. Treatment of scoliosis and/or kyphosis is standard.  •  Affected individuals with recurrent herpetic infections benefit from treatment with acyclovir. A few patients have developed severe disseminated cutaneous papilloma  23  virus infections that have improved with imiquimod and cidofovir (C.F.B., SIOD patient registry). •  Neutropenia usually responds well to supplementation with granulocyte colonystimulating factor or granulocyte-macrophage colony-stimulating factor 161. One affected individual has been successfully treated by bone marrow transplantation (BMT), however, four other patients died within the first few months after BMT 175,176  . A few individuals have been transfusion dependent because of anemia or  thrombocytopenia 161. •  Individuals with transient ischemic attacks or strokes usually have temporary improvement upon treatment with agents that improve blood flow or decrease coagulability (pentoxifylline, acetylsalicylic acid, dipyridamole, warfarin, heparin) 161. To date, no curative or effective long-term therapies have been identified.  •  The migraine headaches are often difficult to treat since response to anti-migraine medication is variable 162. Medications that have helped some individuals include ergotamine, sumatriptan, verapamil, and propranolol 162.  •  TSH concentrations are corrected with levothyroxine supplementation; however, supplementation does not have an ameliorative effect on the renal disease or T-cell deficiency 161.  •  Individuals with recurrent infections, opportunistic infections, or declining lymphocytes or T-cell counts frequently require prophylactic antibiotics and the care of an immunologist 161.  24  1.4 Thesis objectives and significance The aim of my doctoral study was to dissect further the molecular pathophysiology of SIOD. Since SMARCAL1 annealing helicase activity can potentially modulate transcription through altering DNA structure and variations in gene expression can account for alterations in disease expression, I hypothesized that SIOD arises from dysregulation of gene expression. In the last three years, several reports from the Cortez Lab, Elledge Lab, Kadonaga Lab, Chen Lab and Funabiki Lab have demonstrated that SMARCAL1 participates in the DNA stress response and also in reactivation of stalled replication forks 139,141-144. However, it was not clear whether these roles of SMARCAL1 were relevant to the molecular pathophysiology of SIOD. In chapter 2, I addressed this question by looking for dysfunction of various DNA repair pathways in SIOD patients and cells. In chapter 3, I determined that SMARCAL1 also participates in transcription and tested whether this role contributed to the pathobiology of SIOD. Using human tissues, fruit flies and mice, my colleagues and I showed that SMARCAL1 modulates transcription but that SMARCAL1 deficiency is insufficient to cause the disease in model organisms. However, disease manifests when SMARCAL1 deficiency interacts with genetic and environmental factors that further alter gene expression.  25  2. Contribution of DNA repair defects to pathophysiology of SIOD 2.1 Introduction In this and the next chapter, I focus on delineating further the molecular mechanism of SIOD. Herein I evaluate whether defects in the DNA repair pathways are major contributors to the SIOD phenotype. As mentioned earlier in chapter 1, SIOD is associated with biallelic mutations of SMARCAL1, which encodes an enzyme with annealing helicase activity 130,155. This enzyme participates in the DNA stress response to genotoxic agents such as hydroxyurea, camptothecin and aphidicolin 139,141-144. These observations raise the question of whether loss of SMARCAL1 function causes disease by impeding DNA repair. To test the potential contribution of defective DNA repair to the phenotype of SIOD, we compared SIOD to other disorders of DNA repair, profiled the cancer prevalence in SIOD, tested for defects in the DNA repair processes including nucleotide excision repair (NER), homologous recombination (HR), and non-homologous end joining (NHEJ) and measured the sensitivity of Smarcal1-deficient mice to genotoxic agents. We find that SIOD patients have a high frequency of non-Hodgkin lymphoma (NHL) and that Smarcal1-deficient mice are hypersensitive to several genotoxic agents.  26  2.2 Materials and methods 2.2.1 Comet assay Control and SIOD (N859) fibroblasts as well as Smarcal1del/del and Smarcal1+/+ mouse embryonic fibroblasts (MEFs) were analyzed by alkaline comet assay as previously described 177. In brief, cultured cells were trypsinized, washed with medium, resuspended in low melting point agarose, and layered on agarose-coated slides cooling on ice. After 10 minutes the slides were immersed in lysis solution (2.5 M NaCl, 100 mM EDTA, 10 mM Trizma base, 1% Triton X-100, 10% dimethyl sulfoxide, pH 10) for 5 hours. Slides were rinsed in deionized water and immersed in a 4°C alkaline solution (50 mM NaOH, 1 mM EDTA, 1% dimethyl sulfoxide, pH>13) for 25 minutes followed by electrophoresis at a constant voltage of 25 V for 25 minutes at 4°C. Finally, the slides were neutralized in 0.4 M Tris–HCl pH 7.5 and the DNA was stained with SYBR Green I. A total of 150 comets were scored for each sample using CometScore Version 1.5 software (TriTek corporation) and statistically significant differences in the distribution of comet olive moments were determined using the two-tailed Student’s t-test.  2.2.2 Analysis of sister chromatid exchange Mary Shago from the Hospital for Sick Children performed this experiment. Patient and control peripheral blood samples were cultured in MEM/FBS for a total of 72 hours. Thirty-six hours prior to harvesting, 30 µg/mL bromo-deoxyuridine (BrdU) (Sigma) was added to the cultures. Harvesting of cultures and slidemaking were performed according to standard cytogenetic techniques. Slides were aged at room temperature for 5 days and then  27  immersed in Hoechst 33342 Dye (final concentration 3 µg/mL) (Sigma) for 1.5 hours while protected from the light. After rinsing with PBS and coverslipping, the slides were exposed to ultraviolet light (365 nm) for 2 hours. Coverslips were removed, and the slides were rinsed again with PBS and stained with Giemsa (EMD). Sister chromatid exchanges were scored in 20 metaphase cells from the patient and control.  2.2.3 Immunoglobulin switch junction amplification and sequencing Genomic DNA was extracted from peripheral blood cells of 7 SIOD patients and 4 unaffected controls. Amplification, sequencing and analysis of the switch Sµ-Sα1 and SµSγ1 junctions were performed as previously described with minor modifications 178. In brief, a nested polymerase chain reaction (PCR) strategy was used to amplify Sµ-Sα1 and Sµ-Sγ1 junctions. In the first round of PCR reactions, 50 ng or 150 ng of genomic DNA from each individual was amplified in 8 parallel reactions using either Sµ1 and Sα-common-1 primers for a total of 35 cycles of 94°C for 1 minute, 60°C for 1 minute, and 72°C for 90 seconds, or Sµ1 and Sγ-common primers for a total of 35 cycles of 94°C for 1 minute, 66°C for 1 minute, and 72°C for 30 seconds, respectively. In order to amplify Sµ-Sα1 junctions, 1 µl of each Sµ1-Sα-common-1 reaction was amplified using Sµ5 and Sα1-specific primers in reactions consisting of 35 cycles of 94°C for 1 minute, 65°C for 1 minute, and 72°C for 1 minute. Also, in order to amplify Sµ-Sγ1 junctions, 3 µl of each Sµ1- Sγ-common reaction was amplified using Sµ5 and Sγ1-specific primers in reactions consisting of 40 cycles of 94°C for 1 minute, 66°C for 1 minute, and 72°C for 1 minute. PCR products from the second round of reactions were gel purified with QIAEX II Gel Extraction Kit (Qiagen) and sequenced using the Sµ5, 28  Sα1-specific, and Sγ1-specific primers. The switch fragment sequences were aligned with Sµ (X54713) /Sα1 (L19121) or Sµ /Sγ1 (U39737) reference sequences and microhomology at each switch junction was defined as the longest region of identity with both the Sµ and Sα1 or Sµ and Sγ1 reference sequences. The primers are listed in Table 2-1.  Table 2-1- Oligonucleotides used for amplification and sequencing of immunoglobulin switch regions. Switch region Sµ1 Sα-common-1 Sγ-common Sµ5 Sα1-specific Sγ1-specific  Sequence  Reference  GACCATGGGGACCTGCTCATTTTTATC ACGTCGACGCCCTCAGAACCCCTAAGAA  179  GTCTGCAGTGCCCCTGCCTGAGAGC  179  ACGCATGCGGCAATGAGATGGCTTTAG  179  ACGTCGACCAGTCCAGCCCAAGTCATC  180  ACGTCGACGCCCTCAGCTGTCTGTT  178  180  2.2.4 Smarcal1del/del mice and treatment with CPT-11, etoposide, and HU The Smarcal1del/del mice have a deletion of the first two coding exons of Smarcal1 (NM_018817.2:c.172_989del), which includes the replication protein A (RPA) binding site, nuclear localization signal and the first HARP domain. They were generated as described elsewhere 181. Smarcal1-deficient (Smarcal1del/del) and wild-type (Smarcal1+/+) male mice were divided into 4 groups (3-5 mice in each group) at the age of 4-weeks. Mice in each group were given intra-peritoneal (ip) injections of CPT-11 (40 mg/kg, Sandoz), etoposide (20 mg/kg, Sigma), HU (100 mg/kg, Sigma), or carrier (PBS, Gibco). After 5 consecutive daily injections, the mice were followed for 3 days, and then their spleens were harvested. To analyze the long-term effect of these drugs, mice were injected daily for 8 weeks. To assess the recovery of growth retardation, CPT-injected mice were observed for another 12 weeks 29  without further injections. At the end of the treatment, radiography of mice was performed using the Faxitron X-ray cabinet. The density of the distal femur was measured using a Scanco µCT35 scanner (Scanco Medical, Bassersdorf, Switzerland) as previously described 182  . To compare the toxicity of each drug among Smarcal1del/del and Smarcal1+/+ mice, 3-  4 mice of each genotype were given daily ip injections with CPT-11 (80 mg/kg), etoposide (40 mg/kg), HU (500 mg/kg) or PBS for 5 consecutive days and followed for two weeks unless sacrificed earlier.  2.2.5 Urinary creatinine and albumin assays Spot urine was collected from Smarcal1del/del and Smarcal1+/+ mice injected with PBS, CPT-11, etoposide or HU. Urinary creatinine was measured using the creatinine assay kit from Cayman Chemical Company (Ann Arbor, MI, USA) following the manufacturer’s instructions. Urinary albumin was measured using the mouse albumin ELISA kit from Immunology Consultants Laboratory (Portland, OR, USA) following the manufacturer’s instructions. Urinary albumin excretion was normalized to urinary creatinine for each sample.  2.2.6 Histopathology and TUNEL assay Mouse tissues for histopathology and TUNEL assay were fixed in 4% paraformaldehyde (PFA) in PBS, processed, paraffin embedded, and cut into 5 µm sections according to standard protocols as previously described 177. TUNEL detection of apoptotic cells in the spleens was carried out using the ApopTag Peroxidase In Situ Apoptosis Detection Kit (S7101, Chemicon), and the tissue was counterstained with Mayer’s 30  hematoxylin. Harris hematoxylin and eosin (H&E) staining of the femurs and Masson trichrome staining (Sigma) of the kidneys were performed following the manufacturers’ instructions. Images of the processed tissues were captured using a Zeiss Axiovert 200 microscope. For the distal femoral growth plate analysis, we counted all chondrocytes within the proliferative and hypertrophic zones and within 250 µm of the vertical midline.  2.2.7 Cell culture The isolation and culturing of human dermal fibroblast cell lines were performed as described by Clewing et al. 13. The SIOD patient fibroblasts (N859) were derived from patient SD31, who had a homozygous deletion of the first 5 exons of SMARCAL1 (NT_005403.17:g.[67482574_67497178del]+[67482574_67497178del]), and cultured in DMEM (Gibco) containing 15% fetal bovine serum (FBS; Gibco) and 1% antibiotic/antimycotic (penicillin, streptomycin and amphotericin B; Gibco) at 37°C and 5% CO2. Other cell lines including normal human fibroblasts (C5RO) and Cockayne syndrome B fibroblasts (CS188TOR and CS163TOR) were also cultured in DMEM containing 15% FBS and 1% antibiotic/antimycotic at 37°C and 5% CO2.  2.2.8 Cell survival assays Anja Raams from Erasmus Medical Center, the Netherlands performed this experiment. Cell survival following UV or illudin S treatment was performed using a modified assay based on tritiated thymidine incorporation 183. In brief, triplicate sparse cultures (5 x 103 to 1 x 104 cells/6-cm dish) of primary C5RO, N859, CS188TOR, and CS163TOR fibroblasts 31  were grown for 48 hours and exposed to illudin S (0, 0.2, 0.4, 0.6, 0.8, and 1 ng/ml) or UV (0, 5, 10, and 15 J/m2). After 3–5 days additional culture, the cells were pulse-labelled with tritiated thymidine (40–60 Ci/mmol, 5 µCi/ml) for 3 hours in presence of 20 mM HEPES pH 7.3. Following 30 minutes incubation in unlabelled medium, the cells were harvested and the incorporated radioactivity was measured in a liquid scintillation counter.  2.3 Results 2.3.1 SIOD patients have features observed in other disorders of DNA repair Comparison of SIOD patients to individuals with Bloom syndrome, Fanconi anemia, Cockayne syndrome, ataxia telangiectasia, Nijmegen breakage syndrome, xeroderma pigmentosum, Werner syndrome, Rothmund-Thomson syndrome, and RAPADILINO syndrome showed that SIOD shares many features with these disorders, including poor postnatal growth, immune defects, and premature atherosclerosis (Table 2-2) 156,161. Unlike these disorders, however, SIOD is not reported to predispose to cancer, although there are anecdotal reports of patients with non-Hodgkin lymphoma (NHL) 161,184,185. To ascertain better the prevalence of cancer in SIOD, we reviewed the medical records of 71 SIOD patients with identified biallelic SMARCAL1 mutations. Three individuals developed B-cell NHL in the first ten years of their life, and two had EBV positive tumors. One individual developed osteosarcoma. No other cancers were reported for this cohort.  32  Table 2-2- Comparison of the prominent clinical features of SIOD to those of some DNA repair disorders 186-189. Clinical Feature Growth deficiency Radial ray defects Cognitive deficits Ataxia Corneal or lens defects Immunodeficiency Single cytopenias Pancytopenia Malignancy predisposition Photosensitivity Radiosensitivity Abnormal pigmentation Telangiectasias Thin hair Premature atherosclerosis Hypogonadism Chromosomal instability Poor lymphocyte mitogenic response DNA repair defect  BS  FA  CS  AT  NBS  XP  WS  RTS  RS  SIOD  + +  + + + +  + + + +  +/+ -  + + -  + + +/+  + +  + + +  + + -  + +  + + +  + + +  -  + + +  + + +  +  +  +/+/+/+  +  + + + -  + +  +/+  + +  + +/-  + +  + +  +  + + +  + NR +  +  + -  -  + +  + +  -  +/-  + +  + + -  NR  + +  + +  + +  + -  + +  + +  + -  + +  + +  NR NR  + -  +  -  -  +  +  -  -  +/-  -  +  HR  ICL repair, HR  TCNER  DSB repair  HR, BER, telomere maintenance  BER, HR?  Resolution of stalled replication/ transcription intermediates  Replication fork repair  DSB NER reapair, replication fork repair  Abbreviations: BS, Bloom syndrome; FA, Fanconi anemia; CS, Cockayne syndrome; AT, Ataxia telangectasia; NBS, Nijmegen breakage syndrome; XP, Xeroderma pigmentosum; WS, Werner syndrome; RTS, Rothmund-Thomson syndrome; RS, RAPADILINO syndrome; +, common feature; -, uncommon feature; +/-, presented as case reports; NR, not reported; HR, homologous recombination; ICL, interstrand crosslink; TC-NER, transcription-coupled nucleotide excision repair; DSB, doublestrand break; BER, base excision repair.  33  2.3.2 SIOD patient dermal fibroblasts and Smarcal1-deficient mouse embryonic fibroblasts do not have increased DNA breaks detectable by comet assay To determine if defects of DNA repair contribute to this increased prevalence of NHL, we used the alkaline comet assay to test for an increase in DNA breaks in fibroblasts deficient for SMARCAL1 or Smarcal1, the murine homologue. Neither SIOD dermal fibroblasts (N859) nor Smarcal1-deficient MEFs had an increased comet olive moment compared to control fibroblasts (Figure 2-1).  Figure 2-1- Analyses of DNA breaks in cultured SMARCAL1-deficient skin fibroblasts (N859) and Smarcal1-deficient mouse embryonic fibroblasts (MEFs) by alkaline comet assay. (A) Representative photographs of SYBR Green stained comet tails of control and SMARCAL1-deficient (N859) human skin fibroblasts. (B) Graph of the distribution of 150 alkaline comet olive moments for control and N859 fibroblasts (p = 0.27). (C) Representative photographs of SYBR Green stained comet tails of Smarcal1+/+ and Smarcal1del/del MEFs. (D) Graph of the distribution of 150 alkaline comet olive moments for Smarcal1+/+ and Smarcal1del/del MEFs (p = 0.22).  34  2.3.3 SMARCAL1 and DNA nucleotide excision repair Reminiscent of disorders of NER such as xeroderma pigmentosum and Cockayne syndrome, prominent ectodermal features of SIOD include hyperpigmented macules as well as fine sparse hair. Therefore, to test if a defect of NER might contribute to SIOD, we measured hypersensitivity of dermal fibroblasts from a patient with a homozygous deletion of SMARCAL1 promoter (SD31) 157 to ultraviolet light (UV) and to the anti-tumor antibiotic illudin S. The latter agent causes damage that is repaired exclusively by transcription coupled (TC)-NER. In contrast to Cockayne syndrome (CS) cells, which have a defect of TC-NER 183, SMARCAL1-deficient fibroblasts were not hypersensitive to either UV or to illudin S treatment (Figure 2-2).  Figure 2-2- Analysis of SMARCAL1 participation in nucleotide excision repair. (A) Survival curve comparing the sensitivity of SIOD (N859), unaffected (C5RO), and Cockayne syndrome B (CS-B, CS188TOR) skin fibroblasts to killing by UV radiation (254 nm). This is a measure of both TC-NER and global NER. (B) Survival curve comparing the sensitivity of SIOD (N859), unaffected (C5RO), and CS-B (CS163TOR) skin fibroblasts to killing by illudin-S. This is a measure of TC-NER. The data for this figure was provided by Anja Raams.  35  2.3.4 SMARCAL1 and DNA repair by homologous recombination To determine if SMARCAL1 participates in homologous recombination, we looked for the increased sister chromatid exchange (SCE) that arises from a failure to suppress ectopic recombination and crossing-over between homologous chromosomes 190. As detected by bromodeoxyuridine incorporation and Giemsa staining 190, the frequency of SCE in SIOD cells was within the normal range (Figure 2-3).  Figure 2-3- SMARCAL1 participation in homologous recombination. Photomicrograph of a metaphase spread from BrdU labelled SIOD lymphocytes showing no increase in sister chromatid exchange. The data for this figure was provided by Mary Shago.  2.3.5 SMARCAL1 and DNA repair by non-homologous end joining The efficient generation of antibodies and T-cell receptors requires competency for double strand break repair, particularly NHEJ 191,192. Therefore, to test if SIOD patients had defects of NHEJ that could account for their prominent T-cell immunodeficiency and occasional immunoglobulin deficits 161, we checked for a NHEJ defect altering immunoglobulin switching in SIOD patients. We analyzed 25 Sµ-Sα1 and 22 Sµ-Sγ1  36  immunoglobulin switch recombination junctions amplified from the peripheral blood DNA of 7 SIOD patients including one who died of NHL and had hypersensitivity to chemotherapy 185. Comparison of the junctions from these patients to those from 4 control individuals did not identify abnormalities such as increased switch junction homology or breakpoint mutations (Figure 2-4 and Appendices 1 and 2).  37  38  Figure 2-4- Examples of microhomology usage at Sµ-Sα1 and Sµ-Sγ1 junctions in the immunoglobulins of SIOD patients. (A) The Sµ and Sα1 reference sequences are aligned above and below the switch junction sequences from a SIOD patient (SD107) and a control (SD107.1). (B) The Sµ and Sγ1 reference sequences are aligned above and below the switch junction sequences from a SIOD patient (SD107) and a control (SD107.1). Microhomology (solid-line boxes) at each switch junction is the longest region of identity between the Sµ and Sα1 or Sγ1 reference sequences, whereas imperfect microhomology (dashed-line boxes) at each switch junction is the longest region of near identity (1 mismatch on either side of the breakpoint).  39  2.3.6 Smarcal1-deficient mice are hypersensitive to genotoxic agents Recent findings have indicated SMARCAL1 is a component of the DNA stress response and that SMARCAL1-deficient cells are hypersensitive to genotoxic agents hydroxyurea and camptothecin 139,141-144. However, so far we have been unable to find a definable defect of nucleotide excision repair, homologous recombination, or nonhomologous end joining in SMARCAL1-deficient fibroblasts. Therefore to clarify better the contribution of SMARCAL1-deficiency to hypersensitivity to genotoxic agents, we asked if Smarcal1del/del mice were hypersensitive to genotoxic agents (Table 2-3). Using growth and splenic cell apoptosis as outcome measures, Smarcal1del/del mice were more sensitive to CPT11, etoposide, or HU than were Smarcal1+/+ mice (Figure 2-5A-L and Figure 2-6A-J).  Table 2-3- Response of Smarcal1+/+ and Smarcal1del/del mice to exposure to CPT-11, etoposide and hydroxyurea. Compound CPT-11  Dose Frequency (mg/kg) 40 daily x 56 days 80  Etoposide  20 40  Hydroxyurea 100 500  daily x 5 days (1 week rest) daily x 10 days daily x 56 days daily x 5 days daily x 56 days daily x 10 days  Phenotype Smarcal1 Smarcal1del/del Intermittent diarrhea Chronic diarrhea, weakness, severe growth arrest Weight loss (2/3), Weight loss (3/3), mild diarrhea (2/3) diarrhea (3/3), severe weakness and death (2/3) Normal Severe growth arrest +/+  Weight loss (3/3), severe weakness (2/3), death (1/3) Normal  Weight loss and severe weakness (4/4), death (2/4) Mild growth arrest  Weight loss (4/4), death (1/4)  Weight loss (4/4), severe weakness and death (3/4) 40  41  Figure 2-5- Hypersensitivity of Smarcal1del/del mice to CPT-11. (A-D) Photomicrographs of TUNEL-positive nuclei in splenic tissue from postnatal day (P) 36 Smarcal1del/del and Smarcal1+/+ mice following 5 daily ip-injections with PBS. Panels C and D are higher magnification photomicrographs of the boxed areas in panels A and B, respectively. (E) Graph showing the average weight gain of Smarcal1del/del (n = 4) and Smarcal1+/+ (n = 4) mice receiving daily ip-injections of PBS from P28 through P84 and during 90 days following treatment (shaded area). (F) Representative skeletal radiographs of Smarcal1del/del and Smarcal1+/+ mice at P174 following 8 weeks of daily injections with PBS. (G-J) Photomicrographs of TUNEL-positive nuclei in splenic tissue from P36 Smarcal1del/del and Smarcal1+/+ mice following 5 daily ip-injections with CPT-11. Panels I and J are higher magnification photomicrographs of the boxed areas in panels g and h, respectively. (K) Graph showing the average weight gain of Smarcal1del/del (n = 3) and Smarcal1+/+ (n = 4) mice receiving daily ip-injections of CPT-11 from P28 through P84 and during 90 days following treatment (shaded area). (L) Representative skeletal radiographs of Smarcal1del/del and Smarcal1+/+ mice at P173 following 8 weeks of daily injections with CPT-11. (M-T) Photomicrographs of representative sections of the distal femoral growth plate of Smarcal1+/+ and Smarcal1del/del male mice treated with PBS or CPT-11 for 8 weeks. The tissue was stained with H&E. Panels Q-T are higher magnification photomicrographs of the boxed areas in panels M-P, respectively. Note the poorly organized columns of chondrocytes in the smaller hypocellular growth plates of the CPT-11 treated Smarcal1del/del mice. (U) Graph showing the mean bone density of the distal femur of Smarcal1+/+ and Smarcal1del/del mice treated either with PBS or CPT-11. Scale bars = 100 µm. Error bars represent one standard deviation. For statistically significant differences between Smarcal1del/del and Smarcal1+/+ mice, a * indicates p<0.05 and a ** indicates p<0.01. Abbreviations: CPT-11, irinotecan; ip, intraperitoneal; mg HA/ccm, milligrams hydroxyapatite per cubic centimeter.  42  43  Figure 2-6- Hypersensitivity of Smarcal1del/del mice to etoposide and HU. (A-D) Photomicrographs of TUNEL-positive nuclei in splenic tissue from P36 Smarcal1del/del and Smarcal1+/+ mice following 5 daily ip-injections with etoposide. Panels C and D are higher magnification photomicrographs of the boxed areas in panels A and B, respectively. (E) Graph showing the average weight gain of Smarcal1del/del (n = 4) and Smarcal1+/+ (n=3) mice receiving daily ip-injections of etoposide from P28 through P84. (F-I) Photomicrographs of TUNEL-positive nuclei in splenic tissue from P36 Smarcal1del/del and Smarcal1+/+ mice following 5 daily ip-injections with hydroxyurea (HU). Panels H and I are higher magnification photomicrographs of the boxed areas in panels F and G, respectively. (J) Graph showing the average weight gain of Smarcal1del/del (n = 5) and Smarcal1+/+ (n = 4) mice receiving daily ip-injections of HU from P28 through P84. (K-V) Photomicrographs of representative sections of the distal femoral growth plate of Smarcal1+/+ and Smarcal1del/del male mice treated with PBS, etoposide, or HU for 8 weeks. The tissue was stained with H&E. Panels Q-V are higher magnification photomicrographs of the boxed areas in panels K-P, respectively. Note the poorly organized columns of chondrocytes in the hypocellular growth plates of the etoposide and HU treated Smarcal1del/del mice. Also note the near absence of trabeculae in the etoposide treated Smarcal1del/del mice. (W) Graph showing the bone mean density of the distal femur of Smarcal1+/+ and Smarcal1del/del mice treated with PBS, etoposide or HU. Scale bars = 100 µm. Error bars represent one standard deviation. For statistically significant differences between Smarcal1del/del and Smarcal1+/+ mice, a * indicates p<0.05 and a ** indicates p<0.01. Abbreviations: HU, hydroxyurea; ip, intraperitoneal; mg HA/ccm, milligrams hydroxyapatite per cubic centimeter.  2.3.7 Irinotecan, etoposide, and hydroxyurea exposure partially recapitulate the bone phenotype of SIOD in Smarcal1-deficient mice Following detection of hypersensitivity of Smarcal1del/del mice to genotoxic agents, we asked whether these exposures would partially or fully recapitulate SIOD in the Smarcal1del/del mice. Reminiscent of the growth plates of SIOD patients 154,156, the distal femoral growth plates of Smarcal1del/del mice treated with genotoxic agents were hypocellular, and chondrocytes in the proliferative and hypertrophic zones formed less organized columns (Figure 2-5M-T, Figure 2-6K-V, and Figure 2-7A). Also, like the reduced bone density observed in some SIOD patients 164,193, micro-computed tomography scanning of the distal femurs revealed significantly reduced bone density in Smarcal1del/del mice treated with CPT-  44  11 (Figure 2-5U); the bone density was not significantly different from controls after treatment with etoposide or HU (Figure 2-6W). Additionally, we hypothesized that if CPT-11 treatment moves chondrocytes past a state-changed threshold required for expression of skeletal dysplasia in Smarcal1del/del mice, then the growth rate of Smarcal1del/del mice should not return to normal when CPT exposure was removed. To test this, we monitored CPT-11injected mice for another 12 weeks after discontinuation of CPT-11 injections; interestingly, the growth rates of the treated Smarcal1del/del mice approximated that of the Smarcal1+/+ mice negating this hypothesis (Figures 2-5E and K).  45  Figure 2-7- CPT-11, etoposide and HU exposure partially recapitulate SIOD phenotypes in Smarcal1del/del mice. (A) Plot of fold change in chondrocyte number in the proliferative (PZ) and hypertrophic (HZ) zones in the distal femoral growth plate of CPT-11, etoposide and HU -treated Smarcal1del/del (n=3-4) and Smarcal1+/+ (n=3-4) mice, relative to PBS-treated Smarcal1del/del (n=3) and Smarcal1+/+ (n=3) mice. (B) Graph showing urine albumin excretion by Smarcal1del/del mice relative to Smarcal1+/+ mice following PBS or CPT-11, etoposide and HU treatments. (C) Photomicrographs of representative Masson trichrome staining of the kidneys of Smarcal1+/+ and Smarcal1del/del male mice treated with PBS or CPT-11, etoposide and HU for 8 weeks. Scale bar = 100 µm. Error bars in panels A and B represent one standard deviation. For statistically significant differences between Smarcal1del/del and Smarcal1+/+ mice, a * indicates p<0.05.  2.3.8 Irinotecan, etoposide, and hydroxyurea exposure do not recapitulate the renal phenotype of SIOD in Smarcal1-deficient mice Besides skeletal dysplasia, renal failure is another cardinal feature of SIOD and one 46  SIOD patient developed renal failure following treatment with genotoxic agents 175. We hypothesized therefore that the Smarcal1del/del mice treated with genotoxic agents might also develop renal failure. Measurement of urine albumin excretion as well as Masson trichrome staining of the kidneys after 8 weeks of exposure to CPT-11, etoposide, and HU did not detect increased albuminuria in Smarcal1del/del mice or signs of sclerosis compared to controls (Figure 2-7B-C).  2.4 Discussion Despite superficial similarities to classical disorders of DNA repair, SIOD is a distinct disorder. The ectodermal defects cannot be ascribed to an obvious defect of NER as in Cockayne syndrome or xeroderma pigmentosum, and the immune defects cannot be ascribed to molecular defects of NHEJ as in ataxia telangiectasia and Nijmegen breakage syndrome. SIOD is not a classical cancer predisposition syndrome in which there is increased occurrence of multiple cancers although there is an increased prevalence of NHL and possibly osteosarcoma. The detection of EBV in 2 of the 3 NHL tumors suggests that the increased prevalence of NHL is attributable to the immunodeficiency. NHL is a heterogeneous group of malignancies with variable etiologic, morphologic, immune, genetic, and clinical features 194. Risk factors for NHL include congenital and acquired immunodeficiency, chronic antigen stimulation, autoimmune disorders, environmental factors, and genetic deficiency of NHEJ enzymes 195,196. Since the prevalence of NHL in the general population during the first ten years of life is 0.0026% 197, the relative risk for NHL in our cohort of SIOD patients is 1625 (95% confidence interval, 1567 to 1683). Although 47  defective DNA repair might in an undefined manner contribute to this, the absence of recurrent cancers during the lifetime of SIOD patients suggests that the immunodeficiency is likely the major contributor to the increased risk of NHL in SIOD. Whether the single SIOD patient with osteosarcoma represents an increased risk for osteosarcoma or is a coincidental co-occurrence is unclear. Assuming that this is not coincidental co-occurrence, the relative risk for osteosarcoma in our cohort of SIOD patients is 150 (95% confidence interval, 142 to 161) since the prevalence of osteosarcoma in the general population during the first twenty years of life is 0.0093% 197. An increased risk for osteosarcoma is also observed in the DNA repair disorders Rothmund-Thompson syndrome, RAPADILINO syndrome and Werner syndrome 198-200. Again, the absence of recurrent cancers during the lifetime of SIOD patients questions whether SIOD is a cancer predisposition disorder unless one assumes the patients die too early to manifest recurrent tumors. As an annealing helicase, SMARCAL1 resolves single to double-stranded DNA transitions 130 and contributes to reactivation of stalled replication forks, associates with double-strand DNA breaks, and facilitates cell cycle progression from the G2 to the M phase 139,141-144  . Four domains within the SMARCAL1 enzyme are critical to these functions: a  nuclear localization signal (NLS), a replication protein A (RPA) binding domain, two tandem HARP domains with annealing helicase activity, and a SWI/SNF ATPase and DNA binding domain 139,141-144,146,148,157. The deletion of the NLS, RPA and HARP domains is associated with SIOD in humans 13,155, and herein we show that mice with deletion of the homologous domains are hypersensitive to genotoxic agents. Extension of these observations to humans found that one SIOD patient was hypersensitive to anticancer agents 185, another with NHL  48  tolerated standard doses of R-CHOP chemotherapy (rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisolone) but then developed severe infection and delayed neutrophil recovery when treated with one cycle of ifosfamide (76.5 mL/hr x 24 hours) and etoposide (61 mg) for relapse and another with osteosarcoma tolerated and survived chemotherapeutic regimens adjusted for immunodeficiency. Definitive evidence of whether SIOD patients are hypersensitive to genotoxic agents will therefore only come as more patients are treated with anticancer agents; however, in the interim, caution in the use of such agents in SIOD patients seems advisable. Treatment of Smarcal1del/del mice with genotoxic agents induced growth retardation and skeletal features similar to those observed in SIOD. Additionally, exposure to CPT-11 did not induce a continued loss of growth potential after its removal suggesting that the growth of SIOD patients will be retarded by exposure to genotoxic agents during bone marrow ablation or treatment for cancer but that their growth rate will likely return to baseline when the genotoxic therapy is removed. In the management of SIOD, bone marrow transplantation is often considered for the immunodeficiency. Of concern, however, is the one SIOD patient who developed renal failure shortly after bone marrow transplantation 175. The question arises therefore as to whether this was the natural progression of SIOD or prematurely induced by the exposure to the genotoxic agents. The failure of genotoxic agents to induce albuminuria and renal sclerosis in Smarcal1del/del mice suggests that despite the potential hypersensitivity of SIOD patients to chemotherapy or bone marrow ablation, short-term treatment with genotoxic agents is unlikely to hasten renal failure. Nonetheless, since the four other SIOD patients treated with bone marrow transplantation died from viral infection, cerebral hemorrhage,  49  pulmonary embolism and pulmonary edema shortly after transplant, definitive evidence as to whether genotoxic agents cause long term sequelae in SIOD will only come as more patients survive cancer therapy and bone marrow transplantation. In the interim, the hypersensitivity of the Smarcal1del/del mice suggests caution in the use of such agents in SIOD patients. Regarding screening of SIOD patients for cancer, extra hematologic surveillance or imaging appear unnecessary. Patients should maintain close contact with their physicians, and symptoms that cannot be accounted for otherwise should be evaluated promptly as potential early indicators of cancer. In summary, SIOD patients have an increased risk for NHL that is likely attributable to their T-cell immunodeficiency and possibly for osteosarcoma; therefore patients should be evaluated promptly for cancer when they have unexplained symptoms. SIOD patients do not have a detectable defect of NER or NHEJ to explain their ectodermal or immunological features, but as shown by the hypersensitivity of Smarcal1del/del mice to some DNA damaging agents, some SIOD patients are likely to be hypersensitive to genotoxic drugs. We conclude therefore that extra caution should be observed during bone marrow ablation and administration of genotoxic agents to SIOD patients.  50  3. Contribution of gene expression alterations to the penetrance of SMARCAL1 mutations 3.1 Introduction In the previous chapter, I concluded that defective DNA repair is not a major contributor to the pathophysiology of SIOD. In this chapter I further analyze the molecular basis of SIOD and evaluate the role of SMARCAL1 in transcriptional regulation with the aim to characterize the underlying mechanism for the incomplete penetrance of SIOD. With the discovery of incomplete penetrance in 1925 201-203, it became apparent that not all individuals with identical mutant alleles necessarily manifest a trait. Incomplete penetrance has been attributed to genetic and environmental factors as well as to stochastic factors acting in development 5-8. In its strictest sense, incomplete penetrance applies to the entire lifetime of the individual 204, although some traits initially considered incompletely penetrant probably are better described as having age-dependent penetrance 204,205. Incomplete penetrance for autosomal recessive disorders is less commonly described than for autosomal dominant disorders, but it does occur 5,9-12. Examples of genetic and environmental modulators of incomplete penetrance in autosomal recessive disorders are illustrated by the following. The penetrance of the deafness phenotype in individuals with biallelic mutations of DFNB26 can be suppressed by a dominant allele of the DFNM1 locus 9. The penetrance of Bardet-Biedl syndrome can require the triallelic inheritance of mutations compromising BBSome complex assembly and vesicle trafficking to the ciliary membrane 10,206,207  . In cystic fibrosis, the T7 polypyrimidine (poly-T) track variant in intron 8 of CFTR  leads to more efficient splicing of exon 9 and reduces penetrance of the p.R117H mutation 51  and cystic fibrosis to 0.03% for individuals with the compound heterozygous mutations p.[R117H; T7] + [∆F508] 11,208,209. Suppression of phenylketonuria in individuals with biallelic mutations of PAH is possible through restriction of dietary phenylalanine 187. Lastly, the penetrance of hemochromatosis in individuals with biallelic mutations of HFE depends on a combination of genetic factors such as polymorphisms in iron metabolism genes and environmental factors affecting the iron load such as alcohol, dietary iron intake, age, and gender 12,210. Despite delineation of the underlying mechanism for incomplete penetrance in some of these disorders, however, the basis of incomplete penetrance remains undefined for most autosomal recessive disorders including Schimke immuno-osseous dysplasia (SIOD). Recently two families have been reported in which siblings of affected individuals have incomplete penetrance of SIOD 159,171. As mentioned earlier in chapter 1, SIOD is associated with biallelic mutations in SMARCAL1 that cause loss of SMARCAL1 enzymatic function 130,155,157. The SMARCAL1 enzyme is a DNA annealing helicase 130 and serves as a DNA stress response protein that participates in the maintenance of genomic integrity at stalled replication forks 139,141-144. Since components of DNA repair pathways frequently participate in transcription 211-218 and since variations in transcription can modulate trait penetrance 8, we hypothesized that SMARCAL1 also modulates transcription and that penetrance of SMARCAL1 deficiency results from further alteration of gene expression. To test these hypotheses, we explored the effect of deficiency of the human, Drosophila, and mouse SMARCAL1 orthologues on gene expression and the interaction of such deficiency with environmental and genetic modifiers of transcription. We find that in humans, flies and mice, deficiency of the respective SMARCAL1 orthologue alters expression  52  of many genes and that in flies and mice deficiency of the respective orthologue is insufficient to cause disease in the absence of additional environmental or genetic insults.  3.2 Materials and methods 3.2.1 Drosophila genetic studies Kyoung Sang Cho and Marie Morimoto performed the Drosophila genetic studies. y1;P{SUPorP}Marcal1KG9850/CyO flies, which have a P element insertion in the Drosophila homologue of SMARCAL1 (Marcal1) at 25B4, were obtained from the Bloomington Drosophila Stock Center (Bloomington). The loss-of-function mutant was obtained by imprecise P element excision 219; this deleted 679-bp nucleotides extending from the middle of the first exon into the second intron. The Marcal1del flies were crossed to w1118 flies for 8 generations. For expression of tagged and untagged Marcal1 cDNAs, we generated 5 transgenic lines in w1118 flies using the pUAST and pUASP vectors: 1) UAST-Marcal1, 2) UAST-HAGFP-Marcal1, 3) UAST-SMARCAL1, 4) UASP-HA-GFP-Marcal1 and 5) UAST-N-DamMarcal1. All the other UAS lines, insertions, and GAL4 lines used in this study were obtained from the Bloomington Drosophila Stock Center. Using the SMARCAL1 and Marcal1 overexpression lines MS1096-GAL4/MS1096GAL4; +/+; pUAST-SMARCAL1/pUAST-SMARCAL1 and pUAST-Marcal1/CyO; tubulinGAL4/TM3, Sb1, the F1 genetic screen was carried out at 28°C; all other crosses were performed at 20°C unless indicated otherwise in the text. For the wing phenotype analysis, images from ten wings for each genotype were acquired using a Zeiss Axiovert 200  53  microscope and scored by two independent readers. The reference for enhancement or suppression of the wing veins was the average of SMARCAL1 or Marcal1 overexpression flies crossed to w1118 mutants of three different genetic backgrounds (Bloomington stocks 3605, 5905, 6326). For egg hatching efficiency, three groups of 100 yw, Marcal1del/del, RpII2153 or 4 or 8 or K1  /FM7 and RpII2153 or 4 or 8 or K1/FM7;Marcal1del/del embryos were collected at 20ºC.  Hatching rates were calculated 45-48 hours after egg deposition.  3.2.2 ATPase activity assay Analyses of ATPase activity of Marcal1 and SMARCAL1 were performed by Kyoung Sang Cho and Leah Elizondo. The ATPase assay was performed with the purified Marcal1, SMARCAL1, and Smarcal1 proteins as previously described 157,220. To assay ATPase activity, HA-GFP-Marcal1 was immunoprecipitated from protein extracts of tubulinGAL4, UAST-HA-GFP-Marcal1/TM6B flies using the monoclonal anti-HA agarose conjugate (Sigma). His-tagged human SMARCAL1 and mouse Smarcal1 were purified from protein extracts of a stably transfected Flp-In T-Rex-293 cell lines (Invitrogen) using a HisBind Purification Kit (Novagen/EMD). ATPase activity of the SMARCAL1 mutants was measured using the Kinase-Glo Luminescent Kinase Assay (Promega). The ATPase reaction was performed using 20 ng/µl of SMARCAL1, ATPase Buffer (20 mM KPO4, 2 mM MgCl2, 40 mM KCl, 1 mM DTT, 100 µg/ml BSA, 100 µM ATP), and 75 nM hairpin loop DNA or ss-DNA or ds-DNA or total RNA or mRNA or tRNA. The DNA or RNA substrates were prepared by heating to 70°C for 3 min, followed by slow cooling to room temperature over time. Reactions were incubated at 37°C for 1 h. Kinase-Glo buffer was added to each 54  reaction mixture and incubated for 10 min at room temperature. ATPase activity was measured by luminescence.  3.2.3 Immunofluorescence Kyoung Sang Cho performed the immunofluorescence studies of Drosophila tissues. Polytene chromosomes of third instar larva were prepared and processed as described 221 and immunostaining of the polytene chromosomes, wing imaginal discs, and embryos were performed according to standard procedures 222. We used mouse anti-HA (1:200, Sigma), rabbit anti-acetyl-histone H4 (1:200, Upstate Biotechnology/Millipore), rabbit anti-trimethylK4-histone H3 (1:200, Upstate Biotechnology/Millipore) antibodies as primary antibodies. DNA was stained with 4',6-diamidino-2-phenylindole (1:1000, Sigma). Fluorophoreconjugated secondary antibodies were used to detect the primary antibodies. Immunofluorescence studies for human SMARCAL1 were performed with an antiSMARCAL1 antibody as previously described 157,223.  3.2.4 High-dimensional (11-Color) flow cytometry Mrinmoy Sanyal at Stanford University performed the flow cytometry analysis. Lymphoid tissues (spleen and thymus) from Smarcal1-/- and Smarcal1+/+ mice were harvested in RPMI-1640 medium containing 10% FCS. The tissues were pressed through 70 µm nylon cell strainer, suspended in 10 mL of PBS, and incubated with red cell lysis buffer (150 mM NH4CI) for 5 minutes. After washing with 10 volumes of PBS, single cell suspensions were stained with fluorochrome-conjugated anti-mouse B220, TCRaβ, CD4,  55  CD8, CD44 and CD25 antibodies (BD Biosciences) (Table 3-1). “Fluorescence-minus-one” controls were included to determine the level of nonspecific staining and autofluorescence associated with subsets of cells in each fluorescence channel. Propidium iodide was added to all samples before data collection to identify dead cells. High-dimensional flow cytometry data were collected on a LSRII FACS instrument (BD Biosciences). FLOWJO (TreeStar, San Carlos, CA) software was used for fluorescence compensation and analysis.  Table 3-1- Antibodies used for flowcytometry. Antigen TCRβ CD4 CD8 CD44 CD25 B220  Species specificity Mouse Mouse Mouse Mouse Mouse Mouse  Clone  Conjugation  H57-597 GK1.5 53-6.7 IM7 PC61 RA3-6B2  APC APCCy7 Pacific Blue PerCPCy5.5 PE Alexa 700  3.2.5 Cell cultures Human dermal fibroblasts from SIOD patients and unaffected individuals, and fibroblasts from Smarcal1+/+ and Smarcal1del/del embryos were cultured in DMEM (Gibco/Invitrogen) containing 15% fetal bovine serum (Gibco/Invitrogen) and 1% antibiotic/antimycotic (Gibco/Invitrogen) at 37°C and 5% CO2. The SIOD patient fibroblasts had the following mutations in the SMARCAL1 protein or gene: SD8: p.[L397fsX40]+[?], SD31: homozygous deletion of the first 5 exons of SMARCAL1 (NT_005403.17:g.[67482574_67497178del]+[67482574_67497178del]), SD60: p.[E848X]+[E848X], SD120: p.[R764Q]+[E848X], and SD123: p.[R17X]+[R17X].  56  3.2.6 Heat stress Drosophila: Kyoung Sang Cho, Joanna Lubieniecka, and Marie Morimoto performed the heat stress experiments in Drosophila. For assessing survival at 30ºC, 200 flies of each genotype (yw and Marcal1del/del) and sex were maintained in a temperature and humidity controlled incubator for 10 days. Surviving flies were tallied on day 10. To assess reproductive capacity, three groups of 100 yw and Marcal1del/del embryos (300 total for each genotype) were reared at different temperatures: group 1 was reared at 25ºC; group 2 was reared at 25ºC for the first 5 days and then shifted to 30ºC (25/30); and group 3 was reared at 30ºC. Flies surviving to adulthood were counted. For assessing gene or protein expression, ten 1-3-day-old female flies from each genotype (yw and Marcal1del/del) enclosed in a plastic vial with a cotton plug were heat stressed at 37°C in a water bath for 15, 30, 45, and 60 minutes with or without recovery for 1 hour at room temperature. Mouse: Three groups of 45 Smarcal1+/+ and 4-12 Smarcal1del/del female mice at 3-4 months of age were heat stressed at 39.5°C for 1, 3 and 10 hours as previously described 224. Human dermal fibroblasts: SIOD (SD31, SD120, and SD123) and control fibroblasts were heat stressed for 1 hour at 43°C followed by 1 hour of recovery at 37°C as previously described 225.  3.2.7 α-amanitin treatment Mice: Beginning at age 30 days, Smarcal1del/del and Smarcal1+/+ mice were injected intra-peritoneal daily with either PBS (n=9 Smarcal1del/del and n=7 Smarcal1+/+) or 0.1 mg/kg α-amanitin (Sigma) (n=9 Smarcal1del/del and n=7 Smarcal1+/+) diluted in PBS for twelve weeks. At the end of treatment radiography was performed using the Faxitron X-ray cabinet. Human dermal fibroblasts: SIOD (SD31, SD120, and SD123) and control dermal fibroblasts 57  were cultured in 96-well plates (3 x 103 cells/well). After 24 hours the media was supplemented with 0 or 1 µg/ml α-amanitin and the cells were analyzed 48 hours later for cell proliferation and viability using the MTT assay as previously described 226. To measure proliferation with Click-iT EdU assay (Invitrogen), fibroblasts were cultured in the Lab-Tek 8 chambered coverglass system (7.5 x 103 cells/well). After 24 hours the media was supplemented with 0 or 1 µg/ml α-amanitin and after another 24 hours 10 µM EdU was added to each well. EdU detection and analysis was performed after 24 hours using Alexa Fluor 555 and Zeiss Axiovert 200 microscope according to manufacturer’s protocol. Murine embryonic fibroblasts: Sensitivity of Smarcal1del/del and Smarcal1+/+ fibroblasts to αamanitin (0 and 1 µg/ml) was performed as described above for human fibroblasts.  3.2.8 RNA extraction RNA was extracted from the indicated tissue using the RNeasy Mini Kit (Qiagen). Elimination of genomic DNA was performed using either on-column DNase (Qiagen) or DNase I (Ambion) following RNA extraction at 37ºC for 1 hour. cDNA synthesis was performed using SuperScript III First Strand Kit (Invitrogen) or qScript cDNA SuperMix (Quanta Biosciences).  3.2.9 RT-PCR Human and mouse: RT-PCR was performed as described 13,157 using the primers listed in Table 3-2. Quantitative real-time RT-PCR was performed using the ABI 7500 Fast system and PerfeCTa Sybr Fastmx Lrx 1250 (Quanta Biosciences) or human or mouse heat  58  shock proteins and protein folding array (SABiosciences) following the manufacturer’s instructions. Drosophila: For cloning, the Marcal1 cDNA was amplified by PCR using Platinum Taq DNA Polymerase (Invitrogen) with the primers listed in Table 3-2 (94ºC for 5 minutes, 35 cycles of 94°C for 15 seconds, 55°C for 30 seconds and 68°C for 1 minute). PCR amplification of other cDNAs was done using HotStarTaq DNA Polymerase (Qiagen) with the primers listed in Table 3-2 (94ºC for 15 minutes, 30 cycles of 94°C for 1 minute, 57°C for 1 minute and 72°C for 1 minute). Quantitative PCR was performed using the ABI 7500 Fast system and PerfeCTa Sybr Fastmx Lrx 1250 (Quanta Biosciences).  59  Table 3-2- Oligonucleotide primers. Primer Marcal1 cloning Coding-F HA-coding-F Coding-R  Sequence ATGTCCACTTGCAGTTCATCCGAGATAGC ATGTACCCATACGACGTCCCAGACTACGCTATGTC CACTTGCAGTTCATCCGAGATAGC CTAAATATCTAATTCCAAAAAAGCCTCATC  Marcal1 mutagenesis K275R 5′ primer 3′ primer  GAAATGGGCCTGGGCAGAACCTATCAGGCCTTG CAAGGCCTGATAGGTTCTGCCCAGGCCCATTTC  Marcal1 deletion identification 5′-primer 3′-primer-1 3′-primer-2 3′-primer-3 3′-primer-4 3′-primer-5 3′-primer-6  TCAATTGATGTCGCAGCATGTCCACTT CCAGATACGGGTTTGGCCATCGTAGCACTT GGTGATTAGCACCTTGGCCTCACCCACATA AGGACGACAGTCTCACTGCGGATGGAAGAA TTCCTGAATTGCAGGCTTTTAGGGAGAGCA GCCGCGATATCCGACTCAGCCTTGTTTACT GCCAGGTCACATGAAACCGGCTATCTGAAA  Drosophila heat shock RT-PCR primers Hsp83 5′ primer 3′ primer Hsp68 5′ primer 3′ primer Hsp67Ba 5′ primer 3′ primer Hsp67Bb 5′ primer 3′ primer Hsp67Bc 5′ primer 3′ primer Hsp60 5′ primer 3′ primer Hsp60B 5′ primer 3′ primer Hsp27 5′ primer 3′ primer Hsp26 5′ primer 3′ primer Hsp23 5′ primer 3′ primer  GGGTTTCTACTCCGCCTACC CAGTCGTTGGTCAGGGATTT GACAACGGCAAACCAAAGAT GCGTCAATCTCCAAAGAAGC ATCGCCATCATCCGTACAAT CTGCGCATCCTTATCCTTCT GAAGGAAGAGCTCCAGCAGA ATTCATTCCAGGAGCCTTTG CCACGATATGTTCCCGAATC GAACTCCATCCTCCGACAAA GAGGTTATCGAGGGCATGAA TACTCGGAGGTGGTGTCCTC CAAAGTGGGTCCAAGAGGAA CGCATTTCCAAAAGTCCTGT GAGGATGACTTCGGTTTTGG ACTTGGCCTGTTCCTTGCT GATGGTGCCCTTCTATGAGC CCTTGGGATTCTCCTTCACA GTGTCGAAAATCGGAAAGGA CCTTGGGATTCTCCTTCACA  60  Primer  Sequence  Hsp22 5′ primer 3′ primer Hsf 5′ primer 3′ primer DnaJ-1 (Droj1) 5′ primer 3′ primer Gapdh2 5′ primer 3′ primer Drosophila N-Dam-Marcal1 RT-PCR primers 5′ primer 3′ primer  TGCGTTCCTTACCGATGTTT ACCTTGTCCGCCTCGTATC CCGCTGGCGGTAATATTCTA CCCAAATTTTTGTTGCTGGT CCACATTTGCCCAGTTCTTT TTGTCGCGAATGATGAAGAC ATCGTCGAGGGTCTGATGAC TCAGCTTCACGAACTTGTCG GGCACACGTAAAAAGGTGGA GGACCGCTCCTGTTGATCT  Mouse RNA polymerase II large subunit RT-PCR primers Polr2a 5′ primer GGAGGGTGATGAGGATCTGA 3′ primer GCCCAACACAAAACACTCCT Polr2b 5′ primer GTATTGAACCGCCTGACGTT 3′ primer TCCAAAATTGGAGAGGGTTG Human SMARCAL1 RT-PCR primers 5′ primer 3′ primer  CGCCTGACAGCTGGCCTGATC TTGGCAACCTTTAGGACCGGCATAG  Human SMARCAL1 RT-PCR primers 5′ primer 3′ primer  CGCCTGACAGCTGGCCTGATC TTGGCAACCTTTAGGACCGGCATAG  Human GAPDH RT-PCR primers 5′ primer 3′ primer  CTTTTGCGTCGCCAGCCGAG GGTGACCAGGCGCCCAATACG  Human RNA polymerase II large subunit RT-PCR primers POLR2A 5′ primer CGCTTAAGCCTTCCAACAAG 3′ primer GAGGACGACCTTGCTGTCTC POLR2B 5′ primer AAGAACCGCCACGATATTTG 3′ primer TTGACCGCAACATAATTGGA  3.2.10 Urinary protein and creatinine measurement Darren Bridgewater from McMaster University performed this experiment. Spot urine was collected from Smarcal1del/del and Smarcal1+/+ mice injected with alpha-amanitin or PBS. 61  Urinary creatinine measurement was performed using creatinine assay kit from Cayman Chemical Company (Ann Arbor) following the manufacturer’s instructions. Urinary albumin measurement was performed using the bromocresol green method. Ten dilutions of albumin standards from 0 to 8 g/dL were prepared. Two microliters of standards and samples were added to a 96-well plate in duplicates and then 200 µL of albumin reagent (Sigma) was added and mixed. After incubation at room temperature for 1 minute, the absorbance was measured at 630 nm and the concentration was calculated. Finally, the albumin/creatinine ratio was calculated for each sample.  3.2.11 Histopathology Smarcal1del/del and Smarcal1+/+ mice tissues were fixed in 4% PFA in PBS, paraffin embedded, and cut into 5 µm sections according to standard protocols 177. After H&E staining, tissues were analyzed using a Zeiss Axiovert 200 microscope. For the distal femoral growth plate analysis, we counted all chondrocytes within the proliferative and hypertrophic zones and within 250 µm of the vertical midline.  3.2.12 Apoptotic analysis Acridine orange staining for detection of apoptotic cells in 20-23 hour Drosophila embryos was performed as previously described 182. For human fibroblasts and MEFs, apoptotic cells were detected by TUNEL assay using ApopTag Peroxidase In Situ Apoptosis Detection Kit (S7100, Chemicon).  62  3.2.13 RpII knock-down Transfection of fibroblasts was carried out according to the Amaxa Biosystems Human Dermal Fibroblast Nucleofector Kit or the Amaxa Biosystems MEF Nucleofector Kit optimized protocol. For human dermal fibroblasts, we electroporated (Program U-023) 5.0 µg of a plasmid expressing a GFP-tagged shRNA targeting POLR2A (insert sequence: AACGAGTTGGAGCGGGAATTT) or POLR2B (insert sequence: TCAGGTTCATGTTTGCAATCT) (SABiosciences) or 5.0 µg of a plasmid expressing a GFP-tagged non-silencing shRNA (insert sequence: GGAATCTCATTCGATGCATAC) (SABiosciences). For MEFs, we electroporated (Program A-023) 2.5 µg of siRNA duplex 1 (Alexa-488-CAGAATCTGGCTACACTTAAA, Qiagen) or siRNA duplex 3 (Alexa-488CTCAATGATGCTCGAGACAAA, Qiagen) targeting Polr2a or non-silencing siRNA duplex (Alexa-488-ACGUGACACGUUCGGAGAA, Qiagen). Thirty-six hours later, we selected transfected cells by fluorescent activated cell sorting and plated them at a concentration of 1x103-104 cells/100 µL/well of 96-well Wallac cell culture plates. By quantitative real-time RT-PCR at 48 and 96 hours post-transfection, this method reduced expression of POLR2A by 50-80%, of POLR2B by 45-50%, and of Polr2a by 55-65% (siRNA duplex 1) or 70% (siRNA duplex 3). Cell viability and proliferation rate were assessed at 48, 72 and 96 hours post-transfection using the Cell Proliferation Reagent WST-1 (Roche) according to the manufacturer’s protocol and the relative proliferation rates were calculated for either the 24-hour (human fibroblasts) or 48-hour (mouse fibroblasts) intervals. The rate of cell growth in each group was compared for statistically significant differences using the two-tailed Student’s t-test.  63  3.2.14 RNA sequencing and data analysis Chad Shaw at Baylor College of Medicine performed the data analysis for the RNA sequencing. For RNA sequencing, three samples of liver RNA were extracted from each group of 3-4-month-old Smarcal1del/del and Smarcal1+/+ female mice at 20°C and after 1 hour at 39.5°C. The RNA samples for each group were pooled and RNA sequencing libraries were constructed and sequenced using the whole transcriptome shotgun sequencing procedure, as previously described 227-229. The sequencing was performed using two lanes per genotype of an Illumina Genome Analyzer II following the manufacturer’s instructions. Image analysis and base calling were done by the GA pipeline v1.0 (Illumina, Hayward, CA) using phasing and matrix values calculated from a control phiX174 library run on each flow cell. Raw quality scores were calibrated by alignment to the reference mouse genome (NCBI build 37, mm9) using ELAND (Illumina, Hayward, CA). Short read sequences obtained from the Illumina Genome Analyzer for each sample were mapped to the reference mouse genome (NBCI build 37, mm9) plus a database of known exon junctions 230 using MAQ in paired end mode 231. The exon junction sequences consisted of N-1 nucleotides of the donor exon ‘spliced’ to N-1 nucleotides of the acceptor exon for every known pair of exons in the mouse transcriptome, where N is the read length. This was designed to rescue reads that would not map to the mouse reference genome due to their spanning a splice site. The maximum insert size (-a parameter) to MAQ was 500. Mouse sequence summary count data were log2 scaled. All genes with a count per kilobase summary greater than 4 (log2 >2) in either temperature condition in Smarcal1+/+ samples were identified as well enough represented to be considered in our analysis. The mean log2 scaled expression summary (across both Smarcal1+/+ and Smarcal1del/del) was determined for each temperature state. The deviation of  64  each sample (computed by subtracting the observed value from the mean) for the base temperature condition was subsequently determined and plotted in the heatmap. For both heatmaps, the sort order was computed as follows: the difference between Smarcal1+/+ and Smarcal1del/del in each treatment condition was divided by the log2 expression value in the Smarcal1+/+ in the baseline temperature condition. The resulting scores for each treatment condition were averaged and then the genes were sorted according to this score for difference in the high temperature state. The density plots represent the distribution of expression difference values for each temperature state between the Smarcal1+/+ and Smarcal1del/del. The same genes plotted in the heatmap are represented in the line plot (probability density estimate plot).  3.2.15 Microarray gene expression analysis in human cells Chad Shaw at Baylor College of Medicine performed the data analysis for the microarray gene expression in human cells. For analysis of gene expression in primary cultured human dermal fibroblasts, 5.0 µg of total RNA from two biologically independent replicates was extracted from two SIOD (SD8 and SD60) and three from a control skin fibroblast cell lines, labeled and hybridized to Affymetrix Human Genome U133 Plus 2.0 Arrays. CEL file data were normalized using the GCRMA package from the Bioconductor suite 232. Present-absent p values were calculated in R using the Affymetrix test statistic 233. Subsequent to deriving expression measures, an ANOVA model was fit to each genotype (Y=Genotype + Error), where Y is the normalized expression measure for a gene on a particular microarray. The model was fit using the LIMMA R package 234. Coefficients for the linear model were estimated by least squares method. Linear contrast scores were used to 65  compare gene lists between the genotypes. Determination of up- and down-regulation of expression is made by computing a T-statistic for SIOD and control samples, and then adjusting the variance estimate using the empirical Bayes method as implemented in the LIMMA R Package. The p-values obtained are then converted to Q-values using the LBE R package 235,236 to control the false discovery rate (FDR) at 0.05. A pair of lists was determined as well as linear contrast values (log2 fold changes) comparing the SIOD patients and the control. A Q-value cutoff of 0.05 was used to determine a pair of lists for the probe sets either overexpressed or underexpressed.  3.2.16 Microarray gene expression analysis in flies Chad Shaw at Baylor College of Medicine performed the data analysis for the microarray gene expression in flies. For analysis of gene expression in flies, 5.0 µg of total RNA from three biologically independent replicates was extracted from 1) yw, 2) Marcal1del/del, 3) RpII2154/FM7, and 4) RpII2154/FM7;Marcal1del/del ovaries at 20°C and from yw and Marcal1del/del at 25°C, labeled and hybridized to Affymetrix Drosophila Genome 2.0 arrays. Affymetrix CEL file data were processed using the robust multi-array average (RMA) method as implemented in Bioconductor. The yw expression data from both the base and high temperature states were used to determine a set of "expressed" transcripts using the maximum RMA value for each probe set across all individual yw samples. Probe sets were identified as being expressed when the maximum RMA value was greater than or equal to six–a value determined by observation of the distribution of expression values in the yw samples. This analysis identified 6,437 probe sets, which were subsequently analyzed and visualized in the other genotypes. Linear contrast of the RMA values for each treatment was 66  compared by first computing the mean of RMA values with each treatment group and then comparing different pairs of groups of interest. The heatmap was generated by sorting the differenced values and plotting each probe set. The density plots are kernel probability density estimates of the linear contrast scores for the ensemble of 6,437 probe sets, determined to be expressed in yw. FlyBase IDs provided by the Affymetrix website were used to query the FlyBase information.  3.2.17 Gene Ontology (GO) analysis GO analysis was performed using the Database for Annotation, Visualization and Integrated Discovery (DAVID ) v6.7 237,238. Differentially expressed genes (q-value <0.05) between yw vs. Marcal1del/del, yw vs. RpII2154, and yw vs. RpII2154;Marcal1del/del ovaries at 20°C, yw vs. Marcal1del/del ovaries at 25°C, differentially expressed genes (fold-change > 2) between Smarcal1+/+ vs. Smarcal1del/del mouse livers at 20°C, Smarcal1+/+ vs. Smarcal1del/del mouse livers at 39.5°C, and differentially expressed genes (q-value <0.05 and fold-change > 2) between control vs. SIOD fibroblasts, were analyzed for their enrichment in biological process GO biological process annotation terms at all levels.  3.2.18 DNA adenine methyltransferase analysis of Marcal1 binding Marie Morimoto made the Dam-Marcal1 constructs and Bas Tolhuis at the Netherlands Cancer Institute performed the DNA adenine methyltransferase analysis of Marcal1 binding. Full-length Marcal1 was cloned into pNDamMyc such that Dam was fused in frame with the amino terminus of Marcal1. This construct was transfected into Kc167 cells as previously described 239. For microarray analyses, we used a 385K tiling array 67  (NimbleGen Systems/Roche, Madison WI), which was designed by the group of Bas van Steensel (NKI – Amsterdam, The Netherlands). This array contained 60-mer oligomers roughly every 300 base pairs across the entire nonrepetitive part of the Drosophila genome (release 4.3). We made two independent biological replicate experiments that were differentially labeled and in parallel hybridized to the microarrays. The individual replicates were normalized, using Lowess Normalization methods. For each replicate, we defined Marcal1 binding sites as described 239. First, we removed random noise by calculating a running median with a window size of 15 consecutive probes (i.e. ~4.5 kbp). We defined a Marcal1 binding site as: at least two consecutive probes along the DNA template that have a log2-transformed binding ratio (N-Dam-Marcal1/Dam) higher than an empirically determined threshold. This threshold was determined on randomly shuffled data, giving an estimate of the FDR. This FDR was defined as the number of binding sites in the random data / the number of sites in observed data. We chose a threshold that equals the standard deviation of log2-transformed binding ratios across all probes on the microarray, giving FDRs of ~1% and 0% for replicates 1 and 2, respectively, indicating that our definition of a binding site is highly stringent. Next, we further increased confidence in our data by selecting only binding sites that were identified in both replicates. Finally, we identified target genes using the start and end coordinates of Marcal1 binding sites and FlyBase R4.3 gene annotation (www.flybase.org). As the minimal requirements for a target gene, we chose at least one nucleotide overlap with at least one Marcal1 binding site. We used this list of target genes to divide previously published data into target and non-target genes. These data sets include chromatin accessibility 240, gene expression 241, DNA replication timing241, histone acetylation 242, histone methylation 239, and a non-specific antibody control (rabbit anti-IgG)  68  239  . Data derived from Greil et al. 240 and Schubeler et al. 241,242 compared 638 targets to 4718  non-targets, and data from Tolhius et al. 239 compared 1026 targets to 8964 non-targets. Density distribution plots, statistical tests, and alignment plots of Marcal1 binding around transcription start and termination sites of 1822 target genes were made with R (www.rproject.org).  3.3 Results 3.3.1 Deficiency of Marcal1 is insufficient for disease manifestations in Drosophila To investigate whether deficiency of SMARCAL1 orthologues is sufficient to cause disease, we developed a Drosophila melanogaster model. Similar to human SMARCAL1, the only fly orthologue (Marcal1), also encodes a DNA-specific ATPase (NP_608883.1, Marcal1) (Figure 3-1A and B); it shares 32% amino acid identity and 44% amino acid similarity with SMARCAL1 155. Like human SMARCAL1 and mouse Smarcal1 157,158,162,223, Marcal1 is a nuclear protein and is highly expressed in the early embryo and developing tissues and gonads (Figure 3-2). By mobilizing P-element KG9850 and screening for deletions of the Marcal1 gene, we generated a loss-of-function Marcal1 mutant that lacked 679-bp extending from the middle of the first exon into the second intron (NM_135039.1:c. 673_1258delinsATGATGAAATAACATCATTATATCGATTAACACAG, p.G225MfsX3, Marcal1del, Figure 3-3A). Marcal1del/del flies did not express Marcal1 mRNA and protein (Figure 3-3B-C), and surprisingly, like the unaffected individuals with biallelic SMARCAL1  69  mutations 159,171, the mutant flies exhibited no morphological differences from wild type flies and had a normal life span at 20ºC.  70  Figure 3-1- DNA specificity and chromatin binding of Marcal1, SMARCAL1 and Smarcal1. (A) Radiograph of a thin layer chromatography plate showing that Marcal1 has DNAdependent ATPase activity. Purified hemagglutinin (HA)-tagged Marcal1 was immunoprecipitated from transgenic flies expressing HA-tagged Marcal1 under induction (I) of the tubulin-GAL4 driver. Control immunoprecipitates were prepared in parallel from transgenic flies carrying the UAS-HA-Marcal1 transgene but not expressing it (U, uninduced). Both sets of immunoprecipitates were assayed for ability to hydrolyze ATP to AMP and pyrophosphate (Pi) in the presence (+) or absence (-) of DNA, mRNA, rRNA, tRNA, or total RNA. Calf intestinal phosphatase (CIP) was used as positive control, and the samples containing only DNA or buffer without immunoprecipitated enzyme were used as negative controls. (B and C) Plots showing the DNA-dependent ATPase activity of SMARCAL1 and Smarcal1 as measured by Kinase-Glo Luminescent Kinase Assay. For these assays, His-tagged SMARCAL1 and Smarcal1 were purified from HEK293 cells using a nickel column following induction of expression with tetracycline. Nickel column elution fractions from uninduced cells were used as negative controls. Error bars represent one standard deviation. (D) Photographs showing immunofluorescence localization of HA-tagged Marcal1 on polytene chromosomes from tub-GAL4, UAS-HA-Marcal1 flies. Note that Marcal1 (green) binds the interband regions and co-localizes with trimethyl-K4-histone H3 (H3K4me3; red). (E) Photographs showing immunofluorescence localization of human SMARCAL1 on polytene chromosomes from MS1096-GAL4, UAS-SMARCAL1 flies. Note that SMARCAL1 (green) also binds the interband regions and co-localizes with H3K4me3 (red). The data for panels A, D and E was provided by Kyoung Sang Cho and data for panel B was provided by Leah Elizondo.  71  Figure 3-2- Temporospatial expression of Marcal1 in Drosophila cells and tissues. (A) Photograph of S2 cells expressing GFP-tagged Marcal1. (B) Photograph of an ovarian nurse cell dissected from a transgenic fly expressing GFP-tagged Marcal1. (C) Photograph of immunofluorescently detected endogenous Marcal1 expression in the wing imaginal disc. The upper panel was treated with anti-Marcal1 serum and the lower panel with preimmune serum. (D) Northern blot analysis of Marcal1 expression during Drosophila development. The data for this figure was provided by Kyoung Sang Cho.  Figure 3-3- Generation of a fly model for the study of Marcal1 function. (A) Diagram showing that imprecise excision of P element KG9850, which is inserted within exon 1 of Marcal1, was used to generate a fly line deficient for Marcal1 (Marcal1del/del). The mutation generated by this imprecise excision was c.673_1258delinsATGATGAAATAACATCA, p.225Mfs228X. (B) Northern blot analysis showing the absence of Marcal1 mRNA in Marcal1del/del flies. 3 µg of mRNA were used for Northern blot analysis. (C) Immunoblot analysis showing the absence of Marcal1 protein in Marcal1del/del flies. One yw, one Marcal1del/del, and one T>GFP-Marcal1 (tubulin-GAL4, UAS-HA-GFP-Marcal11/TM6B) male fly (about 10 µg of protein of extract) were used. The rabbit polyclonal anti-Marcal1 antibody was used to probe the blot. The data for this figure was provided by Kyoung Sang Cho.  72  3.3.2 Deficiency of murine Smarcal1 is insufficient to cause disease To address whether the absence of disease in Marcal1-deficient flies was attributable to the absence of tissues such as bones, mammalian kidneys, and T cells, we analyzed mice deficient for Smarcal1 181. Smarcal1 is the only SMARCAL1 orthologue in mice and encodes a DNA-specific ATPase (NP_061287.2, Smarcal1) (Figure 3-1C) that has 72% amino acid identity and 78% amino acid similarity to the human SMARCAL1 155. The Smarcal1del/del mice did not show developmental, growth or physical abnormalities or other signs of disease through 24 months (Figure 3-4A-L). Analysis of lymphatic tissues showed that Smarcal1del/del mice had a reduction in their B-cell count but no T-cell deficiency (Figure 34M-P). Therefore, like the incomplete penetrance reported for the two human families 159,171, deficiency of the respective SMARCAL1 orthologue in fruit flies and mice was insufficient to cause overt disease.  73  Figure 3-4- Phenotypic comparison of Smarcal1+/+ and Smarcal1del/del mice. (A) Graphs comparing the body weights and lengths of newborn (P0) Smarcal1+/+(n=20), Smarcal1+/del (n=55), and Smarcal1del/del (n=20) littermates. The error bars represent one standard deviation. None of the differences in these graphs are statistically significant. (B) Genotypes of the offspring of Smarcal1+/del x Smarcal1+/del parents. Note that the genotypes of the offspring have a Mendelian ratio both at birth and at weaning. (C) Graphs comparing the body weights and lengths for each sex of 6 month-old Smarcal1+/+ (9 males and 21 females) and Smarcal1del/del (31 males and 24 females) littermates. The error bars represent one standard deviation. None of the differences in these graphs are statistically significant. (D-G) Photographs of representative H&E staining of the proximal tibia of 6 month-old Smarcal1+/+ (D and E) and Smarcal1del/del (F and G) mice. Panels E and G are higher magnifications of the boxed areas on panels D and F, respectively. Note similar structure and cellularity of the growth plates between Smarcal1+/+ and Smarcal1del/del mice. Bar = 100µm. (H-K) Photographs of representative H&E staining of the kidney cortex from 6 month-old Smarcal1+/+ (H and I) and Smarcal1del/del (J and K) mice. Panels I and K are higher magnifications of the glomeruli boxed on panels H and J, respectively. Note similar glomeruli and tubular structures between Smarcal1+/+ and Smarcal1del/del mice. Bar = 100 µm. (L) Graphs comparing the urinary excretion of protein over 24-hours by 2 and 12 month-old Smarcal1+/+ (n=4) and Smarcal1del/del (n=4) mice. The protein excretion was normalized to the urinary creatinine. The error bars represent one standard deviation. (M) Plots show the 74  representative FACS analysis of the thymus from Smarcal1+/+ (n=3) and Smarcal1del/del (n=3) mice for different lymphocyte subsets. Thymocytes were initially analyzed for T-cell developmental stages based on CD4 and CD8 staining. Double negative (CD4-CD8-) cells were further resolved based on CD44 and CD25 expression into DN1 (CD44+CD25-), DN2 (CD44+CD25+), DN3 (CD44-CD25+) and DN4 (CD44-CD25-) fractions. (N) Quantification of lymphocyte subsets analyzed in panel M. The error bars represent one standard deviation. (O) Plots show the representative FACS analysis of the spleen from Smarcal1+/+ (n=3) and Smarcal1del/del (n=3) mice for different lymphocyte subsets. Splenic B and T cells were initially resolved based on expression of B220 (CD45R) and TCRαβ. Subsequently, T cells (TCRab+) were further resolved into CD4+ and CD8+ T-cell subsets. Note that there is a significant reduction of B cells (B220+) in Smarcal1del/del spleen. (P) Quantification of lymphocyte subsets analyzed in panel O. The error bars represent one standard deviation. The data for panel L was provided by Darren Bridgewater and data for panels M-P was provided by Mrinmoy Sanyal.  3.3.3 SMARCAL1 and Marcal1 bind open chromatin To better understand the function of proteins encoded by SMARCAL1 orthologues in the nucleus, we analyzed the association of SMARCAL1 and Marcal1 with chromatin. We used immunofluorescence to localize HA-tagged SMARCAL1 and Marcal1 on polytene chromosomes from third instar fruit fly larvae. Both SMARCAL1 and Marcal1 colocalized with trimethyl-K4 histone H3 and acetylated histone H4, which are markers of transcriptionally active chromatin (Figure 3-1D-E and Figure 3-5). To confirm and to define better this binding, we tagged Marcal1 on the amino terminus with DNA adenine methyltransferase (Dam), which methylates adenine at GATC sequences 243; we judged the fusion protein to be functionally active since in vivo expression of Dam-Marcal1 induced extra wing veins similar to untagged Marcal1 or SMARCAL1 157 (Figure 3-6A-B and Figure 3-7). Following transient expression of Dam-Marcal1 in Drosophila Kc167 cells, we found increased adenine methylation in regions enriched for trimethyl-K4 histone H3 and for acetylated histone H3 and H4 (Figure 3-6C-E). The regions of increased adenine methylation also corresponded with accessible, transcriptionally active and early replicating chromatin 75  (Figure 3-6F-H and J). In contrast, adenine methylation was decreased in regions enriched for trimethyl-K27 histone H3 (Figure 3-6I), a mark of inactive chromatin 239. The enrichment for adenine methylation spanned transcribed regions and was preferentially enriched in promoter regions compared to the rest of the gene (Figure 3-6K-L). To determine if this preference for promoter regions might correlate with promoter proximal pausing or stalling of RNA polymerase II (RpII) 244, we compared our adenine methylation data to published RpII distribution in S2 cells 232 or Toll10b embryos 245. This showed that adenine methylation was enriched in genes bound by RpII regardless of whether the RpII was stalled or active and was underrepresented in genes without RpII binding. In contrast, transcriptionally inactive Polycomb (Pc) targets 239 were underrepresented among actively transcribed RpII genes (Table 3-3). Thus, Marcal1 likely has a broader role in transcription than modulating promoter proximal pausing or stalling of RpII.  Figure 3-5- Photographs showing immunofluorescent co-localization of Marcal1 (green) with panacetyl-histone H4 (AcH4; red) on Drosophila polytene chromosomes. GFP-Marcal1 was expressed in transgenic flies (tubulin-GAL4, UAS-HA-GFP-Marcal1). The data for this figure was provided by Kyoung Sang Cho.  76  Figure 3-6- Expression of Marcal1 tagged with DNA adenine methyltransferase (Dam) on its amino terminus methylates adenine in genomic regions of Kc167 cells with hallmarks of active transcription. (A) Photograph of an agarose gel showing that by RT-PCR tubulin-GAL4 specifically induces expression of Dam-Marcal1 in transgenic UAS-Dam-Marcal1;tub>GAL4 flies. (B) Expression of Dam-Marcal1 in UAS-Dam-Marcal1;tub>GAL4 flies induces extra wing veins similar to those observed in UAS-Marcal1;tub>GAL4 flies. (C-J) Density distribution plots showing relative frequencies (y-axes) of adenine methylation (Dam-Marcal1 target regions, black) and absence of adenine methylation (non-target regions, grey) for the indicated log2transformed features: (C) trimethylation levels of lysine 4 of histone H3 (H3K4me3, a mark 77  of actively transcribed chromatin), (D) acetylation levels of histone H3 (a mark of actively transcribed chromatin), (E) acetylation levels of histone H4 (a mark of actively transcribed chromatin), (F) chromatin accessibility (open and closed chromatin), (G) mRNA expression levels, (H) DNA replication timing, (I) trimethylation levels of lysine 27 of histone H3 (H3K27me3, a mark of non-transcribed genes) and (J) a non-specific antibody control (rabbit anti-IgG). The log2-transformed features were obtained from previously published genomewide data 239-242. All p-values were calculated using the Mann-Whitney U test. (K and L) Alignment plots showing the log2-transformed median adenine methylation level (y-axes) relative to transcription start sites (K) and termination sites (L) of all target genes. The grey shading indicates the transcribed region. Transcription start and termination sites are at position 0 (dashed vertical lines). Note that Dam-Marcal1 preferentially targeted transcriptional start and termination sites. The data for panels A and B was provided by Marie Morimoto and data for panels C-L was provided by Bas Tolhuis.  Figure 3-7- Photographs of Drosophila wings showing the extra wing veins induced by expression of Marcal1 and SMARCAL1. Marcal1 (A) and SMARCAL1 (B) expression were driven in transgenic flies by the GAL4UAS system. No extra wing veins are observed with the UAS-Marcal1 or UAS-SMARCAL1 constructs alone or with the GAL4 drivers (tubulin>GAL4 or MS1096>GAL4) alone. Also, note the absence of ectopic wing veins when the expressed protein product has no ATPase activity (Marcal1K275R and SMARCAL1R586W) 157,246. The data for this figure was provided by Marie Morimoto.  78  Table 3-3- Distribution of RpII for Marcal1 and Pc target genes. Data  RpII absent  Source  Profile  Toll10b  S2  Marcal1  Obser ved (%) 15  Expe cted (%) 39  Pc  45  Marcal1 Pc  RpII stalled χ2  5E-69  Obse rved (%) 21  Expe cted (%) 11  39  1  27  28  55  2E-82  64  55  7E-04  RpII active χ2  6E-25  Obse rved (%) 33  Expe cted (%) 27  11  2E-45  11  15  5  8E-41  12  5  5E-11  RpII undetermined χ2  χ2  0.2  Obse rved (%) 32  Expe cted (%) 23  7E-09  27  1E-24  17  23  0.1  42  29  3E-22  -  -  -  13  29  7E-25  -  -  -  - Expected is based on genome-wide distribution of RpII - P values from the χ2 test were corrected for multiple testing, using Bonferroni correction  3.3.4 Marcal1 and SMARCAL1 genetically interact with transcriptional components To obtain genetic evidence that Marcal1 and SMARCAL1 are involved in transcription, we conducted a screen in Drosophila melanogaster for enhancers and suppressors of the wing vein phenotype induced by expressing Marcal1 or SMARCAL1 under the control of the UAS promoter and the tubulin-GAL4 or MS1096-GAL4 drivers, respectively (Appendix 3) 157. We observed epistatic interactions with mutations of transcriptional regulators including chromatin proteins, mediator complex members, RpII complex components, and transcription initiation, elongation, and termination factors (Appendix 3). Generally, but not always, loss-of-function mutations of transcriptional enhancers suppressed the wing vein phenotype, whereas loss-of-function mutations of transcriptional repressors enhanced the wing vein phenotype.  79  3.3.5 SMARCAL1 deficiency alters gene expression in SIOD skin fibroblasts To clarify whether the SMARCAL1 chromatin binding and its genetic interactions with transcriptional components were indicative of function, we checked if deficiency of SMARCAL1 altered gene expression. Using the Affymetrix Human Genome U133 Plus 2.0 Array, RNA derived from dermal fibroblasts of two SIOD patients (SD8 and SD60) showed significantly (q-value<0.05) altered expression of 5644 genes (log2 median fold change of 0.255) (Figure 3-8 and http://www.ncbi.nlm.nih.gov/gds GEO accession number GSE35551). Of these, 632 had >2 fold higher expression and 766 genes had >2 fold lower expression. The gene ontology (GO) biological process annotations enriched among these differentially expressed genes included cellular and molecular metabolic processes, programmed cell death, cell cycle, signalling pathways and stress response (Appendices 4 and 5). Identification of the stress response was particularly intriguing since several patients with SMARCAL1 deficiency have developed severe migraine-like headaches, transient weakness, and transient paraplegia during hot weather (C.F.B., unpublished data). To test if SMARCAL1 modulated expression of heat shock genes, we heat stressed skin fibroblasts from a control individual and three SIOD patients (SD31, SD120, and SD123) for 1 hour at 43°C. Using quantitative reverse-transcriptase PCR (qRT-PCR), we found that many heat stress response genes were significantly over- or under-expressed in the SMARCAL1deficient fibroblasts (Figure 3-9 and Appendix 6).  80  Figure 3-8- SMARCAL1 deficiency alters gene expression. (A) Heat map of the log2 fold differences in RNA levels (q-value < 0.05) between control and SIOD patient (SD8 and SD60) skin fibroblasts. The RNA levels were measured using Affymetrix Human Genome U133 Plus 2.0 arrays and are the average of three biological replicates. (B) Density plot showing the distribution of the log2 fold differences in RNA levels (q-value < 0.05) between control and SIOD fibroblasts. The data for this figure was provided by Chad Shaw.  81  Figure 3-9- SMARCAL1 deficiency causes abnormal expression of heat stress genes. Volcano plots of qRT-PCR comparison of stress gene expression in SIOD dermal fibroblasts (SD31, SD120, and SD123) to that in control unaffected dermal fibroblasts after one hour incubation at 43ºC followed by one hour incubation at 37°C. Each plot is based on three biological replicates. 82  3.3.6 Marcal1 contributes to heat tolerance and modulates heat stress gene expression in Drosophila Given the abnormal response to heat stress by SIOD patients and SMARCAL1deficient skin fibroblasts, we hypothesized that heat stress modifies the penetrance of Marcal1 deficiency. To test this, we reared Marcal1del/del and yellow white (yw) control flies at 20ºC, 25ºC and 30ºC. Although no differences were noted at 20ºC, Marcal1del/del embryos and flies were significantly less viable at 25ºC (<75% viability) and at 30ºC (<20% viability) than yw control flies (Figure 3-10A-B). Also, compared to yw flies, Marcal1del/del flies had abnormal expression of heat shock genes and proteins both at baseline and after 15 minutes at 37ºC (Figure 3-11). The Marcal1del/del flies also laid smaller eggs than yw controls at 25ºC but not at 20ºC (Figure 3-10C-D). At 20ºC the mean (±SD) egg volume was 0.0116±0.0018 mm3 for yw vs. 0.0115±0.0015 for Marcal1del/del (n=100, p=0.56). In contrast, at 25ºC the mean (±SD) egg volume was 0.0117±0.0013 mm3 for yw vs. 0.0094±0.0015 for Marcal1del/del (n=100, p=7.45e-21). To see if this change in egg size correlated with altered gene expression, we compared RNA extracted from ovaries of yw and Marcal1del/del flies housed at 20ºC to those housed at 25ºC using Affymetrix Drosophila Genome 2.0 Arrays. We found significant differences (q-value<0.05) in the expression of 123 genes at 20ºC and of 148 genes at 25ºC; 81 genes were common in both groups. Furthermore, comparison of the gene expression differences between yw and Marcal1del/del ovaries at 20ºC and 25ºC showed a shift in the log2 median fold change from 0.01 at 20ºC to -0.03 at 25ºC (Figure 3-10E-F). For both 20ºC and 25ºC, the GO biological process annotations enriched among genes differentially expressed 83  between yw and Marcal1del/del ovaries included metabolic processes and response to stress (http://www.ncbi.nlm.nih.gov/gds GEO accession number GSE35552, and Tables 3-4 and 35).  84  Figure 3-10- Marcal1 and Smarcal1 deficiency increase susceptibility to heat stress. (A) Graph of the percent of yw control and Marcal1del/del flies surviving after 10 days at 30ºC. Error bars represent one standard deviation. (B) Graph of the percent of yw control and Marcal1del/del embryos surviving through eclosion when raised at 25ºC, when raised at 25ºC for the first 5 days and then switched to 30ºC, or when raised at 30ºC. Error bars represent one standard deviation. (C and D) Distribution plots of the dimensions of yw and Marcal1del/del eggs laid at 20ºC (C) or at 25ºC (D). (E) Heat maps of the log2 fold differences in all expressed mRNAs between yw and Marcal1del/del ovaries at 20ºC and at 25ºC. The RNA levels were measured using Affymetrix Drosophila Genome 2.0 arrays and are the average of three biological replicates. (F) Density plots showing the distribution of the log2 fold differences in gene expression between yw and Marcal1del/del ovaries at 20ºC and 25ºC. (G) Survival curve for Smarcal1+/+ (n=5) and Smarcal1del/del (n=12) mice maintained for 10 hours at 39.5ºC. (H) Heat map of the log2 fold differences for all expressed RNAs between Smarcal1+/+ and Smarcal1del/del livers at 20ºC and 39.5ºC. The RNA levels were derived from transcriptome sequencing and are the average of three biological replicates. (I) Density plots showing the distribution of the log2 fold differences in RNA levels between Smarcal1+/+ and Smarcal1del/del livers at 20ºC and 39.5ºC. The data for panels A and B was provided by Kyoung Sang Cho, data for panels C and D was provided by Marie Morimoto, and data for panels E, F, H and I was provided by Chad Shaw.  85  Figure 3-11- Effect of Marcal1 deficiency on expression of heat stress genes and proteins in 1-3 day old Drosophila females. (A) Graphs showing qRT-PCR measurement of stress gene mRNA levels in Marcal1del/del flies relative to yw control flies. The duration of heat shock at 37ºC and recovery at 20ºC is shown above the graphs. The values in each graph represent the mean of three independent experiments assessed in triplicate. The data was normalized to Gapdh2 mRNA levels. The error bars represent one standard deviation. (B) Photographs of immunoblots showing the expression of stress gene proteins in Marcal1del/del flies and yw control flies. The duration of heat shock at 37ºC and recovery at 20ºC is shown above. β-tubulin was used as a loading control. Abbreviations: del, Marcal1del/del flies; RQ, relative quotient. The data for panel A was provided by Joanna Lubieniecka, and data for panel B was provided by Marie Morimoto.  86  Table 3-3- Enrichment in biological process GO-terms (all levels) of differentially expressed genes (q<0.05) between Marcal1del/del and yw ovaries at 20oC. Term GO:0008152~metabolic process GO:0016043~cellular component organization GO:0006950~response to stress GO:0009056~catabolic process GO:0051716~cellular response to stimulus GO:0006259~DNA metabolic process GO:0033554~cellular response to stress GO:0006281~DNA repair GO:0006974~response to DNA damage stimulus  Count  p-value  50 24 9 9 7 6 5 4 4  0.077378231 0.04586477 0.073882931 0.084881356 0.037973165 0.052919286 0.079115927 0.067768971 0.089674196  Fold Enrichment 1.168941048 1.453506787 2.00765625 1.946818182 2.776018519 2.907013575 3.041903409 4.199019608 3.724347826  Table 3-4- Enrichment in biological process GO-terms (all levels) of differentially expressed genes (q<0.05) between Marcal1del/del and yw ovaries at 25oC. Term GO:0008152~metabolic process GO:0006950~response to stress GO:0033036~macromolecule localization GO:0008104~protein localization GO:0009888~tissue development GO:0002009~morphogenesis of an epithelium GO:0060429~epithelium development GO:0048729~tissue morphogenesis GO:0002164~larval development GO:0032787~monocarboxylic acid metabolic process GO:0002168~instar larval development  Count  p-value  58 11 11 10 10 8 8 8 4 4  0.096794378 0.03703737 0.053968425 0.027665154 0.054081143 0.011638694 0.014511411 0.018591517 0.038431652 0.084146882  Fold Enrichment 1.141870834 2.066359649 1.933435929 2.300214823 2.030820294 3.205988304 3.06956327 2.92043469 5.304024768 3.836954087  3  0.097172331  5.635526316  87  3.3.7 Smarcal1 contributes to heat tolerance and modulates heat stress gene expression in mice To test if heat stress modified penetrance in the Smarcal1del/del mice, we housed the mice at 39.5ºC. All Smarcal1del/del mice died within 6.5 hours, whereas only 20% of wildtype (Smarcal1+/+) mice died in 10 hours (Figure 3-10G). We used Illumina next generation sequencing to characterize the transcriptomes of livers from Smarcal1del/del and Smarcal1+/+ mice at an ambient temperature of 20ºC or following 1 hour at 39.5ºC (Figure 3-10H-I). At 20ºC, 365 genes had >2 fold higher and 940 genes had >2 fold lower gene expression in Smarcal1del/del livers compared to Smarcal1+/+ livers, and the affected genes mapped to multiple GO biological process annotations including cellular and molecular metabolic processes and gene expression (http://www.ncbi.nlm.nih.gov/gds GEO accession number GSE35553, and Appendices 3-8). Following 1 hour at 39.5ºC, 107 genes had >2 fold higher and 309 genes had >2 fold lower gene expression in Smarcal1del/del livers compared to Smarcal1+/+ livers, and the median of gene expression differences between Smarcal1del/del liver and Smarcal1+/+ liver shifted from a log2 median fold change of -0.06 at 20ºC to -0.24 at 39.5ºC (Figure 3-10H-I). The genes with altered expression mapped to multiple GO biological process annotations including cellular and molecular metabolic processes, gene expression, stress response and immune response (Appendices 9-10). To confirm the altered stress response identified in the liver transcriptome data, we used qRT-PCR to analyze heat shock gene expression in RNA isolated from the livers and brains of the 3-hour heat stressed Smarcal1del/del and Smarcal1+/+ mice. This confirmed dysregulated expression of heat shock genes in both tissues (Table 3-6).  88  Table 3-5- qRT-PCR measurement of mRNA levels of stress genes in the brain and liver of mice following 3 hours of heat shock at 39.5ºC. Gene Dnajc21 Atf6 Bag1 Bag2 Bag3 Bag4 Bag5 Cabc1 Ccs Cct2 Cct3 Cct4 Cct5 Cct6a Cct6b Cct7 Cryaa Cryab Dnaja1 Dnaja2 Dnaja3 Dnaja4 Dnajb1 Dnajb2 Dnajb11 Dnajb12 Dnajb13 Dnajb14 Dnajb5 Dnajb6 Dnajb7 Dnajb8 Dnajb9 Dnajc1 Dnajc10 Dnajc11 Dnajc12 Dnajc13 Dnajc14 Dnajc15 Dnajc16 Dnajc17 Dnajc18 Dnajc19 Dnajc3 Dnajc4 Dnajc5  Brain Fold * p-value change 0.5539 0.103303 1.6647 0.005168 0.8096 0.073824 0.6678 0.098269 1.2282 0.69129 0.7621 0.177136 0.9877 0.933817 0.9734 0.799302 1.0806 0.855899 1.3147 0.151575 0.9056 0.328878 1.344 0.133211 1.1644 0.031368 1.1063 0.367545 0.5358 0.394047 1.005 0.843311 0.7794 0.396386 0.6529 0.13472 1.4577 0.001304 0.8556 0.220376 0.7889 0.053368 1.8024 0.005696 2.7974 0.003117 0.6692 0.023008 0.2557 0.339799 0.9954 0.900606 0.7095 0.428443 0.7177 0.071358 3.126 0.006149 0.9888 0.850383 0.6096 0.42118 0.5007 0.377314 0.6582 0.00112 1.4859 0.005896 0.9356 0.361546 0.9057 0.477053 0.4137 0.021857 0.8298 0.177084 1.0748 0.374884 0.7344 0.144963 0.7201 0.053174 1.1979 0.177347 0.8688 0.336257 0.8057 0.117401 0.711 0.103528 0.6764 0.184894 1.1447 0.283714  Liver Fold * p-value change 0.6619 0.01114 0.6862 0.226613 1.056 0.825353 0.3263 0.008426 12.4831 0.001895 0.4633 0.010735 0.3471 0.002917 1.9504 0.053862 1.8411 0.070995 0.8364 0.516403 0.8311 0.102503 1.0124 0.868098 1.1865 0.126963 0.8571 0.116482 0.5841 0.325782 0.723 0.049662 0.8414 0.448701 0.9309 0.514309 1.6457 0.104811 0.4867 0.052802 0.4787 0.130644 1.3622 0.394316 9.8775 0.000192 0.8844 0.465361 0.1911 0.127867 0.7651 0.162726 0.9409 0.473346 0.4677 0.028752 0.2583 0.061209 0.6414 0.007803 2.3162 0.067284 0.8587 0.44971 1.3041 0.458707 0.7579 0.235999 0.3696 0.002008 0.7642 0.245459 0.8988 0.572277 0.422 0.004247 0.5152 0.001132 1.4294 0.246661 0.5555 0.090918 0.8909 0.519996 0.4949 0.0002 1.0616 0.917233 0.8585 0.574645 1.273 0.016873 0.5081 0.014792  Gene Dnajc5 Dnajc5b Dnajc5g Dnajc6 Dnajc7 Dnajc8 Dnajc9 Hsf1 Hsf2 Hsf4 Hsph1 Hsp90aa1 Hsp90ab1 Hsp90b1 Hspa14 Hspa1a Hspa1b Hspa1l Hspa2 Hspa4 Hspa4l Hspa5 Hspa8 Hspa9 Hspb1 Hspb2 Hspb3 Hspb6 Hspb7 Hspb8 Hspd1 Hspe1 Pfdn1 Pfdn2 Serpinh1 Sil1 Tcp1 Tor1a Gusb$ Hprt1$ Hsp90ab1$ Gapdh$ Actb$  Brain Fold * p-value change 1.1447 0.283714 0.7204 0.388559 0.5655 0.379182 0.967 0.607897 1.294 0.026786 0.4721 0.033914 0.6716 0.097667 0.6871 0.09983 0.924 0.514831 0.701 0.260822 1.2425 0.213459 0.9517 0.654922 1.1284 0.031751 0.8877 0.325235 0.827 0.376506 19.8949 0.000918 18.4604 0.000675 0.7101 0.109201 1.9834 0.03778 1.2709 0.057047 0.4652 0.063573 1.0546 0.813525 1.5838 0.00096 0.832 0.654396 2.3665 0.003963 1.1072 0.70863 1.2617 0.722348 0.7388 0.265384 0.7674 0.212276 0.546 0.168098 1.285 0.004456 1.1327 0.213775 0.9881 0.870701 0.7737 0.063529 1.4643 0.182529 1.2234 0.342094 1.3309 0.018088 1.2889 0.019206 0.5093 0.006591 0.955 0.343731 1.1395 0.020618 1.1904 0.007638 1.5157 0.004774  Liver Fold * p-value change 0.5081 0.014792 0.8587 0.44971 0.8058 0.445654 0.1212 0.025154 0.7721 0.184159 0.5724 0.41244 0.3377 0.145668 0.4489 0.002501 1.481 0.214062 0.5157 0.077468 2.6855 0.000429 1.2593 0.732777 1.0249 0.986762 1.0267 0.755551 0.5518 0.043781 504.2773 0.000067 232.0417 0.000392 1.7557 0.032631 1.2014 0.718687 0.4114 0.028217 0.8071 0.385973 1.4061 0.086402 2.3528 0.000481 0.7577 0.261593 3.8697 0.001453 0.4993 0.330753 0.4965 0.373041 0.5696 0.130521 0.6188 0.364641 1.9018 0.04364 1.7756 0.029237 1.4252 0.249831 1.2651 0.259957 0.9846 0.870173 0.63 0.493928 1.7865 0.015409 1.0342 0.721104 0.9866 0.968326 0.8001 0.270133 1.0434 0.661078 1.0932 0.688567 1.417 0.083667 0.7732 0.352965  Key: * Fold change of Smarcal1del/del relative to Smarcal1+/+; $ control genes 89  3.3.8 RpII inhibition decreases proliferation in SMARCAL1-deficient human fibroblasts Having found that SMARCAL1, Marcal1 and Smarcal1 modulate gene expression during the heat stress response and are needed for heat tolerance, we hypothesized that other environmental and genetic factors altering transcription also induce penetrance when SMARCAL1 orthologues are deficient. To test this, we incubated skin fibroblasts from a control individual and three SIOD patients (SD31, SD120, and SD123) for 48 hours with 1 µg/ml of α-amanitin, a toxin that preferentially inhibits RpII 247,248. At this dose, SIOD fibroblasts proliferated significantly slower than control fibroblasts as measured by MTT assay and EdU incorporation by the Click-iT EdU assay (Figure 3-12A); there was no difference in apoptosis or necrosis as judged by TUNEL assay and trypan blue staining. Also, knockdown of the largest subunits of RpII using shRNAs against POLR2A or POLR2B in SIOD fibroblasts resulted in significantly decreased proliferation compared to a non-targeting shRNA or to knockdown of RpII components in control fibroblasts (Figure 3-13A-B). This interaction between RpII and SMARCAL1 is unlikely to result from protein-protein interactions since SMARCAL1 did not co-precipitate with RpII (data not shown).  90  91  Figure 3-12- Inhibition of RpII function causes penetrance of SMARCAL1, Marcal1 and Smarcal1 deficiency. (A) Graph showing the proliferation of α-amanitin treated control and SMARCAL1del/del skin fibroblasts relative to untreated cells. The fibroblast cultures were treated with α-amanitin (1 µg/mL) for 48 hours and proliferation was measured by the MTT and Click-iT EdU assays. (B) Graph showing the hatching rate at 20ºC for Marcal1del/del, RpII2153 or 4 or 8 or K1/FM7 and RpII2153 or 4 or 8 or K1/FM7;Marcal1del/del embryos relative to the hatching rate of yw embryos. FM7 is a X chromosome balancer. (C) Distribution plot of egg dimensions showing that RpII2154/FM7;Marcal1del/del flies lay smaller eggs than yw, Marcal1del/del and RpII2154/FM7 flies. (D) Heat map comparing the log2 fold differences in all expressed mRNAs among yw, Marcal1del/del, RpII2154/FM7, and RpII2154/FM7; Marcal1del/del ovaries at 20ºC. The RNA levels were measured using Affymetrix Drosophila Genome 2.0 arrays and are the average of five biological replicates. (E) Density plots showing distribution of the log2 fold differences for transcripts depicted in panel D. (F) Graph showing the proliferation of α-amanitin treated Smarcal1+/+ and Smarcal1del/del MEFs relative to untreated MEFs. The MEFs were treated with α-amanitin (1 µg/mL) for 48 hours and proliferation was measured by the MTT and Click-iT EdU assays. Error bars in panels A, B, and F represent one standard deviation. The data for panels B and C was provided by Marie Morimoto, and data for panel D and E was provided by Chad Shaw.  92  Figure 3-13- Effect of knocking down RpII components in SMARCAL1 and Smarcal1 deficient fibroblasts. (A) The ratio of WST-1 assay measurement of SMARCAL1del/del (SD31) and unaffected control dermal fibroblasts 72 and 96 hours following electroporation with non-targeting or POLR2A- and POLR2B-targeting shRNAs. The values in each graph represent the mean of 3 independent experiments and were normalized to the non-targeting values. (B) As measured by qRT-PCR, POLR2A and POLR2B mRNA levels were reduced approximately by 50-80% and 45-50%, respectively. The data was normalized to GAPDH mRNA levels and to the nontargeting control. (C) The ratio of WST-1 assay measurement of Smarcal1del/del and Smarcal1+/+ MEFs 48 and 96 hours following electroporation with non-targeting or Polr2atargeting siRNAs (Polr2a-1 and Polr2a-3). The values in each graph represent the mean of 3 independent experiments and were normalized to the non-targeting values. (D) As measured by qRT-PCR, Polr2a mRNA levels were reduced approximately by 55-65% for siRNA duplex 1 and 70% for siRNA duplex 3. The data was normalized to Gapdh mRNA levels and to the non-targeting control. The error bars throughout represent one standard deviation.  93  3.3.9 RpII mutations decrease the viability and increase gene expression changes in Marcal1del/del flies Given the sensitivity of SMARCAL1-deficient cells to RpII inhibition and knockdown, we tested for analogous epistatic interactions in Drosophila. We introduced a single mutant allele of the largest subunit of RpII (RpII2153, RpII2154, RpII2158 or RpII215K1) into the Marcal1del/del background (RpII2153/FM7;Marcal1del/del, RpII2154/FM7;Marcal1del/del, RpII2158/FM7;Marcal1del/del or RpII215K1/FM7;Marcal1del/del). Comparing the hatching of these embryos to Marcal1del/del and RpII heterozygous mutant embryos showed that these had a significantly reduced hatching rate at 20ºC (Figure 3-12B). This reduced hatching was not associated with increased apoptosis as measured by acridine orange staining or from altered protein-protein interactions between RpII215 and Marcal1 since Marcal1 did not coprecipitate with RpII215 (data not shown). Besides reduced hatching, the introduction of a single mutant allele of RpII215 into the Marcal1del/del background reduced the size of eggs relative to those of Marcal1del/del and RpII215 heterozygous mutants (Figure 3-12C). The mean (±SD) egg volume was 0.0116±0.0018 mm3 for yw vs. 0.0115±0.0015 for Marcal1del/del (n=100, p=0.56), 0.0104±0.0015 for RpII2154/FM7 (n=100, p=9.28e-7), and 0.0094±0.0016 for RpII2154/FM7;Marcal1del/del flies (n=100, p=1.03e-13). To test if this reduced egg size was associated with changes in gene expression, we used the Affymetrix Drosophila Genome 2.0 Array to compare gene expression in the ovaries of Marcal1del/del, heterozygous RpII2154 (RpII2154/FM7), RpII2154/FM7;Marcal1del/del and yw flies. The introduction of the RpII2154 allele increased both the number of differentially expressed genes and the magnitude of the overall 94  expression differences. 744 genes were differentially (q-value<0.05) expressed between RpII2154/FM7;Marcal1del/del and yw ovaries compared to 123 genes between Marcal1del/del and yw ovaries. The log2 median fold change of expression differences for Marcal1del/del vs. yw ovaries was 0.01, whereas for RpII2154/FM7;Marcal1del/del vs. yw ovaries, it was 0.07. The 744 differentially expressed genes mapped to multiple GO biological process annotations including cellular and metabolic processes, cell cycle and response to stress (Figure 3-12D-E, http://www.ncbi.nlm.nih.gov/gds GEO accession number GSE35552, and Appendix 11). Reciprocally the introduction of the biallelic deletion of Marcal1 into the background of the RpII2154 mutation also increased the number of differentially expressed genes and the magnitude of the overall expression differences. Comparison of gene expression in RpII2154/FM7 and yw ovaries identified 378 differentially (q-value<0.05) expressed genes and this increased to 744 for the comparison of RpII2154/FM7;Marcal1del/del and yw ovaries. Also, the log2 median fold change of expression differences was 0.01 for RpII2154/FM7 vs. yw and 0.07 for RpII2154/FM7;Marcal1del/del vs. yw ovaries. The 378 differentially expressed genes mapped to many GO biological process annotations including cellular and metabolic processes and gene expression (Figure 3-12D-E, http://www.ncbi.nlm.nih.gov/gds GEO accession number GSE35552, and Appendix 12).  3.3.10 RpII inhibition decreases proliferation in Smarcal1-deficient mouse embryonic fibroblasts Having observed the interactions of SMARCAL1 and Marcal1 with RpII, we asked if inhibition of RpII function had a similar effect in Smarcal1del/del MEFs. When treated with 1 95  µg/ml of α-amanitin, Smarcal1del/del MEFs proliferated significantly more slowly than Smarcal1+/+ fibroblasts as measured by the MTT assay and EdU incorporation by the ClickiT EdU assay (Figure 3-12F). Also, they exhibited no difference in apoptosis or necrosis as judged by TUNEL assay and trypan blue staining (data not shown). Furthermore, knockdown of the largest subunit of RpII using siRNAs against Polr2a in Smarcal1del/del MEFs resulted in a significantly decreased proliferation rate compared to knockdown of Polr2a in Smarcal1+/+ MEFs or to treatment of Smarcal1del/del MEFs with a non-targeting siRNA (Figure 3-13C-D).  3.3.11 RpII inhibition modifies the penetrance of Smarcal1 deficiency and partially recapitulates SIOD in Smarcal1-deficient mice Based on the preceding findings, we hypothesized that variations in gene expression are critical for expression of SIOD disease features. To test this in vivo, we injected Smarcal1del/del and Smarcal1+/+ mice with either carrier (phosphate buffered saline) or αamanitin (0.1 mg/kg/day) for 12 weeks. Although they did not develop T-cell deficiency (Figure 3-14), the Smarcal1del/del mice injected with α-amanitin developed features of SIOD that were not observed in α-amanitin-treated Smarcal1+/+ mice or in PBS-treated Smarcal1del/del and Smarcal1+/+ mice (Figure 3-15). First, they had length and weight growth restriction (Figure 3-15A-C), and consistent with the growth restriction in SIOD, the mice had a disproportionately short spine (Figure 3-15D-E). Second, as reported for SIOD growth plates 154,156, the distal femur growth plates were hypocellular, and chondrocytes in the proliferation and hypertrophic zones formed less organized columns (Figure 3-15F-N).  96  Finally, reminiscent of the early renal disease in SIOD, the treated Smarcal1del/del mice developed albuminuria (Figure 3-15O).  97  Figure 3-14- Treatment of Smarcal1del/del mice with α-amanitin does not recapitulate T-cell deficiency in SIOD. (A) Plots show the representative FACS analysis of the thymus from Smarcal1+/+ (n=3) and Smarcal1del/del (n=5) mice treated with α-amanitin for different developmental T-cell subsets. Thymocytes were initially analyzed for T-cell developmental stages based on CD4 and CD8 staining. Double negative (CD4-CD8-) cells were further resolved based on CD44 and CD25 expression into DN1 (CD44+CD25-), DN2 (CD44+CD25+), DN3 (CD44-CD25+) and DN4 (CD44-CD25-) fractions. (B) Quantification of T-cell subsets analyzed in panel A. (C) Plots show the representative FACS analysis of the spleen from Smarcal1+/+ (n=3) and Smarcal1del/del (n=5) mice treated with α-amanitin for different lymphocyte subsets. Splenic B and T cells were initially resolved based on expression of B220 (CD45R) and TCRαβ. Subsequently, T cells (TCRab+) were further resolved into CD4+ and CD8+ T-cell subsets. (D) Quantification of T-cell subsets analyzed in panel C. Note that compared to untreated mice (Figure 19), treatment with α-amanitin did not significantly alter the representation of the lymphocyte subsets. The error bars represent one standard deviation. The data for this figure was provided by Mrinmoy Sanyal. 98  Figure 3-15- Treatment of Smarcal1del/del mice with α-amanitin partially recapitulates SIOD. (A) Radiographs of representative male mice after 12 weeks of daily intra-peritoneal (ip) injections with PBS or 0.1 mg/kg α-amanitin. (B) Growth curve showing that Smarcal1+/+ (n=7) and Smarcal1del/del (n=9) mice gain weight equally when given daily ip-injections of PBS. (C) Growth curve showing that Smarcal1del/del (n=9) mice gain less weight than Smarcal1+/+ (n=7) mice when given daily ip-injections of 0.1 mg/kg α-amanitin. (D and E) Graphs showing the ratio of lumbar spine (L1-L6) length to femur length (D) or humerus length (E) for α-amanitin- and PBS-treated mice. Note that the α-amanitin treatment disproportionately shortened the lumbar spine of the Smarcal1del/del mice. (F) Plot of fold change in chondrocyte number in the proliferative (PZ) and hypertrophic (HZ) zones in the distal femoral growth plate of α-amanitin-treated mice, Smarcal1del/del (n=7) and Smarcal1+/+ 99  (n=7), relative to PBS-treated mice, Smarcal1del/del (n=7) and Smarcal1+/+ (n=6). (G-N) Photographs of representative H&E staining of the distal femoral growth plate of Smarcal1+/+ and Smarcal1del/del male mice treated with PBS or α-amanitin for 12 weeks. Panels K-N are higher magnifications of the boxed areas on panels G-J, respectively. Note the hypocellular growth plate and poorly organized columns of chondrocytes in the growth plate of the α-amanitin treated Smarcal1del/del mouse. Bar = 100 µm. (O) Graph showing urine albumin excretion by Smarcal1del/del mice relative to Smarcal1+/+ mice following PBS or α-amanitin treatment. Bars in panels B-F and O represent standard errors. The data for panel O was provided by Darren Bridgewater.  3.4 Discussion We have shown that the proteins encoded by SMARCAL1 orthologues localize to transcriptionally active chromatin, modulate gene expression and have epistatic interactions with transcription factors. We also found that similar to the lack of penetrance for biallelic SMARCAL1 mutations in humans, deficiency of the orthologues in fruit flies and mice is insufficient to cause disease in these organisms and that penetrance is associated with environmental or genetic insults that further modify gene expression. As an annealing helicase, SMARCAL1 resolves single to double-stranded DNA transitions 130. Such transitions occur during DNA replication, repair, recombination, and transcription, and recent studies have shown that SMARCAL1 participates in the DNA stress response both at stalled replication forks and double-strand DNA breaks repaired by recombination or end joining 139,141-144. However, since clinical and molecular analyses of SIOD patients and SMARCAL1-deficient cells and tissues did not detect defects of DNA repair, replication and recombination 161,249,250, we reasoned that, like many DNA repair enzymes 211-213,215,218,251, SMARCAL1 contributes to transcription and that its deficiency results in gene expression changes contributing to the pathophysiology of SIOD. SMARCAL1 could modulate RpII transcription through maintenance of the topology  100  and helicity of duplex DNA. In prokaryotes, changes in DNA helicity cause gene expression to be enhanced, repressed or unchanged 16, and the equilibrium between duplex DNA and strand opening modulates transcription factor binding and production of full-length RNA 18,19  . Similarly, in eukaryotes, in vitro and in vivo studies of MYC expression show that  transcription-induced supercoiling melts MYC Far Upstream Element (FUSE) to enable binding by structure-sensitive regulatory proteins such as FUSE Binding Protein (FBP) and FBP-Interacting Repressor (FIR) 17,252. Binding of FBP and FIR to FUSE modify the rate of MYC promoter firing 17,252. Since negative and positive supercoiling are generated upstream and downstream of the transcription bubbles 253,254, respectively, SMARCAL1, Marcal1 or Smarcal1 might contribute to the maintenance of DNA topology within and adjacent to transcribed regions. Deficiency of these orthologues would then alter gene expression as a consequence of the changes in DNA helicity or topology. In summary, SMARCAL1 deficiency is insufficient to cause SIOD, but the addition of environmental and genetic insults affecting transcription do cause penetrance and partial recapitulation of SIOD in model organisms. At both the molecular and genetic levels, SMARCAL1 plays a role in modulating gene expression. From these observations, we hypothesize that the annealing helicase function of SMARCAL1, Marcal1, or Smarcal1 maintains DNA topology to buffer variability in gene expression and thereby mitigates penetrance of pathological traits arising from environmental and genetic insults.  101  4. Discussion and concluding remarks In the genomic era, ability to predict a phenotype from a genotype is a privilege that might lead to efficient diagnosis, prognosis, and perhaps therapy. However, expecting a simple genotype-phenotype correlation even in Mendelian disorders is frequently more hope than reality since environmental factors, genetic modifiers and developmental processes often prevent simple correlation between genotype and phenotype. The incomplete penetrance and variable expressivity observed with specific genotypes in Mendelian disorders contradicts the traditional assumption of the qualitative nature of these disorders and suggests that some Mendelian disorders arise from defects in biological pathways that are sensitive to quantitative modulation. In this dissertation, I advanced understanding of the pathophysiology of Schimke immuno-osseous dysplasia. Using clinical, pathological, phenotypic, biochemical, and molecular analyses, I showed that defective DNA repair is not a major contributor to the pathophysiology of SIOD, and that SIOD is a quantitative trait associated with environmental and genetic disturbances of gene expression. In this context, we speculate that SMARCAL1 modulates chromatin structure and thereby higher order regulation of gene expression.  4.1 Improved molecular understanding of SIOD The aim of chapters 2 and 3 of this dissertation was to improve the molecular understanding of SIOD.  102  4.1.1 SMARCAL1 is a multifunctional protein facilitating the cross-talk among DNA repair, replication, recombination and transcription Cellular functions such as DNA repair, replication, recombination and transcription share chromatin as a common substrate. Since these DNA metabolic functions frequently share components and sometimes occur simultaneously on the same DNA fragment, a constant cross-talk among these processes is required for their co-existence and also for the maintenance of genomic structure and integrity (Figure 4-1). Focusing on transcription, examples of such close interactions are illustrated by the following. Several different types of DNA damage constitute obstacles for RpII progression and significantly affect transcription 255  . In return, transcription causes substantial changes in DNA supercoiling, sensitizes ss-  DNA to genotoxic agents, and increases the rate of mutation (transcription-associated mutagenesis) and DNA recombination (transcription-associated recombination, TAR) 256-259. TAM and TAR in highly transcribed regions can be partially ascribed to the head on collisions between RpII and DNA polymerase machinery 259. Consequent to these clashes, replication forks either collapse causing chromosomal deletions or DNA repair by homologous recombination or replication restart after displacement of RpII 257,260-262. The cross-talk between transcription and other DNA metabolic functions is also intertwined by proteins functioning in several processes. For example, DNA repair components such as ERCC2 211, ERCC3 215, ERCC6 212, GTF2H5 216, and CDK9 217,218 contribute to both initiation and elongation of RpII. It has recently been shown that RPA, a component of DNA damage response and replication, is also associated with RpII during elongation 263. Also, in Arabidopsis mutations in RPA2 leads to impaired transcriptional gene silencing of retrotransposons and of transgene repeat loci 213. Interestingly, Faucher et al. have shown that  103  trimethylated H3K4, which is known as a marker of transcriptionally active genes, is also involved in DNA damage response and replication 214. Moreover, early replication sites are associated with actively transcribed regions in higher eukaryotes, and in mouse embryonic stem cells, it has been shown that most of the replication initiation sites are associated with transcriptional units 242,264-267. SMARCAL1 is an annealing helicase that resolves single to double-stranded DNA transitions 130. Such transitions occur during DNA replication, repair, recombination, and transcription. Consistent with a role for SMARCAL1 in DNA replication, recombination and repair, recent studies have implicated SMARCAL1 in the DNA stress response both at stalled replication forks and double-strand DNA breaks, cell cycle progression, and remodeling of Holliday junctions 139-144. Considering the constant cross-talk among DNA metabolic functions and that DNA repair components frequently modulate transcription, we proposed that SMARCAL1 could facilitate the cross-talk between DNA repair, replication, recombination and transcription (Figure 4-1). To determine which of these functions contribute most to the pathophysiology of SIOD and its phenotypic variability, we evaluated the role of SMARCAL1 in the processes of DNA repair, replication, recombination and transcription.  104  Figure 4-1- Schematic model showing cross-talk between basic DNA metabolic functions and maintenance of genomic structure. Evidence in favour (black) or against (red) SMARCAL1 role in each process is summarized.  4.1.2 SIOD does not arise from defective DNA replication, repair or recombination In vitro analyses suggest that SMARCAL1 facilitates cell cycle progression from the G2 to the M phase 139,141-144. However, despite these findings, the proliferation rate of SMARCAL1-deficient cultured cells is not detectably perturbed relative to control cells 139,141,250  . Furthermore, our analysis of the mouse testis revealed that Smarcal1 is highly  expressed in quiescent or slowly proliferating Leydig and Sertoli cells and is nearly undetectable in the highly proliferative germ cell lineage (unpublished data). Based on these 105  observations, we conclude that SIOD does not arise from defective DNA replication. Also, our evaluations regarding the efficiency of several DNA repair pathways in SMARCAL1-deficient cells show that SMARCAL1 is not essential for the DNA repair processes of nucleotide excision repair, homologous recombination, and non-homologous end joining. However, our in vivo analyses show that similar to SMARCAL1-deficient cells 139  , Smarcal1-deficient mice are hypersensitive to several genotoxic agents. These  observations might suggest that SMARCAL1 deficiency causes SIOD and sensitivity to genotoxic agents by compromising a process of DNA repair not assessed by our methods. Processes of DNA repair not assessed by our assays include base excision repair (BER) and mismatch repair (MMR). Although defects in BER and MMR pathways also increase sensitivity to genotoxic agents 177,268, the absence of neurodegenerative symptoms, chromosomal rearrangements, and cancers other than NHL among SIOD patients 161,269 suggest that SMARCAL1 is not a major contributor to BER and MMR and that dysfunction of these pathways is not a major contributor to the pathobiology of SIOD. These data also suggest that SMARCAL1 deficiency may cause SIOD by affecting another basic DNA metabolic function such as transcription.  4.1.3 SIOD is associated with transcriptional alterations beyond a threshold We concluded that defects in DNA replication, repair and recombination are not major contributors to the pathophysiology of SIOD and cannot explain the incomplete penetrance observed in these patients. The other DNA metabolic function that SMARCAL1 participates in is transcription. The hypothesis that SIOD features arise from impaired transcription parallels observations from other DNA repair disorders including xeroderma 106  pigmentosum, trichothiodystrophy and Cockayne syndrome 186,270. Like SIOD, these disorders have phenotypic variability and poor genotype-phenotype correlation and arise in part from direct effects on transcription 212,251. Many features of SIOD such as the T-cell immunodeficiency, hypothyroidism, anemia, skeletal dysplasia, renal disease and heat sensitivity can be explained by impaired gene expression. Specifically, the proliferation of T cells, responsiveness to thyroxine, responsiveness to erythropoietin, chondrocyte proliferation and differentiation, maintenance of podocytes and heat shock response are all dependent on a robust transcriptional responses 271-282. Furthermore, since transcription rates alter sensitivity to DNA damaging agents 283,284, and CPT-11, etoposide, and HU also have deleterious effects on gene expression 285-289, the hypersensitivity of Smarcal1-deficient mice to these agents may, in part, be attributable to impaired gene expression. Consistent with the role of SMARCAL1 in transcriptional regulation, we observed that SMARCAL1 orthologues localize to transcriptionally active chromatin and have epistatic interactions with transcription factors. We also found modest but diffuse alterations in the expression of many genes in SMARCAL1-deficient organisms. However, deficiency of SMARCAL1 orthologues was not sufficient to cause disease in model organisms, and the addition of either environmental or genetic modifiers of gene expression was necessary for the penetrance of disease. Since gene expression is a quantitative trait and many genes are dysregulated in SIOD, there are two nonexclusive models by which alterations in gene expression could lead to SIOD. In the first model, SIOD is defined as a polygenic trait, and its features arise from cumulative effects of multiple dysregulated genes each with small effect size. The observed modest changes in expression of many genes in SMARCAL1-deficient organisms support this  107  idea (Figure 4-2). In the second model, SIOD is defined as an oligogenic trait and its features arise when the expression of a few key regulatory genes pass a certain threshold. In this model, SMARCAL1 orthologues buffer random fluctuations in gene expression and thereby modulate phenotypic changes induced by genetic or non-genetic insults. In contrast, the absence of a SMARCAL1 orthologue creates a chromatin environment permissive for such insults, pushing gene expression beyond a threshold of disease. In this model, although many genes are dysregulated, the expression of only a limited number of them passes a tolerance threshold (Figure 4-3A). Consistent with this model, other members of the Boerkoel Lab have recently linked the arteriosclerosis of SIOD to decreased ELN expression 6 and the renal glomerulosclerosis to increased NOTCH1 expression (unpublished data) (Figure 4-3B). Also, through collaboration with Mrinmoy Sanyal at Stanford University, we have linked the T-cell deficiency in SIOD to decreased IL7RA expression (unpublished data) (Figure 4-3B).  108  Figure 4-2- Polygenic model for SIOD depicting the contribution of many dysregulated genes each with small effect size to the penetrance of SIOD. Left panel: SMARCAL1 orthologues buffer random fluctuations in gene expression by modulating DNA helicity within the promoter and across transcribed regions. Middle panel: Deficiency of the SMARCAL1 orthologues impairs maintenance of DNA structure within the transcriptionally active regions, and thereby alters gene expression. The number of dysregulated genes is still not sufficient for the penetrance of the disease. Right panel: However, when transcription is further compromised by environmental or genetic factors the disease features will arise from the contribution of many mildly dysregulated genes.  109  Figure 4-3- Oligogenic model for SIOD depicting the contribution of a few dysregulated genes to the penetrance of SIOD. (A) Left panel: SMARCAL1 orthologues buffer random fluctuations in gene expression by modulating DNA helicity within the promoter and across transcribed regions. Middle panel: Deficiency of the SMARCAL1 orthologues impairs maintenance of DNA structure within the transcriptionally active regions, and thereby alters gene expression. These alterations in gene expression are within a threshold of tolerance and compensated for such that few or no 110  phenotypic features are apparent in humans and model organisms. Right panel: However, when transcription is further compromised by environmental or genetic factors that cause gene expression of a few key regulatory genes to pass a threshold, then the organism is unable to compensate and manifests a phenotype. (B) Examples of dysregulated NOTCH1, ELN, and IL7RA that contribute respectively to the focal segmental glomerulosclerosis, arteriosclerosis, and T-cell deficiency in SIOD patients.  4.1.4 Possible mechanisms by which SMARCAL1 modulates gene expression There are at least three nonexclusive models by which SMARCAL1 deficiency can alter gene expression. First, unrepaired DNA damage impedes RpII progression and impairs transcription 255. Second, like ERCC6, SMARCAL1 could be part of the transcriptional complex and thus its deficiency directly affects RpII transcription 212. Third, the DNA structure maintained by SMARCAL1 modulates gene expression. Evidence against the first are the findings that i) SMARCAL1-deficient fibroblasts and Smarcal1-deficient MEFs do not have increased DNA breaks compared to control fibroblasts as measured by comet assay, ii) SMARCAL1-deficient fibroblasts do not have hypersensitivity following exposure to ultraviolet light or illuidin S, iii) SIOD patients do not have defective homologous recombination, iv) SIOD patients do not have defects in non-homologous end joining, and v) the proliferation rate of SMARCAL1-deficient cells is not detectably perturbed relative to control cells even though the transition from G2 to M phase is slightly delayed 139,141,250. Evidence against the second proposed mechanism includes i) failure of SMARCAL1 homologues to co-purify or co-immunoprecipitate with RpII and studied transcription complexes 290-292 and ii) failure of RpII to co-purify or co-immunoprecipitate with SMARCAL1 or Marcal1. Evidence supporting the third mechanism that SMARCAL1 influences gene expression through maintenance of DNA structure include i) SMARCAL1deficient cells accumulate more RPA indicative of increased levels of ss-DNA in these cells 111  139  ; ii) SMARCAL1-deficient cells show increased S1-nuclease sensitivity when pulsed with  potassium permanganate (unpublished data), and iii) ectopic expression of Ubx, which is induced by heterozygous mutations of Polycomb group genes in Drosophila, is suppressed by Marcal1-deficiency and is associated with insensitivity of the Ubx promoter to micrococcal nuclease digestion (unpublished data). Therefore, since alterations in DNA structure and topology are associated with transcriptional alterations in both prokaryotes and eukaryotes 16-19,252, we hypothesize that the SMARCAL1 orthologues influence gene expression through maintenance of DNA structure (Figure 4-1). This model could also explain why, in contrast to transcription factors that bind conserved promoter elements, SMARCAL1, Marcal1 and Smarcal1 deficiency do not consistently affect expression of homologous genes. Homologous genes in humans, flies and mice frequently reside in different genomic neighborhoods or chromatin regions 293; therefore, the need for the SMARCAL1, Marcal1 and Smarcal1 to maintain duplex DNA around homologous genes might vary among species and thereby have differing effects on expression of homologous genes and on recapitulation of disease features in model organisms. The changes in DNA structure could directly or indirectly affect transcription. Our DamID experiment shows Marcal1 enrichment mostly at promoters compared to the rest of the gene bodies that could be suggestive of the direct effect of Marcal1 on those promoters. Alternatively, SMARCAL1 orthologues could modulate the DNA structure of the genes encoding transcription activators or repressors and thus indirectly affect transcription of other genes. Indeed, Morimoto et al. showed that ELN downregulation in aorta is associated with alterations in the expression of ELN transcription factors 168. Also, like several other SNF2  112  members including Lsh, ATRX, BRM, BRG1, and NoRC complex, chromatin remodeling activity of SMARCAL1 could modulate genome-wide methylation and affect gene expression 294-298. Consistent with this, preliminary data from our collaborator has recently identified genome-wide methylation changes in SMARCAL1-deficient lymphoblastoid cell lines (unpublished data). Whether this alteration in methylation pattern correlates with the transcriptional changes in SIOD needs further study.  4.2 Overall significance In summary, my work on elucidating the phenotype and molecular basis of SIOD has led to a better understanding of this disease and uncovered unstudied areas of biology. Firstly, it appears that SMARCAL1 orthologues modulate random fluctuations in gene expression and buffer genetic or non-genetic insults, whereas the absence of the SMARCAL1 orthologues creates a chromatin environment permissive for such insults pushing gene expression beyond a threshold of disease. Secondly, understanding that SMARCAL1 has a role in modulating gene expression is allowing us to identify likely causes of the pathophysiology for each affected organ in SIOD, and this insight will hopefully identify potential therapeutic approaches for SIOD patients.  4.3 Future directions Further studies are required to clarify the mechanisms by which SMARCAL1 orthologues modulate DNA structure and also how changes in DNA structure in SMARCAL1-deficient organisms lead to transcriptional alterations. Also, defining a 113  connection between SMARCAL1 and DNA methylation will likely uncover another layer of SMARCAL1 function in regulating gene expression. Since SMARCAL1-deficient organisms are hypersensitive to heat stress and transient neurological symptoms of SIOD patients are precipitated by stress, further studies are also required to delineate the role of SMARCAL1 in stress responses.  114  Bibliography 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17.  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Nat Genet 32, 393-6 (2002). Gibbons, R.J. et al. Mutations in ATRX, encoding a SWI/SNF-like protein, cause diverse changes in the pattern of DNA methylation. Nat Genet 24, 36871 (2000). Banine, F. et al. SWI/SNF chromatin-remodeling factors induce changes in DNA methylation to promote transcriptional activation. Cancer Res 65, 3542-7 (2005).  132  Appendices  133  Appendix 1- Figure showing microhomology usage at Sµ-Sα1 junctions in the immunoglobulins of SIOD patients. The Sµ and Sα1 reference sequences are aligned above and below the switch junctional sequences from 7 SIOD patients (SD106, SD107, SD111, SD114, SD115, SD120, and SD123) and 4 controls (SD106.1, SD107.1, SD114.1, and SD121.1). Microhomology (solidline boxes) at each switch junction is the longest region of identity with both the Sµ and Sα1 reference sequences, whereas imperfect microhomology (dashed-line boxes) at each switch junction is the longest region of near identity (1 mismatch on either side of the breakpoint). Red nucleotides indicate insertion of nucleotides at the switch region breakpoints.  134  135  Appendix 2- Figure showing microhomology usage at Sµ-Sγ1 junctions in the immunoglobulins of SIOD patients. The Sµ and Sγ1 reference sequences are aligned above and below the switch junctional sequences from 7 SIOD patients (SD106, SD107, SD111, SD114, SD115, SD120, and SD121) and 4 controls (SD106.1, SD107.1, SD114.1, and SD121.1). Microhomology (solidline boxes) at each switch junction is the longest region of identity with both the Sµ and Sγ1 reference sequences, whereas imperfect microhomology (dashed-line boxes) at each switch junction is the longest region of near identity (1 mismatch on either side of the breakpoint). Red nucleotides indicate insertion of nucleotides at the switch region breakpoints.  136  137  Appendix 3- Table showing suppressors and enhancers of ectopic wing veins induced by the overexpression of Drosophila Marcal1 and human SMARCAL1. Gene  Allele  BEAF-32  e00756 KG069 04 91 98 sz18 G0015 8 k11904 1 u1 KG085 15  Lam LamC mei-S332 mod(mdg4)  Acf1  mod Nap1  nej  nhk-1 Nipped-A pr-set7  Cdk8 MED6 MED12 (Kto) MED13 (skuld)  MED15 MED17  1 2 EY0862 9 07570 KG039 59 EY0859 6 K01 K02 P  Drosophila Marcal1  Human SMARCAL1  Gene  Drosophila Marcal1  Human SMARCAL1  Nuclear Matrix and Chromatin Structure Interactors E E Nipped-B 02047 S 0 ord 1  S S  S S  E E E S  E E E S  KG04816 c00402 2 8  0 E S S  0 E S S  0 S S S  0 0 S S  e04061 s2325 KG08276  E S S  E E S  S 0 S  0 E S  san SMC1 su(Hw)  Trl  Allele  Chromatin Remodeling or Chromatin Structural Factors 0 0 Pcaf f02830 E E f05456 E E C137T S E  S E  E333st Q186st  0 S  E 0  E  E  S  S  E 0 S  E E S  DeltaT280 -F285 17 2A-7-11 5  0 E E  E E E  Q7  S  S  3  S  S  Z30437 NC116 NC186 1 EY0466 8  E  0  1  S  E  S S 0 E  S S 0 E  2 1 3 4  S S S S  S S S S  EY06632  E  E  A162 EY0508 7 1 2  S E  Mediator Complex 0 MED18 E MED20  e03853 C6R20  S 0  S S  E E  E E  f00955 KG00948  S E  E 0  rK760 L7062 EY0736 9 f04180 s2956  E 0 E  E S 0  BG01670 e03165 1  E E 0  E E S  0 E  E E  KG04582  0  0  Sir2 Su(var)20 5 Su(var)31 Su(var)34 trr  MED23 MED24 MED28 MED29 (intersex)  138  Gene  Allele  Drosophila Marcal1  KG029 00 EP2518 1 k05605 wimp S  E  1  S  10  S  23 27  S S  Trf2  PL28#1  S  TfIIA-L  e01040 d08487  0 S  TfIIA-S  E32  S  E73  S E  mia (TFIID)  EY0232 3 DG143 11 EP1564 BG009 48 B560  Taf1 (TFIID)  cul-4 RpII33 RpII140  pb (srb)  TfIIB caz (TFIID) e(y)1 (TFIID)  S 0 0 E S  Human SMARCAL1  Gene  RNA Polymerase II Complex E RpII215  Allele  Drosophila Marcal1  Human SMARCAL1  3  0  0  S E E E 0 S S E E  S S E E S S E S E  S  0  E  S  S E  E 0  0  E  0 0  E 0  E  E  E  S  S  0  0 0 S E S  4 8 12 102 G0040 K1 ts Ubl EY06155 RNA Polymerase II Initiation Factors E Taf2 c03353 (TFIID) S Taf4 1 (TFIID) S e02502 0 Taf5 EY01764b (TFIID) S Taf6 1 (TFIID) E f06930 E Taf10 KG07031 (TFIID) E Taf10b KG01574 (TFIID) 0 Taf12L KG00946 (TFIID) S e01382 TfIIEα  S  E  TfIIEβ  e00364  S  E  E S  E S  TfIIFα TfIIFβ  d01485 j3C1  S E  E S  S  S  Cdk7 (TFIIH)  T170A  E, blistered  E  EY0788 3 1  E  E  D136R  E  E  S  S  KG02273  E  E  EP421  E  E  f00028  0  E  CycH (TFIIH) hay (TFIIH, Xpb, Ercc3)  139  Gene  Allele  Drosophila Marcal1  Cdk9  f05537  E  CycT  c04764 c06571 EY0160 4 EP3132 EY0402 2 e01107 DG125 05 EY0813 8 EY0869 6  S E E  dre4 (FACT, Spt16) Elongin-B Elongin-C Mi-2  Ids  1 A190 e00889 Hor-1  cdc2  B47 c03495 E1-23 E1-24 GT000294 03946 c05304 C8LR1 H170 EY1174 6 KG092 94 NP471 9  CycA  Dref  barr Cap-G (condensin) gluon  k14014 L305 BG018 73 EP2346 88-37 k08819  Human SMARCAL1  Gene  Allele  RNA Polymerase II Elongation Factors E mus209 02448 (PCNA) S k00704 E EY09082 S Spt4 k05316  Drosophila Marcal1  Human SMARCAL1  S  S  0 E S  S E S  S E  0 E  Spt5  SIE-27 W049  S S, small  S 0  S S  0 0  Spt6 Su(Tpl) (ELL)  G0063 10  S S  S S  E  E  c00783  0  0  E  E  c03115  S  0  S S  E 0  S S  E 0  0 S S E S  S S S E S  i2 KG03332 EY14408 06850 IM  0 S E E E  S S 0 E E  s2140  E  S  S E E  S E E  S S S  S S S  S-192 TfIIS 2 RNA Polymerase II Transcription Termination Factors S E Pcf11 k08015 0 E Slbp EP1045 S E E E Regulators of DNA Replication Gene Transcription S E Dp 49Fk-1 E S a1 E E KG00660 E E EY09085 E E E2f 07172 E E S S E  0 S E S S  0  S  0  0  grh  Regulators of Chromatin Condensation and Segregation S S mei-9 f01366 S S mei-P22 A054 E E P22 E S S  E 0 S  mei-W68 pros  1 k05603 17  Key: S = suppressor, 0 = Neither a suppressor nor an enhancer, E = enhancer.  140  Appendix 4- Table showing enrichment in biological process GO-terms (all levels) of upregulated expressed genes (q<0.05 and fold change >2) in SIOD compared to control human skin fibroblasts. Term GO:0009987~cellular process GO:0008152~metabolic process GO:0044237~cellular metabolic process GO:0044238~primary metabolic process GO:0043170~macromolecule metabolic process GO:0044260~cellular macromolecule metabolic process GO:0060255~regulation of macromolecule metabolic process GO:0019538~protein metabolic process GO:0016043~cellular component organization GO:0044267~cellular protein metabolic process GO:0048518~positive regulation of biological process GO:0048522~positive regulation of cellular process GO:0048519~negative regulation of biological process GO:0048523~negative regulation of cellular process GO:0006950~response to stress GO:0006996~organelle organization GO:0007242~intracellular signaling cascade GO:0043687~post-translational protein modification GO:0008219~cell death GO:0016265~death GO:0033036~macromolecule localization GO:0051641~cellular localization GO:0016070~RNA metabolic process GO:0042981~regulation of apoptosis GO:0043067~regulation of programmed cell death GO:0010941~regulation of cell death GO:0031325~positive regulation of cellular metabolic process  Count  p-value  401 292 265 265 229 216  3.81E-06 0.002569399 2.59E-04 0.005201134 9.89E-04 2.30E-04  Fold Enrichment 1.114107687 1.118294973 1.169510453 1.121027209 1.174529652 1.213241719  128  0.046000907  1.150244646  123 115 113 99  0.001809831 4.26E-04 9.19E-05 1.77E-04  1.281015565 1.348248723 1.405245307 1.426140875  90  3.81E-04  1.427053403  82  0.005801357  1.325318531  75  0.008995627  1.323176524  72 71 57 54  0.033087325 1.58E-04 0.022358971 0.023643914  1.251403031 1.561056908 1.329076037 1.337953114  51 51 49 47 45 44 44  1.21E-06 1.49E-06 0.032408923 0.006627596 0.019158633 0.002250946 0.002678309  2.077331933 2.062985718 1.333670117 1.483250465 1.404993409 1.602733222 1.586942747  44 43  0.002905771 0.016797479  1.58110124 1.431035458  141  Term GO:0008104~protein localization GO:0009893~positive regulation of metabolic process GO:0007049~cell cycle GO:0051649~establishment of localization in cell GO:0012501~programmed cell death GO:0006915~apoptosis GO:0009057~macromolecule catabolic process GO:0044265~cellular macromolecule catabolic process GO:0015031~protein transport GO:0045184~establishment of protein localization GO:0042127~regulation of cell proliferation GO:0046907~intracellular transport GO:0051246~regulation of protein metabolic process GO:0010605~negative regulation of macromolecule metabolic process GO:0006396~RNA processing GO:0051603~proteolysis involved in cellular protein catabolic process GO:0044257~cellular protein catabolic process GO:0030163~protein catabolic process GO:0019941~modification-dependent protein catabolic process GO:0043632~modification-dependent macromolecule catabolic process GO:0022402~cell cycle process GO:0043065~positive regulation of apoptosis GO:0043068~positive regulation of programmed cell death GO:0010942~positive regulation of cell death GO:0032268~regulation of cellular protein metabolic process GO:0033554~cellular response to stress GO:0016071~mRNA metabolic process GO:0006397~mRNA processing GO:0000278~mitotic cell cycle  Count  p-value  43 43  0.017376476 0.032409111  Fold Enrichment 1.42779048 1.367330297  42 42 41 40 39 38  0.003465433 0.016008514 5.87E-05 9.04E-05 0.017024787 0.009034006  1.585083629 1.443691193 1.965202274 1.945934024 1.462440429 1.535006439  38 38  0.01909319 0.021206917  1.460472005 1.447177722  37 36 35  0.043581024 0.005863484 5.15E-04  1.37686577 1.604729154 1.877327375  35  0.042952226  1.396486031  34 34  0.001076341 0.00454528  1.820355466 1.6595574  34 34 32  0.005102412 0.007935734 0.007731843  1.651300895 1.600859228 1.632686108  32  0.007731843  1.632686108  30 29 29  0.018796618 8.12E-04 9.10E-04  1.555025153 1.975123034 1.961438579  29  9.82E-04  1.95242047  29  0.003414836  1.79177828  29 26 25 25  0.030924616 9.13E-04 2.75E-04 0.00198551  1.500535167 2.057956712 2.280865035 1.978804531 142  Term GO:0051128~regulation of cellular component organization GO:0022403~cell cycle phase GO:0008283~cell proliferation GO:0008380~RNA splicing GO:0043066~negative regulation of apoptosis GO:0043069~negative regulation of programmed cell death GO:0060548~negative regulation of cell death GO:0007243~protein kinase cascade GO:0006917~induction of apoptosis GO:0012502~induction of programmed cell death GO:0000279~M phase GO:0044419~interspecies interaction between organisms GO:0031399~regulation of protein modification process GO:0010608~posttranscriptional regulation of gene expression GO:0002520~immune system development GO:0051301~cell division GO:0048285~organelle fission GO:0006511~ubiquitin-dependent protein catabolic process GO:0010627~regulation of protein kinase cascade GO:0048534~hemopoietic or lymphoid organ development GO:0080134~regulation of response to stress GO:0007067~mitosis GO:0000280~nuclear division GO:0000087~M phase of mitotic cell cycle GO:0000398~nuclear mRNA splicing, via spliceosome GO:0000377~RNA splicing, via transesterification reactions with bulged adenosine as nucleophile GO:0000375~RNA splicing, via transesterification reactions GO:0010035~response to inorganic substance GO:0033043~regulation of organelle organization  Count  p-value  25  0.02463692  Fold Enrichment 1.598597547  24 24 23 23 23  0.014968538 0.025690403 2.98E-04 0.004995943 0.005812809  1.697756931 1.612090297 2.371778388 1.902782662 1.87628151  23 21 19 19 19 18  0.006090459 0.028709615 0.026168464 0.027214012 0.033125271 0.01720956  1.871069617 1.662195806 1.738874481 1.733457427 1.691306486 1.862733311  18  0.024629861  1.786961108  17  0.002389789  2.359560284  17 17 16 16  0.027336969 0.045796846 0.011981384 0.018921815  1.803866739 1.687685491 2.04620486 1.936284764  16 16  0.02375317 0.033108102  1.881851056 1.80223428  16 15 15 15 14  0.048419471 0.018694996 0.018694996 0.021450152 0.002222452  1.710149317 1.996793663 1.996793663 1.961136633 2.679792802  14  0.002222452  2.679792802  14  0.002222452  2.679792802  14 14  0.023503298 0.034963921  2.000040482 1.889439165 143  Term GO:0010740~positive regulation of protein kinase cascade GO:0051248~negative regulation of protein metabolic process GO:0044087~regulation of cellular component biogenesis GO:0018193~peptidyl-amino acid modification GO:0006979~response to oxidative stress GO:0006457~protein folding GO:0032269~negative regulation of cellular protein metabolic process GO:0051130~positive regulation of cellular component organization GO:0009101~glycoprotein biosynthetic process GO:0070647~protein modification by small protein conjugation or removal GO:0043523~regulation of neuron apoptosis GO:0010038~response to metal ion GO:0030155~regulation of cell adhesion GO:0007005~mitochondrion organization GO:0051640~organelle localization GO:0045937~positive regulation of phosphate metabolic process GO:0010562~positive regulation of phosphorus metabolic process GO:0043122~regulation of I-kappaB kinase/NFkappaB cascade GO:0009791~post-embryonic development GO:0007059~chromosome segregation GO:0060191~regulation of lipase activity GO:0043123~positive regulation of I-kappaB kinase/NF-kappaB cascade GO:0042327~positive regulation of phosphorylation GO:0043524~negative regulation of neuron apoptosis GO:0051592~response to calcium ion GO:0051656~establishment of organelle localization GO:0031349~positive regulation of defense response  Count  p-value  13  0.011949331  Fold Enrichment 2.279772405  13  0.026591009  2.03594648  12  0.009309886  2.474899188  12 12 12 12  0.022914376 0.024814323 0.040034652 0.044306334  2.169356078 2.142900516 1.985512343 1.95242047  12  0.045797201  1.941633617  11 11  0.044035898 0.047264982  2.038920111 2.01343361  10 10 10 10 9 9  0.003520201 0.032311256 0.044730063 0.04647877 0.013115858 0.020771924  3.254034117 2.270256361 2.137686646 2.122196163 2.86496482 2.635767635  9  0.020771924  2.635767635  9  0.029700616  2.463334238  8 8 8 8  0.011993542 0.020337977 0.02878751 0.047622255  3.209458307 2.892474771 2.692993752 2.41536553  8  0.047622255  2.41536553  7  0.00745701  4.019689203  7 7  0.010715017 0.029862946  3.727348171 2.971074629  7  0.037918032  2.808276019  144  Term GO:0000302~response to reactive oxygen species GO:0031647~regulation of protein stability GO:0006944~membrane fusion GO:0042542~response to hydrogen peroxide GO:0016197~endosome transport GO:0000186~activation of MAPKK activity GO:0002831~regulation of response to biotic stimulus GO:0006984~ER-nuclear signaling pathway GO:0002711~positive regulation of T cell mediated immunity GO:0002709~regulation of T cell mediated immunity GO:0048538~thymus development GO:0006829~zinc ion transport GO:0001916~positive regulation of T cell mediated cytotoxicity GO:0002839~positive regulation of immune response to tumor cell GO:0002833~positive regulation of response to biotic stimulus GO:0002834~regulation of response to tumor cell GO:0002836~positive regulation of response to tumor cell GO:0002837~regulation of immune response to tumor cell GO:0001914~regulation of T cell mediated cytotoxicity GO:0009435~NAD biosynthetic process GO:0019359~nicotinamide nucleotide biosynthetic process GO:0001953~negative regulation of cell-matrix adhesion  Count  p-value  7 6 6 6 6 5 5  0.04241817 0.013549339 0.033795482 0.041454286 0.047097032 0.009538241 0.016095999  Fold Enrichment 2.733388658 4.183758151 3.315430987 3.137818613 3.029617971 5.857261411 5.049363285  5 4  0.030268257 0.013178866  4.183758151 7.809681881  4  0.033143367  5.578344201  4 4 3  0.037432742 0.046814116 0.021717286  5.324783101 4.881051176 12.55127445  3  0.02831063  10.98236515  3  0.02831063  10.98236515  3 3  0.02831063 0.02831063  10.98236515 10.98236515  3  0.02831063  10.98236515  3  0.035590042  9.762102351  3 3  0.035590042 0.043501312  9.762102351 8.785892116  3  0.043501312  8.785892116  145  Appendix 5- Table showing enrichment in biological process GO-terms (all levels) of downregulated expressed genes (q<0.05 and fold change >2) in SIOD compared to control human skin fibroblasts. Term GO:0009987~cellular process GO:0008152~metabolic process GO:0044238~primary metabolic process GO:0044237~cellular metabolic process GO:0043170~macromolecule metabolic process GO:0044260~cellular macromolecule metabolic process GO:0006807~nitrogen compound metabolic process GO:0034641~cellular nitrogen compound metabolic process GO:0009058~biosynthetic process GO:0006139~nucleobase, nucleoside, nucleotide and nucleic acid metabolic process GO:0044249~cellular biosynthetic process GO:0019538~protein metabolic process GO:0010467~gene expression GO:0009059~macromolecule biosynthetic process GO:0034645~cellular macromolecule biosynthetic process GO:0044267~cellular protein metabolic process GO:0016043~cellular component organization GO:0048518~positive regulation of biological process GO:0048519~negative regulation of biological process GO:0048522~positive regulation of cellular process GO:0048523~negative regulation of cellular process GO:0006996~organelle organization GO:0051641~cellular localization GO:0016070~RNA metabolic process  Count  p-value  494 353 333 325 288  4.46E-09 0.00138666 6.81E-05 1.72E-05 8.74E-06  Fold Enrichment 1.130839368 1.113882546 1.160661785 1.181769473 1.217060488  271  1.65E-06  1.254163183  181  0.014593108  1.156038785  179  0.00724506  1.176908638  169 167  0.021436468 0.008790601  1.151314386 1.182075602  165 155 153 143  0.020140687 6.88E-05 0.002703185 0.005928128  1.156721644 1.330062856 1.231035986 1.218424357  142  0.00602068  1.218509197  139  6.72E-06  1.424228501  132 100  0.001720248 0.04314565  1.275079551 1.186911684  99  0.002875626  1.318356257  96  0.013345635  1.254180723  92  0.00281572  1.337320564  88 64 64  1.04E-05 6.48E-05 8.77E-05  1.594168528 1.664132037 1.646390757 146  Term GO:0033036~macromolecule localization GO:0051649~establishment of localization in cell GO:0006508~proteolysis GO:0007049~cell cycle GO:0008104~protein localization GO:0044248~cellular catabolic process GO:0046907~intracellular transport GO:0015031~protein transport GO:0045184~establishment of protein localization GO:0022607~cellular component assembly GO:0009892~negative regulation of metabolic process GO:0009057~macromolecule catabolic process GO:0022402~cell cycle process GO:0044265~cellular macromolecule catabolic process GO:0010605~negative regulation of macromolecule metabolic process GO:0031324~negative regulation of cellular metabolic process GO:0043067~regulation of programmed cell death GO:0010941~regulation of cell death GO:0051603~proteolysis involved in cellular protein catabolic process GO:0044257~cellular protein catabolic process GO:0030163~protein catabolic process GO:0019941~modification-dependent protein catabolic process GO:0043632~modification-dependent macromolecule catabolic process GO:0006396~RNA processing GO:0006412~translation GO:0051246~regulation of protein metabolic process GO:0006259~DNA metabolic process GO:0016192~vesicle-mediated transport GO:0000278~mitotic cell cycle  Count  p-value  63 59  0.004707418 1.19E-04  Fold Enrichment 1.412810981 1.67096826  59 56 56 55 54 51 51  0.015287291 6.29E-05 0.001470351 0.039031249 2.30E-06 8.20E-04 9.81E-04  1.350725766 1.741334038 1.532058065 1.296040331 1.983280646 1.61499428 1.600293421  49 48  0.03380139 0.006139044  1.332994151 1.484917817  47 46 46  0.009906301 1.93E-05 0.004102933  1.452120337 1.964559413 1.531001474  46  0.005301377  1.512228976  45  0.006204503  1.508119658  45  0.040055776  1.337248958  45 41  0.04235056 0.00198611  1.332326569 1.648877493  41 41 40  0.002190998 0.003785536 0.001617958  1.640674122 1.590557067 1.681527145  40  0.001617958  1.681527145  39 38 38  0.001236903 3.71E-08 0.002198151  1.720414381 2.770201668 1.679371341  36 36 34  0.002058718 0.014772651 2.84E-05  1.716752812 1.508119658 2.217343497 147  Term GO:0022403~cell cycle phase GO:0009890~negative regulation of biosynthetic process GO:0032268~regulation of cellular protein metabolic process GO:0045934~negative regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolic process GO:0051172~negative regulation of nitrogen compound metabolic process GO:0010558~negative regulation of macromolecule biosynthetic process GO:0031327~negative regulation of cellular biosynthetic process GO:0051128~regulation of cellular component organization GO:0016071~mRNA metabolic process GO:0034613~cellular protein localization GO:0070727~cellular macromolecule localization GO:0045595~regulation of cell differentiation GO:0010629~negative regulation of gene expression GO:0006397~mRNA processing GO:0008380~RNA splicing GO:0007010~cytoskeleton organization GO:0034621~cellular macromolecular complex subunit organization GO:0016481~negative regulation of transcription GO:0006886~intracellular protein transport GO:0032989~cellular component morphogenesis GO:0000279~M phase GO:0034622~cellular macromolecular complex assembly GO:0043069~negative regulation of programmed cell death GO:0060548~negative regulation of cell death GO:0006325~chromatin organization  Count  p-value  34 34  2.45E-04 0.034713442  Fold Enrichment 1.981683802 1.431792485  33  0.004526851  1.679930758  33  0.013118819  1.555248397  33  0.01596552  1.534272022  33  0.030433277  1.455735246  33  0.041037632  1.419406737  32  0.004946304  1.685932893  31 31 31  3.49E-04 0.001922284 0.002104962  2.021695542 1.820017884 1.806829349  31 31  0.021870139 0.029362287  1.520380794 1.484181251  30 29 29 28  6.83E-05 1.91E-05 0.014571112 0.001893405  2.255132199 2.463970146 1.604971379 1.892542316  28  0.04203877  1.471977357  27 26  0.006916062 0.02459913  1.741999177 1.580296669  25 24  0.005188806 0.006777963  1.833580131 1.821125625  24  0.025433379  1.613141918  24  0.026055164  1.608660969  24  0.042046722  1.532058065 148  Term GO:0044419~interspecies interaction between organisms GO:0007264~small GTPase mediated signal transduction GO:0006519~cellular amino acid and derivative metabolic process GO:0043066~negative regulation of apoptosis GO:0000902~cell morphogenesis GO:0006511~ubiquitin-dependent protein catabolic process GO:0032535~regulation of cellular component size GO:0001501~skeletal system development GO:0006414~translational elongation GO:0000398~nuclear mRNA splicing, via spliceosome GO:0000377~RNA splicing, via transesterification reactions with bulged adenosine as nucleophile GO:0000375~RNA splicing, via transesterification reactions GO:0000087~M phase of mitotic cell cycle GO:0044106~cellular amine metabolic process GO:0006605~protein targeting GO:0007067~mitosis GO:0000280~nuclear division GO:0048285~organelle fission GO:0051169~nuclear transport GO:0030036~actin cytoskeleton organization GO:0030029~actin filament-based process GO:0006913~nucleocytoplasmic transport GO:0006260~DNA replication GO:0006916~anti-apoptosis GO:0010608~posttranscriptional regulation of gene expression GO:0000904~cell morphogenesis involved in differentiation GO:0051130~positive regulation of cellular component organization GO:0009968~negative regulation of signal transduction  Count  p-value  23  0.003413072  Fold Enrichment 1.96108846  23  0.008230071  1.819632899  23  0.035545322  1.576670552  23 23 22  0.037848088 0.039923928 0.001119248  1.567762808 1.558955152 2.193628594  22  0.004380449  1.95888605  22 21 21  0.024485677 4.54E-09 5.04E-06  1.664132037 5.017110942 3.311949053  21  5.04E-06  3.311949053  21  5.04E-06  3.311949053  20 20 19 19 19 19 18 18 18 17 17 17 17  0.00245136 0.049954855 0.003619753 0.004602839 0.004602839 0.006936248 2.93E-04 0.012866985 0.022611851 7.44E-04 0.005577274 0.011730717 0.014481678  2.154456654 1.582289477 2.132411051 2.083947164 2.083947164 2.00204531 2.748977605 1.9218516 1.80223428 2.629541968 2.158992353 1.991303626 1.944116337  17  0.04681793  1.68118257  16  0.008244027  2.133031119  16  0.041107244  1.746962138 149  Term GO:0006520~cellular amino acid metabolic process GO:0044087~regulation of cellular component biogenesis GO:0032269~negative regulation of cellular protein metabolic process GO:0051248~negative regulation of protein metabolic process GO:0060348~bone development GO:0048193~Golgi vesicle transport GO:0006417~regulation of translation GO:0051329~interphase of mitotic cell cycle GO:0051325~interphase GO:0001503~ossification GO:0006333~chromatin assembly or disassembly GO:0051493~regulation of cytoskeleton organization GO:0043254~regulation of protein complex assembly GO:0031400~negative regulation of protein modification process GO:0042692~muscle cell differentiation GO:0031398~positive regulation of protein ubiquitination GO:0031396~regulation of protein ubiquitination GO:0007498~mesoderm development GO:0051028~mRNA transport GO:0032956~regulation of actin cytoskeleton organization GO:0065004~protein-DNA complex assembly GO:0032970~regulation of actin filamentbased process GO:0009894~regulation of catabolic process GO:0051348~negative regulation of transferase activity GO:0050658~RNA transport GO:0051236~establishment of RNA localization GO:0050657~nucleic acid transport  Count  p-value  16  0.048692909  Fold Enrichment 1.708312533  14  0.006020286  2.379005658  14  0.036411103  1.87677113  14  0.047054499  1.806517665  13 13 13 12 12 12 12  0.004942309 0.008105847 0.011379132 0.003513838 0.004384042 0.008055309 0.01621979  2.55031617 2.394571671 2.289699919 2.811252178 2.731688437 2.517904125 2.279991924  12  0.025568552  2.129110106  11  0.003970442  2.949211776  11  0.025700206  2.230496301  11 10  0.028433831 0.007776489  2.193628594 2.872608873  10  0.022583441  2.412991453  9 9 9  0.011191389 0.027340759 0.030790635  2.934719335 2.496198055 2.440103717  9 9  0.034527709 0.036506704  2.386475063 2.360535117  9 9  0.045181887 0.045181887  2.262179487 2.262179487  9 9  0.047544783 0.047544783  2.238858049 2.238858049  9  0.047544783  2.238858049 150  Term  Count  p-value  GO:0051168~nuclear export GO:0009116~nucleoside metabolic process GO:0009896~positive regulation of catabolic process GO:0000082~G1/S transition of mitotic cell cycle GO:0030832~regulation of actin filament length GO:0018209~peptidyl-serine modification GO:0006888~ER to Golgi vesicle-mediated transport GO:0030111~regulation of Wnt receptor signaling pathway GO:0009156~ribonucleoside monophosphate biosynthetic process GO:0009161~ribonucleoside monophosphate metabolic process GO:0045732~positive regulation of protein catabolic process GO:0000245~spliceosome assembly GO:0006406~mRNA export from nucleus GO:0046112~nucleobase biosynthetic process GO:0060070~Wnt receptor signaling pathway through beta-catenin GO:0006611~protein export from nucleus GO:0006541~glutamine metabolic process GO:0060260~regulation of transcription initiation from RNA polymerase II promoter GO:0006563~L-serine metabolic process GO:0008535~respiratory chain complex IV assembly  8 8 7  0.01156751 0.01616677 0.01508882  Fold Enrichment 3.217321937 3.016239316 3.447130647  7  0.027544912  3.016239316  7  0.045400815  2.681101614  6 6  0.021467463 0.028689536  3.712294543 3.447130647  6  0.040465698  3.147380156  5  0.013722009  5.245633593  5  0.018370462  4.825982906  5  0.023889125  4.468502691  5 5 4 4  0.041676657 0.045931594 0.018232464 0.03107872  3.770299145 3.656047656 6.894261294 5.677626948  4 4 3  0.036177914 0.041678094 0.031246927  5.362203229 5.079982006 10.34139194  3 3  0.040537411 0.040537411  9.048717949 9.048717949  151  Appendix 6- Table showing qRT-PCR measurement of mRNA levels of stress response genes in skin fibroblasts of three SIOD patients (SD31, SD120, and SD123) compared to control fibroblasts after 1 hour incubation at 43°C followed by 1 hour of recovery at 37°C. Gene  ATF6 BAG1 BAG2 BAG3 BAG4 BAG5 CABC1 CCS CCT2 CCT3 CCT4 CCT5 CCT6A CCT6B CCT7 CRYAA CRYAB DNAJA1 DNAJA2 DNAJA3 DNAJA4 DNAJC21 DNAJB1 DNAJB11 DNAJB12 DNAJB13 DNAJB14 DNAJB2 DNAJB5 DNAJB6 DNAJB7 DNAJB8 DNAJB9 DNAJC1 DNAJC10 DNAJC11 DNAJC12 DNAJC13 DNAJC14 DNAJC15 DNAJC16 DNAJC17  SD31 Fold p-value Change1 1.2622 2.8363 2.6069 2.3752 1.7519 1.6503 4.4718 1.6052 1.0555 1.1803 1.2538 1.703 -1.2678 2.4445 1.121 2.0308 2.7728 1.8902 1.8288 1.5186 1.6543 1.6838 3.0693 1.256 1.5516 4.908 2.4886 1.8237 1.5158 2.309 -1.8478 2.0308 1.6876 1.24 2.0484 1.3614 4.0663 2.8202 1.6656 1.0088 2.0805 -1.1704  0.135459 0.000352 0.015457 0.005095 0.007574 0.000079 0.00748 0.091673 0.71912 0.371998 0.291481 0.044326 0.182014 0.008641 0.318941 0.031656 0.000798 0.004721 0.015735 0.086909 0.04226 0.004414 0.003061 0.391398 0.062903 0.011193 0.009531 0.053194 0.023366 0.013448 0.122297 0.031656 0.047743 0.240858 0.013372 0.148716 0.00048 0.00894 0.037315 0.875137 0.007253 0.550877  SD120 Fold p-value Change1 1.1527 1.0019 1.3677 1.1335 -1.6417 -1.3089 -1.1867 1.5811 1.2794 1.2696 1.0296 1.5918 1.3918 2.232 1.1537 -1.6865 1.1662 -1.0411 -1.0806 -1.3755 1.1148 -1.3175 -1.3566 1.556 -1.1573 2.574 -1.216 1.7778 -1.5119 -1.2422 -2.4916 -1.6865 1.1626 1.066 1.2707 -1.3231 4.9156 -1.0573 -1.3898 -1.2968 -1.5147 -1.0757  0.341137 0.966192 0.076477 0.246809 0.015668 0.007806 0.322074 0.033582 0.07323 0.041069 0.782612 0.021589 0.019737 0.003443 0.159775 0.013274 0.170989 0.59516 0.533833 0.062798 0.410201 0.01605 0.048129 0.019928 0.2057 0.008645 0.160202 0.017276 0.00172 0.128193 0.034937 0.013274 0.134903 0.507613 0.097916 0.129836 0.002463 0.651368 0.060453 0.048745 0.00464 0.647931  SD123 Fold p-value Change1 1.1267 3.5748 1.7561 2.1359 -1.4703 1.0188 3.1199 1.6779 1.0454 -1.0921 -1.1474 2.2955 -1.226 2.6615 1.0567 1.1369 2.3195 1.4992 1.1494 -1.1313 4.9672 1.8026 2.3388 2.1741 -1.0132 1.3815 1.3437 1.8953 1.1922 1.5142 -11.5765 1.1369 1.428 1.5821 1.373 -1.0958 5.1697 1.8742 -1.0039 1.834 -1.1601 1.0509  0.229573 0.001308 0.005454 0.000965 0.04208 0.713173 0.002126 0.00864 0.731147 0.802387 0.155044 0.000936 0.117257 0.000856 0.589396 0.397599 0.000731 0.003205 0.133854 0.21911 0.000418 0.00075 0.000324 0.002693 0.837028 0.192883 0.031363 0.006963 0.007919 0.011459 0.00032 0.397599 0.214447 0.002946 0.027786 0.414228 0.000236 0.001514 0.941755 0.001982 0.244467 0.727862  152  Gene  DNAJC18 DNAJC19 DNAJC3 DNAJC4 DNAJC5 DNAJC5B DNAJC5G DNAJC6 DNAJC7 DNAJC8 DNAJC9 HSF1 HSF2 HSF4 HSP90AA1 HSP90AB1 HSP90B1 HSPA14 HSPA1A HSPA1B HSPA1L HSPA2 HSPA4 HSPA4L HSPA5 HSPA8 HSPA9 HSPB1 HSPB2 HSPB3 HSPB6 HSPB7 HSPB8 HSPD1 HSPE1 HSPH1 PFDN1 PFDN2 SERPINH1 SIL1 TCP1 TOR1A  SD31 Fold p-value Change1 2.3974 2.0104 1.6272 2.1059 1.4992 -1.7485 2.7951 4.3437 1.4678 2.9316 -1.2187 1.7037 3.7187 3.0363 2.938 2.1555 1.3814 1.1383 2.5847 2.9215 5.5563 2.8723 2.2979 3.8847 3.8825 1.5769 1.197 1.4327 2.071 2.8403 -1.0588 14.0196 -1.2165 3.1641 2.0426 4.2396 2.8813 1.2087 1.0267 1.2471 1.7705 2.0642  0.000544 0.02115 0.0203 0.007588 0.089455 0.05082 0.074388 0.002866 0.079094 0.082972 0.059206 0.001014 0.000054 0.000718 0.00552 0.002423 0.011546 0.063373 0.046463 0.005535 0.000001 0.007686 0.002071 0.016677 0.00498 0.002565 0.234855 0.141766 0.017525 0.014347 0.751031 0.000908 0.248509 0.002914 0.000039 0.001114 0.001943 0.320503 0.771942 0.001528 0.214631 0.016952  SD120 Fold p-value Change1 1.0137 -1.0308 -1.0526 1.213 -1.0945 -13.9052 -2.2499 -4.2096 -1.2378 1.1456 -1.297 1.2039 1.1685 1.3445 1.0408 1.0505 1.1989 -1.0317 -1.2247 -1.4627 -1.2233 -1.1206 1.0027 -1.1327 1.6645 -1.2295 1.0549 1.0467 -1.1902 -1.5145 -1.1489 -1.3056 -1.0672 -1.2302 1.0677 1.0436 -1.2699 1.2494 1.4885 1.1006 -1.1336 1.1888  0.761849 0.732268 0.483296 0.134052 0.556829 0.001171 0.04763 0.00158 0.105793 0.606909 0.002987 0.012965 0.245527 0.035484 0.692262 0.454187 0.025172 0.782365 0.344951 0.002436 0.036845 0.283253 0.932654 0.339189 0.002534 0.00289 0.51817 0.748537 0.111889 0.018669 0.165979 0.047857 0.531006 0.118704 0.301475 0.598721 0.384879 0.075045 0.003026 0.053786 0.604575 0.229031  SD123 Fold p-value Change1 1.2689 1.3744 1.1837 1.672 1.0841 -6.931 2.627 5.0898 1.0816 1.2251 -1.6626 1.693 2.6181 -1.1376 3.2181 1.8069 1.4283 1.1064 2.1791 1.7568 3.9498 4.2841 1.6326 1.761 7.3608 1.1998 -1.3069 1.4403 1.5279 3.3656 -1.1973 3.3633 -2.5981 1.6812 1.6065 4.093 1.2868 1.3943 1.0247 1.1353 1.0429 1.7942  0.05454 0.042366 0.045033 0.002261 0.581058 0.002672 0.08139 0.000102 0.430962 0.402511 0.000321 0.000554 0.000216 0.042188 0.000208 0.000318 0.000416 0.333144 0.007469 0.00079 0.00004 0.000186 0.007511 0.002674 0.00008 0.01201 0.023021 0.023439 0.002922 0.000012 0.092469 0.000037 0.00206 0.006083 0.000192 0.000038 0.385838 0.01892 0.744577 0.206732 0.994102 0.008074  Key: 1 Fold change of SMARCAL1-deficient fibroblast relative to control fibroblasts.  153  Appendix 7- Table showing enrichment in biological process GO-terms (all levels) of  upregulated expressed genes (fold change >2) between Smarcal1del/del and Smarcal1+/+ mouse livers at 20°C. Term GO:0009987~cellular process GO:0008152~metabolic process GO:0044238~primary metabolic process GO:0044237~cellular metabolic process GO:0043170~macromolecule metabolic process GO:0044260~cellular macromolecule metabolic process GO:0010467~gene expression GO:0034641~cellular nitrogen compound metabolic process GO:0006807~nitrogen compound metabolic process GO:0006139~nucleobase, nucleoside, nucleotide and nucleic acid metabolic process GO:0009058~biosynthetic process GO:0019222~regulation of metabolic process GO:0044249~cellular biosynthetic process GO:0034645~cellular macromolecule biosynthetic process GO:0009059~macromolecule biosynthetic process GO:0060255~regulation of macromolecule metabolic process GO:0031323~regulation of cellular metabolic process GO:0080090~regulation of primary metabolic process GO:0032502~developmental process GO:0010468~regulation of gene expression GO:0007275~multicellular organismal development GO:0031326~regulation of cellular biosynthetic process GO:0009889~regulation of biosynthetic process GO:0010556~regulation of macromolecule biosynthetic process GO:0019219~regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolic process GO:0051171~regulation of nitrogen compound metabolic process  Count  p-value  168 126 119 110 104 95  0.002641961 0.041472607 0.005718276 0.018369419 0.001672704 0.001393976  Fold Enrichment 1.137409509 1.124285553 1.200130932 1.176415284 1.274839867 1.308129879  77 77  1.23E-08 2.61E-05  1.87599573 1.553360716  77 71  7.25E-05 8.23E-05  1.509131734 1.54368359  69 68 68 63  0.001702868 8.38E-04 0.001191447 4.07E-05  1.405095868 1.447802897 1.429340981 1.645638987  63 63  4.50E-05 0.00102386  1.640167203 1.46809609  63  0.002514426 1.416454519  62  0.001479369 1.453444433  59 57 57 56  0.010833413 0.001966547 0.004506159 0.00455405  56 55  0.004919706 1.416708774 0.003461829 1.446926568  54  0.004396992 1.437523754  54  0.005191711 1.426009019  1.347315795 1.469909301 1.416267232 1.421877148  154  Term GO:0045449~regulation of transcription GO:0006350~transcription GO:0048856~anatomical structure development GO:0048731~system development GO:0048518~positive regulation of biological process GO:0030154~cell differentiation GO:0048869~cellular developmental process GO:0048513~organ development GO:0048522~positive regulation of cellular process GO:0006950~response to stress GO:0048523~negative regulation of cellular process GO:0048519~negative regulation of biological process GO:0042981~regulation of apoptosis GO:0043067~regulation of programmed cell death GO:0010941~regulation of cell death GO:0007242~intracellular signaling cascade GO:0016070~RNA metabolic process GO:0043065~positive regulation of apoptosis GO:0043068~positive regulation of programmed cell death GO:0010942~positive regulation of cell death GO:0009790~embryonic development GO:0051716~cellular response to stimulus GO:0009605~response to external stimulus GO:0048468~cell development GO:0006357~regulation of transcription from RNA polymerase II promoter GO:0006396~RNA processing GO:0033554~cellular response to stress GO:0043009~chordate embryonic development GO:0009792~embryonic development ending in birth or egg hatching GO:0031324~negative regulation of cellular metabolic process GO:0009892~negative regulation of metabolic process GO:0031327~negative regulation of cellular biosynthetic process  Count  p-value  53 49 47 43 40  Fold Enrichment 0.002262042 1.490729513 1.30E-04 1.732110361 0.02301666 1.356692178 0.04103519 1.328794751 0.001247878 1.678198701  38 38 37 36 32 32 32  0.009112483 0.016942011 0.033211865 0.001771508 0.003969109 0.004381093 0.018742393  1.517063816 1.454934675 1.393646639 1.708329996 1.692939636 1.681577625 1.511644441  28 28 28 28 25 19 19  2.13E-07 2.77E-07 3.05E-07 0.00138857 1.43E-04 8.82E-08 9.95E-08  3.171583115 3.131938326 3.115249489 1.916814713 2.365512331 4.798937758 4.760546256  19 19 18 18 17 17  1.12E-07 0.020838927 0.007637899 0.026914448 0.034895793 0.037331128  4.722764142 1.77632323 2.027873736 1.761715308 1.742813471 1.728667258  16 15 15 15  0.004303463 2.293410216 0.005324625 2.325696777 0.007488582 2.23178503 0.008095696 2.210779995  15  0.024559617 1.921434556  15  0.046216925 1.759515913  14  0.019983076 2.039401701 155  Term GO:0009890~negative regulation of biosynthetic GO:0012501~programmed cell death GO:0006917~induction of apoptosis GO:0012502~induction of programmed cell death GO:0010558~negative regulation of macromolecule biosynthetic process GO:0001701~in utero embryonic development GO:0006412~translation GO:0000122~negative regulation of transcription from RNA polymerase II promoter GO:0007264~small GTPase mediated signal transduction GO:0006974~response to DNA damage stimulus GO:0045892~negative regulation of transcription, DNA-dependent GO:0051253~negative regulation of RNA metabolic process GO:0034470~ncRNA processing GO:0034660~ncRNA metabolic process GO:0001944~vasculature development GO:0001568~blood vessel development GO:0046578~regulation of Ras protein signal transduction GO:0048514~blood vessel morphogenesis GO:0006351~transcription, DNA-dependent GO:0032774~RNA biosynthetic process GO:0009991~response to extracellular stimulus GO:0002460~adaptive immune response based on somatic recombination of immune receptors built from immunoglobulin superfamily domains GO:0002250~adaptive immune response GO:0035023~regulation of Rho protein signal transduction GO:0051789~response to protein stimulus GO:0031667~response to nutrient levels GO:0009451~RNA modification GO:0006959~humoral immune response GO:0007050~cell cycle arrest GO:0042770~DNA damage response, signal transduction  Count  p-value  14 14 13 13 13  Fold Enrichment 0.021588102 2.020605372 0.03909713 1.854001546 1.46E-05 4.876071645 1.46E-05 4.876071645 0.035038155 1.948095609  12 12 11  0.003666728 2.815225462 0.013128177 2.356317236 0.003909218 2.982798406  11  0.008344968 2.670645084  11 11  0.016570406 2.400788961 0.02551341 2.237098804  11  0.026733462 2.222665909  10 10 10 9 8  9.56E-04 0.005046953 0.018670222 0.04153762 0.025696357  3.964478894 3.100929036 2.505550661 2.310446306 2.768564266  8 7 7 7 6  0.038985868 0.01325368 0.015334994 0.01950439 0.010847465  2.530859253 3.594027587 3.479931473 3.296777185 4.474197609  6 6  0.010847465 4.474197609 0.011930806 4.370146501  6 6 5 5 5 5  0.012499086 0.036506779 0.00433406 0.010565775 0.012721112 0.012721112  4.319914932 3.268109558 7.456996014 5.799885789 5.494628642 5.494628642  156  Term GO:0001666~response to hypoxia GO:0070482~response to oxygen levels GO:0008033~tRNA processing GO:0030330~DNA damage response, signal transduction by p53 class mediator GO:0008630~DNA damage response, signal transduction resulting in induction of apoptosis GO:0007266~Rho protein signal transduction GO:0008629~induction of apoptosis by intracellular signals GO:0002455~humoral immune response mediated by circulating immunoglobulin GO:0031668~cellular response to extracellular stimulus GO:0009266~response to temperature stimulus GO:0042771~DNA damage response, signal transduction by p53 class mediator resulting in induction of apoptosis GO:0002886~regulation of myeloid leukocyte mediated immunity GO:0006400~tRNA modification GO:0045682~regulation of epidermis development GO:0032764~negative regulation of mast cell cytokine production GO:0042092~T-helper 2 type immune response GO:0002701~negative regulation of production of molecular mediator of immune response GO:0002719~negative regulation of cytokine production during immune response GO:0032763~regulation of mast cell cytokine production  Count  p-value  5 5 5 4  Fold Enrichment 0.018785915 4.893653634 0.019775435 4.818366655 0.02520166 4.474197609 0.003181089 13.18710874  4  0.005548627 10.89369853  4 4  0.008747268 9.279817262 0.017840719 7.158716174  4  0.017840719 7.158716174  4  0.034479228 5.567890357  4 3  0.047250824 4.912844433 0.020182964 13.42259283  3  0.023047212  3 3 2  0.026067652 11.74476872 0.032554682 10.43979442 0.031536926 62.63876652  2 2  0.031536926 62.63876652 0.046932062 41.75917768  2  0.046932062 41.75917768  2  0.046932062 41.75917768  12.5277533  157  Appendix 8- Table showing enrichment in biological process GO-terms (all levels) of  downregulated expressed genes (fold change >2) between Smarcal1del/del and Smarcal1+/+ mouse livers at 20°C. Term GO:0009987~cellular process GO:0008152~metabolic process GO:0044238~primary metabolic process GO:0044237~cellular metabolic process GO:0043170~macromolecule metabolic process GO:0044260~cellular macromolecule metabolic process GO:0009058~biosynthetic process GO:0044249~cellular biosynthetic process GO:0006807~nitrogen compound metabolic process GO:0034641~cellular nitrogen compound metabolic process GO:0006139~nucleobase, nucleoside, nucleotide and nucleic acid metabolic process GO:0019222~regulation of metabolic process GO:0010467~gene expression GO:0034645~cellular macromolecule biosynthetic process GO:0009059~macromolecule biosynthetic process GO:0060255~regulation of macromolecule metabolic process GO:0080090~regulation of primary metabolic process GO:0019538~protein metabolic process GO:0010468~regulation of gene expression GO:0031326~regulation of cellular biosynthetic process GO:0009889~regulation of biosynthetic process GO:0051171~regulation of nitrogen compound metabolic process GO:0010556~regulation of macromolecule biosynthetic process GO:0006810~transport GO:0019219~regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolic process GO:0051234~establishment of localization GO:0044267~cellular protein metabolic process  Count  p-value  391 343 293 290 231 218  1.17E-05 5.69E-13 4.96E-08 1.99E-10 1.85E-04 6.15E-06  Fold Enrichment 1.131659221 1.308372903 1.263224745 1.325858896 1.210502283 1.283261278  159 155 152 148  4.32E-06 4.28E-06 5.89E-04 6.43E-04  1.384156914 1.392803878 1.273536365 1.276364287  141  2.93E-04  1.310540322  128 126 122  0.034484236 1.165042677 6.91E-04 1.312329833 1.94E-04 1.362338986  122 121  2.29E-04 1.357809181 0.015912722 1.205398479  119  0.023253486 1.192573187  115 110 109  0.034991225 1.177607818 0.019242851 1.212661818 0.03676522 1.183128406  109 107  0.039317286 1.178827859 0.023060951 1.20793517  107  0.025084653 1.203369266  106 106  0.021882276 1.211974571 0.025307516 1.206308731  106 105  0.026288695 1.203750825 9.52E-04 1.346583653 158  Term GO:0045449~regulation of transcription GO:0006350~transcription GO:0006464~protein modification process GO:0009056~catabolic process GO:0033036~macromolecule localization GO:0044248~cellular catabolic process GO:0006629~lipid metabolic process GO:0009057~macromolecule catabolic process GO:0030163~protein catabolic process GO:0044265~cellular macromolecule catabolic process GO:0051603~proteolysis involved in cellular protein catabolic process GO:0044257~cellular protein catabolic process GO:0008104~protein localization GO:0019941~modification-dependent protein catabolic process GO:0043632~modification-dependent macromolecule catabolic process GO:0007049~cell cycle GO:0015031~protein transport GO:0045184~establishment of protein localization GO:0044255~cellular lipid metabolic process GO:0022402~cell cycle process GO:0022403~cell cycle phase GO:0000278~mitotic cell cycle GO:0055086~nucleobase, nucleoside and nucleotide metabolic process GO:0051301~cell division GO:0008610~lipid biosynthetic process GO:0009117~nucleotide metabolic process GO:0006753~nucleoside phosphate metabolic process GO:0006511~ubiquitin-dependent protein catabolic process GO:0070647~protein modification by small protein conjugation or removal GO:0008202~steroid metabolic process GO:0009165~nucleotide biosynthetic process  Count  p-value  103 89 60 54 48 47 46 45 43 43  0.013613902 0.002767204 0.039632935 0.012234347 0.012274357 0.006673421 2.25E-04 1.04E-04 1.08E-05 9.07E-05  Fold Enrichment 1.238487252 1.344933534 1.275132275 1.390384615 1.424981523 1.484145702 1.769795658 1.842507645 2.070943245 1.890713373  41  2.14E-05  2.055971702  41 39 38  2.45E-05 2.044485827 0.035654369 1.386896857 7.88E-05 2.003062117  38  7.88E-05  2.003062117  36 36 36 28 24 21 19 19  0.007789552 0.018992568 0.020583667 0.022949004 0.022339819 0.021679455 0.004626069 0.012146806  1.577741408 1.480798771 1.469512195 1.555555556 1.635284139 1.714430894 2.085154827 1.891367204  18 18 17 17  0.03441481 1.715302491 0.038563972 1.69122807 0.023018101 1.843004948 0.023018101 1.843004948  14  0.002354923 2.658786446  13 13 13  4.84E-04  3.347222222  0.017438114 2.162180814 0.02979772 2.00063857  159  Term GO:0034654~nucleobase, nucleoside, nucleotide and nucleic acid biosynthetic process GO:0034404~nucleobase, nucleoside and nucleotide biosynthetic process GO:0032446~protein modification by small protein conjugation GO:0009152~purine ribonucleotide biosynthetic process GO:0009260~ribonucleotide biosynthetic process GO:0022900~electron transport chain GO:0009150~purine ribonucleotide metabolic process GO:0009259~ribonucleotide metabolic process GO:0016567~protein ubiquitination GO:0009206~purine ribonucleoside triphosphate biosynthetic process GO:0009201~ribonucleoside triphosphate biosynthetic process GO:0009145~purine nucleoside triphosphate biosynthetic process GO:0009142~nucleoside triphosphate biosynthetic process GO:0009205~purine ribonucleoside triphosphate metabolic process GO:0009199~ribonucleoside triphosphate metabolic process GO:0009144~purine nucleoside triphosphate metabolic process GO:0045454~cell redox homeostasis GO:0051236~establishment of RNA localization GO:0050657~nucleic acid transport GO:0050658~RNA transport GO:0006403~RNA localization GO:0015931~nucleobase, nucleoside, nucleotide and nucleic acid transport GO:0006754~ATP biosynthetic process GO:0051028~mRNA transport GO:0046777~protein amino acid autophosphorylation GO:0051325~interphase  Count  p-value  13  Fold Enrichment 0.035923876 1.944754811  13  0.035923876 1.944754811  10  0.002625486 3.389592124  10  0.018414059 2.502596054  10 10 10  0.02281297 2.412412412 0.024020833 2.390873016 0.033774613 2.250233427  10 9 9  0.044069951 2.142222222 0.003033492 3.651515152 0.022608486 2.591397849  9  0.022608486 2.591397849  9  0.023937549 2.563829787  9  0.025320479 2.536842105  9  0.034801002 2.386138614  9  0.036586194 2.362745098  9  0.04434035  8 8  0.008026038 3.455197133 0.011197479 3.245791246  8 8 8 8  0.011197479 3.245791246 0.011197479 3.245791246 0.012114748 3.1973466 0.020105616 2.894894895  8 7 7  0.033055356 2.612466125 0.02751857 3.023297491 0.035972482 2.84006734  6  0.04063239  2.273584906  3.150326797 160  Term GO:0030518~steroid hormone receptor signaling pathway GO:0060322~head development GO:0030521~androgen receptor signaling pathway  Count  p-value  4  Fold Enrichment 0.041583328 5.100529101  4 3  0.041583328 5.100529101 0.025712762 11.47619048  161  Appendix 9- Table showing enrichment in biological process GO-terms (all levels) of  upregulated expressed genes (fold change >2) between Smarcal1del/del and Smarcal1+/+ mouse livers at 39.5°C. Term GO:0008152~metabolic process GO:0044237~cellular metabolic process GO:0044238~primary metabolic process GO:0043170~macromolecule metabolic process GO:0044260~cellular macromolecule metabolic process GO:0009058~biosynthetic process GO:0010467~gene expression GO:0044249~cellular biosynthetic process GO:0034645~cellular macromolecule biosynthetic process GO:0009059~macromolecule biosynthetic process GO:0044267~cellular protein metabolic process GO:0009057~macromolecule catabolic process GO:0006412~translation GO:0044257~cellular protein catabolic process GO:0030163~protein catabolic process GO:0044265~cellular macromolecule catabolic process GO:0001889~liver development GO:0006351~transcription, DNA-dependent GO:0032774~RNA biosynthetic process  Count  p-value  23 20 20 18 17  0.003300414 0.007034519 0.014637179 0.01055318 0.00816963  Fold Enrichment 1.552882241 1.618462239 1.526216927 1.669549902 1.771253755  13 12 12 11  0.013022419 0.00933004 0.027232697 0.016557519  2.0031101 2.212213147 1.908590604 2.174159021  11 10 6 5 5 5 5  0.016931463 0.019537026 0.009614252 0.003791732 0.022593811 0.025292651 0.03383289  2.166929897 2.2699553 4.348318043 7.428944619 4.413097455 4.262290168 3.891351943  3 3 3  0.003443706 0.025489793 0.027060159  33.06744186 11.65491803 11.28492063  162  Appendix 10- Table showing enrichment in biological process GO-terms (all levels) of downregulated expressed genes (fold change >2) between Smarcal1del/del and Smarcal1+/+ mouse livers at 39.5°C. Term GO:0008152~metabolic process GO:0050896~response to stimulus GO:0002376~immune system process GO:0048518~positive regulation of biological process GO:0006955~immune response GO:0007242~intracellular signaling cascade GO:0048583~regulation of response to stimulus GO:0002682~regulation of immune system process GO:0002684~positive regulation of immune system process GO:0050776~regulation of immune response GO:0002520~immune system development GO:0007049~cell cycle GO:0048534~hemopoietic or lymphoid organ development GO:0032879~regulation of localization GO:0042981~regulation of apoptosis GO:0043067~regulation of programmed cell death GO:0010941~regulation of cell death GO:0050778~positive regulation of immune response GO:0048584~positive regulation of response to stimulus GO:0006952~defense response GO:0051249~regulation of lymphocyte activation GO:0002694~regulation of leukocyte activation GO:0050865~regulation of cell activation GO:0001775~cell activation GO:0002253~activation of immune response GO:0051251~positive regulation of lymphocyte activation GO:0002696~positive regulation of leukocyte activation  Count  p-value  103 45 34 27  0.016272015 0.005603062 7.00E-10 0.048865517  Fold Enrichment 1.172058164 1.475047604 3.433614114 1.444617955  23 22 19 18  9.55E-08 0.004868256 1.58E-07 5.61E-07  3.90082063 1.92066065 4.599267961 4.465454672  16  4.33E-08  6.20442893  15 15 14 13  1.14E-07 1.95E-05 0.041924611 2.09E-04  6.273457262 4.061797753 1.830357307 3.695609581  13 13 13  0.004894491 0.043815882 0.047401685  2.557798749 1.877877563 1.854404093  13 12  0.048998886 1.03E-06  1.844522721 7.048413748  12  2.12E-05  5.153678869  12 11  0.024600279 1.26E-05  2.13969703 6.102098939  11 11 11 10 10  2.27E-05 2.53E-05 0.001033108 1.18E-06 2.51E-06  5.705858748 5.632706713 3.571960354 9.288607264 8.498087497  10  3.88E-06  8.068891159 163  Term GO:0050867~positive regulation of cell activation GO:0045321~leukocyte activation GO:0030097~hemopoiesis GO:0046649~lymphocyte activation GO:0043065~positive regulation of apoptosis GO:0043068~positive regulation of programmed cell death GO:0010942~positive regulation of cell death GO:0008284~positive regulation of cell proliferation GO:0002460~adaptive immune response based on somatic recombination of immune receptors built from immunoglobulin superfamily domains GO:0002250~adaptive immune response GO:0002697~regulation of immune effector process GO:0080134~regulation of response to stress GO:0007243~protein kinase cascade GO:0000278~mitotic cell cycle GO:0050851~antigen receptor-mediated signaling pathway GO:0002429~immune response-activating cell surface receptor signaling pathway GO:0002768~immune response-regulating cell surface receptor signaling pathway GO:0002699~positive regulation of immune effector process GO:0002757~immune response-activating signal transduction GO:0050671~positive regulation of lymphocyte proliferation GO:0032946~positive regulation of mononuclear cell proliferation GO:0070665~positive regulation of leukocyte proliferation GO:0002764~immune response-regulating signal transduction GO:0050864~regulation of B cell activation GO:0002703~regulation of leukocyte mediated immunity  Count  p-value  10  4.58E-06  Fold Enrichment 7.909111136  10 10 9 9 9  0.00169721 0.004225054 0.002706634 0.012474879 0.013084144  3.647580935 3.182550696 3.764074357 2.898944364 2.875752809  9 9  0.013697532 0.025881579  2.852929374 2.531472543  8  8.32E-05  7.607811664  8 8  8.32E-05 1.12E-04  7.607811664 7.262002043  8 8 8 7  0.009212006 0.028380712 0.033158027 4.88E-06  3.399234999 2.707865169 2.619082704 15.53261548  7  1.07E-05  13.63839408  7  1.63E-05  12.70850358  7  2.12E-05  12.15595994  7  2.72E-05  11.64946161  7  3.45E-05  11.18348315  7  3.45E-05  11.18348315  7  4.33E-05  10.75334918  7  4.33E-05  10.75334918  7 7  5.98E-05 2.32E-04  10.16680286 7.988202247  164  Term GO:0042113~B cell activation GO:0050670~regulation of lymphocyte proliferation GO:0032944~regulation of mononuclear cell proliferation GO:0070663~regulation of leukocyte proliferation GO:0050863~regulation of T cell activation GO:0002252~immune effector process GO:0002521~leukocyte differentiation GO:0010627~regulation of protein kinase cascade GO:0009967~positive regulation of signal transduction GO:0010647~positive regulation of cell communication GO:0007067~mitosis GO:0000280~nuclear division GO:0000087~M phase of mitotic cell cycle GO:0048285~organelle fission GO:0050853~B cell receptor signaling pathway GO:0050871~positive regulation of B cell activation GO:0016064~immunoglobulin mediated immune response GO:0019724~B cell mediated immunity GO:0002706~regulation of lymphocyte mediated immunity GO:0002449~lymphocyte mediated immunity GO:0002443~leukocyte mediated immunity GO:0043408~regulation of MAPKKK cascade GO:0031347~regulation of defense response GO:0030098~lymphocyte differentiation GO:0016053~organic acid biosynthetic process GO:0046394~carboxylic acid biosynthetic process GO:0006260~DNA replication GO:0030888~regulation of B cell proliferation GO:0002705~positive regulation of leukocyte mediated immunity  Count  p-value  7 7  4.18E-04 4.79E-04  Fold Enrichment 7.168899453 6.989676966  7  4.79E-04  6.989676966  7  5.47E-04  6.81919704  7 7 7 7  0.002293823 0.004917707 0.008689088 0.013010348  5.177538494 4.437890137 3.937846178 3.607575208  7  0.020681219  3.251012542  7  0.030931302  2.958593425  7 7 7 7 6 6  0.031660108 0.031660108 0.03454287 0.036832348 5.16E-07 8.92E-05  2.943021881 2.943021881 2.882341017 2.838447499 34.23515249 12.95384148  6  0.001107776  7.607811664  6 6  0.001276053 0.001276053  7.373725151 7.373725151  6 6 6 6 6 6 6  0.002557754 0.005050415 0.006077862 0.009273909 0.01395435 0.031544275 0.031544275  6.306475458 5.385304886 5.153678869 4.653321697 4.204316972 3.399234999 3.399234999  6 5 5  0.041482863 6.36E-04 0.001495156  3.153237729 12.48156601 9.985252809  165  Term GO:0002708~positive regulation of lymphocyte mediated immunity GO:0030183~B cell differentiation GO:0006959~humoral immune response GO:0002822~regulation of adaptive immune response based on somatic recombination of immune receptors built from immunoglobulin superfamily domains GO:0002819~regulation of adaptive immune response GO:0050727~regulation of inflammatory response GO:0050870~positive regulation of T cell activation GO:0002526~acute inflammatory response GO:0010740~positive regulation of protein kinase cascade GO:0032101~regulation of response to external stimulus GO:0042330~taxis GO:0006935~chemotaxis GO:0030890~positive regulation of B cell proliferation GO:0002889~regulation of immunoglobulin mediated immune response GO:0002712~regulation of B cell mediated immunity GO:0002824~positive regulation of adaptive immune response based on somatic recombination of immune receptors built from immunoglobulin superfamily domains GO:0046634~regulation of alpha-beta T cell activation GO:0002821~positive regulation of adaptive immune response GO:0042102~positive regulation of T cell proliferation GO:0002455~humoral immune response mediated by circulating immunoglobulin GO:0046651~lymphocyte proliferation GO:0032943~mononuclear cell proliferation GO:0070661~leukocyte proliferation  Count  p-value  5  0.001495156  Fold Enrichment 9.985252809  5 5 5  0.002519638 0.004521448 0.005151322  8.68282853 7.396483562 7.132323435  5  0.005151322  7.132323435  5  0.005487218  7.007194954  5  0.009185436  6.051668369  5 5  0.018381732 0.024110205  4.930989041 4.538751277  5  0.039684279  3.877768081  5 5 4  0.047201078 0.047201078 0.002453711  3.664312957 3.664312957 14.52400409  4  0.006014582  10.65093633  4  0.006014582  10.65093633  4  0.008549035  9.397884997  4  0.008549035  9.397884997  4  0.008549035  9.397884997  4  0.009266223  9.129373997  4  0.009266223  9.129373997  4 4 4  0.015257265 0.016254455 0.016254455  7.607811664 7.430885811 7.430885811 166  Term GO:0043410~positive regulation of MAPKKK cascade GO:0050730~regulation of peptidyl-tyrosine phosphorylation GO:0031349~positive regulation of defense response GO:0045619~regulation of lymphocyte differentiation GO:0051052~regulation of DNA metabolic process GO:0042129~regulation of T cell proliferation GO:0043406~positive regulation of MAP kinase activity GO:0007059~chromosome segregation GO:0051605~protein maturation by peptide bond cleavage GO:0048585~negative regulation of response to stimulus GO:0046641~positive regulation of alpha-beta T cell proliferation GO:0002863~positive regulation of inflammatory response to antigenic stimulus GO:0007159~leukocyte adhesion GO:0002714~positive regulation of B cell mediated immunity GO:0002891~positive regulation of immunoglobulin mediated immune response GO:0046640~regulation of alpha-beta T cell proliferation GO:0002886~regulation of myeloid leukocyte mediated immunity GO:0009067~aspartate family amino acid biosynthetic process GO:0045577~regulation of B cell differentiation GO:0002861~regulation of inflammatory response to antigenic stimulus GO:0048535~lymph node development GO:0051053~negative regulation of DNA metabolic process GO:0009066~aspartate family amino acid metabolic process GO:0000018~regulation of DNA recombination  Count  p-value  4  0.020602171  Fold Enrichment 6.798469998  4  0.028205284  6.028831885  4  0.033992386  5.605755963  4  0.03552811  5.509104998  4  0.03552811  5.509104998  4 4  0.037099138 0.037099138  5.415730337 5.415730337  4 4  0.04547771 0.047256716  4.992626404 4.915816768  4  0.047256716  4.915816768  3  0.006493239  23.96460674  3  0.010982563  18.43431288  3 3  0.012708992 0.012708992  17.11757624 17.11757624  3  0.012708992  17.11757624  3  0.012708992  17.11757624  3  0.014545318  15.97640449  3  0.01648857  14.97787921  3 3  0.01648857 0.020684244  14.97787921 13.31367041  3 3  0.022931001 0.025273351  12.61295092 11.98230337  3  0.030234083  10.89300306  3  0.035545458  9.985252809 167  Term GO:0050729~positive regulation of inflammatory response GO:0002637~regulation of immunoglobulin production GO:0046635~positive regulation of alpha-beta T cell activation GO:0042098~T cell proliferation GO:0051307~meiotic chromosome separation GO:0051304~chromosome separation GO:0032413~negative regulation of ion transmembrane transporter activity GO:0032410~negative regulation of transporter activity  Count  p-value  3  0.035545458  Fold Enrichment 9.985252809  3  0.0383263  9.585842697  3  0.041187296  9.217156439  3 2 2 2  0.047140192 0.036884021 0.036884021 0.048875547  8.558788122 53.25468165 53.25468165 39.94101124  2  0.048875547  39.94101124  168  Appendix 11- Table showing enrichment in biological process GO-terms (all levels) of  differentially expressed genes (q<0.05) between RpII2154/FM7;Marcal1del/del and yw fly ovaries. Term GO:0009987~cellular process GO:0008152~metabolic process GO:0044238~primary metabolic process GO:0044237~cellular metabolic process GO:0043170~macromolecule metabolic process GO:0065007~biological regulation GO:0044260~cellular macromolecule metabolic process GO:0050789~regulation of biological process GO:0050794~regulation of cellular process GO:0016043~cellular component organization GO:0051179~localization GO:0006807~nitrogen compound metabolic process GO:0034641~cellular nitrogen compound metabolic process GO:0051234~establishment of localization GO:0006139~nucleobase, nucleoside, nucleotide and nucleic acid metabolic process GO:0006810~transport GO:0006996~organelle organization GO:0043412~biopolymer modification GO:0006464~protein modification process GO:0033036~macromolecule localization GO:0007049~cell cycle GO:0044085~cellular component biogenesis GO:0043687~post-translational protein modification GO:0051641~cellular localization GO:0016070~RNA metabolic process GO:0065008~regulation of biological quality GO:0009056~catabolic process GO:0048519~negative regulation of biological process GO:0022402~cell cycle process  Count  p-value  350 300 250 223 191  7.11E-08 2.90E-05 8.69E-05 2.26E-05 0.027556497  Fold Enrichment 1.182962437 1.168941048 1.195140191 1.242854726 1.121973063  171 169  0.012492805 1.09E-04  1.158556378 1.281200439  160 148 140 118 115  0.005729838 0.010568064 4.61E-06 0.009257764 8.13E-04  1.191211236 1.184387145 1.413131599 1.225732441 1.320637602  111  5.10E-05  1.425098921  102 99  0.00849426 2.04E-04  1.256228433 1.41339  97 81 61 58 53 52 49 48  0.016600255 1.39E-04 4.57E-04 5.60E-04 1.71E-05 0.002722216 0.006815028 9.74E-04  1.234697456 1.502611746 1.557361707 1.568270202 1.843721572 1.50646645 1.459842794 1.616226415  47 47 47 46 46  0.001688624 0.002271936 0.013660778 7.73E-04 0.02861235  1.585546629 1.561925822 1.414425239 1.658400673 1.359119757  45  0.008840369  1.468121572 169  Term GO:0008104~protein localization GO:0006793~phosphorus metabolic process GO:0007010~cytoskeleton organization GO:0022607~cellular component assembly GO:0022403~cell cycle phase GO:0048523~negative regulation of cellular process GO:0051649~establishment of localization in cell GO:0048699~generation of neurons GO:0000279~M phase GO:0006950~response to stress GO:0022008~neurogenesis GO:0007017~microtubule-based process GO:0000902~cell morphogenesis GO:0044248~cellular catabolic process GO:0000278~mitotic cell cycle GO:0050793~regulation of developmental process GO:0000226~microtubule cytoskeleton organization GO:0046907~intracellular transport GO:0016192~vesicle-mediated transport GO:0051716~cellular response to stimulus GO:0051128~regulation of cellular component organization GO:0048518~positive regulation of biological process GO:0030030~cell projection organization GO:0051276~chromosome organization GO:0051239~regulation of multicellular organismal process GO:0045184~establishment of protein localization GO:0006629~lipid metabolic process GO:0006396~RNA processing GO:0006259~DNA metabolic process GO:0009057~macromolecule catabolic process GO:0015031~protein transport GO:0048858~cell projection morphogenesis  Count  p-value  43 43 42 42 41 41  3.21E-05 0.024241749 0.002320114 0.025399639 0.011826147 0.03795045  Fold Enrichment 1.957578656 1.392687538 1.61188172 1.393169145 1.47515961 1.359998451  40  0.002594879  1.626044039  40 40 40 40 38 36 35 34 33  0.010288425 0.010691232 0.011361063 0.020110822 0.002135805 0.022882898 0.002475963 0.00307323 6.51E-04  1.49650594 1.493375174 1.487152778 1.430527722 1.670299672 1.453506787 1.70191871 1.69485568 1.881509585  32  5.86E-04  1.916331096  32 32 31 31  0.001329529 0.030243692 2.35E-04 3.88E-04  1.824494143 1.460528559 2.048966049 1.990002998  31  0.01176345  1.589715038  31 29 29  0.021537837 0.002171798 0.002398442  1.515673516 1.835209811 1.822285798  29  0.002512304  1.815891813  29 29 28 28 27 27  0.003934782 0.008777374 9.92E-05 0.003317298 0.006769389 0.035267791  1.760303288 1.658747329 2.261010558 1.803910951 1.733228417 1.505742188 170  Term GO:0032990~cell part morphogenesis GO:0048667~cell morphogenesis involved in neuron differentiation GO:0009966~regulation of signal transduction GO:0000904~cell morphogenesis involved in differentiation GO:0048522~positive regulation of cellular process GO:0010646~regulation of cell communication GO:0043933~macromolecular complex subunit organization GO:0048812~neuron projection morphogenesis GO:0031175~neuron projection development GO:0045595~regulation of cell differentiation GO:0007051~spindle organization GO:0010324~membrane invagination GO:0006897~endocytosis GO:0016071~mRNA metabolic process GO:0044265~cellular macromolecule catabolic process GO:0009605~response to external stimulus GO:0030163~protein catabolic process GO:0033554~cellular response to stress GO:0006397~mRNA processing GO:0006909~phagocytosis GO:0051726~regulation of cell cycle GO:0044255~cellular lipid metabolic process GO:0006911~phagocytosis, engulfment GO:0007052~mitotic spindle organization GO:0007409~axonogenesis GO:0034621~cellular macromolecular complex subunit organization GO:0007059~chromosome segregation GO:0042592~homeostatic process GO:0044257~cellular protein catabolic process GO:0051603~proteolysis involved in cellular protein catabolic process GO:0032879~regulation of localization GO:0016311~dephosphorylation  Count  p-value  27 26  0.049511237 0.018881001  Fold Enrichment 1.455702417 1.611082176  26 26  0.023674724 0.033093738  1.578202948 1.531325633  26  0.042167891  1.49193462  26 25  0.042167891 0.025116097  1.49193462 1.587707592  25 25 24 24 23 23 22 22  0.030173439 0.030993553 2.49E-04 0.003623308 0.031610381 0.031610381 0.010804123 0.014372148  1.559950466 1.554515099 2.315135135 1.903555556 1.590907623 1.590907623 1.792732116 1.744925926  21 21 20 20 20 19 19  0.00621043 0.00817114 0.004358407 0.012084936 0.014066487 0.005198615 0.013769279  1.921858974 1.8738125 2.027935606 1.839776632 1.811759729 2.042595382 1.852846084  19 19 19 19  0.016878101 0.023601968 0.028265593 0.035028892  1.813213012 1.747787801 1.712478956 1.670299672  18 18 18 18  2.53E-04 0.009510974 0.027037229 0.027037229  2.745512821 1.970705521 1.755327869 1.755327869  17 17  1.08E-04 3.40E-04  3.064436027 2.783295107 171  Term GO:0019941~modification-dependent protein catabolic process GO:0043632~modification-dependent macromolecule catabolic process GO:0060284~regulation of cell development GO:0022603~regulation of anatomical structure morphogenesis GO:0007067~mitosis GO:0000087~M phase of mitotic cell cycle GO:0000280~nuclear division GO:0048285~organelle fission GO:0006470~protein amino acid dephosphorylation GO:0019725~cellular homeostasis GO:0006974~response to DNA damage stimulus GO:0009968~negative regulation of signal transduction GO:0006281~DNA repair GO:0010648~negative regulation of cell communication GO:0033043~regulation of organelle organization GO:0022604~regulation of cell morphogenesis GO:0006403~RNA localization GO:0000398~nuclear mRNA splicing, via spliceosome GO:0000377~RNA splicing, via transesterification reactions with bulged adenosine as nucleophile GO:0006260~DNA replication GO:0007346~regulation of mitotic cell cycle GO:0007264~small GTPase mediated signal transduction GO:0045454~cell redox homeostasis GO:0060341~regulation of cellular localization GO:0044087~regulation of cellular component biogenesis GO:0019637~organophosphate metabolic process GO:0051049~regulation of transport  Count  p-value  17  0.026868496  Fold Enrichment 1.795142998  17  0.028195026  1.784583333  16 16  0.006283738 0.033909195  2.179643766 1.784583333  15 15 15 15 14  0.033572894 0.037073808 0.037073808 0.046957866 5.70E-04  1.833476027 1.808699324 1.808699324 1.749591503 3.046849593  14 14  0.008806922 0.011710995  2.250825826 2.172536232  13  0.011212454  2.274468954  13 13  0.011212454 0.012070809  2.274468954 2.252386731  13  0.018324001  2.128402141  13 13 13  0.03372718 0.04651578 0.048932949  1.949544818 1.855966667 1.841236772  13  0.048932949  1.841236772  12 12 12  0.01781505 0.020496925 0.040774274  2.230729167 2.185204082 1.964678899  11 11 11  6.03E-04 0.004245002 0.013258339  3.703852201 2.88682598 2.453802083  11  0.043964131  2.023754296  10  0.002427666  3.367138365 172  Term GO:0006261~DNA-dependent DNA replication GO:0046486~glycerolipid metabolic process GO:0006644~phospholipid metabolic process GO:0045132~meiotic chromosome segregation GO:0050657~nucleic acid transport GO:0050658~RNA transport GO:0051236~establishment of RNA localization GO:0050767~regulation of neurogenesis GO:0002164~larval development GO:0015931~nucleobase, nucleoside, nucleotide and nucleic acid transport GO:0051169~nuclear transport GO:0006913~nucleocytoplasmic transport GO:0031023~microtubule organizing center organization GO:0002168~instar larval development GO:0045995~regulation of embryonic development GO:0006650~glycerophospholipid metabolic process GO:0032880~regulation of protein localization GO:0048193~Golgi vesicle transport GO:0051297~centrosome organization GO:0010627~regulation of protein kinase cascade GO:0007127~meiosis I GO:0000070~mitotic sister chromatid segregation GO:0000819~sister chromatid segregation GO:0048585~negative regulation of response to stimulus GO:0051050~positive regulation of transport GO:0022411~cellular component disassembly GO:0010769~regulation of cell morphogenesis involved in differentiation GO:0010975~regulation of neuron projection development GO:0030261~chromosome condensation  Count  p-value  10  0.004043948  Fold Enrichment 3.130847953  10 10 9 9 9 9  0.005731113 0.044237619 0.01329798 0.02332665 0.02332665 0.025406222  2.974305556 2.124503968 2.817763158 2.549404762 2.549404762 2.509570312  9 9 9  0.032413809 0.035016101 0.035016101  2.397201493 2.361948529 2.361948529  9 9 8  0.046827578 0.046827578 0.014725806  2.230729167 2.230729167 3.037588652  8 8  0.01643681 0.029728228  2.974305556 2.64382716  8  0.029728228  2.64382716  7 7 7 7  0.017794576 0.031122715 0.031122715 0.034401593  3.287390351 2.905135659 2.905135659 2.839109848  7 7  0.037895519 0.041607995  2.776018519 2.71567029  7 6  0.045541974 0.006380093  2.657890071 4.867045455  6 6 6  0.013259737 0.018078793 0.023929637  4.118269231 3.824107143 3.569166667  6  0.023929637  3.569166667  6  0.023929637  3.569166667 173  Term GO:0046822~regulation of nucleocytoplasmic transport GO:0032386~regulation of intracellular transport GO:0006270~DNA replication initiation GO:0010741~negative regulation of protein kinase cascade GO:0050770~regulation of axonogenesis GO:0007426~tracheal outgrowth, open tracheal system GO:0043269~regulation of ion transport GO:0032508~DNA duplex unwinding GO:0032392~DNA geometric change GO:0035099~hemocyte migration GO:0043624~cellular protein complex disassembly GO:0043241~protein complex disassembly GO:0033044~regulation of chromosome organization GO:0034765~regulation of ion transmembrane transport GO:0034762~regulation of transmembrane transport GO:0032412~regulation of ion transmembrane transporter activity GO:0051924~regulation of calcium ion transport GO:0032409~regulation of transporter activity GO:0022898~regulation of transmembrane transporter activity GO:0010959~regulation of metal ion transport GO:0032837~distributive segregation GO:0006268~DNA unwinding during replication GO:0006415~translational termination  Count  p-value  6  0.034779589  Fold Enrichment 3.24469697  6  0.038972833  3.149264706  5 5  0.008043526 0.015787154  5.948611111 4.957175926  5 5  0.015787154 0.027058084  4.957175926 4.249007937  4 4 4 4 4  0.003060597 0.00787683 0.00787683 0.039881238 0.039881238  11.89722222 8.922916667 8.922916667 5.098809524 5.098809524  4 4  0.039881238 0.047840666  5.098809524 4.758888889  3  0.017362884  13.384375  3  0.017362884  13.384375  3  0.017362884  13.384375  3  0.017362884  13.384375  3 3  0.017362884 0.017362884  13.384375 13.384375  3 3 3  0.027873818 0.027873818 0.040280429  10.7075 10.7075 8.922916667  3  0.040280429  8.922916667  174  Appendix 12- Table showing enrichment in biological process GO-terms (all levels) of differentially expressed genes (q<0.05) between RpII2154/FM7 and yw fly ovaries.  Term GO:0009987~cellular process GO:0008152~metabolic process GO:0044238~primary metabolic process GO:0044237~cellular metabolic process GO:0044260~cellular macromolecule metabolic process GO:0050789~regulation of biological process GO:0016043~cellular component organization GO:0006807~nitrogen compound metabolic process GO:0034641~cellular nitrogen compound metabolic process GO:0010467~gene expression GO:0006139~nucleobase, nucleoside, nucleotide and nucleic acid metabolic process GO:0043412~biopolymer modification GO:0048519~negative regulation of biological process GO:0007389~pattern specification process GO:0033036~macromolecule localization GO:0044085~cellular component biogenesis GO:0003002~regionalization GO:0016070~RNA metabolic process GO:0006796~phosphate metabolic process GO:0006793~phosphorus metabolic process GO:0048523~negative regulation of cellular process GO:0008104~protein localization GO:0007444~imaginal disc development GO:0016310~phosphorylation GO:0006396~RNA processing GO:0035220~wing disc development GO:0048736~appendage development GO:0007560~imaginal disc morphogenesis GO:0048563~post-embryonic organ morphogenesis  Count  p-value  181 161 125 124 89  1.57E-04 2.29E-04 0.022834886 4.59E-05 0.003132667  Fold Enrichment 1.179297493 1.209314112 1.151942353 1.332229605 1.300655468  84 66 57  0.031554616 0.019002973 0.042133297  1.205563179 1.284222864 1.261834985  55  0.012305381  1.361214643  51 50  0.019970999 0.014752062  1.346494189 1.376064257  31 28  0.018527719 0.015566646  1.525679255 1.594776457  27 27 27 26 26 26 26  0.001468989 0.003662632 0.024350343 0.00144818 0.012464648 0.016586938 0.016586938  1.935090361 1.810610865 1.550656717 1.970136051 1.665627127 1.623306292 1.623306292  24  0.038173228  1.534644153  22 21 21 20 18 15 15 15  0.00482586 0.01614927 0.021749883 0.001736517 0.003229869 0.012058473 0.036210253 0.036210253  1.930702401 1.753479939 1.699844082 2.205231181 2.203661622 2.097658928 1.816986255 1.816986255  175  Term GO:0048569~post-embryonic organ development GO:0002009~morphogenesis of an epithelium GO:0060429~epithelium development GO:0035107~appendage morphogenesis GO:0048737~imaginal disc-derived appendage development GO:0048729~tissue morphogenesis GO:0045595~regulation of cell differentiation GO:0007476~imaginal disc-derived wing morphogenesis GO:0007472~wing disc morphogenesis GO:0035120~post-embryonic appendage morphogenesis GO:0035114~imaginal disc-derived appendage morphogenesis GO:0034621~cellular macromolecular complex subunit organization GO:0007167~enzyme linked receptor protein signaling pathway GO:0009891~positive regulation of biosynthetic process GO:0031328~positive regulation of cellular biosynthetic process GO:0031325~positive regulation of cellular metabolic process GO:0022613~ribonucleoprotein complex biogenesis GO:0016331~morphogenesis of embryonic epithelium GO:0006403~RNA localization GO:0006730~one-carbon metabolic process GO:0009968~negative regulation of signal transduction GO:0010648~negative regulation of cell communication GO:0032259~methylation GO:0015931~nucleobase, nucleoside, nucleotide and nucleic acid transport GO:0043414~biopolymer methylation GO:0017145~stem cell division  Count  p-value  15  0.049294478  Fold Enrichment 1.73745487  14 14 14 14  0.01361855 0.018897383 0.023418194 0.024129689  2.1405444 2.049457404 1.990175578 1.981985555  14 13 13  0.027116667 0.007439984 0.024419573  1.949888623 2.417410181 2.051471943  13 13  0.026027967 0.033956683  2.032822198 1.952929622  13  0.044715196  1.871217086  12  0.033607907  2.033592498  11  0.009320195  2.609777039  10  0.033453144  2.248471008  10  0.033453144  2.248471008  10  0.047008098  2.110528002  9  0.00574828  3.293770828  9  0.022953709  2.580120482  9 8 8  0.028449931 0.006261493 0.028229202  2.476915663 3.621221729 2.69816521  8  0.029569966  2.671969431  7 7  0.004072624 0.013572868  4.543608396 3.541341838  6 6  0.007662472 0.015523668  4.800224152 4.047247815 176  Term GO:0008356~asymmetric cell division GO:0050657~nucleic acid transport GO:0050658~RNA transport GO:0051236~establishment of RNA localization GO:0042254~ribosome biogenesis GO:0035222~wing disc pattern formation GO:0007173~epidermal growth factor receptor signaling pathway GO:0006364~rRNA processing GO:0016072~rRNA metabolic process GO:0006446~regulation of translational initiation GO:0007179~transforming growth factor beta receptor signaling pathway GO:0033227~dsRNA transport GO:0008213~protein amino acid alkylation GO:0006479~protein amino acid methylation GO:0022411~cellular component disassembly GO:0048096~chromatin-mediated maintenance of transcription GO:0045815~positive regulation of gene expression, epigenetic  Count  p-value  6 6 6 6 6 6 5  0.02575562 0.035215408 0.035215408 0.037333192 0.037333192 0.04657453 0.019532476  Fold Enrichment 3.558786872 3.276343469 3.276343469 3.225150602 3.225150602 3.035435861 4.778000892  5 5 4  0.027717191 0.030037905 0.014180198  4.300200803 4.195317857 7.644801428  4  0.027686318  5.982888074  4 4 4 4 3  0.034474406 0.046111135 0.046111135 0.046111135 0.032228518  5.504257028 4.914515204 4.914515204 4.914515204 10.32048193  3  0.038650506  9.382256298  177  

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