Supplementary Table 1: Genes Located on Chromosome 18P11-18Q23, an Area Significantly Linked to TMPRSS2-ERG Fusion
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Extreme HOT Regions Are Cpg-Dense Promoters in C. Elegans and Humans
Research Extreme HOT regions are CpG-dense promoters in C. elegans and humans Ron A.-J. Chen, Przemyslaw Stempor, Thomas A. Down, Eva Zeiser, Sky K. Feuer, and Julie Ahringer1 The Gurdon Institute and Department of Genetics, University of Cambridge, Cambridge CB3 0DH, United Kingdom Most vertebrate promoters lie in unmethylated CpG-dense islands, whereas methylation of the more sparsely distributed CpGs in the remainder of the genome is thought to contribute to transcriptional repression. Nonmethylated CG di- nucleotides are recognized by CXXC finger protein 1 (CXXC1, also known as CFP1), which recruits SETD1A (also known as Set1) methyltransferase for trimethylation of histone H3 lysine 4, an active promoter mark. Genomic regions enriched for CpGs are thought to be either absent or irrelevant in invertebrates that lack DNA methylation, such as C. elegans; however, a CXXC1 ortholog (CFP-1) is present. Here we demonstrate that C. elegans CFP-1 targets promoters with high CpG density, and these promoters are marked by high levels of H3K4me3. Furthermore, as for mammalian promoters, high CpG content is associated with nucleosome depletion irrespective of transcriptional activity. We further show that highly occupied target (HOT) regions identified by the binding of a large number of transcription factors are CpG-rich pro- moters in C. elegans and human genomes, suggesting that the unusually high factor association at HOT regions may be a consequence of CpG-linked chromatin accessibility. Our results indicate that nonmethylated CpG-dense sequence is a conserved genomic signal that promotes an open chromatin state, targeting by a CXXC1 ortholog, and H3K4me3 modification in both C. -
Congenital Cataracts–Facial Dysmorphism–Neuropathy
Orphanet Journal of Rare Diseases BioMed Central Review Open Access Congenital Cataracts – Facial Dysmorphism – Neuropathy Luba Kalaydjieva* Address: Western Australian Institute for Medical Research and Centre for Medical Research, The University of Western Australia, Hospital Avenue, WA 6009 Nedlands, Australia Email: Luba Kalaydjieva* - [email protected] * Corresponding author Published: 29 August 2006 Received: 11 July 2006 Accepted: 29 August 2006 Orphanet Journal of Rare Diseases 2006, 1:32 doi:10.1186/1750-1172-1-32 This article is available from: http://www.OJRD.com/content/1/1/32 © 2006 Kalaydjieva; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Abstract Congenital Cataracts Facial Dysmorphism Neuropathy (CCFDN) syndrome is a complex developmental disorder of autosomal recessive inheritance. To date, CCFDN has been found to occur exclusively in patients of Roma (Gypsy) ethnicity; over 100 patients have been diagnosed. Developmental abnormalities include congenital cataracts and microcorneae, primary hypomyelination of the peripheral nervous system, impaired physical growth, delayed early motor and intellectual development, mild facial dysmorphism and hypogonadism. Para-infectious rhabdomyolysis is a serious complication reported in an increasing number of patients. During general anaesthesia, patients with CCFDN require careful monitoring as they have an elevated risk of complications. CCFDN is a genetically homogeneous condition in which all patients are homozygous for the same ancestral mutation in the CTDP1 gene. Diagnosis is clinical and is supported by electrophysiological and brain imaging studies. -
Gene Expression and Splicing Alterations Analyzed by High Throughput RNA Sequencing of Chronic Lymphocytic Leukemia Specimens
Liao et al. BMC Cancer (2015) 15:714 DOI 10.1186/s12885-015-1708-9 RESEARCH ARTICLE Open Access Gene expression and splicing alterations analyzed by high throughput RNA sequencing of chronic lymphocytic leukemia specimens Wei Liao1, Gwen Jordaan1, Phillipp Nham2, Ryan T. Phan2, Matteo Pelegrini3 and Sanjai Sharma1,4* Abstract Background: To determine differentially expressed and spliced RNA transcripts in chronic lymphocytic leukemia specimens a high throughput RNA-sequencing (HTS RNA-seq) analysis was performed. Methods: Ten CLL specimens and five normal peripheral blood CD19+ B cells were analyzed by HTS RNA-seq. The library preparation was performed with Illumina TrueSeq RNA kit and analyzed by Illumina HiSeq 2000 sequencing system. Results: An average of 48.5 million reads for B cells, and 50.6 million reads for CLL specimens were obtained with 10396 and 10448 assembled transcripts for normal B cells and primary CLL specimens respectively. With the Cuffdiff analysis, 2091 differentially expressed genes (DEG) between B cells and CLL specimens based on FPKM (fragments per kilobase of transcript per million reads and false discovery rate, FDR q < 0.05, fold change >2) were identified. Expression of selected DEGs (n = 32) with up regulated and down regulated expression in CLL from RNA-seq data were also analyzed by qRT-PCR in a test cohort of CLL specimens. Even though there was a variation in fold expression of DEG genes between RNA-seq and qRT-PCR; more than 90 % of analyzed genes were validated by qRT-PCR analysis. Analysis of RNA-seq data for splicing alterations in CLL and B cells was performed by Multivariate Analysis of Transcript Splicing (MATS analysis). -
Association Analyses of Known Genetic Variants with Gene
ASSOCIATION ANALYSES OF KNOWN GENETIC VARIANTS WITH GENE EXPRESSION IN BRAIN by Viktoriya Strumba A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Bioinformatics) in The University of Michigan 2009 Doctoral Committee: Professor Margit Burmeister, Chair Professor Huda Akil Professor Brian D. Athey Assistant Professor Zhaohui S. Qin Research Statistician Thomas Blackwell To Sam and Valentina Dmitriy and Elizabeth ii ACKNOWLEDGEMENTS I would like to thank my advisor Professor Margit Burmeister, who tirelessly guided me though seemingly impassable corridors of graduate work. Throughout my thesis writing period she provided sound advice, encouragement and inspiration. Leading by example, her enthusiasm and dedication have been instrumental in my path to becoming a better scientist. I also would like to thank my co-advisor Tom Blackwell. His careful prodding always kept me on my toes and looking for answers, which taught me the depth of careful statistical analysis. His diligence and dedication have been irreplaceable in most difficult of projects. I also would like to thank my other committee members: Huda Akil, Brian Athey and Steve Qin as well as David States. You did not make it easy for me, but I thank you for believing and not giving up. Huda’s eloquence in every subject matter she explained have been particularly inspiring, while both Huda’s and Brian’s valuable advice made the completion of this dissertation possible. I would also like to thank all the members of the Burmeister lab, both past and present: Sandra Villafuerte, Kristine Ito, Cindy Schoen, Karen Majczenko, Ellen Schmidt, Randi Burns, Gang Su, Nan Xiang and Ana Progovac. -
Analysis of Gene Expression Data for Gene Ontology
ANALYSIS OF GENE EXPRESSION DATA FOR GENE ONTOLOGY BASED PROTEIN FUNCTION PREDICTION A Thesis Presented to The Graduate Faculty of The University of Akron In Partial Fulfillment of the Requirements for the Degree Master of Science Robert Daniel Macholan May 2011 ANALYSIS OF GENE EXPRESSION DATA FOR GENE ONTOLOGY BASED PROTEIN FUNCTION PREDICTION Robert Daniel Macholan Thesis Approved: Accepted: _______________________________ _______________________________ Advisor Department Chair Dr. Zhong-Hui Duan Dr. Chien-Chung Chan _______________________________ _______________________________ Committee Member Dean of the College Dr. Chien-Chung Chan Dr. Chand K. Midha _______________________________ _______________________________ Committee Member Dean of the Graduate School Dr. Yingcai Xiao Dr. George R. Newkome _______________________________ Date ii ABSTRACT A tremendous increase in genomic data has encouraged biologists to turn to bioinformatics in order to assist in its interpretation and processing. One of the present challenges that need to be overcome in order to understand this data more completely is the development of a reliable method to accurately predict the function of a protein from its genomic information. This study focuses on developing an effective algorithm for protein function prediction. The algorithm is based on proteins that have similar expression patterns. The similarity of the expression data is determined using a novel measure, the slope matrix. The slope matrix introduces a normalized method for the comparison of expression levels throughout a proteome. The algorithm is tested using real microarray gene expression data. Their functions are characterized using gene ontology annotations. The results of the case study indicate the protein function prediction algorithm developed is comparable to the prediction algorithms that are based on the annotations of homologous proteins. -
GRIM19 Impedes Obesity by Regulating Inflammatory White Fat
cells Article GRIM19 Impedes Obesity by Regulating Inflammatory White Fat Browning and Promoting Th17/Treg Balance JooYeon Jhun 1,†, Jin Seok Woo 1,† , Seung Hoon Lee 2, Jeong-Hee Jeong 1, KyungAh Jung 3, Wonhee Hur 4, Seon-Yeong Lee 1, Jae Yoon Ryu 1, Young-Mee Moon 1, Yoon Ju Jung 5, Kyo Young Song 5, Kiyuk Chang 6, Seung Kew Yoon 4,7 , Sung-Hwan Park 1,8 and Mi-La Cho 1,8,* 1 The Rheumatism Research Center, Catholic Research Institute of Medical Science, The Catholic University of Korea, Seoul 137-040, Korea; [email protected] (J.J.); [email protected] (J.S.W.); [email protected] (J.-H.J.); [email protected] (S.-Y.L.); [email protected] (J.Y.R.); [email protected] (Y.-M.M.); [email protected] (S.-H.P.) 2 Division of Immunology, Department of Microbiology and Immunobiology, Harvard Medical School, Boston, MA 02115, USA; [email protected] 3 Research Center, Impact Biotech, Seoul 137-040, Korea; [email protected] 4 The Catholic University Liver Research Center & WHO Collaborating Center of Viral Hepatitis, College of Medicine, The Catholic University of Korea, Seoul 137-040, Korea; [email protected] (W.H.); [email protected] (S.K.Y.) 5 Division of Gastrointestinal Surgery, Department of General Surgery, Seoul St. Mary’s Hospital, The Catholic University of Korea, Seoul 137-040, Korea; [email protected] (Y.J.J.); [email protected] (K.Y.S.) 6 Cardiovascular Center and Cardiology Division, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul 137-040, Korea; [email protected] 7 Department of Internal Medicine, Seoul St. -
Characterization of the Human CIDEA Promoter in Fat Cells
International Journal of Obesity (2008) 32, 1380–1387 & 2008 Macmillan Publishers Limited All rights reserved 0307-0565/08 $32.00 www.nature.com/ijo ORIGINAL ARTICLE Characterization of the human CIDEA promoter in fat cells AT Pettersson1, J Laurencikiene1, EA Nordstro¨m1, BM Stenson1, V van Harmelen1, C Murphy2, I Dahlman1 and M Ryde´n1 1Department of Medicine, Huddinge, Lipid Laboratory, Novum, Karolinska Institutet, Stockholm, Sweden and 2Department of Laboratory Medicine, Karolinska Institutet, Stockholm, Sweden. Background: Cell death-inducing DFFA (DNA fragmentation factor-a)-like effector A (CIDEA) is a protein that regulates lipolysis in human adipocytes through cross-talk involving tumor necrosis factor-a (TNF-a). TNF-a downregulates CIDEA mRNA although it is unclear whether this is mediated through transcriptional or post-transcriptional mechanisms. CIDEA has important metabolic effects in human fat cells and genetic variations in the human CIDEA gene have been correlated to the development of obesity. However, little is known about the factors regulating CIDEA expression in human adipocytes. We set out to describe the transcriptional control of human CIDEA. Methods: A 1.1-kb genomic fragment upstream of the transcriptional start site (TSS) of human CIDEA was cloned and deletion fragments were generated. Transcriptional activity of the promoter was analyzed by luciferase reporter assays in in vitro- differentiated human adipocytes. The effect of TNF-a was assessed in human adipocytes and murine 3T3-L1 cells transfected with deletion fragments of the CIDEA promoter. Protein–DNA interactions were analyzed by electrophoretic mobility shift assays (EMSA). Results: Basal transcriptional activity was found in a 97-bp region upstream of the TSS. -
The Structural Basis for Selective Binding of Non-Methylated Cpg Islands by the CFP1 CXXC Domain
ARTICLE Received 13 Dec 2010 | Accepted 9 Feb 2011 | Published 8 Mar 2011 DOI: 10.1038/ncomms1237 The structural basis for selective binding of non-methylated CpG islands by the CFP1 CXXC domain Chao Xu1,*, Chuanbing Bian1,*, Robert Lam1, Aiping Dong1 & Jinrong Min1,2 CFP1 is a CXXC domain-containing protein and an essential component of the SETD1 histone H3K4 methyltransferase complex. CXXC domain proteins direct different chromatin-modifying activities to various chromatin regions. Here, we report crystal structures of the CFP1 CXXC domain in complex with six different CpG DNA sequences. The crescent-shaped CFP1 CXXC domain is wedged into the major groove of the CpG DNA, distorting the B-form DNA, and interacts extensively with the major groove of the DNA. The structures elucidate the molecular mechanism of the non-methylated CpG-binding specificity of the CFP1 CXXC domain. The CpG motif is confined by a tripeptide located in a rigid loop, which only allows the accommodation of the non-methylated CpG dinucleotide. Furthermore, we demonstrate that CFP1 has a preference for a guanosine nucleotide following the CpG motif. 1 Structural Genomics Consortium, University of Toronto, 101 College Street, Toronto, Ontario M5G 1L7, Canada. 2 Department of Physiology, University of Toronto, Toronto, Ontario M5S 1A8, Canada. *These authors contributed equally to this work. Correspondence and requests for materials should be addressed to J.M. (email: [email protected]). NATURE COMMUNICATIONS | 2:227 | DOI: 10.1038/ncomms1237 | www.nature.com/naturecommunications © 2011 Macmillan Publishers Limited. All rights reserved. ARTICLE NATURE COMMUNICATIONS | DOI: 10.1038/ncomms1237 pG islands contain a high density of CpG content and embrace the promoters of most genes in vertebrate genomes1. -
Identification and Characterization of TPRKB Dependency in TP53 Deficient Cancers
Identification and Characterization of TPRKB Dependency in TP53 Deficient Cancers. by Kelly Kennaley A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Molecular and Cellular Pathology) in the University of Michigan 2019 Doctoral Committee: Associate Professor Zaneta Nikolovska-Coleska, Co-Chair Adjunct Associate Professor Scott A. Tomlins, Co-Chair Associate Professor Eric R. Fearon Associate Professor Alexey I. Nesvizhskii Kelly R. Kennaley [email protected] ORCID iD: 0000-0003-2439-9020 © Kelly R. Kennaley 2019 Acknowledgements I have immeasurable gratitude for the unwavering support and guidance I received throughout my dissertation. First and foremost, I would like to thank my thesis advisor and mentor Dr. Scott Tomlins for entrusting me with a challenging, interesting, and impactful project. He taught me how to drive a project forward through set-backs, ask the important questions, and always consider the impact of my work. I’m truly appreciative for his commitment to ensuring that I would get the most from my graduate education. I am also grateful to the many members of the Tomlins lab that made it the supportive, collaborative, and educational environment that it was. I would like to give special thanks to those I’ve worked closely with on this project, particularly Dr. Moloy Goswami for his mentorship, Lei Lucy Wang, Dr. Sumin Han, and undergraduate students Bhavneet Singh, Travis Weiss, and Myles Barlow. I am also grateful for the support of my thesis committee, Dr. Eric Fearon, Dr. Alexey Nesvizhskii, and my co-mentor Dr. Zaneta Nikolovska-Coleska, who have offered guidance and critical evaluation since project inception. -
A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus
Page 1 of 781 Diabetes A Computational Approach for Defining a Signature of β-Cell Golgi Stress in Diabetes Mellitus Robert N. Bone1,6,7, Olufunmilola Oyebamiji2, Sayali Talware2, Sharmila Selvaraj2, Preethi Krishnan3,6, Farooq Syed1,6,7, Huanmei Wu2, Carmella Evans-Molina 1,3,4,5,6,7,8* Departments of 1Pediatrics, 3Medicine, 4Anatomy, Cell Biology & Physiology, 5Biochemistry & Molecular Biology, the 6Center for Diabetes & Metabolic Diseases, and the 7Herman B. Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN 46202; 2Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202; 8Roudebush VA Medical Center, Indianapolis, IN 46202. *Corresponding Author(s): Carmella Evans-Molina, MD, PhD ([email protected]) Indiana University School of Medicine, 635 Barnhill Drive, MS 2031A, Indianapolis, IN 46202, Telephone: (317) 274-4145, Fax (317) 274-4107 Running Title: Golgi Stress Response in Diabetes Word Count: 4358 Number of Figures: 6 Keywords: Golgi apparatus stress, Islets, β cell, Type 1 diabetes, Type 2 diabetes 1 Diabetes Publish Ahead of Print, published online August 20, 2020 Diabetes Page 2 of 781 ABSTRACT The Golgi apparatus (GA) is an important site of insulin processing and granule maturation, but whether GA organelle dysfunction and GA stress are present in the diabetic β-cell has not been tested. We utilized an informatics-based approach to develop a transcriptional signature of β-cell GA stress using existing RNA sequencing and microarray datasets generated using human islets from donors with diabetes and islets where type 1(T1D) and type 2 diabetes (T2D) had been modeled ex vivo. To narrow our results to GA-specific genes, we applied a filter set of 1,030 genes accepted as GA associated. -
Supplementary Table 3 Complete List of RNA-Sequencing Analysis of Gene Expression Changed by ≥ Tenfold Between Xenograft and Cells Cultured in 10%O2
Supplementary Table 3 Complete list of RNA-Sequencing analysis of gene expression changed by ≥ tenfold between xenograft and cells cultured in 10%O2 Expr Log2 Ratio Symbol Entrez Gene Name (culture/xenograft) -7.182 PGM5 phosphoglucomutase 5 -6.883 GPBAR1 G protein-coupled bile acid receptor 1 -6.683 CPVL carboxypeptidase, vitellogenic like -6.398 MTMR9LP myotubularin related protein 9-like, pseudogene -6.131 SCN7A sodium voltage-gated channel alpha subunit 7 -6.115 POPDC2 popeye domain containing 2 -6.014 LGI1 leucine rich glioma inactivated 1 -5.86 SCN1A sodium voltage-gated channel alpha subunit 1 -5.713 C6 complement C6 -5.365 ANGPTL1 angiopoietin like 1 -5.327 TNN tenascin N -5.228 DHRS2 dehydrogenase/reductase 2 leucine rich repeat and fibronectin type III domain -5.115 LRFN2 containing 2 -5.076 FOXO6 forkhead box O6 -5.035 ETNPPL ethanolamine-phosphate phospho-lyase -4.993 MYO15A myosin XVA -4.972 IGF1 insulin like growth factor 1 -4.956 DLG2 discs large MAGUK scaffold protein 2 -4.86 SCML4 sex comb on midleg like 4 (Drosophila) Src homology 2 domain containing transforming -4.816 SHD protein D -4.764 PLP1 proteolipid protein 1 -4.764 TSPAN32 tetraspanin 32 -4.713 N4BP3 NEDD4 binding protein 3 -4.705 MYOC myocilin -4.646 CLEC3B C-type lectin domain family 3 member B -4.646 C7 complement C7 -4.62 TGM2 transglutaminase 2 -4.562 COL9A1 collagen type IX alpha 1 chain -4.55 SOSTDC1 sclerostin domain containing 1 -4.55 OGN osteoglycin -4.505 DAPL1 death associated protein like 1 -4.491 C10orf105 chromosome 10 open reading frame 105 -4.491 -
Evidence for Differential Alternative Splicing in Blood of Young Boys With
Stamova et al. Molecular Autism 2013, 4:30 http://www.molecularautism.com/content/4/1/30 RESEARCH Open Access Evidence for differential alternative splicing in blood of young boys with autism spectrum disorders Boryana S Stamova1,2,5*, Yingfang Tian1,2,4, Christine W Nordahl1,3, Mark D Shen1,3, Sally Rogers1,3, David G Amaral1,3 and Frank R Sharp1,2 Abstract Background: Since RNA expression differences have been reported in autism spectrum disorder (ASD) for blood and brain, and differential alternative splicing (DAS) has been reported in ASD brains, we determined if there was DAS in blood mRNA of ASD subjects compared to typically developing (TD) controls, as well as in ASD subgroups related to cerebral volume. Methods: RNA from blood was processed on whole genome exon arrays for 2-4–year-old ASD and TD boys. An ANCOVA with age and batch as covariates was used to predict DAS for ALL ASD (n=30), ASD with normal total cerebral volumes (NTCV), and ASD with large total cerebral volumes (LTCV) compared to TD controls (n=20). Results: A total of 53 genes were predicted to have DAS for ALL ASD versus TD, 169 genes for ASD_NTCV versus TD, 1 gene for ASD_LTCV versus TD, and 27 genes for ASD_LTCV versus ASD_NTCV. These differences were significant at P <0.05 after false discovery rate corrections for multiple comparisons (FDR <5% false positives). A number of the genes predicted to have DAS in ASD are known to regulate DAS (SFPQ, SRPK1, SRSF11, SRSF2IP, FUS, LSM14A). In addition, a number of genes with predicted DAS are involved in pathways implicated in previous ASD studies, such as ROS monocyte/macrophage, Natural Killer Cell, mTOR, and NGF signaling.