Genome-Wide Analysis of DNA Methylation in Pigs Using Reduced Representation Bisulfite Sequencing
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Análise Integrativa De Perfis Transcricionais De Pacientes Com
UNIVERSIDADE DE SÃO PAULO FACULDADE DE MEDICINA DE RIBEIRÃO PRETO PROGRAMA DE PÓS-GRADUAÇÃO EM GENÉTICA ADRIANE FEIJÓ EVANGELISTA Análise integrativa de perfis transcricionais de pacientes com diabetes mellitus tipo 1, tipo 2 e gestacional, comparando-os com manifestações demográficas, clínicas, laboratoriais, fisiopatológicas e terapêuticas Ribeirão Preto – 2012 ADRIANE FEIJÓ EVANGELISTA Análise integrativa de perfis transcricionais de pacientes com diabetes mellitus tipo 1, tipo 2 e gestacional, comparando-os com manifestações demográficas, clínicas, laboratoriais, fisiopatológicas e terapêuticas Tese apresentada à Faculdade de Medicina de Ribeirão Preto da Universidade de São Paulo para obtenção do título de Doutor em Ciências. Área de Concentração: Genética Orientador: Prof. Dr. Eduardo Antonio Donadi Co-orientador: Prof. Dr. Geraldo A. S. Passos Ribeirão Preto – 2012 AUTORIZO A REPRODUÇÃO E DIVULGAÇÃO TOTAL OU PARCIAL DESTE TRABALHO, POR QUALQUER MEIO CONVENCIONAL OU ELETRÔNICO, PARA FINS DE ESTUDO E PESQUISA, DESDE QUE CITADA A FONTE. FICHA CATALOGRÁFICA Evangelista, Adriane Feijó Análise integrativa de perfis transcricionais de pacientes com diabetes mellitus tipo 1, tipo 2 e gestacional, comparando-os com manifestações demográficas, clínicas, laboratoriais, fisiopatológicas e terapêuticas. Ribeirão Preto, 2012 192p. Tese de Doutorado apresentada à Faculdade de Medicina de Ribeirão Preto da Universidade de São Paulo. Área de Concentração: Genética. Orientador: Donadi, Eduardo Antonio Co-orientador: Passos, Geraldo A. 1. Expressão gênica – microarrays 2. Análise bioinformática por module maps 3. Diabetes mellitus tipo 1 4. Diabetes mellitus tipo 2 5. Diabetes mellitus gestacional FOLHA DE APROVAÇÃO ADRIANE FEIJÓ EVANGELISTA Análise integrativa de perfis transcricionais de pacientes com diabetes mellitus tipo 1, tipo 2 e gestacional, comparando-os com manifestações demográficas, clínicas, laboratoriais, fisiopatológicas e terapêuticas. -
Whole Exome Sequencing in Families at High Risk for Hodgkin Lymphoma: Identification of a Predisposing Mutation in the KDR Gene
Hodgkin Lymphoma SUPPLEMENTARY APPENDIX Whole exome sequencing in families at high risk for Hodgkin lymphoma: identification of a predisposing mutation in the KDR gene Melissa Rotunno, 1 Mary L. McMaster, 1 Joseph Boland, 2 Sara Bass, 2 Xijun Zhang, 2 Laurie Burdett, 2 Belynda Hicks, 2 Sarangan Ravichandran, 3 Brian T. Luke, 3 Meredith Yeager, 2 Laura Fontaine, 4 Paula L. Hyland, 1 Alisa M. Goldstein, 1 NCI DCEG Cancer Sequencing Working Group, NCI DCEG Cancer Genomics Research Laboratory, Stephen J. Chanock, 5 Neil E. Caporaso, 1 Margaret A. Tucker, 6 and Lynn R. Goldin 1 1Genetic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; 2Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; 3Ad - vanced Biomedical Computing Center, Leidos Biomedical Research Inc.; Frederick National Laboratory for Cancer Research, Frederick, MD; 4Westat, Inc., Rockville MD; 5Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; and 6Human Genetics Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA ©2016 Ferrata Storti Foundation. This is an open-access paper. doi:10.3324/haematol.2015.135475 Received: August 19, 2015. Accepted: January 7, 2016. Pre-published: June 13, 2016. Correspondence: [email protected] Supplemental Author Information: NCI DCEG Cancer Sequencing Working Group: Mark H. Greene, Allan Hildesheim, Nan Hu, Maria Theresa Landi, Jennifer Loud, Phuong Mai, Lisa Mirabello, Lindsay Morton, Dilys Parry, Anand Pathak, Douglas R. Stewart, Philip R. Taylor, Geoffrey S. Tobias, Xiaohong R. Yang, Guoqin Yu NCI DCEG Cancer Genomics Research Laboratory: Salma Chowdhury, Michael Cullen, Casey Dagnall, Herbert Higson, Amy A. -
Gene Expression Profiles Complement the Analysis of Genomic Modifiers of the Clinical Onset of Huntington Disease
bioRxiv preprint doi: https://doi.org/10.1101/699033; this version posted July 11, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. 1 Gene expression profiles complement the analysis of genomic modifiers of the clinical onset of Huntington disease Galen E.B. Wright1,2,3; Nicholas S. Caron1,2,3; Bernard Ng1,2,4; Lorenzo Casal1,2,3; Xiaohong Xu5; Jolene Ooi5; Mahmoud A. Pouladi5,6,7; Sara Mostafavi1,2,4; Colin J.D. Ross3,7 and Michael R. Hayden1,2,3* 1Centre for Molecular Medicine and Therapeutics, Vancouver, British Columbia, Canada; 2Department of Medical Genetics, University of British Columbia, Vancouver, British Columbia, Canada; 3BC Children’s Hospital Research Institute, Vancouver, British Columbia, Canada; 4Department of Statistics, University of British Columbia, Vancouver, British Columbia, Canada; 5Translational Laboratory in Genetic Medicine (TLGM), Agency for Science, Technology and Research (A*STAR), Singapore; 6Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore; 7Department of Physiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore; 8Faculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, British Columbia, Canada; *Corresponding author ABSTRACT Huntington disease (HD) is a neurodegenerative disorder that is caused by a CAG repeat expansion in the HTT gene. In an attempt to identify genomic modifiers that contribute towards the age of onset of HD, we performed a transcriptome wide association study assessing heritable differences in genetically determined expression in diverse tissues, employing genome wide data from over 4,000 patients. -
Genomic and Transcriptome Analysis Revealing an Oncogenic Functional Module in Meningiomas
Neurosurg Focus 35 (6):E3, 2013 ©AANS, 2013 Genomic and transcriptome analysis revealing an oncogenic functional module in meningiomas XIAO CHANG, PH.D.,1 LINGLING SHI, PH.D.,2 FAN GAO, PH.D.,1 JONATHAN RUssIN, M.D.,3 LIYUN ZENG, PH.D.,1 SHUHAN HE, B.S.,3 THOMAS C. CHEN, M.D.,3 STEVEN L. GIANNOTTA, M.D.,3 DANIEL J. WEISENBERGER, PH.D.,4 GAbrIEL ZADA, M.D.,3 KAI WANG, PH.D.,1,5,6 AND WIllIAM J. MAck, M.D.1,3 1Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California, Los Angeles, California; 2GHM Institute of CNS Regeneration, Jinan University, Guangzhou, China; 3Department of Neurosurgery, Keck School of Medicine, University of Southern California, Los Angeles, California; 4USC Epigenome Center, Keck School of Medicine, University of Southern California, Los Angeles, California; 5Department of Psychiatry, Keck School of Medicine, University of Southern California, Los Angeles, California; and 6Division of Bioinformatics, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California Object. Meningiomas are among the most common primary adult brain tumors. Although typically benign, roughly 2%–5% display malignant pathological features. The key molecular pathways involved in malignant trans- formation remain to be determined. Methods. Illumina expression microarrays were used to assess gene expression levels, and Illumina single- nucleotide polymorphism arrays were used to identify copy number variants in benign, atypical, and malignant me- ningiomas (19 tumors, including 4 malignant ones). The authors also reanalyzed 2 expression data sets generated on Affymetrix microarrays (n = 68, including 6 malignant ones; n = 56, including 3 malignant ones). -
Association of Chromosome 19 to Lung Cancer Genotypes and Phenotypes
Cancer Metastasis Rev DOI 10.1007/s10555-015-9556-2 Association of chromosome 19 to lung cancer genotypes and phenotypes Xiangdong Wang1 & Yong Zhang 1 & Carol L. Nilsson2 & Frode S. Berven3 & Per E. Andrén4 & Elisabet Carlsohn5 & Johan Malm7 & Manuel Fuentes7 & Ákos Végvári6,8 & Charlotte Welinder6,9 & Thomas E. Fehniger6,10 & Melinda Rezeli8 & Goutham Edula11 & Sophia Hober12 & Toshihide Nishimura13 & György Marko-Varga6,8,13 # Springer Science+Business Media New York 2015 Abstract The Chromosome 19 Consortium, a part of the aberrations include translocation t(15, 19) (q13, p13.1) fusion Chromosome-Centric Human Proteome Project (C-HPP, oncogene BRD4-NUT, DNA repair genes (ERCC1, ERCC2, http://www.C-HPP.org), is tasked with the understanding XRCC1), TGFβ1 pathway activation genes (TGFB1, LTBP4) chromosome 19 functions at the gene and protein levels, as , Dyrk1B, and potential oncogenesis protector genes such as well as their roles in lung oncogenesis. Comparative genomic NFkB pathway inhibition genes (NFKBIB, PPP1R13L) and hybridization (CGH) studies revealed chromosome aberration EGLN2. In conclusion, neXtProt is an effective resource for in lung cancer subtypes, including ADC, SCC, LCC, and the validation of gene aberrations identified in genomic SCLC. The most common abnormality is 19p loss and 19q studies. It promises to enhance our understanding of lung gain. Sixty-four aberrant genes identified in previous genomic cancer oncogenesis. studies and their encoded protein functions were further vali- dated in the neXtProt database (http://www.nextprot.org/). Among those, the loss of tumor suppressor genes STK11, Keywords Proteins . Genes . Antibodies . mRNA . Mass MUM1, KISS1R (19p13.3), and BRG1 (19p13.13) is spectrometry . -
(NF1) As a Breast Cancer Driver
INVESTIGATION Comparative Oncogenomics Implicates the Neurofibromin 1 Gene (NF1) as a Breast Cancer Driver Marsha D. Wallace,*,† Adam D. Pfefferle,‡,§,1 Lishuang Shen,*,1 Adrian J. McNairn,* Ethan G. Cerami,** Barbara L. Fallon,* Vera D. Rinaldi,* Teresa L. Southard,*,†† Charles M. Perou,‡,§,‡‡ and John C. Schimenti*,†,§§,2 *Department of Biomedical Sciences, †Department of Molecular Biology and Genetics, ††Section of Anatomic Pathology, and §§Center for Vertebrate Genomics, Cornell University, Ithaca, New York 14853, ‡Department of Pathology and Laboratory Medicine, §Lineberger Comprehensive Cancer Center, and ‡‡Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27514, and **Memorial Sloan-Kettering Cancer Center, New York, New York 10065 ABSTRACT Identifying genomic alterations driving breast cancer is complicated by tumor diversity and genetic heterogeneity. Relevant mouse models are powerful for untangling this problem because such heterogeneity can be controlled. Inbred Chaos3 mice exhibit high levels of genomic instability leading to mammary tumors that have tumor gene expression profiles closely resembling mature human mammary luminal cell signatures. We genomically characterized mammary adenocarcinomas from these mice to identify cancer-causing genomic events that overlap common alterations in human breast cancer. Chaos3 tumors underwent recurrent copy number alterations (CNAs), particularly deletion of the RAS inhibitor Neurofibromin 1 (Nf1) in nearly all cases. These overlap with human CNAs including NF1, which is deleted or mutated in 27.7% of all breast carcinomas. Chaos3 mammary tumor cells exhibit RAS hyperactivation and increased sensitivity to RAS pathway inhibitors. These results indicate that spontaneous NF1 loss can drive breast cancer. This should be informative for treatment of the significant fraction of patients whose tumors bear NF1 mutations. -
Table S1. 103 Ferroptosis-Related Genes Retrieved from the Genecards
Table S1. 103 ferroptosis-related genes retrieved from the GeneCards. Gene Symbol Description Category GPX4 Glutathione Peroxidase 4 Protein Coding AIFM2 Apoptosis Inducing Factor Mitochondria Associated 2 Protein Coding TP53 Tumor Protein P53 Protein Coding ACSL4 Acyl-CoA Synthetase Long Chain Family Member 4 Protein Coding SLC7A11 Solute Carrier Family 7 Member 11 Protein Coding VDAC2 Voltage Dependent Anion Channel 2 Protein Coding VDAC3 Voltage Dependent Anion Channel 3 Protein Coding ATG5 Autophagy Related 5 Protein Coding ATG7 Autophagy Related 7 Protein Coding NCOA4 Nuclear Receptor Coactivator 4 Protein Coding HMOX1 Heme Oxygenase 1 Protein Coding SLC3A2 Solute Carrier Family 3 Member 2 Protein Coding ALOX15 Arachidonate 15-Lipoxygenase Protein Coding BECN1 Beclin 1 Protein Coding PRKAA1 Protein Kinase AMP-Activated Catalytic Subunit Alpha 1 Protein Coding SAT1 Spermidine/Spermine N1-Acetyltransferase 1 Protein Coding NF2 Neurofibromin 2 Protein Coding YAP1 Yes1 Associated Transcriptional Regulator Protein Coding FTH1 Ferritin Heavy Chain 1 Protein Coding TF Transferrin Protein Coding TFRC Transferrin Receptor Protein Coding FTL Ferritin Light Chain Protein Coding CYBB Cytochrome B-245 Beta Chain Protein Coding GSS Glutathione Synthetase Protein Coding CP Ceruloplasmin Protein Coding PRNP Prion Protein Protein Coding SLC11A2 Solute Carrier Family 11 Member 2 Protein Coding SLC40A1 Solute Carrier Family 40 Member 1 Protein Coding STEAP3 STEAP3 Metalloreductase Protein Coding ACSL1 Acyl-CoA Synthetase Long Chain Family Member 1 Protein -
An Integrative Genomic Analysis of the Longshanks Selection Experiment for Longer Limbs in Mice
bioRxiv preprint doi: https://doi.org/10.1101/378711; this version posted August 19, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 1 Title: 2 An integrative genomic analysis of the Longshanks selection experiment for longer limbs in mice 3 Short Title: 4 Genomic response to selection for longer limbs 5 One-sentence summary: 6 Genome sequencing of mice selected for longer limbs reveals that rapid selection response is 7 due to both discrete loci and polygenic adaptation 8 Authors: 9 João P. L. Castro 1,*, Michelle N. Yancoskie 1,*, Marta Marchini 2, Stefanie Belohlavy 3, Marek 10 Kučka 1, William H. Beluch 1, Ronald Naumann 4, Isabella Skuplik 2, John Cobb 2, Nick H. 11 Barton 3, Campbell Rolian2,†, Yingguang Frank Chan 1,† 12 Affiliations: 13 1. Friedrich Miescher Laboratory of the Max Planck Society, Tübingen, Germany 14 2. University of Calgary, Calgary AB, Canada 15 3. IST Austria, Klosterneuburg, Austria 16 4. Max Planck Institute for Cell Biology and Genetics, Dresden, Germany 17 Corresponding author: 18 Campbell Rolian 19 Yingguang Frank Chan 20 * indicates equal contribution 21 † indicates equal contribution 22 Abstract: 23 Evolutionary studies are often limited by missing data that are critical to understanding the 24 history of selection. Selection experiments, which reproduce rapid evolution under controlled 25 conditions, are excellent tools to study how genomes evolve under strong selection. Here we 1 bioRxiv preprint doi: https://doi.org/10.1101/378711; this version posted August 19, 2018. -
Heme, a Metabolic Sensor, Directly Regulates the Activity of the KDM4 Histone Demethylase Family and Their Interactions with Partner Proteins
cells Article Heme, A Metabolic Sensor, Directly Regulates the Activity of the KDM4 Histone Demethylase Family and Their Interactions with Partner Proteins Purna Chaitanya Konduri y , Tianyuan Wang y, Narges Salamat and Li Zhang * Department of Biological Sciences, University of Texas at Dallas, Mail Stop RL11, 800 W. Campbell Road, Richardson, TX 75080, USA; [email protected] (P.C.K.); [email protected] (T.W.); [email protected] (N.S.) * Correspondence: [email protected]; Tel.: +1-972-883-5757 These authors contributed equally to this paper. y Received: 7 February 2020; Accepted: 19 March 2020; Published: 22 March 2020 Abstract: The KDM4 histone demethylase subfamily is constituted of yeast JmjC domain-containing proteins, such as Gis1, and human Gis1 orthologues, such as KDM4A/B/C. KDM4 proteins have important functions in regulating chromatin structure and gene expression in response to metabolic and nutritional stimuli. Heme acts as a versatile signaling molecule to regulate important cellular functions in diverse organisms ranging from bacteria to humans. Here, using purified KDM4 proteins containing the JmjN/C domain, we showed that heme stimulates the histone demethylase activity of the JmjN/C domains of KDM4A and Cas well as full-length Gis1. Furthermore, we found that the C-terminal regions of KDM4 proteins, like that of Gis1, can confer heme regulation when fused to an unrelated transcriptional activator. Interestingly, biochemical pull-down of Gis1-interacting proteins followed by mass spectrometry identified 147 unique proteins associated with Gis1 under heme-sufficient and/or heme-deficient conditions. These 147 proteins included a significant number of heterocyclic compound-binding proteins, Ubl-conjugated proteins, metabolic enzymes/proteins, and acetylated proteins. -
Proteomic Landscape of the Human Choroid–Retinal Pigment Epithelial Complex
Supplementary Online Content Skeie JM, Mahajan VB. Proteomic landscape of the human choroid–retinal pigment epithelial complex. JAMA Ophthalmol. Published online July 24, 2014. doi:10.1001/jamaophthalmol.2014.2065. eFigure 1. Choroid–retinal pigment epithelial (RPE) proteomic analysis pipeline. eFigure 2. Gene ontology (GO) distributions and pathway analysis of human choroid– retinal pigment epithelial (RPE) protein show tissue similarity. eMethods. Tissue collection, mass spectrometry, and analysis. eTable 1. Complete table of proteins identified in the human choroid‐RPE using LC‐ MS/MS. eTable 2. Top 50 signaling pathways in the human choroid‐RPE using MetaCore. eTable 3. Top 50 differentially expressed signaling pathways in the human choroid‐RPE using MetaCore. eTable 4. Differentially expressed proteins in the fovea, macula, and periphery of the human choroid‐RPE. eTable 5. Differentially expressed transcription proteins were identified in foveal, macular, and peripheral choroid‐RPE (p<0.05). eTable 6. Complement proteins identified in the human choroid‐RPE. eTable 7. Proteins associated with age related macular degeneration (AMD). This supplementary material has been provided by the authors to give readers additional information about their work. © 2014 American Medical Association. All rights reserved. 1 Downloaded From: https://jamanetwork.com/ on 09/25/2021 eFigure 1. Choroid–retinal pigment epithelial (RPE) proteomic analysis pipeline. A. The human choroid‐RPE was dissected into fovea, macula, and periphery samples. B. Fractions of proteins were isolated and digested. C. The peptide fragments were analyzed using multi‐dimensional LC‐MS/MS. D. X!Hunter, X!!Tandem, and OMSSA were used for peptide fragment identification. E. Proteins were further analyzed using bioinformatics. -
Discovery of Putative STAT5 Transcription Factor Binding Sites in Mice with Diabetic
Discovery of Putative STAT5 Transcription Factor Binding Sites in Mice with Diabetic Nephropathy A thesis presented to the faculty of the Russ College of Engineering and Technology of Ohio University In partial fulfillment of the requirements for the degree Master of Science Jens Schmidt December 2013 © 2013 Jens Schmidt. All Rights Reserved. 2 This thesis titled Discovery of Putative STAT5 Transcription Factor Binding Sites in Mice with Diabetic Nephropathy by JENS SCHMIDT has been approved for the School of Electrical Engineering and Computer Science and the Russ College of Engineering and Technology by Lonnie R. Welch Professor of Electrical Engineering and Computer Science Dennis Irwin Dean, Russ College of Engineering and Technology 3 ABSTRACT SCHMIDT, JENS, M.S., December 2013, Computer Science Discovery of Putative STAT5 Transcription Factor Binding Sites in Mice with Diabetic Nephropathy Director of Thesis: Lonnie R. Welch Type 1 diabetes mellitus has become a major disease and impacts patients’ lives significantly. Because the underlying pathways and the genetic causes have not been exhaustively examined yet, this thesis focuses on identifying potential binding sites for STAT5, a transcription factor that is hypothesized to play a role in the inflammation process of diabetic nephropathy, a complication of type 1 diabetes. In this study, motif finding was applied to determine a set of putative STAT5 binding sites. This set was filtered by comparison to three gene ontology terms that are associated with processes that can occur in diabetic nephropathy and by comparison to experimentally validated STAT5 binding sites. This work generated a short list of six genes and their associated sites that should be given the highest priority for experimental validation in the laboratory in an effort to demonstrate a direct, repressive role for STAT5 in diabetic nephropathy. -
RARA Polyclonal Antibody
TECHNICAL DATASHEET RARA polyclonal antibody Cat. No. C15310155 (CS-155-100) Specificity: Human: positive Type: Polyclonal ChIP grade/ChIP-seq grade Other species: not tested Source: Rabbit Purity: Whole antiserum from rabbit containing 0.05% azide. Lot #: A704-001 Storage: Store at -20°C; for long storage, store at -80°C. Size: 100 µl Avoid multiple freeze-thaw cycles. Concentration: not determined Precautions: This product is for research use only. Not for use in diagnostic or therapeutic procedures. Description: Polyclonal antibody raised in rabbit against human RARA (Retinoic Acid Receptor alpha) using two KLH-conjugated synthetic peptides containing sequences from the C-terminal region of the protein. Applications Suggested dilution Results ChIP/ChIP-Seq * 4 µl/ChIP Fig 1,2 ELISA 1:50 Fig 3 Western blotting 1:750 Fig 4 * Please note that the optimal antibody amount per IP should be determined by the end-user. We recommend testing 1-10 µl per IP. References citing this antibody: (1) Martens JHA, Brinkman AB, Simmer F, Francoijs K-J, Nebbioso A, Ferrara F, Altucci L, and Stunnenberg HG (2010) PML-RARa/RXR Alters the Epigenetic Landscape in Acute Promyelocytic Leukemia. Cancer Cell 17, 173–185. Target description RARA (UniProtKB/Swiss-Prot entry P10276) is a receptor for retinoic acid, a vitamin A metabolite, which directly regulates gene expression in target cells by binding to specific DNA response elements. In the absence of its ligand, this receptor represses transcription through the recruitment of specific corepressors and of HDAC’s, whereas binding of retinioc acid causes the recruitment of coactivators and HAT’s.