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Your search keyword '"Epigenome, Center"' showing total 3 results
Start Over Author "Epigenome, Center" Topic epigenomics
3 results on '"Epigenome, Center"'

1. Integrative analysis of 111 reference human epigenomes.

Author

Kundaje A, Meuleman W, Ernst J, Bilenky M, Yen A, Heravi-Moussavi A, Kheradpour P, Zhang Z, Wang J, Ziller MJ, Amin V, Whitaker JW, Schultz MD, Ward LD, Sarkar A, Quon G, Sandstrom RS, Eaton ML, Wu YC, Pfenning AR, Wang X, Claussnitzer M, Liu Y, Coarfa C, Harris RA, Shoresh N, Epstein CB, Gjoneska E, Leung D, Xie W, Hawkins RD, Lister R, Hong C, Gascard P, Mungall AJ, Moore R, Chuah E, Tam A, Canfield TK, Hansen RS, Kaul R, Sabo PJ, Bansal MS, Carles A, Dixon JR, Farh KH, Feizi S, Karlic R, Kim AR, Kulkarni A, Li D, Lowdon R, Elliott G, Mercer TR, Neph SJ, Onuchic V, Polak P, Rajagopal N, Ray P, Sallari RC, Siebenthall KT, Sinnott-Armstrong NA, Stevens M, Thurman RE, Wu J, Zhang B, Zhou X, Beaudet AE, Boyer LA, De Jager PL, Farnham PJ, Fisher SJ, Haussler D, Jones SJ, Li W, Marra MA, McManus MT, Sunyaev S, Thomson JA, Tlsty TD, Tsai LH, Wang W, Waterland RA, Zhang MQ, Chadwick LH, Bernstein BE, Costello JF, Ecker JR, Hirst M, Meissner A, Milosavljevic A, Ren B, Stamatoyannopoulos JA, Wang T, and Kellis M

Subjects
Base Sequence, Cell Lineage genetics, Cells, Cultured, Chromatin chemistry, Chromatin genetics, Chromatin metabolism, Chromosomes, Human chemistry, Chromosomes, Human genetics, Chromosomes, Human metabolism, DNA chemistry, DNA genetics, DNA metabolism, DNA Methylation, Datasets as Topic, Enhancer Elements, Genetic genetics, Genetic Variation genetics, Genome-Wide Association Study, Histones metabolism, Humans, Organ Specificity genetics, RNA genetics, Reference Values, Epigenesis, Genetic genetics, Epigenomics, Genome, Human genetics
Abstract

The reference human genome sequence set the stage for studies of genetic variation and its association with human disease, but epigenomic studies lack a similar reference. To address this need, the NIH Roadmap Epigenomics Consortium generated the largest collection so far of human epigenomes for primary cells and tissues. Here we describe the integrative analysis of 111 reference human epigenomes generated as part of the programme, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression. We establish global maps of regulatory elements, define regulatory modules of coordinated activity, and their likely activators and repressors. We show that disease- and trait-associated genetic variants are enriched in tissue-specific epigenomic marks, revealing biologically relevant cell types for diverse human traits, and providing a resource for interpreting the molecular basis of human disease. Our results demonstrate the central role of epigenomic information for understanding gene regulation, cellular differentiation and human disease.

Published
2015
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2. Epigenomic footprints across 111 reference epigenomes reveal tissue-specific epigenetic regulation of lincRNAs.

Author

Amin V, Harris RA, Onuchic V, Jackson AR, Charnecki T, Paithankar S, Lakshmi Subramanian S, Riehle K, Coarfa C, and Milosavljevic A

Subjects
Embryonic Stem Cells physiology, Humans, Organ Specificity, Phenotype, Polycomb-Group Proteins physiology, Cell Differentiation, Epigenesis, Genetic, Epigenomics, RNA, Long Noncoding metabolism, Regulatory Elements, Transcriptional
Abstract

Tissue-specific expression of lincRNAs suggests developmental and cell-type-specific functions, yet tissue specificity was established for only a small fraction of lincRNAs. Here, by analysing 111 reference epigenomes from the NIH Roadmap Epigenomics project, we determine tissue-specific epigenetic regulation for 3,753 (69% examined) lincRNAs, with 54% active in one of the 14 cell/tissue clusters and an additional 15% in two or three clusters. A larger fraction of lincRNA TSSs is marked in a tissue-specific manner by H3K4me1 than by H3K4me3. The tissue-specific lincRNAs are strongly linked to tissue-specific pathways and undergo distinct chromatin state transitions during cellular differentiation. Polycomb-regulated lincRNAs reside in the bivalent state in embryonic stem cells and many of them undergo H3K27me3-mediated silencing at early stages of differentiation. The exquisitely tissue-specific epigenetic regulation of lincRNAs and the assignment of a majority of them to specific tissue types will inform future studies of this newly discovered class of genes.

Published
2015
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3. Genomic and epigenomic landscapes of adult de novo acute myeloid leukemia

Author

Ley, Timothy, Miller, Christopher, Ding, Li, Raphael, Benjamin J., Mungall, Andrew J., Robertson, A. Gordon, Hoadley, Katherine, Triche, Timothy J., Laird, Peter W., Baty, Jack D., Fulton, Lucinda L., Fulton, Robert, Heath, Sharon E., Kalicki Veizer, Joelle, Kandoth, Cyriac, Klco, Jeffery M., Koboldt, Daniel C., Kanchi, Krishna Latha, Shashikant, Kulkarni, M. S., P. h. D., F. A. C. M. G., Lamprecht, Tamara L., B. S., Washington, University, Louis, S. t., Larson, David E., P. h. D., Ling, Lin, M. S., Charles, Lu, Mclellan, Michael D., Mcmichael, Joshua F., the Genome Institute at Washington University, Jacqueline, Payton, M. D., P. h. D., Heather, Schmidt, Spencer, David H., Tomasson, Michael H., M. D., Siteman Cancer Center, S. t. Louis, Wallis, John W., Wartman, Lukas D., Watson, Mark A., John, Welch, Wendl, Michael C., Adrian, Ally, B. S. c., Miruna, Balasundaram, B. A. S. c., Inanc, Birol, Yaron, Butterfield, Readman, Chiu, M. S. c., Andy, Chu, Eric, Chuah, Hye Jung Chun, Richard, Corbett, Noreen, Dhalla, Ranabir, Guin, An, He, Carrie, Hirst, Martin, Hirst, Holt, Robert A., Steven, Jones, Aly, Karsan, Darlene, Lee, Haiyan I., Li, Marra, Marco A., Michael, Mayo, Moore, Richard A., Karen, Mungall, Jeremy, Parker, Erin, Pleasance, Patrick, Plettner, Jacquie, Schein, Dominik, Stoll, Lucas, Swanson, Angela, Tam, Nina, Thiessen, Richard, Varhol, Natasja, Wye, Yongjun, Zhao, M. S. c., D. V. M., British Columbia Cancer Agency's Genome Sciences Centre, Vancouver, Canada, Stacey, Gabriel, Gad, Getz, Carrie, Sougnez, Lihua, Zou, Broad Institute of Harvard, Massachusetts Institute of Technology, Cambridge, Ma, Mark D. M. Leiserson, B. A., Vandin, Fabio, Hsin Ta Wu, Brown, University, Center for Computational Molecular Biology, Providence, Ri, Frederick, Applebaum, Fred Hutchinson Cancer Research Center, Division of Medical Oncology, Seattle Cancer Care Alliance, Seattle, Baylin, Stephen B., Johns Hopkins University, Baltimore, Rehan, Akbani, Broom, Bradley M., Ken, Chen, Motter, Thomas C., B. A., Khanh, Nguyen, Weinstein, John N., Nianziang, Zhang, Anderson Cancer Center, University of Texas M. D., Houston, Ferguson, Martin L., Mlf, Consulting, Biotechnology Consultant, Boston, Christopher, Adams, Aaron, Black, Jay, Bowen, Julie Gastier Foster, Thomas, Grossman, Tara, Lichtenberg, Lisa, Wise, the Research Institute at Nationwide Children's Hospital, Columbus, Oh, Tanja, Davidsen, Demchok, John A., Mills Shaw, Kenna R., Margi, Sheth, National Cancer Institute, Bethesda, Md, Sofia, Heidi J., P. h. D., M. P. H., National Human Genome Research Institute, Liming, Yang, Downing, James R., Jude Children's Research Hospital, S. t., Memphis, Greg, Eley, Sciementis, Llc, Statham, Ga, Shelley, Alonso, Brenda, Ayala, Julien, Baboud, Mark, Backus, Barletta, Sean P., Berton, Dominique L., M. S. C. S., Chu, Anna L., Stanley, Girshik, Jensen, Mark A., Ari, Kahn, Prachi, Kothiyal, Nicholls, Matthew C., Pihl, Todd D., Pot, David A., Rohini, Raman, B. E., Sanbhadti, Rashmi N., Snyder, Eric E., Deepak, Srinivasan, Jessica, Walton, Yunhu, Wan, Zhining, Wang, Sra, International, Fairfax, Va, Issa, Jean Pierre J., Temple, University, Philadelphia, Michelle Le Beau, University of Chicago, Chicago, Martin, Carroll, University of Pennsylvania, Hagop Kantarjian, M. D., Steven, Kornblau, Bootwalla, Moiz S., B. S. c., M. S., Lai, Phillip H., Hui, Shen, Van Den Berg, David J., Weisenberger, Daniel J., University of Southern California, Epigenome, Center, Los, Angeles, Daniel C. Link, M. D., Walter, Matthew J., Ozenberger, Bradley A., Mardis, Elaine R., Peter, Westervelt, Graubert, Timothy A., Dipersio, John F., and Wilson, Richard K.

Subjects
Myeloid, Adult, Epigenomics, Male, NPM1, Gene Expression, CpG Islands, DNA Methylation, Female, Gene Fusion, Genome, Human, Humans, Leukemia, Myeloid, Acute, MicroRNAs, Middle Aged, Sequence Analysis, DNA, Mutation, Acute, Enasidenib, Biology, CEBPA, Genetics, Genome, Leukemia, Massive parallel sequencing, MicroRNA sequencing, Myeloid leukemia, DNA, General Medicine, KMT2A, biology.protein, Sequence Analysis, Nucleophosmin, Human, Comparative genomic hybridization
Abstract

BACKGROUND—Many mutations that contribute to the pathogenesis of acute myeloid leukemia (AML) are undefined. The relationships between patterns of mutations and epigenetic phenotypes are not yet clear. METHODS—We analyzed the genomes of 200 clinically annotated adult cases of de novo AML, using either whole-genome sequencing (50 cases) or whole-exome sequencing (150 cases), along with RNA and microRNA sequencing and DNA-methylation analysis. RESULTS—AML genomes have fewer mutations than most other adult cancers, with an average of only 13 mutations found in genes. Of these, an average of 5 are in genes that are recurrently mutated in AML. A total of 23 genes were significantly mutated, and another 237 were mutated in two or more samples. Nearly all samples had at least 1 nonsynonymous mutation in one of nine categories of genes that are almost certainly relevant for pathogenesis, including transcriptionfactor fusions (18% of cases), the gene encoding nucleophosmin (NPM1) (27%), tumorsuppressor genes (16%), DNA-methylation–related genes (44%), signaling genes (59%), chromatin-modifying genes (30%), myeloid transcription-factor genes (22%), cohesin-complex genes (13%), and spliceosome-complex genes (14%). Patterns of cooperation and mutual exclusivity suggested strong biologic relationships among several of the genes and categories. CONCLUSIONS—We identified at least one potential driver mutation in nearly all AML samples and found that a complex interplay of genetic events contributes to AML pathogenesis in individual patients. The databases from this study are widely available to serve as a foundation for further investigations of AML pathogenesis, classification, and risk stratification. (Funded by the National Institutes of Health.) The molecular pathogenesis of acute myeloid leukemia (AML) has been studied with the use of cytogenetic analysis for more than three decades. Recurrent chromosomal structural variations are well established as diagnostic and prognostic markers, suggesting that acquired genetic abnormalities (i.e., somatic mutations) have an essential role in pathogenesis. 1,2 However, nearly 50% of AML samples have a normal karyotype, and many of these genomes lack structural abnormalities, even when assessed with high-density comparative genomic hybridization or single-nucleotide polymorphism (SNP) arrays 3-5 (see Glossary). Targeted sequencing has identified recurrent mutations in FLT3, NPM1, KIT, CEBPA, and TET2. 6-8 Massively parallel sequencing enabled the discovery of recurrent mutations in DNMT3A 9,10 and IDH1. 11 Recent studies have shown that many patients with

Published
2013

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