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Integrative analysis of 111 reference human epigenomes

Roadmap Epigenomics Consortium, 1 , 2 , 3 , 1 , 2 , 1 , 2 , 4 , 5 , 1 , 2 , 1 , 2 , 1 , 2 , 5 , 1 , 2 , 6 , 2 , 7 , 8 , 9 , 10 , 1 , 2 , 1 , 2 , 1 , 2 , 1 , 2 , 1 , 2 , 1 , 2 , 1 , 2 , 11 , 1 , 2 , 1 , 2 , 6 , 6 , 2 , 2 , 12 , 2 , 8 , 8 , 8 ,   9 , 13 , 14 , 5 , 5 , 5 , 5 , 10 , 10 , 15 , 10 , 1 , 2 , 16 , 17 , 8 , 2 , 1 , 2 , 18 , 1 , 2 , 19 , 20 , 20 , 21 , 10 , 6 , 2 , 22 , 8 , 19 , 1 , 2 , 10 , 1 , 2 , 20 , 10 , 23 , 24 , 20 , 20 , 47 , 11 , 34 , 35 , 31 , 28 , 5 , 48 , 49 , 5 , 17 , 41 , 2 , 22 , 34 , 27 , 14 , 12 , 2 , 8 , 50 , 19 , 51 , 2 , 43 , 25 , 13 , 9 , 5 , 17 , 2 , 6 , 8 , 10 , 20 , 1 , 2

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      Abstract

      The reference human genome sequence set the stage for studies of genetic variation and its association with human disease, but a similar reference has lacked for epigenomic studies. To address this need, the NIH Roadmap Epigenomics Consortium generated the largest collection to-date of human epigenomes for primary cells and tissues. Here, we describe the integrative analysis of 111 reference human epigenomes generated as part of the program, 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.

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      Gene ontology: tool for the unification of biology. The Gene Ontology Consortium.

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        Fast and accurate short read alignment with Burrows–Wheeler transform

        Motivation: The enormous amount of short reads generated by the new DNA sequencing technologies call for the development of fast and accurate read alignment programs. A first generation of hash table-based methods has been developed, including MAQ, which is accurate, feature rich and fast enough to align short reads from a single individual. However, MAQ does not support gapped alignment for single-end reads, which makes it unsuitable for alignment of longer reads where indels may occur frequently. The speed of MAQ is also a concern when the alignment is scaled up to the resequencing of hundreds of individuals. Results: We implemented Burrows-Wheeler Alignment tool (BWA), a new read alignment package that is based on backward search with Burrows–Wheeler Transform (BWT), to efficiently align short sequencing reads against a large reference sequence such as the human genome, allowing mismatches and gaps. BWA supports both base space reads, e.g. from Illumina sequencing machines, and color space reads from AB SOLiD machines. Evaluations on both simulated and real data suggest that BWA is ∼10–20× faster than MAQ, while achieving similar accuracy. In addition, BWA outputs alignment in the new standard SAM (Sequence Alignment/Map) format. Variant calling and other downstream analyses after the alignment can be achieved with the open source SAMtools software package. Availability: http://maq.sourceforge.net Contact: rd@sanger.ac.uk
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          Cytoscape: a software environment for integrated models of biomolecular interaction networks.

          Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.
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            Author and article information

            Affiliations
            [1 ] Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge MA 02139, USA
            [2 ] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge MA 02142, USA.
            [3 ] Department of Genetics, Department of Computer Science, 300 Pasteur Dr., Lane Building, L301, Stanford, CA 94305-5120.
            [4 ] Department of Biological Chemistry, University of California, Los Angeles, 615 Charles E Young Dr South, Los Angeles, CA 90095, USA.
            [5 ] BC Cancer Agency, Canada's Micheal Smith Genome Sciences Centre, 675 West 10th Avenue, Vancouver, BC, V5Z 1L3, Canada.
            [6 ] Epigenome Center, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA.
            [7 ] Department of Stem Cell and Regenerative Biology, 7 Divinity Ave, Cambridge, MA 02138, USA.
            [8 ] Department of Cellular and Molecular Medicine, Institute of Genomic Medicine, Moores Cancer Center, Department of Chemistry and Biochemistry, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA.
            [9 ] Genomic Analysis Laboratory, Howard Hughes Medical Institute & The Salk Institute for Biological Studies, 10010 N.Torrey Pines Road, La Jolla, CA 92037, USA.
            [10 ] Department of Genome Sciences, University of Washington, 1705 NE Pacific Street Seattle WA 98195 USA 206-267-1091, USA.
            [11 ] Biology Department, Massachusetts Institute of Technology, 31 Ames St, Cambridge, MA 02142, USA.
            [12 ] Picower Institute for Learning and Memory, Massachusetts Institute of Technology, 43 Vassar St, Cambridge, MA 02139, USA.
            [13 ] Department of Neurosurgery, Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, 1450 3rd Street, San Francisco, CA, 94158, USA.
            [14 ] Department of Pathology, University of California San Francisco, 513 Parnassus Avenue, San Francisco CA 94143-0511, USA.
            [15 ] Department of Medicine, Division of Medical Genetics, University of Washington, 2211 Elliot Avenue Seattle WA 98121 USA 206-267-1091, USA.
            [16 ] Department of Computer Science & Engineering, University of Connecticut , 371 Fairfield Way, Storrs CT 06269, USA.
            [17 ] Department of Microbiology and Immunology and Centre for High-Throughput Biology, University of British Columbia, 2125 East Mall, Vancouver, BC, V6T 1Z4, Canada.
            [18 ] Bioinformatics Group, Division of Biology, Faculty of Science, Zagreb University, Horvatovac 102a, 10000 Zagreb, Croatia.
            [19 ] Department of Molecular and Cell Biology, Center for Systems Biology, The University of Texas, Dallas, NSERL, RL10, 800 W Campbell Road, Richardson, TX 75080, USA.
            [20 ] Department of Genetics, Center for Genome Sciences and Systems Biology, Washington University in St. Louis, 4444 Forest Park Ave. Saint Louis, MO 63108, USA.
            [21 ] Institute for Molecular Bioscience, University of Queensland, St Lucia Queensland 4072, Australia.
            [22 ] Brigham & Women's Hospital and Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA.
            [23 ] Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY 11794-3600, USA.
            [24 ] Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA.
            [25 ] Massachusetts General Hospital, 55 Fruit St, Boston, MA 02114, USA.
            [26 ] University of Virginia, School of Medicine, 1340 Jefferson Park Ave. Charlottesville, VA, 22908, USA.
            [27 ] Morgridge Institute for Research, 330 N. Orchard St., Madison, WI 53707, USA, USA.
            [28 ] Center for Biomolecular Sciences and Engineering, University of Santa Cruz, 1156 High Street, Santa Cruz, CA 95064, USA.
            [29 ] UCSF School of Medicine, 513 Parnassus Avenue, San Francisco CA 94143, USA.
            [30 ] Rush University Medical Center, 1653 W Congress Pkwy, Chicago, IL 60612, USA.
            [31 ] OB/GYN & Reproductive Sciences, University of California San Francisco, 35 Medical Center Way, San Fancisco, CA 94143, USA.
            [32 ] Rikshospitalet University Hospital, Sognsvannsveien 20, 0372 Oslo, Norway.
            [33 ] Reproductive Endocrinology and Infertility, University of California San Francisco, 2356 Sutter St, San Francisco, CA, 94115, USA.
            [34 ] Harvard Medical School, 25 Shattuck St, Boston, MA 02115, USA.
            [35 ] Department of Biochemistry, Keck School of Medicine, University of Southern California, 1450 Biggy Street, Los Angeles, CA 90089-9601, USA.
            [36 ] Ludwig Institute for Cancer Research, 9500 Gilman Drive, La Jolla, CA 92093, USA, USA.
            [37 ] Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N, Seattle, WA 98109, USA.
            [38 ] Clinical Research Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave. North Seattle WA 98109 U 206-667-4004, USA.
            [39 ] Department of Pediatrics, Seattle Children's Hospital/University of Washington, 4800 Sand Point Way NE Seattle WA 98105 USA, USA.
            [40 ] Yale School of Medicine, 333 Cedar Street, New Haven, CT 06510, USA.
            [41 ] Department of Microbiology and Immunology, Diabetes Center, University of California, San Francisco, 513 Parnassus Ave., San Francisco, CA 94143-0534, USA.
            [42 ] School of Medicine, University of California San Francisco, 513 Parnassus Avenue, San Francisco CA 94143, USA.
            [43 ] Howard Hughes Medical Institute, 4000 Jones Bridge Road, Chevy Chase, MD 20815-6789, USA.
            [44 ] Center for Molecular Oncologic Pathology, Dana-Farber Cancer Institute/Brigham and Women's Hospital, 450 Brookline Avenue, Boston, MA 02215, USA.
            [45 ] Vincent's Clinical School, University of New South Wales, Level 2, ASGM Building/Botany St, Sydney NSW 2052, Australia.
            [46 ] Immunology Research Program, Benaroya Research Institute, 1201 Ninth Avenue Seattle WA 98101 USA, USA.
            [47 ] Molecular and Human Genetics Department, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA.
            [48 ] Simon Fraser University, 8888 University Drive, Burnaby, BC V5A 1S6, Canada.
            [49 ] Dan L. Duncan Cancer Center, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA.
            [50 ] USDA/ARS Children's Nutrition Research Center, Baylor College of Medicine, 1100 Bates Street, Houston, TX 77030, USA.
            [51 ] National Institute of Environmental Health Sciences, 111 T.W. Alexander Drive, Research Triangle Park, N.C. 27709, USA.
            Author notes
            [†]

            Equal contributors, integrative analysis.

            [‡]

            Equal contributors, data production and processing.

            [¥]

            Equal contributors, joint senior authors.

            Correspondence should be addressed to: manoli@ 123456mit.edu
            Journal
            0410462
            6011
            Nature
            Nature
            Nature
            0028-0836
            1476-4687
            31 July 2015
            19 February 2015
            19 August 2015
            : 518
            : 7539
            : 317-330
            25693563
            4530010
            10.1038/nature14248
            NIHMS657700
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