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      Comprehensive analysis of the chromatin landscape in Drosophila

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          Summary

          Chromatin is composed of DNA and a variety of modified histones and non-histone proteins, which impact cell differentiation, gene regulation and other key cellular processes. We present a genome-wide chromatin landscape for Drosophila melanogaster based on 18 histone modifications, summarized by 9 prevalent combinatorial patterns. Integrative analysis with other data (non-histone chromatin proteins, DNaseI hypersensitivity, GRO-seq reads produced by engaged polymerase, short/long RNA products) reveals discrete characteristics of chromosomes, genes, regulatory elements, and other functional domains. We find that active genes display distinct chromatin signatures that are correlated with disparate gene lengths, exon patterns, regulatory functions, and genomic contexts. We also demonstrate a diversity of signatures among Polycomb targets that include a subset with paused polymerase. This systematic profiling and integrative analysis of chromatin signatures provides insights into how genomic elements are regulated, and will serve as a resource for future experimental investigations of genome structure and function.

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          Most cited references32

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          Evolution of genes and genomes on the Drosophila phylogeny.

          Comparative analysis of multiple genomes in a phylogenetic framework dramatically improves the precision and sensitivity of evolutionary inference, producing more robust results than single-genome analyses can provide. The genomes of 12 Drosophila species, ten of which are presented here for the first time (sechellia, simulans, yakuba, erecta, ananassae, persimilis, willistoni, mojavensis, virilis and grimshawi), illustrate how rates and patterns of sequence divergence across taxa can illuminate evolutionary processes on a genomic scale. These genome sequences augment the formidable genetic tools that have made Drosophila melanogaster a pre-eminent model for animal genetics, and will further catalyse fundamental research on mechanisms of development, cell biology, genetics, disease, neurobiology, behaviour, physiology and evolution. Despite remarkable similarities among these Drosophila species, we identified many putatively non-neutral changes in protein-coding genes, non-coding RNA genes, and cis-regulatory regions. These may prove to underlie differences in the ecology and behaviour of these diverse species.
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            ChIP-seq accurately predicts tissue-specific activity of enhancers.

            A major yet unresolved quest in decoding the human genome is the identification of the regulatory sequences that control the spatial and temporal expression of genes. Distant-acting transcriptional enhancers are particularly challenging to uncover because they are scattered among the vast non-coding portion of the genome. Evolutionary sequence constraint can facilitate the discovery of enhancers, but fails to predict when and where they are active in vivo. Here we present the results of chromatin immunoprecipitation with the enhancer-associated protein p300 followed by massively parallel sequencing, and map several thousand in vivo binding sites of p300 in mouse embryonic forebrain, midbrain and limb tissue. We tested 86 of these sequences in a transgenic mouse assay, which in nearly all cases demonstrated reproducible enhancer activity in the tissues that were predicted by p300 binding. Our results indicate that in vivo mapping of p300 binding is a highly accurate means for identifying enhancers and their associated activities, and suggest that such data sets will be useful to study the role of tissue-specific enhancers in human biology and disease on a genome-wide scale.
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              Identification of functional elements and regulatory circuits by Drosophila modENCODE.

              To gain insight into how genomic information is translated into cellular and developmental programs, the Drosophila model organism Encyclopedia of DNA Elements (modENCODE) project is comprehensively mapping transcripts, histone modifications, chromosomal proteins, transcription factors, replication proteins and intermediates, and nucleosome properties across a developmental time course and in multiple cell lines. We have generated more than 700 data sets and discovered protein-coding, noncoding, RNA regulatory, replication, and chromatin elements, more than tripling the annotated portion of the Drosophila genome. Correlated activity patterns of these elements reveal a functional regulatory network, which predicts putative new functions for genes, reveals stage- and tissue-specific regulators, and enables gene-expression prediction. Our results provide a foundation for directed experimental and computational studies in Drosophila and related species and also a model for systematic data integration toward comprehensive genomic and functional annotation.
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                Author and article information

                Journal
                0410462
                6011
                Nature
                Nature
                0028-0836
                1476-4687
                3 January 2011
                22 December 2010
                24 March 2011
                24 September 2011
                : 471
                : 7339
                : 480-485
                Affiliations
                [1 ]Center for Biomedical Informatics, Harvard Medical School, Boston, MA, USA
                [2 ]Children’s Hospital Informatics Program, Boston, MA USA
                [3 ]Division of Genetics, Department of Medicine, Brigham & Women’s Hospital, Boston, MA USA
                [4 ]Department of Genetics, Harvard Medical School, Boston, MA, USA
                [5 ]Department of Molecular Biology & Biochemistry, Rutgers University, Piscataway, NJ, USA
                [6 ]Department of Molecular and Cell Biology, University of California at Berkeley, and Department of Genome Dynamics, Lawrence Berkeley National Lab, Berkeley, CA, USA
                [7 ]Department of Biology, Washington University in St. Louis, St. Louis, MO, USA
                [8 ]MIT Computer Science and Artificial Intelligence Laboratory, Cambridge MA, USA
                [9 ]Broad Institute of MIT and Harvard, Cambridge, MA, USA
                [10 ]Department of Genome Sciences, University of Washington, Seattle, WA, USA
                [11 ]Department of Molecular Biology, Cell Biology and Biochemistry, Brown University, Providence, RI, USA
                [12 ]Graduate Program in Bioinformatics, Boston University, Boston, MA, USA
                [13 ]Department of Pharmacology and Cancer Biology, Duke University Medical Center, Durham, NC, USA
                [14 ]Department of Medicine, University of Washington, Seattle, WA, USA
                Author notes
                [* ]Correspondence and requests for materials should be addressed to P.J.P ( peter_park@ 123456harvard.edu ) and G.H.K ( karpen@ 123456fruitfly.org )
                [†]

                Present address: Department of Molecular Biology, Umea University, 901 87, Umea, Sweden.

                [§]

                Present address: Department of Plant Biology and Pathology, SEBS, Rutgers University

                [‡]

                Present address: Department of Basic Sciences, The Commonwealth Medical College, Scranton, PA

                Article
                nihpa256870
                10.1038/nature09725
                3109908
                21179089
                ee62abb2-3301-4aca-a755-1d54625c2321
                History
                Funding
                Funded by: National Human Genome Research Institute : NHGRI
                Award ID: U01 HG004258-04 ||HG
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