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      The Drosophila melanogaster Genetic Reference Panel

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          Abstract

          A major challenge of biology is understanding the relationship between molecular genetic variation and variation in quantitative traits, including fitness. This relationship determines our ability to predict phenotypes from genotypes and to understand how evolutionary forces shape variation within and between species. Previous efforts to dissect the genotype-phenotype map were based on incomplete genotypic information. Here, we describe the Drosophila melanogaster Genetic Reference Panel (DGRP), a community resource for analysis of population genomics and quantitative traits. The DGRP consists of fully sequenced inbred lines derived from a natural population. Population genomic analyses reveal reduced polymorphism in centromeric autosomal regions and the X chromosome, evidence for positive and negative selection, and rapid evolution of the X chromosome. Many variants in novel genes, most at low frequency, are associated with quantitative traits and explain a large fraction of the phenotypic variance. The DGRP facilitates genotype-phenotype mapping using the power of Drosophila genetics.

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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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            Finding the missing heritability of complex diseases.

            Genome-wide association studies have identified hundreds of genetic variants associated with complex human diseases and traits, and have provided valuable insights into their genetic architecture. Most variants identified so far confer relatively small increments in risk, and explain only a small proportion of familial clustering, leading many to question how the remaining, 'missing' heritability can be explained. Here we examine potential sources of missing heritability and propose research strategies, including and extending beyond current genome-wide association approaches, to illuminate the genetics of complex diseases and enhance its potential to enable effective disease prevention or treatment.
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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
                Nature
                0028-0836
                1476-4687
                6 June 2013
                08 February 2012
                17 June 2013
                : 482
                : 7384
                : 173-178
                Affiliations
                [1 ]Department of Genetics, North Carolina State University, Raleigh NC 27695, USA
                [2 ]Human Genome Sequencing Center, Baylor College of Medicine, One Baylor Plaza, Houston TX 77030 USA
                [3 ]Genomics, Bioinformatics and Evolution Group, Institut de Biotecnologia i de Biomedicina - IBB / Department of Genetics and Microbiology, Campus Universitat Autònoma de Barcelona, 08193 Bellaterra, Spain
                [4 ]Department of Ecology and Evolutionary Biology, University of California - Irvine, Irvine CA, USA
                [5 ]Faculty of Life Sciences, University of Manchester, Manchester, M13 9PT, UK
                [6 ]Department of Biology, North Carolina State University, Raleigh NC 27695, USA
                [7 ]Molecular Evolutionary Genetics Group, Department of Genetics, Faculty of Biology, Universitat de Barcelona, Diagonal 645, 08028 Barcelona, Spain
                [8 ]Center for Public Health Genomics, University of Virginia, PO Box 800717, Charlottesville VA 22908, USA
                [9 ]Virginia Bioinformatics Institute and Department of Biological Sciences, Virginia Tech, Blacksburg, VA 24061, USA
                Author notes
                Correspondence and requests for materials should be addressed to trudy_mackay@ 123456ncsu.edu
                [*]

                Equal contributions

                [10]

                Current address: FAS Society of Fellows, Harvard University, 78 Mt Auburn St, Cambridge MA 02138, USA

                [11]

                Current address: Functional Comparative Genomics Group. Institut de Biotecnologia i de Biomedicina - IBB, Campus Universitat Autònoma de Barcelona, 08193 Bellaterra, Spain

                [12]

                Current address: Department of Biological Sciences, University of Cincinnati, Cincinnati, OH 45221, USA

                Article
                NIHMS345805
                10.1038/nature10811
                3683990
                22318601
                920354f7-8d89-4d87-813d-5c422bfd0dd8

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                History
                Funding
                Funded by: National Institute of General Medical Sciences : NIGMS
                Award ID: R01 GM045146 || GM
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