Discovery of functional elements in 12 Drosophila genomes using evolutionary signatures View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2007-11

AUTHORS

Alexander Stark, Michael F. Lin, Pouya Kheradpour, Jakob S. Pedersen, Leopold Parts, Joseph W. Carlson, Madeline A. Crosby, Matthew D. Rasmussen, Sushmita Roy, Ameya N. Deoras, J. Graham Ruby, Julius Brennecke, , , Emily Hodges, Angie S. Hinrichs, Anat Caspi, Benedict Paten, Seung-Won Park, Mira V. Han, Morgan L. Maeder, Benjamin J. Polansky, Bryanne E. Robson, Stein Aerts, Jacques van Helden, Bassem Hassan, Donald G. Gilbert, Deborah A. Eastman, Michael Rice, Michael Weir, Matthew W. Hahn, Yongkyu Park, Colin N. Dewey, Lior Pachter, W. James Kent, David Haussler, Eric C. Lai, David P. Bartel, Gregory J. Hannon, Thomas C. Kaufman, Michael B. Eisen, Andrew G. Clark, Douglas Smith, Susan E. Celniker, William M. Gelbart, Manolis Kellis

ABSTRACT

Sequencing of multiple related species followed by comparative genomics analysis constitutes a powerful approach for the systematic understanding of any genome. Here, we use the genomes of 12 Drosophila species for the de novo discovery of functional elements in the fly. Each type of functional element shows characteristic patterns of change, or ‘evolutionary signatures’, dictated by its precise selective constraints. Such signatures enable recognition of new protein-coding genes and exons, spurious and incorrect gene annotations, and numerous unusual gene structures, including abundant stop-codon readthrough. Similarly, we predict non-protein-coding RNA genes and structures, and new microRNA (miRNA) genes. We provide evidence of miRNA processing and functionality from both hairpin arms and both DNA strands. We identify several classes of pre- and post-transcriptional regulatory motifs, and predict individual motif instances with high confidence. We also study how discovery power scales with the divergence and number of species compared, and we provide general guidelines for comparative studies. More... »

PAGES

219-232

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  • Journal

    TITLE

    Nature

    ISSUE

    7167

    VOLUME

    450

    Author Affiliations

  • Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, Massachusetts 02139, USA
  • Center for Biomolecular Science and Engineering, University of California, Santa Cruz, California 95064, USA
  • Institute of Computer Science, University of Tartu, Estonia
  • BDGP, LBNL, 1 Cyclotron Road MS 64-0119, Berkeley, California 94720, USA
  • FlyBase, The Biological Laboratories, Harvard University, 16 Divinity Avenue, Cambridge, Massachusetts 02138, USA
  • Department of Computer Science, University of New Mexico, Albuquerque, New Mexico 87131, USA
  • Whitehead Institute, Cambridge, Massachusetts 02142, USA
  • Cold Spring Harbor Laboratory, Watson School of Biological Sciences, 1 Bungtown Road, Cold Spring Harbor, New York 11724, USA
  • University of California, San Francisco/University of California, Berkeley Joint Graduate Group in Bioengineering, Berkeley, California 97210, USA
  • EMBL Nucleotide Sequence Submissions, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK
  • Department of Cell Biology and Molecular Medicine, G-629, MSB, 185 South Orange Avenue, UMDNJ-New Jersey Medical School, Newark, New Jersey 07103, USA
  • Department of Biology and School of Informatics, Indiana University, Indiana 47405, USA
  • Department of Biology, Connecticut College, New London, Connecticut 06320, USA
  • Department of Human Genetics, K. U. Leuven School of Medicine, 3000 Leuven, Belgium
  • Department de Biologie Moleculaire, Universite Libre de Bruxelles, 1050 Brussels, Belgium
  • Department of Biology, Indiana University, Bloomington, Indiana 47405, USA
  • Department of Mathematics and Computer Science, Wesleyan University, Middletown, Connecticut 06459, USA
  • Biology Department, Wesleyan University Middletown, Connecticut 06459, USA
  • Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, Wisconsin 53706, USA
  • Department of Computer Science, University of California at Berkeley, Berkeley, California 94720, USA
  • Department of Developmental Biology, Memorial Sloan-Kettering Cancer Center, New York, New York 10021, USA
  • Life Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA
  • Department of Molecular Biology and Genetics, Cornell University, Ithaca, New York 14853, USA
  • Agencourt Bioscience Corporation, 500 Cummings Center, Suite 2450, Beverly, Massachusetts 01915, USA
  • The Department of Molecular and Cellular Biology, Harvard University, Cambridge, Massachusetts 02138, USA
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/nature06340

    DOI

    http://dx.doi.org/10.1038/nature06340

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1050041079

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/17994088


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