Analyses of deep mammalian sequence alignments and constraint predictions for 1% of the human genome

Elliott H. Margulies, Gregory M. Cooper, George Asimenos, Daryl J. Thomas, Colin N. Dewey, Adam Siepel, Ewan Birney, Damian Keefe, Ariel S. Schwartz, Minmei Hou, James Taylor, Sergey Nikolaev, Juan I. Montoya-Burgos, Ari Löytynoja, Simon Whelan, Fabio Pardi, Tim Massingham, James B. Brown, Peter Bickel, Ian HolmesJames C. Mullikin, Abel Ureta-Vidal, Benedict Paten, Eric A. Stone, Kate R. Rosenbloom, W. James Kent, Stylianos E. Antonarakis, Serafim Batzoglou, Nick Goldman, Ross Hardison, David Haussler, Webb Miller, Lior Pachter, Eric D. Green, Arend Sidow, Gerard G. Bouffard, Xiaobin Guan, Nancy F. Hansen, Jacquelyn R. Idol, Valerie V.B. Maduro, Baishali Maskeri, Jennifer C. McDowell, Morgan Park, Pamela J. Thomas, Alice C. Young, Robert W. Blakesley, Donna M. Muzny, Erica Sodergren, David A. Wheeler, Kim C. Worley, Huaiyang Jiang, George M. Weinstock, Richard A. Gibbs, Tina Graves, Robert Fulton, Elaine R. Mardis, Richard K. Wilson, Michele Clamp, James Cuff, Sante Gnerre, David B. Jaffe, Jean L. Chang, Kerstin Lindblad-Toh, Eric S. Lander, Angie Hinrichs, Heather Trumbower, Hiram Clawson, Ann Zweig, Robert M. Kuhn, Galt Barber, Rachel Harte, Donna Karolchik, Matthew A. Field, Richard A. Moore, Carrie A. Mathewson, Jacqueline E. Schein, Marco A. Marra

Research output: Contribution to journalArticle

162 Scopus citations

Abstract

A key component of the ongoing ENCODE project involves rigorous comparative sequence analyses for the initially targeted 1% of the human genome. Here, we present orthologous sequence generation, alignment, and evolutionary constraint analyses of 23 mammalian species for all ENCODE targets. Alignments were generated using four different methods; comparisons of these methods reveal large-scale consistency but substantial differences in terms of small genomic rearrangements, sensitivity (sequence coverage), and specificity (alignment accuracy). We describe the quantitative and qualitative trade-offs concomitant with alignment method choice and the levels of technical error that need to be accounted for in applications that require multisequence alignments. Using the generated alignments, we identified constrained regions using three different methods. While the different constraint-detecting methods are in general agreement, there are important discrepancies relating to both the underlying alignments and the specific algorithms. However, by integrating the results across the alignments and constraint-detecting methods, we produced constraint annotations that were found to be robust based on multiple independent measures. Analyses of these annotations illustrate that most classes of experimentally annotated functional elements are enriched for constrained sequences; however, large portions of each class (with the exception of protein-coding sequences) do not overlap constrained regions. The latter elements might not be under primary sequence constraint, might not be constrained across all mammals, or might have expendable molecular functions. Conversely, 40% of the constrained sequences do not overlap any of the functional elements that have been experimentally identified. Together, these findings demonstrate and quantify how many genomic functional elements await basic molecular characterization.

Original languageEnglish (US)
Pages (from-to)760-774
Number of pages15
JournalGenome research
Volume17
Issue number6
DOIs
StatePublished - Jun 2007

All Science Journal Classification (ASJC) codes

  • Genetics
  • Genetics(clinical)

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    Margulies, E. H., Cooper, G. M., Asimenos, G., Thomas, D. J., Dewey, C. N., Siepel, A., Birney, E., Keefe, D., Schwartz, A. S., Hou, M., Taylor, J., Nikolaev, S., Montoya-Burgos, J. I., Löytynoja, A., Whelan, S., Pardi, F., Massingham, T., Brown, J. B., Bickel, P., ... Marra, M. A. (2007). Analyses of deep mammalian sequence alignments and constraint predictions for 1% of the human genome. Genome research, 17(6), 760-774. https://doi.org/10.1101/gr.6034307