Journal Article

Identifying novel constrained elements by exploiting biased substitution patterns

Manuel Garber, Mitchell Guttman, Michele Clamp, Michael C. Zody, Nir Friedman and Xiaohui Xie

in Bioinformatics

Volume 25, issue 12, pages i54-i62
Published in print June 2009 | ISSN: 1367-4803
Published online May 2009 | e-ISSN: 1460-2059 | DOI: http://dx.doi.org/10.1093/bioinformatics/btp190

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Motivation: Comparing the genomes from closely related species provides a powerful tool to identify functional elements in a reference genome. Many methods have been developed to identify conserved sequences across species; however, existing methods only model conservation as a decrease in the rate of mutation and have ignored selection acting on the pattern of mutations.

Results: We present a new approach that takes advantage of deeply sequenced clades to identify evolutionary selection by uncovering not only signatures of rate-based conservation but also substitution patterns characteristic of sequence undergoing natural selection. We describe a new statistical method for modeling biased nucleotide substitutions, a learning algorithm for inferring site-specific substitution biases directly from sequence alignments and a hidden Markov model for detecting constrained elements characterized by biased substitutions. We show that the new approach can identify significantly more degenerate constrained sequences than rate-based methods. Applying it to the ENCODE regions, we identify as much as 10.2% of these regions are under selection.

Availability: The algorithms are implemented in a Java software package, called SiPhy, freely available at http://www.broadinstitute.org/science/software/.

Contact: xhx@ics.uci.edu

Supplementary information: Supplementary data are available at Bioinformatics online.

Journal Article.  7023 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology

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