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Bioinformatics. 2009 Jun 15;25(12):i54-62. doi: 10.1093/bioinformatics/btp190.

Identifying novel constrained elements by exploiting biased substitution patterns.

Author information

1
Department of Biology, Broad Institute of MIT and Harvard, 7 Cambridge Center, MIT, Cambridge, MA 02142, USA.

Abstract

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/.

SUPPLEMENTARY INFORMATION:

Supplementary data are available at Bioinformatics online.

PMID:
19478016
PMCID:
PMC2687944
DOI:
10.1093/bioinformatics/btp190
[Indexed for MEDLINE]
Free PMC Article
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