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Identifying novel constrained elements by exploiting biased substitution patterns
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.Many UC-authored scholarly publications are freely available on this site because of the UC's open access policies. Let us know how this access is important for you.
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