Identifying novel constrained elements by exploiting biased substitution patterns

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

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

256 Scopus citations

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.

Original languageAmerican English
Pages (from-to)i54-i62
JournalBioinformatics
Volume25
Issue number12
DOIs
StatePublished - 2009

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