Identifying novel constrained elements by exploiting biased substitution patterns

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.

Guttman, Mitchell (author)
Clamp, Michele (author)
Zody, Michael C.Uppsala universitet,Institutionen för medicinsk biokemi och mikrobiologi(Swepub:uu)miczo266 (author)
Friedman, Nir (author)
Xie, Xiaohui (author)
Uppsala universitetInstitutionen för medicinsk biokemi och mikrobiologi (creator_code:org_t)

In:Bioinformatics: Oxford University Press (OUP)25:12, s. I54-I621367-48031367-4811

By the author/editor: Garber, Manuel; Guttman, Mitchel ...; Clamp, Michele; Zody, Michael C.; Friedman, Nir; Xie, Xiaohui

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