Identifying novel constrained elements by exploiting biased substitution patterns.
BACKGROUND
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.


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


BACKGROUND
Supplementary data are available at Bioinformatics online.
Garber
Manuel
M
Department of Biology, Broad Institute of MIT and Harvard, 7 Cambridge Center, MIT, Cambridge, MA 02142, USA.
Guttman
Mitchell
M
Clamp
Michele
M
Zody
Michael C
MC
Friedman
Nir
N
Xie
Xiaohui
X
D000465:Algorithms; D001483:Base Sequence; D019143:Evolution, Molecular; D023281:Genomics / Q000379:methods*; D016415:Sequence Alignment / Q000379:methods*; D012984:Software