Journal Article

Is Transcription Factor Binding Site Turnover a Sufficient Explanation for Cis-Regulatory Sequence Divergence?

Sandeep Venkataram and Justin C. Fay

in Genome Biology and Evolution

Published on behalf of Society for Molecular Biology and Evolution

Volume 2, issue , pages 851-858
Published in print January 2010 |
Published online November 2010 | e-ISSN: 1759-6653 | DOI:

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The molecular evolution of cis-regulatory sequences is not well understood. Comparisons of closely related species show that cis-regulatory sequences contain a large number of sites constrained by purifying selection. In contrast, there are a number of examples from distantly related species where cis-regulatory sequences retain little to no sequence similarity but drive similar patterns of gene expression. Binding site turnover, whereby the gain of a redundant binding site enables loss of a previously functional site, is one model by which cis-regulatory sequences can diverge without a concurrent change in function. To determine whether cis-regulatory sequence divergence is consistent with binding site turnover, we examined binding site evolution within orthologous intergenic sequences from 14 yeast species defined by their syntenic relationships with adjacent coding sequences. Both local and global alignments show that nearly all distantly related orthologous cis-regulatory sequences have no significant level of sequence similarity but are enriched for experimentally identified binding sites. Yet, a significant proportion of experimentally identified binding sites that are conserved in closely related species are absent in distantly related species and so cannot be explained by binding site turnover. Depletion of binding sites depends on the transcription factor but is detectable for a quarter of all transcription factors examined. Our results imply that binding site turnover is not a sufficient explanation for cis-regulatory sequence evolution.

Keywords: evolution; regulation; yeast

Journal Article.  5004 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology ; Evolutionary Biology ; Genetics and Genomics

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