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Frequent Gain and Loss of Functional Transcription Factor Binding Sites

Overview of attention for article published in PLoS Computational Biology, May 2007
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Title
Frequent Gain and Loss of Functional Transcription Factor Binding Sites
Published in
PLoS Computational Biology, May 2007
DOI 10.1371/journal.pcbi.0030099
Pubmed ID
Authors

Scott W Doniger, Justin C Fay

Abstract

Cis-regulatory sequences are not always conserved across species. Divergence within cis-regulatory sequences may result from the evolution of species-specific patterns of gene expression or the flexible nature of the cis-regulatory code. The identification of functional divergence in cis-regulatory sequences is therefore important for both understanding the role of gene regulation in evolution and annotating regulatory elements. We have developed an evolutionary model to detect the loss of constraint on individual transcription factor binding sites (TFBSs). We find that a significant fraction of functionally constrained binding sites have been lost in a lineage-specific manner among three closely related yeast species. Binding site loss has previously been explained by turnover, where the concurrent gain and loss of a binding site maintains gene regulation. We estimate that nearly half of all loss events cannot be explained by binding site turnover. Recreating the mutations that led to binding site loss confirms that these sequence changes affect gene expression in some cases. We also estimate that there is a high rate of binding site gain, as more than half of experimentally identified S. cerevisiae binding sites are not conserved across species. The frequent gain and loss of TFBSs implies that cis-regulatory sequences are labile and, in the absence of turnover, may contribute to species-specific patterns of gene expression.

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The data shown below were compiled from readership statistics for 182 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 14 8%
Netherlands 2 1%
Germany 1 <1%
France 1 <1%
Hong Kong 1 <1%
Israel 1 <1%
Switzerland 1 <1%
Canada 1 <1%
United Kingdom 1 <1%
Other 2 1%
Unknown 157 86%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 62 34%
Researcher 39 21%
Professor > Associate Professor 19 10%
Student > Master 14 8%
Student > Bachelor 10 5%
Other 28 15%
Unknown 10 5%
Readers by discipline Count As %
Agricultural and Biological Sciences 118 65%
Biochemistry, Genetics and Molecular Biology 34 19%
Computer Science 7 4%
Neuroscience 3 2%
Physics and Astronomy 3 2%
Other 6 3%
Unknown 11 6%