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Gene. 2012 Sep 10;506(1):125-34. doi: 10.1016/j.gene.2012.06.005. Epub 2012 Jun 10.

Differences in local genomic context of bound and unbound motifs.

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1
Computational Biology Branch, National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 8900 Rockville Pike, Bethesda, MD 20894, USA.

Abstract

Understanding gene regulation is a major objective in molecular biology research. Frequently, transcription is driven by transcription factors (TFs) that bind to specific DNA sequences. These motifs are usually short and degenerate, rendering the likelihood of multiple copies occurring throughout the genome due to random chance as high. Despite this, TFs only bind to a small subset of sites, thus prompting our investigation into the differences between motifs that are bound by TFs and those that remain unbound. Here we constructed vectors representing various chromatin- and sequence-based features for a published set of bound and unbound motifs representing nine TFs in the budding yeast Saccharomyces cerevisiae. Using a machine learning approach, we identified a set of features that can be used to discriminate between bound and unbound motifs. We also discovered that some TFs bind most or all of their strong motifs in intergenic regions. Our data demonstrate that local sequence context can be strikingly different around motifs that are bound compared to motifs that are unbound. We concluded that there are multiple combinations of genomic features that characterize bound or unbound motifs.

PMID:
22692006
PMCID:
PMC3412921
DOI:
10.1016/j.gene.2012.06.005
[Indexed for MEDLINE]
Free PMC Article
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