4.7 Article

A systematic genome-wide account of binding sites for the model transcription factor Gcn4

Journal

GENOME RESEARCH
Volume 32, Issue 2, Pages 367-377

Publisher

COLD SPRING HARBOR LAB PRESS, PUBLICATIONS DEPT
DOI: 10.1101/gr.276080.121

Keywords

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Funding

  1. Intramural Research Program of the NIH (NICHD)

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Sequence-specific DNA-binding transcription factors, such as Gcn4, play a central role in gene regulation. Gcn4 has a strong binding affinity to an AP-1-like sequence and a weaker affinity to half-sites. However, only a fraction of the exact matches to this sequence are bound by Gcn4, even in vitro. The binding of Gcn4 is independent of chromatin structure and is determined by the presence of nucleosome-depleted regulatory regions.
Sequence-specific DNA-binding transcription factors are central to gene regulation. They are often associated with consensus binding sites that predict far more genomic sites than are bound in vivo. One explanation is that most sites are blocked by nucleosomes, such that only sites in nucleosome-depleted regulatory regions are bound. We compared the binding of the yeast transcription factor Gcn4 in vivo using published ChIP-seq data (546 sites) and in vitro, using a modified SELEX method (G-SELEX), which utilizes short genomic DNA fragments to quantify binding at all sites. We confirm that Gcn4 binds strongly to an AP-1-like sequence (TGACTCA) and weakly to half-sites. However, Gcn4 binds only some of the 1078 exact matches to this sequence, even in vitro. We show that there are only 166 copies of the high-affinity RTGACTCAY site (exact match) in the yeast genome, all occupied in vivo, largely independently of whether they are located in nucleosome-depleted or nucleosomal regions. Generally, RTGACTCAR/YTGACTCAY sites are bound much more weakly and YTGACTCAR sites are unbound, with biological implications for determining induction levels. We conclude that, to a first approximation, Gcn4 binding can be predicted using the high-affinity site, without reference to chromatin structure. We propose that transcription factor binding sites should be defined more precisely using quantitative data, allowing more accurate genome-wide prediction of binding sites and greater insight into gene regulation.

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