Abstract
The short length and high degeneracy of sites recognized by DNA-binding transcription factors limit the amount of information they can carry, and individual sites are rarely sufficient to mediate the regulation of specific targets. Computational analysis of microbial genomes has suggested that many factors function optimally when in a particular orientation and position with respect to their target promoters. To investigate this further, we developed and trained spatial models of binding site positioning and applied them to the genome of the yeast Saccharomyces cerevisiae. We found evidence of non-random organization of sites within promoters, differences in binding site density, or both for thirty-eight transcription factors. We show that these signatures allow transcription factors with substantial differences in binding site specificity to share similar promoter specificities. We illustrate how spatial information dictating the positioning and density of binding sites can in principle increase the information available to the organism for differentiating a transcription factor’s true targets, and we indicate how this information could potentially be leveraged for the same purpose in bioinformatic analyses.
Highlights
A typical transcription factor in the yeast Saccharomyces cerevisiae binds to short, six to ten base pair sequences in promoters [1], with the strength of this binding depending on the specific sequence of the site [2,3]
We found that the scores generated by our model were more likely to be significantly associated with expression than those generated by the other two computational methods, and that the ORFs ranked highly according to our model typically exhibited a larger expression change upon transcription factor deletion: comparing the spatial signature model with the spatially-agnostic thermodynamic model, the signature model shows a greater magnitude of expression difference in twelve of the fifteen cases in which either model was significantly associated with expression
Spatial Specificity Compensating for Poor Site Quality Our principal finding is that well-specified promoter recognition signatures, often including restricted spacing, orientation bias, and, most importantly, multiple binding sites, are common and appear able to compensate for poor site specificity
Summary
A typical transcription factor in the yeast Saccharomyces cerevisiae binds to short, six to ten base pair sequences in promoters [1], with the strength of this binding depending on the specific sequence of the site [2,3]. Both strongly- and weakly-bound sites can impact the expression of adjacent genes [4,5]. They found that binding sites in eukaryotes carry far less information than would be required to accurately differentiate them from the rest of the genome, suggesting that transcription factors must bind promiscuously to nonfunctional sites
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