Although interactions between transcriptional factors (TFs) and genes through low-affinity promoters have been largely ignored and their contribution in transcriptional regulation disregarded, they are abundant in vivo. These bindings between TFs and low-affinity promoters form a notable fraction of the interactions between TFs and DNA and are promoter sequence dependent.
The strongest evidence that supports this highlight is the fact that through analyzing data from the current Chromatin Immunoprecipitation (ChIP) experiments quantitatively, the study reveals widespread low affinity transcriptional interactions in a genome. Unlike previous analysis methods the ChIP data was interpreted quantitatively, the focus was therefore not only on a few dozens high specificity hits for each TF but covered the entire specificity range of the TFs (Tanay, 2006).
The previous working hypothesis that TFs either bind perfectly to a sequence motif or do not bind at all meant that the analysis of ChIP data made use of a digital model such that all the data was transformed into binary TF-gene interactions. This openly ignores the contribution of low-affinity TF-gene interactions that do not give perfect binary ChIP measurements. The quantitative approach employs an analogue model that analyses the ChIP data as it is without any transformations thus increasing the possibility of detecting low-affinity TF-gene interactions.
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