Cells use thousands of regulatory sequences to recruit transcription factors (TFs) and produce specific transcriptional outcomes. Since TFs bind degenerate DNA sequences, discriminating functional TF binding sites (TFBSs) from background sequences represents a significant challenge. Here, we show that a Drosophila regulatory element that activates Epidermal Growth Factor signaling requires overlapping, low-affinity TFBSs for competing TFs (Pax2 and Senseless) to ensure cell- and segment-specific activity. Testing available TF binding models for Pax2 and Senseless, however, revealed variable accuracy in predicting such low-affinity TFBSs. To better define parameters that increase accuracy, we developed a method that systematically selects subsets of TFBSs based on predicted affinity to generate hundreds of position-weight matrices (PWMs). Counterintuitively, we found that degenerate PWMs produced from datasets depleted of high-affinity sequences were more accurate in identifying both low- and high-affinity TFBSs for the Pax2 and Senseless TFs. Taken together, these findings reveal how TFBS arrangement can be constrained by competition rather than cooperativity and that degenerate models of TF binding preferences can improve identification of biologically relevant low affinity TFBSs.
Degenerate Pax2 and Senseless binding motifs improve detection of low-affinity sites required for enhancer specificity
Arya Zandvakili,I. Campbell,Lisa M Gutzwiller,M. Weirauch,B. Gebelein
Published 2018 in PLoS Genetics
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- Publication year
2018
- Venue
PLoS Genetics
- Publication date
2018-04-01
- Fields of study
Biology, Medicine
- Identifiers
- External record
- Source metadata
Semantic Scholar, PubMed
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