Journal
MOLECULAR SYSTEMS BIOLOGY
Volume 13, Issue 2, Pages -Publisher
WILEY-BLACKWELL
DOI: 10.15252/msb.20167238
Keywords
binding specificity; DNA shape; feature selection; quantitative modeling; transcription factor
Categories
Funding
- National Institutes of Health [R01GM106056, U01GM103804]
- Alfred P. Sloan Research Fellowship
- Israel Science Foundation [317/13]
- Raymond and Beverly Sackler Chair in Bioinformatics
- Knut and Alice Wallenberg Foundation
- Swedish Research Council
- Edmond J. Safra Center for Bioinformatics at Tel Aviv University
- National Science Foundation [MCB-1413539]
- Dan David Prize scholarships
- Direct For Biological Sciences
- Div Of Molecular and Cellular Bioscience [1413539] Funding Source: National Science Foundation
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Transcription factors (TFs) achieve DNA-binding specificity through contacts with functional groups of bases (base readout) and readout of structural properties of the double helix (shape readout). Currently, it remains unclear whether DNA shape readout is utilized by only a few selected TF families, or whether this mechanism is used extensively by most TF families. We resequenced data from previously published HT-SELEX experiments, the most extensive mammalian TF-DNA binding data available to date. Using these data, we demonstrated the contributions of DNA shape readout across diverse TF families and its importance in core motifflanking regions. Statistical machine-learning models combined with feature-selection techniques helped to reveal the nucleotide position-dependent DNA shape readout in TF-binding sites and the TF family-specific position dependence. Based on these results, we proposed novel DNA shape logos to visualize the DNA shape preferences of TFs. Overall, this work suggests a way of obtaining mechanistic insights into TF-DNA binding without relying on experimentally solved all-atom structures.
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