Abstract
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 motif-flanking 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.
Original language | English |
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Article number | 910 |
Journal | Molecular Systems Biology |
Volume | 13 |
Issue number | 2 |
DOIs | |
State | Published - 6 Feb 2017 |
Keywords
- DNA shape
- binding specificity
- feature selection
- quantitative modeling
- transcription factor
All Science Journal Classification (ASJC) codes
- Information Systems
- General Immunology and Microbiology
- Applied Mathematics
- General Biochemistry,Genetics and Molecular Biology
- General Agricultural and Biological Sciences
- Computational Theory and Mathematics