Divergence in DNA Specificity among Paralogous Transcription Factors Contributes to Their Differential In Vivo Binding

Ning Shen; Jingkang Zhao; Joshua L Schipper; Yuning Zhang; Tristan Bepler; Dan Leehr; John Bradley; John Horton; Hilmar Lapp; Raluca Gordan

doi:10.1016/j.cels.2018.02.009

Divergence in DNA Specificity among Paralogous Transcription Factors Contributes to Their Differential In Vivo Binding

Cell Syst. 2018 Apr 25;6(4):470-483.e8. doi: 10.1016/j.cels.2018.02.009. Epub 2018 Mar 28.

Authors

Ning Shen¹, Jingkang Zhao², Joshua L Schipper³, Yuning Zhang⁴, Tristan Bepler⁵, Dan Leehr⁵, John Bradley⁵, John Horton³, Hilmar Lapp⁵, Raluca Gordan⁶

Affiliations

¹ Center for Genomic and Computational Biology, Duke University, Durham, NC 27708, USA; Department of Pharmacology and Cancer Biology, Duke University, Durham, NC 27710, USA; Department of Biostatistics and Bioinformatics, Duke University, Durham, NC 27710, USA.
² Center for Genomic and Computational Biology, Duke University, Durham, NC 27708, USA; Department of Biostatistics and Bioinformatics, Duke University, Durham, NC 27710, USA; Program in Computational Biology and Bioinformatics, Duke University, Durham, NC 27708, USA.
³ Center for Genomic and Computational Biology, Duke University, Durham, NC 27708, USA; Department of Biostatistics and Bioinformatics, Duke University, Durham, NC 27710, USA.
⁴ Center for Genomic and Computational Biology, Duke University, Durham, NC 27708, USA; Program in Computational Biology and Bioinformatics, Duke University, Durham, NC 27708, USA.
⁵ Center for Genomic and Computational Biology, Duke University, Durham, NC 27708, USA.
⁶ Center for Genomic and Computational Biology, Duke University, Durham, NC 27708, USA; Department of Biostatistics and Bioinformatics, Duke University, Durham, NC 27710, USA; Department of Computer Science, Duke University, Durham, NC 27708, USA; Department of Molecular Genetics and Microbiology, Duke University, Durham, NC 27710, USA. Electronic address: raluca.gordan@duke.edu.

Abstract

Paralogous transcription factors (TFs) are oftentimes reported to have identical DNA-binding motifs, despite the fact that they perform distinct regulatory functions. Differential genomic targeting by paralogous TFs is generally assumed to be due to interactions with protein co-factors or the chromatin environment. Using a computational-experimental framework called iMADS (integrative modeling and analysis of differential specificity), we show that, contrary to previous assumptions, paralogous TFs bind differently to genomic target sites even in vitro. We used iMADS to quantify, model, and analyze specificity differences between 11 TFs from 4 protein families. We found that paralogous TFs have diverged mainly at medium- and low-affinity sites, which are poorly captured by current motif models. We identify sequence and shape features differentially preferred by paralogous TFs, and we show that the intrinsic differences in specificity among paralogous TFs contribute to their differential in vivo binding. Thus, our study represents a step forward in deciphering the molecular mechanisms of differential specificity in TF families.

Keywords: E2F; ETS; RUNX; bHLH; differential protein-DNA binding; divergence in DNA specificity; genetic variation; iMADS; paralogous transcription factors.

MeSH terms

Binding Sites
Gene Expression Regulation / physiology
Models, Genetic*
Models, Molecular
Nucleotide Motifs
Sequence Analysis, Protein
Transcription Factors / chemistry
Transcription Factors / physiology*

Substances

Transcription Factors

Abstract

MeSH terms

Substances

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