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| Status |
Public on Apr 03, 2018 |
| Title |
Divergence in DNA specificity among paralogous transcription factors contributes to their differential in vivo binding [uPBM_Elk1Ets1Gabpa_MycMaxMad] |
| Organism |
Homo sapiens |
| Experiment type |
Other
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| Summary |
Members of transcription factor (TF) families, i.e. paralogous TFs, are oftentimes reported to have identical DNA-binding motifs, despite the fact that they perform distinct regulatory functions in the cell. Differential genomic targeting by paralogous TFs is generally assumed to be due to interactions with protein cofactors or the chromatin environment. Contrary to previous assumptions, we find that paralogous TFs have different intrinsic preferences for DNA, not captured by current motif models, and these differences partly explain differential genomic binding and functional specificity. Our finding was possible due to a unique combination of carefully designed high-throughput assays and rigorous computation modeling, integrated into a unified framework called iMADS. We used iMADS to quantity, model, and analyze specificity differences between 11 paralogous TFs from 4 distinct human TF families. Our finding of differential specificity between closely related TFs has important implications for the interpretation of the regulatory effects of non-coding genetic variants.
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| Overall design |
Universal protein-binding microarray (PBM) experiments were performed for recombinant, full-length, human transcription factors c-Myc, Max, and Mad1. Briefly, universal PBMs involved binding of his-tagged transcription factor dimers to double-stranded 44K Agilent microarrays containing a DNA library designed to cover all possible 10-bp sequences, with every 8-mer occurring in at least 16 different spots on the array. This design allows comprehensive and unbiased characterization of the binding specificity of transcription factors for all possible 8-bp sequences.
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| Contributor(s) |
Gordan R |
| Citation(s) |
29605182 |
| NIH grant(s) |
| Grant ID |
Grant title |
Affiliation |
Name |
| R01 GM117106 |
New methods for quantitative modeling of protein-DNA interactions |
DUKE UNIVERSITY |
Raluca Gordan |
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| Submission date |
Aug 18, 2017 |
| Last update date |
Jul 25, 2021 |
| Contact name |
Raluca Gordan |
| E-mail(s) |
raluca.gordan@duke.edu
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| Organization name |
Duke University
|
| Department |
Center for Genomic and Computational Biology
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| Street address |
101 Science Dr, CIEMAS 2179
|
| City |
Durham |
| State/province |
NC |
| ZIP/Postal code |
27708 |
| Country |
USA |
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| Platforms (1) |
| GPL23935 |
Universal PBM 4x44k (Bulyk lab design) |
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| Samples (3) |
| GSM2746659 |
Mad1 at 1 uM concentration and Max at 100 nM concentration [Universal PBM 4x44k] |
| GSM2746660 |
Max at 100 nM concentration [Universal PBM 4x44k] |
| GSM2746661 |
c-Myc at 1 uM concentration and Max at 100 nM concentration [Universal PBM 4x44k] |
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| This SubSeries is part of SuperSeries: |
| GSE97794 |
Divergence in DNA specificity among paralogous transcription factors contributes to their differential in vivo binding |
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| Relations |
| BioProject |
PRJNA399106 |
