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Sequence and Structural Determinants of Specificity Differences between Paralogous Transcription Factors

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Date
2016
Author
Shen, Ning
Advisor
Gordan, Raluca
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Abstract

Transcription factors (TFs) control the temporal and spatial expression of target genes by interacting with DNA in a sequence-specific manner. Recent advances in high throughput experiments that measure TF-DNA interactions in vitro and in vivo have facilitated the identification of DNA binding sites for thousands of TFs. However, it remains unclear how each individual TF achieves its specificity, especially in the case of paralogous TFs that recognize distinct target genomic sites despite sharing very similar DNA binding motifs. In my work, I used a combination of high throughput in vitro protein-DNA binding assays and machine-learning algorithms to characterize and model the binding specificity of 11 paralogous TFs from 4 distinct structural families. My work proves that even very closely related paralogous TFs, with indistinguishable DNA binding motifs, oftentimes exhibit differential binding specificity for their genomic target sites, especially for sites with moderate binding affinity. Importantly, the differences I identify in vitro and through computational modeling help explain, at least in part, the differential in vivo genomic targeting by paralogous TFs. Future work will focus on in vivo factors that might also be important for specificity differences between paralogous TFs, such as DNA methylation, interactions with protein cofactors, or the chromatin environment. In this larger context, my work emphasizes the importance of intrinsic DNA binding specificity in targeting of paralogous TFs to the genome.

Type
Dissertation
Department
Pharmacology
Subject
Systematic biology
Genetics
Bioinformatics
gcPBM
SVR model
TF-DNA specificity
Transcription factor
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https://hdl.handle.net/10161/12215
Citation
Shen, Ning (2016). Sequence and Structural Determinants of Specificity Differences between Paralogous Transcription Factors. Dissertation, Duke University. Retrieved from https://hdl.handle.net/10161/12215.
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This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 United States License.

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