Impact of Coding Variation on Transcription Factor - DNA Recognition

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ABSTRACT Binding by sequence-specific transcription factors (TFs) to their recognition sites is a primary step in gene regulation. In-depth characterization of the DNA binding specificities of TFs is essential for understanding how transcriptional regulation is specified. Technologies developed in the past decade for highly parallel analysis of TF DNA binding specificities have been used to survey the DNA binding specificities of TFs from a variety of TF DNA binding domain (DBD) structural classes (e.g., homeodomains) and species. Nevertheless, despite the generation of these large datasets, a detailed understanding of TF-DNA binding specificity determinants is still lacking for most TFs. Disease mutations and naturally occurring coding variation in TFs, especially those within DBDs, have the potential to alter TF DNA binding activity. However, there is insufficient understanding of the determinants of TF-DNA binding activity to allow for accurate prediction of the effects of such coding mutations on DNA binding activity. This is an important problem, since mutations or coding variation that damage TF DNA binding activity have the potential to disrupt the regulation of 1,000s of genes in the human genome. The goals of this project are to investigate novel DNA binding activity determinants for major structural classes of human TFs, to determine how heterodimeric protein partners might modulate the effects of TF coding variants on DNA binding activity, and to determine the extent to which coding variation that damages intrinsic TF-DNA recognition alters TF genomic targeting and gene regulation. We anticipate our results and datasets will reveal determinants of TF-DNA binding specificity, identify what mutations damage DNA binding specificity or affinity, inform future interpretations of exome and whole-genome sequence data, and open new areas of investigation into studies of how TF coding variation impacts transcriptional gene regulation and human phenotypes.