Complex Patterns of Association between Pleiotropy and Transcription Factor Evolution

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Genome Biology And Evolution


Geisel School of Medicine


Pleiotropy hasbeen claimedtoconstraingeneevolution but specificmechanisms andextent of these constraintshavebeen difficult to demonstrate. The expansion of molecular data makes it possible to investigate these pleiotropic effects. Few classes of genes have been characterized as intensely as human transcription factors ( TFs). We therefore analyzed the evolutionary rates of full TF proteins, along with theirDNAbinding domains and protein-protein interacting domains ( PID) in light of the degree of pleiotropy, measured by the number of TF-TF interactions, or the number of DNA-binding targets. Data were extracted fromthe ENCODE Chip-Seq dataset, the String v 9.2 database, and the NHGRIGWAScatalog. Evolutionary rates of proteins and domainswere calculated using the PAML CodeML package. Our analysis shows that the numbers of TF-TF interactions and DNA binding targets associated with constrained gene evolution; however, the constraint caused by the number of DNA binding targets was restricted to the DNA binding domains, whereas the number of TF-TF interactions constrained the full protein and did so more strongly. Additionally, we found a positive correlation between the number of protein-PIDs and the evolutionary rates of the protein-PIDs. These findings show that not only does pleiotropy associate with constrained protein evolution but the constraint differs by domain function. Finally, we show that GWASassociated TF genes are more highly pleiotropic. TheGWASdata illustrates thatmutations inhighly pleiotropic genes aremore likely to be associated with disease phenotypes.