NIH Research Festival
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Evolutionary turnover in non-coding regions has driven phenotypic divergence during past speciation events and continues to facilitate environmental adaptation through variants occurring in the human population. However, purifying selection restricts the impact of regulatory variants on core physiological processes and suggests the presence of dynamic and constrained regions in the genome, which facilitate adaptability alongside stability in biological systems. Here, we used a deep learning model to identify the genomic substrates of novel enhancer activity using three synthetic trajectories comprising mutations mimicking either 1) human-chimp substitutions, 2) population variations, or 3) random mutations. We observed enhancer turnover in approximately 6% of the whole genome, with more than 80% of the novel activity arising from repurposing of enhancers between cell types that is independent of the mutational trajectory. Loci of neurodevelopmental genes such as CNTNAP2, NPAS3, and AUTS2 exhibit the highest turnover. Compared with active enhancers in a cell type, these loci are gene-distal regions with reduced evolutionary constraints and are depleted in trait-associated variants. By leveraging multiple synthetic trajectories to assess changes in activity, we categorized these loci as vulnerable enhancers that are differentially abundant in cell type-specific transcription factor binding sites (TFBSs), as opposed to mutationally robust enhancers, which have a higher abundance of ubiquitous TFBSs. We conclude that distal cell type-specific enhancers undergo frequent turnover in the face of genome-wide mutations and are hotspots of cis-regulatory novelty.
Scientific Focus Area: Genetics and Genomics
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