Extreme purifying selection against point mutations in the human genome

Noah Dukler, Mehreen R. Mughal, Ritika Ramani, Yi-Fei Huang and Adam Siepel ()
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Noah Dukler: Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory
Mehreen R. Mughal: Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory
Ritika Ramani: Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory
Yi-Fei Huang: The Pennsylvania State University
Adam Siepel: Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory

Nature Communications, 2022, vol. 13, issue 1, 1-12

Abstract: Abstract Large-scale genome sequencing has enabled the measurement of strong purifying selection in protein-coding genes. Here we describe a new method, called ExtRaINSIGHT, for measuring such selection in noncoding as well as coding regions of the human genome. ExtRaINSIGHT estimates the prevalence of “ultraselection” by the fractional depletion of rare single-nucleotide variants, after controlling for variation in mutation rates. Applying ExtRaINSIGHT to 71,702 whole genome sequences from gnomAD v3, we find abundant ultraselection in evolutionarily ancient miRNAs and neuronal protein-coding genes, as well as at splice sites. By contrast, we find much less ultraselection in other noncoding RNAs and transcription factor binding sites, and only modest levels in ultraconserved elements. We estimate that ~0.4–0.7% of the human genome is ultraselected, implying ~ 0.26–0.51 strongly deleterious mutations per generation. Overall, our study sheds new light on the genome-wide distribution of fitness effects by combining deep sequencing data and classical theory from population genetics.

Date: 2022
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DOI: 10.1038/s41467-022-31872-6

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