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Deleterious Alleles in the Human Genome Are on Average Younger Than Neutral Alleles of the Same Frequency

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2013

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Public Library of Science
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Kiezun, Adam, Sara L. Pulit, Laurent C. Francioli, Freerk van Dijk, Morris Swertz, Dorret I. Boomsma, Cornelia M. van Duijn, et al. 2013. Deleterious alleles in the human genome are on average younger than neutral alleles of the same frequency. PLoS Genetics 9(2): e1003301.

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Abstract

Large-scale population sequencing studies provide a complete picture of human genetic variation within the studied populations. A key challenge is to identify, among the myriad alleles, those variants that have an effect on molecular function, phenotypes, and reproductive fitness. Most non-neutral variation consists of deleterious alleles segregating at low population frequency due to incessant mutation. To date, studies characterizing selection against deleterious alleles have been based on allele frequency (testing for a relative excess of rare alleles) or ratio of polymorphism to divergence (testing for a relative increase in the number of polymorphic alleles). Here, starting from Maruyama's theoretical prediction (Maruyama T (1974), Am J Hum Genet USA 6:669–673) that a (slightly) deleterious allele is, on average, younger than a neutral allele segregating at the same frequency, we devised an approach to characterize selection based on allelic age. Unlike existing methods, it compares sets of neutral and deleterious sequence variants at the same allele frequency. When applied to human sequence data from the Genome of the Netherlands Project, our approach distinguishes low-frequency coding non-synonymous variants from synonymous and non-coding variants at the same allele frequency and discriminates between sets of variants independently predicted to be benign or damaging for protein structure and function. The results confirm the abundance of slightly deleterious coding variation in humans.

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Biology, Genetics, Population Genetics, Genetic Drift, Genetic Polymorphism, Mutation, Natural Selection, Genomics, Genome Evolution

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