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Nat Rev Genet. 2015 Jun;16(6):333-43. doi: 10.1038/nrg3931. Epub 2015 May 12.

Estimating the mutation load in human genomes.

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Department of Ecology and Evolution, Stony Brook University, 650 Life Sciences Building, Stony Brook, New York 11794-5245, USA.
Stanford University School of Medicine, Department of Genetics, 291 Campus Drive, Stanford, California 94305, USA.
Cornell University, Department of Molecular Biology and Genetics, 526 Campus Road, Ithaca, New York 14853-2703, USA.
McGill University, Department of Human Genetics and Genome Quebec Innovation Centre, 740 Dr Penfield Avenue, Montreal, Quebec H3A 0G1, Canada.


Next-generation sequencing technology has facilitated the discovery of millions of genetic variants in human genomes. A sizeable fraction of these variants are predicted to be deleterious. Here, we review the pattern of deleterious alleles as ascertained in genome sequencing data sets and ask whether human populations differ in their predicted burden of deleterious alleles - a phenomenon known as mutation load. We discuss three demographic models that are predicted to affect mutation load and relate these models to the evidence (or the lack thereof) for variation in the efficacy of purifying selection in diverse human genomes. We also emphasize why accurate estimation of mutation load depends on assumptions regarding the distribution of dominance and selection coefficients - quantities that remain poorly characterized for current genomic data sets.

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