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      The Impact of Population Demography and Selection on the Genetic Architecture of Complex Traits

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      PLoS Genetics
      Public Library of Science

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          Abstract

          Population genetic studies have found evidence for dramatic population growth in recent human history. It is unclear how this recent population growth, combined with the effects of negative natural selection, has affected patterns of deleterious variation, as well as the number, frequency, and effect sizes of mutations that contribute risk to complex traits. Because researchers are performing exome sequencing studies aimed at uncovering the role of low-frequency variants in the risk of complex traits, this topic is of critical importance. Here I use simulations under population genetic models where a proportion of the heritability of the trait is accounted for by mutations in a subset of the exome. I show that recent population growth increases the proportion of nonsynonymous variants segregating in the population, but does not affect the genetic load relative to a population that did not expand. Under a model where a mutation's effect on a trait is correlated with its effect on fitness, rare variants explain a greater portion of the additive genetic variance of the trait in a population that has recently expanded than in a population that did not recently expand. Further, when using a single-marker test, for a given false-positive rate and sample size, recent population growth decreases the expected number of significant associations with the trait relative to the number detected in a population that did not expand. However, in a model where there is no correlation between a mutation's effect on fitness and the effect on the trait, common variants account for much of the additive genetic variance, regardless of demography. Moreover, here demography does not affect the number of significant associations detected. These findings suggest recent population history may be an important factor influencing the power of association tests and in accounting for the missing heritability of certain complex traits.

          Author Summary

          Many human populations have dramatically expanded over the last several thousand years. I use population genetic models to investigate how recent population expansions affect patterns of mutations that reduce reproductive fitness and contribute to the genetic basis of complex traits (including common disease). I show that recent population growth increases the proportion of mutations found in the population that reduce fitness. When mutations that have the greatest effect on reproductive fitness also have the greatest effect on a complex trait, more of the heritability of the trait is due to mutations at very low-frequency in populations that have recently expanded, as compared to populations that have not. Also, under this model, for a given sample size and false-positive rate, fewer variants show statistically significant associations with the trait in the population that has expanded than in one that has not. Both of these findings suggest that recent population growth may make it more difficult to fully elucidate the genetic basis of complex traits that are directly or indirectly correlated with reproductive fitness.

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          Most cited references63

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          Rare and common variants: twenty arguments.

          Genome-wide association studies have greatly improved our understanding of the genetic basis of disease risk. The fact that they tend not to identify more than a fraction of the specific causal loci has led to divergence of opinion over whether most of the variance is hidden as numerous rare variants of large effect or as common variants of very small effect. Here I review 20 arguments for and against each of these models of the genetic basis of complex traits and conclude that both classes of effect can be readily reconciled.
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            Linkage disequilibrium in the human genome.

            With the availability of a dense genome-wide map of single nucleotide polymorphisms (SNPs), a central issue in human genetics is whether it is now possible to use linkage disequilibrium (LD) to map genes that cause disease. LD refers to correlations among neighbouring alleles, reflecting 'haplotypes' descended from single, ancestral chromosomes. The size of LD blocks has been the subject of considerable debate. Computer simulations and empirical data have suggested that LD extends only a few kilobases (kb) around common SNPs, whereas other data have suggested that it can extend much further, in some cases greater than 100 kb. It has been difficult to obtain a systematic picture of LD because past studies have been based on only a few (1-3) loci and different populations. Here, we report a large-scale experiment using a uniform protocol to examine 19 randomly selected genomic regions. LD in a United States population of north-European descent typically extends 60 kb from common alleles, implying that LD mapping is likely to be practical in this population. By contrast, LD in a Nigerian population extends markedly less far. The results illuminate human history, suggesting that LD in northern Europeans is shaped by a marked demographic event about 27,000-53,000 years ago.
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              Linkage disequilibrium in humans: models and data.

              In this review, we describe recent empirical and theoretical work on the extent of linkage disequilibrium (LD) in the human genome, comparing the predictions of simple population-genetic models to available data. Several studies report significant LD over distances longer than those predicted by standard models, whereas some data from short, intergenic regions show less LD than would be expected. The apparent discrepancies between theory and data present a challenge-both to modelers and to human geneticists-to identify which important features are missing from our understanding of the biological processes that give rise to LD. Salient features may include demographic complications such as recent admixture, as well as genetic factors such as local variation in recombination rates, gene conversion, and the potential segregation of inversions. We also outline some implications that the emerging patterns of LD have for association-mapping strategies. In particular, we discuss what marker densities might be necessary for genomewide association scans.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS Genet
                PLoS Genet
                plos
                plosgen
                PLoS Genetics
                Public Library of Science (San Francisco, USA )
                1553-7390
                1553-7404
                May 2014
                29 May 2014
                : 10
                : 5
                : e1004379
                Affiliations
                [1]Department of Ecology and Evolutionary Biology, Interdepartmental Program in Bioinformatics, University of California, Los Angeles, California, United States of America
                Dartmouth College, United States of America
                Author notes

                The author has declared that no competing interests exist.

                Conceived and designed the experiments: KEL. Performed the experiments: KEL. Analyzed the data: KEL. Contributed reagents/materials/analysis tools: KEL. Wrote the paper: KEL.

                Article
                PGENETICS-D-13-01679
                10.1371/journal.pgen.1004379
                4038606
                24875776
                9cea4048-b9c2-4032-91b1-dea0b2d16f63
                Copyright @ 2014

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 21 June 2013
                : 28 March 2014
                Page count
                Pages: 16
                Funding
                This work was supported by funds from the Miller Institute for Basic Research at UC Berkeley and startup funds from UCLA. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Computational Biology
                Genome Analysis
                Genome-Wide Association Studies
                Ecology
                Ecological Metrics
                Population Size
                Effective Population Size
                Evolutionary Biology
                Evolutionary Processes
                Genetic Drift
                Natural Selection
                Population Genetics
                Genetic Polymorphism
                Neutral Theory
                Genetics
                Human Genetics
                Genetic Association Studies
                Genetics of Disease
                Genomics
                Mutation
                Molecular Biology
                Molecular Biology Techniques
                Sequencing Techniques
                Genome Sequencing

                Genetics
                Genetics

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