Literature DB >> 25461617

The distribution of deleterious genetic variation in human populations.

Kirk E Lohmueller.   

Abstract

Population genetic studies suggest that most amino-acid changing mutations are deleterious. Such mutations are of tremendous interest in human population genetics as they are important for the evolutionary process and may contribute risk to common disease. Genomic studies over the past 5 years have documented differences across populations in the number of heterozygous deleterious genotypes, number of homozygous derived deleterious genotypes, number of deleterious segregating sites and proportion of sites that are potentially deleterious. These differences have been attributed to population history affecting the ability of natural selection to remove deleterious variants from the population. However, recent studies have suggested that the genetic load is the same across populations and that the efficacy of natural selection has not differed across human populations. Here I show that these observations are not incompatible with each other and that the apparent differences are due to examining different features of the genetic data and differing definitions of terms.

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Year:  2014        PMID: 25461617     DOI: 10.1016/j.gde.2014.09.005

Source DB:  PubMed          Journal:  Curr Opin Genet Dev        ISSN: 0959-437X            Impact factor:   5.578


  55 in total

1.  Bottlenecks and selective sweeps during domestication have increased deleterious genetic variation in dogs.

Authors:  Clare D Marsden; Diego Ortega-Del Vecchyo; Dennis P O'Brien; Jeremy F Taylor; Oscar Ramirez; Carles Vilà; Tomas Marques-Bonet; Robert D Schnabel; Robert K Wayne; Kirk E Lohmueller
Journal:  Proc Natl Acad Sci U S A       Date:  2015-12-22       Impact factor: 11.205

2.  Patterns of deleterious variation between human populations reveal an unbalanced load.

Authors:  Rajiv C McCoy; Joshua M Akey
Journal:  Proc Natl Acad Sci U S A       Date:  2016-01-19       Impact factor: 11.205

3.  The Effect of an Extreme and Prolonged Population Bottleneck on Patterns of Deleterious Variation: Insights from the Greenlandic Inuit.

Authors:  Casper-Emil T Pedersen; Kirk E Lohmueller; Niels Grarup; Peter Bjerregaard; Torben Hansen; Hans R Siegismund; Ida Moltke; Anders Albrechtsen
Journal:  Genetics       Date:  2016-11-30       Impact factor: 4.562

4.  Characteristics of neutral and deleterious protein-coding variation among individuals and populations.

Authors:  Wenqing Fu; Rachel M Gittelman; Michael J Bamshad; Joshua M Akey
Journal:  Am J Hum Genet       Date:  2014-10-02       Impact factor: 11.025

5.  When Is Selection Effective?

Authors:  Simon Gravel
Journal:  Genetics       Date:  2016-03-23       Impact factor: 4.562

Review 6.  The impact of recent population history on the deleterious mutation load in humans and close evolutionary relatives.

Authors:  Yuval B Simons; Guy Sella
Journal:  Curr Opin Genet Dev       Date:  2016-10-13       Impact factor: 5.578

Review 7.  Evolutionary perspectives on polygenic selection, missing heritability, and GWAS.

Authors:  Lawrence H Uricchio
Journal:  Hum Genet       Date:  2019-06-14       Impact factor: 4.132

8.  Relationship between Deleterious Variation, Genomic Autozygosity, and Disease Risk: Insights from The 1000 Genomes Project.

Authors:  Trevor J Pemberton; Zachary A Szpiech
Journal:  Am J Hum Genet       Date:  2018-03-15       Impact factor: 11.025

9.  Distance from sub-Saharan Africa predicts mutational load in diverse human genomes.

Authors:  Brenna M Henn; Laura R Botigué; Stephan Peischl; Isabelle Dupanloup; Mikhail Lipatov; Brian K Maples; Alicia R Martin; Shaila Musharoff; Howard Cann; Michael P Snyder; Laurent Excoffier; Jeffrey M Kidd; Carlos D Bustamante
Journal:  Proc Natl Acad Sci U S A       Date:  2015-12-28       Impact factor: 11.205

Review 10.  Genetics of Type 2 Diabetes: the Power of Isolated Populations.

Authors:  Mette Korre Andersen; Casper-Emil Tingskov Pedersen; Ida Moltke; Torben Hansen; Anders Albrechtsen; Niels Grarup
Journal:  Curr Diab Rep       Date:  2016-07       Impact factor: 4.810

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