Literature DB >> 26836758

The genetic consequences of selection in natural populations.

Timothy J Thurman1,2, Rowan D H Barrett1.   

Abstract

The selection coefficient, s, quantifies the strength of selection acting on a genetic variant. Despite this parameter's central importance to population genetic models, until recently we have known relatively little about the value of s in natural populations. With the development of molecular genetic techniques in the late 20th century and the sequencing technologies that followed, biologists are now able to identify genetic variants and directly relate them to organismal fitness. We reviewed the literature for published estimates of natural selection acting at the genetic level and found over 3000 estimates of selection coefficients from 79 studies. Selection coefficients were roughly exponentially distributed, suggesting that the impact of selection at the genetic level is generally weak but can occasionally be quite strong. We used both nonparametric statistics and formal random-effects meta-analysis to determine how selection varies across biological and methodological categories. Selection was stronger when measured over shorter timescales, with the mean magnitude of s greatest for studies that measured selection within a single generation. Our analyses found conflicting trends when considering how selection varies with the genetic scale (e.g., SNPs or haplotypes) at which it is measured, suggesting a need for further research. Besides these quantitative conclusions, we highlight key issues in the calculation, interpretation, and reporting of selection coefficients and provide recommendations for future research.
© 2016 John Wiley & Sons Ltd.

Entities:  

Keywords:  evolution; genetics; meta-analysis; natural populations; natural selection; selection coefficient

Mesh:

Year:  2016        PMID: 26836758     DOI: 10.1111/mec.13559

Source DB:  PubMed          Journal:  Mol Ecol        ISSN: 0962-1083            Impact factor:   6.185


  14 in total

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2.  Seasonally fluctuating selection can maintain polymorphism at many loci via segregation lift.

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Journal:  Nat Ecol Evol       Date:  2020-06-22       Impact factor: 15.460

4.  Evolution of resistance under alternative models of selective interference.

Authors:  Philip G Madgwick; Ricardo Kanitz
Journal:  J Evol Biol       Date:  2021-09-25       Impact factor: 2.516

5.  Fitness maps to a large-effect locus in introduced stickleback populations.

Authors:  Dolph Schluter; Kerry B Marchinko; Matthew E Arnegard; Haili Zhang; Shannon D Brady; Felicity C Jones; Michael A Bell; David M Kingsley
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6.  Genome scans for divergent selection in natural populations of the widespread hardwood species Eucalyptus grandis (Myrtaceae) using microsatellites.

Authors:  Zhijiao Song; Miaomiao Zhang; Fagen Li; Qijie Weng; Chanpin Zhou; Mei Li; Jie Li; Huanhua Huang; Xiaoyong Mo; Siming Gan
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Review 7.  Detecting positive selection in the genome.

Authors:  Tom R Booker; Benjamin C Jackson; Peter D Keightley
Journal:  BMC Biol       Date:  2017-10-30       Impact factor: 7.431

8.  How diverse can rare species be on the margins of genera distribution?

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9.  Predicting future from past: The genomic basis of recurrent and rapid stickleback evolution.

Authors:  Garrett A Roberts Kingman; Deven N Vyas; Felicity C Jones; Shannon D Brady; Heidi I Chen; Kerry Reid; Mark Milhaven; Thomas S Bertino; Windsor E Aguirre; David C Heins; Frank A von Hippel; Peter J Park; Melanie Kirch; Devin M Absher; Richard M Myers; Federica Di Palma; Michael A Bell; David M Kingsley; Krishna R Veeramah
Journal:  Sci Adv       Date:  2021-06-18       Impact factor: 14.136

10.  Integrating viability and fecundity selection to illuminate the adaptive nature of genetic clines.

Authors:  Susana M Wadgymar; S Caroline Daws; Jill T Anderson
Journal:  Evol Lett       Date:  2017-05-03
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