Estimates of Genetic Differentiation Measured by FST Do Not Necessarily Require Large Sample Sizes When Using Many SNP Markers
Population genetic studies provide insights into the evolutionary processes that influence the distribution of sequence variants within and among wild populations. FST is among the most widely used measures for genetic differentiation and plays a central role in ecological and evolutionary genetic s...
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description | Population genetic studies provide insights into the evolutionary processes that influence the distribution of sequence variants within and among wild populations. FST is among the most widely used measures for genetic differentiation and plays a central role in ecological and evolutionary genetic studies. It is commonly thought that large sample sizes are required in order to precisely infer FST and that small sample sizes lead to overestimation of genetic differentiation. Until recently, studies in ecological model organisms incorporated a limited number of genetic markers, but since the emergence of next generation sequencing, the panel size of genetic markers available even in non-reference organisms has rapidly increased. In this study we examine whether a large number of genetic markers can substitute for small sample sizes when estimating FST. We tested the behavior of three different estimators that infer FST and that are commonly used in population genetic studies. By simulating populations, we assessed the effects of sample size and the number of markers on the various estimates of genetic differentiation. Furthermore, we tested the effect of ascertainment bias on these estimates. We show that the population sample size can be significantly reduced (as small as n = 4–6) when using an appropriate estimator and a large number of bi-allelic genetic markers (k>1,000). Therefore, conservation genetic studies can now obtain almost the same statistical power as studies performed on model organisms using markers developed with next-generation sequencing. |
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FST is among the most widely used measures for genetic differentiation and plays a central role in ecological and evolutionary genetic studies. It is commonly thought that large sample sizes are required in order to precisely infer FST and that small sample sizes lead to overestimation of genetic differentiation. Until recently, studies in ecological model organisms incorporated a limited number of genetic markers, but since the emergence of next generation sequencing, the panel size of genetic markers available even in non-reference organisms has rapidly increased. In this study we examine whether a large number of genetic markers can substitute for small sample sizes when estimating FST. We tested the behavior of three different estimators that infer FST and that are commonly used in population genetic studies. By simulating populations, we assessed the effects of sample size and the number of markers on the various estimates of genetic differentiation. Furthermore, we tested the effect of ascertainment bias on these estimates. We show that the population sample size can be significantly reduced (as small as n = 4–6) when using an appropriate estimator and a large number of bi-allelic genetic markers (k>1,000). Therefore, conservation genetic studies can now obtain almost the same statistical power as studies performed on model organisms using markers developed with next-generation sequencing.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0042649</identifier><identifier>PMID: 22905157</identifier><language>eng</language><publisher>San Francisco: Public Library of Science</publisher><subject>Animal populations ; Bias ; Binomial distribution ; Biological evolution ; Biology ; Computer simulation ; Conservation ; Datasets ; Developmental biology ; Differentiation ; Ecological models ; Ecological monitoring ; Ecology ; Estimates ; Evolution ; Expected values ; Fish ; Gene sequencing ; Genetic markers ; Genetics ; Genomes ; Markers ; Molecular biology ; Organisms ; Population (statistical) ; Population genetics ; Population studies ; Single-nucleotide polymorphism</subject><ispartof>PloS one, 2012-08, Vol.7 (8), p.e42649</ispartof><rights>Willing et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License: https://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2012 Willing et al 2012 Willing et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c404t-11c88b38f756b91f379cc7273f297353cb9781c1072ecb0e52a4d9b8a24cdbc3</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3419229/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3419229/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2915,23845,27901,27902,53766,53768,79342,79343</link.rule.ids></links><search><creatorcontrib>Willing, Eva-Maria</creatorcontrib><creatorcontrib>Dreyer, Christine</creatorcontrib><creatorcontrib>van Oosterhout, Cock</creatorcontrib><title>Estimates of Genetic Differentiation Measured by FST Do Not Necessarily Require Large Sample Sizes When Using Many SNP Markers</title><title>PloS one</title><description>Population genetic studies provide insights into the evolutionary processes that influence the distribution of sequence variants within and among wild populations. FST is among the most widely used measures for genetic differentiation and plays a central role in ecological and evolutionary genetic studies. It is commonly thought that large sample sizes are required in order to precisely infer FST and that small sample sizes lead to overestimation of genetic differentiation. Until recently, studies in ecological model organisms incorporated a limited number of genetic markers, but since the emergence of next generation sequencing, the panel size of genetic markers available even in non-reference organisms has rapidly increased. In this study we examine whether a large number of genetic markers can substitute for small sample sizes when estimating FST. We tested the behavior of three different estimators that infer FST and that are commonly used in population genetic studies. By simulating populations, we assessed the effects of sample size and the number of markers on the various estimates of genetic differentiation. Furthermore, we tested the effect of ascertainment bias on these estimates. We show that the population sample size can be significantly reduced (as small as n = 4–6) when using an appropriate estimator and a large number of bi-allelic genetic markers (k>1,000). Therefore, conservation genetic studies can now obtain almost the same statistical power as studies performed on model organisms using markers developed with next-generation sequencing.</description><subject>Animal populations</subject><subject>Bias</subject><subject>Binomial distribution</subject><subject>Biological evolution</subject><subject>Biology</subject><subject>Computer simulation</subject><subject>Conservation</subject><subject>Datasets</subject><subject>Developmental biology</subject><subject>Differentiation</subject><subject>Ecological models</subject><subject>Ecological monitoring</subject><subject>Ecology</subject><subject>Estimates</subject><subject>Evolution</subject><subject>Expected values</subject><subject>Fish</subject><subject>Gene sequencing</subject><subject>Genetic markers</subject><subject>Genetics</subject><subject>Genomes</subject><subject>Markers</subject><subject>Molecular biology</subject><subject>Organisms</subject><subject>Population 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Oosterhout, Cock</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Estimates of Genetic Differentiation Measured by FST Do Not Necessarily Require Large Sample Sizes When Using Many SNP Markers</atitle><jtitle>PloS one</jtitle><date>2012-08-14</date><risdate>2012</risdate><volume>7</volume><issue>8</issue><spage>e42649</spage><pages>e42649-</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Population genetic studies provide insights into the evolutionary processes that influence the distribution of sequence variants within and among wild populations. FST is among the most widely used measures for genetic differentiation and plays a central role in ecological and evolutionary genetic studies. It is commonly thought that large sample sizes are required in order to precisely infer FST and that small sample sizes lead to overestimation of genetic differentiation. Until recently, studies in ecological model organisms incorporated a limited number of genetic markers, but since the emergence of next generation sequencing, the panel size of genetic markers available even in non-reference organisms has rapidly increased. In this study we examine whether a large number of genetic markers can substitute for small sample sizes when estimating FST. We tested the behavior of three different estimators that infer FST and that are commonly used in population genetic studies. By simulating populations, we assessed the effects of sample size and the number of markers on the various estimates of genetic differentiation. Furthermore, we tested the effect of ascertainment bias on these estimates. We show that the population sample size can be significantly reduced (as small as n = 4–6) when using an appropriate estimator and a large number of bi-allelic genetic markers (k>1,000). Therefore, conservation genetic studies can now obtain almost the same statistical power as studies performed on model organisms using markers developed with next-generation sequencing.</abstract><cop>San Francisco</cop><pub>Public Library of Science</pub><pmid>22905157</pmid><doi>10.1371/journal.pone.0042649</doi><oa>free_for_read</oa></addata></record> |
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subjects | Animal populations Bias Binomial distribution Biological evolution Biology Computer simulation Conservation Datasets Developmental biology Differentiation Ecological models Ecological monitoring Ecology Estimates Evolution Expected values Fish Gene sequencing Genetic markers Genetics Genomes Markers Molecular biology Organisms Population (statistical) Population genetics Population studies Single-nucleotide polymorphism |
title | Estimates of Genetic Differentiation Measured by FST Do Not Necessarily Require Large Sample Sizes When Using Many SNP Markers |
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