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Estimates of Genetic Differentiation Measured by F(ST) 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. F(ST) is among the most widely used measures for genetic differentiation and plays a central role in ecological and evolutionary genetic...

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Detalles Bibliográficos
Autores principales: Willing, Eva-Maria, Dreyer, Christine, van Oosterhout, Cock
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3419229/
https://www.ncbi.nlm.nih.gov/pubmed/22905157
http://dx.doi.org/10.1371/journal.pone.0042649
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author Willing, Eva-Maria
Dreyer, Christine
van Oosterhout, Cock
author_facet Willing, Eva-Maria
Dreyer, Christine
van Oosterhout, Cock
author_sort Willing, Eva-Maria
collection PubMed
description Population genetic studies provide insights into the evolutionary processes that influence the distribution of sequence variants within and among wild populations. F(ST) 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 F(ST) 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 F(ST). We tested the behavior of three different estimators that infer F(ST) 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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spelling pubmed-34192292012-08-19 Estimates of Genetic Differentiation Measured by F(ST) Do Not Necessarily Require Large Sample Sizes When Using Many SNP Markers Willing, Eva-Maria Dreyer, Christine van Oosterhout, Cock PLoS One Research Article Population genetic studies provide insights into the evolutionary processes that influence the distribution of sequence variants within and among wild populations. F(ST) 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 F(ST) 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 F(ST). We tested the behavior of three different estimators that infer F(ST) 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. Public Library of Science 2012-08-14 /pmc/articles/PMC3419229/ /pubmed/22905157 http://dx.doi.org/10.1371/journal.pone.0042649 Text en © 2012 Willing et al http://creativecommons.org/licenses/by/4.0/ 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 properly credited.
spellingShingle Research Article
Willing, Eva-Maria
Dreyer, Christine
van Oosterhout, Cock
Estimates of Genetic Differentiation Measured by F(ST) Do Not Necessarily Require Large Sample Sizes When Using Many SNP Markers
title Estimates of Genetic Differentiation Measured by F(ST) Do Not Necessarily Require Large Sample Sizes When Using Many SNP Markers
title_full Estimates of Genetic Differentiation Measured by F(ST) Do Not Necessarily Require Large Sample Sizes When Using Many SNP Markers
title_fullStr Estimates of Genetic Differentiation Measured by F(ST) Do Not Necessarily Require Large Sample Sizes When Using Many SNP Markers
title_full_unstemmed Estimates of Genetic Differentiation Measured by F(ST) Do Not Necessarily Require Large Sample Sizes When Using Many SNP Markers
title_short Estimates of Genetic Differentiation Measured by F(ST) Do Not Necessarily Require Large Sample Sizes When Using Many SNP Markers
title_sort estimates of genetic differentiation measured by f(st) do not necessarily require large sample sizes when using many snp markers
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3419229/
https://www.ncbi.nlm.nih.gov/pubmed/22905157
http://dx.doi.org/10.1371/journal.pone.0042649
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