Estimating effective population size using RADseq: Effects of SNP selection and sample size

Type Article
Date 2020-02
Language English
Author(s) Marandel FlorianneORCID1, Charrier Gregory2, Lamy Jean-BaptisteORCID3, Le Cam Sabrina2, 3, Lorance PascalORCID1, Trenkel VerenaORCID1
Affiliation(s) 1 : Ifremer ,Ecologie et Modèles pour l’Halieutique Nantes ,France
2 : Laboratoire des Sciences de l’Environnement Marin (LEMAR, UMR 6539 CNRS/IRD/UBO/Ifremer) Université de Bretagne OccidentaleInstitut Universitaire Européen de la Mer Plouzané ,France
3 : Ifremer, Génétique et Pathologie des Mollusques Marin (SG2M‐LGPMM) La Tremblade, France
4 : Laboratoire des Sciences de l’Environnement Marin (LEMAR, UMR 6539 CNRS/IRD/UBO/Ifremer) Université de Bretagne OccidentaleInstitut Universitaire Européen de la Mer Plouzané ,France
Source Ecology And Evolution (2045-7758) (Wiley), 2020-02 , Vol. 10 , N. 4 , P. 1929-1937
DOI 10.1002/ece3.6016
WOS© Times Cited 32
Keyword(s) effective population size, linkage disequilibrium, NeEstimator, RADseq, skates and rays
Abstract

Effective population size (Ne) is a key parameter of population genetics. However, Ne remains challenging to estimate for natural populations as several factors are likely to bias estimates. These factors include sampling design, sequencing method, and data filtering. One issue inherent to the restriction site‐associated DNA sequencing (RADseq) protocol is missing data and SNP selection criteria (e.g., minimum minor allele frequency, number of SNPs). To evaluate the potential impact of SNP selection criteria on Ne estimates (Linkage Disequilibrium method) we used RADseq data for a nonmodel species, the thornback ray. In this data set, the inbreeding coefficient FIS was positively correlated with the amount of missing data, implying data were missing nonrandomly. The precision of Neestimates decreased with the number of SNPs. Mean Ne estimates (averaged across 50 random data sets with2000 SNPs) ranged between 237 and 1784. Increasing the percentage of missing data from 25% to 50% increased Ne estimates between 82% and 120%, while increasing the minor allele frequency (MAF) threshold from 0.01 to 0.1 decreased estimates between 71% and 75%. Considering these effects is important when interpreting RADseq data‐derived estimates of effective population size in empirical studies.

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Marandel Florianne, Charrier Gregory, Lamy Jean-Baptiste, Le Cam Sabrina, Lorance Pascal, Trenkel Verena (2020). Estimating effective population size using RADseq: Effects of SNP selection and sample size. Ecology And Evolution, 10(4), 1929-1937. Publisher's official version : https://doi.org/10.1002/ece3.6016 , Open Access version : https://archimer.ifremer.fr/doc/00607/71934/