Estimation of contemporary effective population size in plant populations: limitations of genomic datasets
Gargiulo, Roberta | Decroocq, Véronique | González-Martínez, Santiago | Paz-Vinas, Ivan | Aury, Jean‐marc | Lesur Kupin, Isabelle | Plomion, Christophe | Schmitt, Sylvain | Scotti, Ivan | Heuertz, Myriam | Royal Botanic Gardens [Kew] | Biologie du fruit et pathologie (BFP) ; Université de Bordeaux (UB)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE) | Biodiversité, Gènes & Communautés (BioGeCo) ; Université de Bordeaux (UB)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE) | Colorado State University [Pueblo] (CSUPueblo) | Institut de Biologie François JACOB (JACOB) ; Direction de Recherche Fondamentale (CEA) (DRF (CEA)) ; Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA) | Botanique et Modélisation de l'Architecture des Plantes et des Végétations (UMR AMAP) ; Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [Occitanie])-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université de Montpellier (UM) | Ecologie des Forêts Méditerranéennes (URFM) ; Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
International audience
Показать больше [+] Меньше [-]Английский. Effective population size ( N e ) is a pivotal evolutionary parameter with crucial implications in conservation practice and policy. Genetic methods to estimate N e have been preferred over demographic methods because they rely on genetic data rather than time-consuming ecological monitoring. Methods based on linkage disequilibrium, in particular, have become popular in conservation as they require a single sampling and provide estimates that refer to recent generations. A recently developed software based on linkage disequilibrium, GONE, looks particularly promising to estimate contemporary and recent-historical N e (up to 200 generations in the past). Genomic datasets from non-model species, especially plants, may present some constraints to the use of GONE, as linkage maps and reference genomes are seldom available, and SNPs genotyping is usually based on reduced-representation methods. In this study, we use empirical datasets from four plant species to explore the limitations of plant genomic datasets when estimating N e using the algorithm implemented in GONE, in addition to exploring some typical biological limitations that may affect N e estimation using the linkage disequilibrium method, such as the occurrence of population structure. We show how accuracy and precision of N e estimates potentially change with the following factors: occurrence of missing data, limited number of SNPs/individuals sampled, and lack of information about the location of SNPs on chromosomes, with the latter producing a significant bias, previously unexplored with empirical data.
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