Estimating the effective population size (Ne) in ectomycorrhizal fungi from genetic data | Estimation de la taille efficace (Ne) chez les champignons ectomycorhiziens à partir de données génétiques
2024
Champion, Anouck | Biodiversité, Gènes & Communautés (BioGeCo) ; Université de Bordeaux (UB)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE) | Labex CEBA | Université de Bordeaux | Myriam Heuertz | Roberta Gargiulo | ANR-10-LABX-0025,CEBA,CEnter of the study of Biodiversity in Amazonia(2010)
Master
Mostrar más [+] Menos [-]Inglés. Genetic diversity is the basis for evolutionary change, and high genetic diversity confers greater adaptive capacity and long-term survival to populations. However, the genetic diversity of many species is under severe threat due to human activities, particularly through the destruction and fragmentation of natural habitats. The 2022 Kunming-Montreal Global Biodiversity Framework includes a genetic indicator based on effective population size, Ne, to assess the genetic conservation status in all species. Although this indicator can be computed from genetic or proxy data, uncertainties remain regarding best practices for Ne estimation in species with complex life history traits (e.g., clonality, long lifespan) such as ectomycorrhizal fungi. The aim of this internship was to understand the factors influencing Ne estimation in ectomycorrhizal fungi, and to obtain reference Ne estimates in these organisms using genetic data extracted from the literature. The effects of haploidy and clonality on Ne estimation were assessed, as well as the influence of population genetic structure when estimating Ne. Biases associated with sampling design were also investigated, particularly in terms of missing data, sample size, number of molecular markers and their non-independence (i.e. pseudo-replication). Through the analysis of four datasets covering the genera Boletus, Suillus and Tuber, several biases were identified which allows to propose several recommendations for an unbiased estimation of Ne in ectomycorrhizal fungi using the software programme NeEstimator. While no clear recommendation can be made for the analyse of haploid data, working at the level of homogeneous populations as well as removing clones from the datasets help limit downward biases. It is also shown that using small subsets of SNPs prevents biases related to pseudoreplication when estimating Ne. The estimates obtained here will need to be developed further in order to use effective population size as an indicator of genetic diversity in ectomycorrhizal fungi.
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