Genetic Relatedness and Parentage Analysis as a Framework to Enhance Local Conservation Strategies for Marine Species

International audience ; Conservation of marine species faces specific challenges, especially considering the environmental factors and cryptic behaviors that affect organismal dispersal. In the context of conservation genetics, microsatellite markers have been successfully applied in population genetics to assess genetic differentiation and delineate population clusters, helping to identify broader scale conservation needs. Here, we tested the relevance of using microsatellite markers to perform parentage analysis with very little information on a marine sessile organism to inform spatial conservation efforts. Specifically, we investigated the genetic structure of Atrina vexillum, a large marine bivalve, sampled in the lagoon of Bora-Bora. Our primary objective was to sample a significant portion of the population with a stratified underwater survey, which led to the sampling of 1389 individuals, estimated to represent ~80% of the total population. We then screened 30 microsatellite loci to compute a relatedness matrix and assess genetic relationships among individuals. Based on pairwise relatedness values, we computed a UPGMA hierarchical clustering to construct family groups and compared the results with a maximum-likelihood-based parentage analysis implemented in COLONY. In parallel, we also looked for genetic structure using Bayesian clustering with STRUCTURE. We then investigated spatial patterns of genetic relatedness, testing correlations with geographic distances. The distribution of relatedness values indicated a relatively even contribution to reproduction among sampled individuals. Although no population structure was detected using the Bayesian clustering algorithm, we identified multiple family groups, some comprising up to 19 individuals. Spatial analyses showed no significant correlation between genetic relatedness and proximity, except among closely related individuals, who tended to be found in close proximity. Our findings highlight the value of the relatedness-based approach to identify ...