Abstract
The optimization of aquaculture production requires the selection of efficient strains. Thus, genetic improvement has become one of the important levers to boost the development of aquaculture. The objective of this study was to carry out genetic characterization of Nile tilapia Oreochromis niloticus, one of the most cultivated fish species in Senegal, in order to select an efficient strain to optimize local fish production. Thus, fish from five different populations (Richard-Toll, ANA, ITACA, Mbodiene and Sauvage) were analyzed, with 15 individuals per population. Genetic diversity and population structure were assessed using molecular genetic analyses by sequence characterized amplified region (SCAR) and microsatellite (SSR) markers. The analyses of the SCARII marker were conducted on four populations (ANA, ITACA, Sauvage and Mbodiene) while microsatellite analyses were conducted on all five populations. The results show high levels of polymorphism of SSR markers, and a high level of observed heterozygosity (Ho), indicating a high within-population genetic variability. These results are in agreement with the AMOVA results, which indicated a high within-population genetic variability (94%). The genetic structure analysis by DAPC indicates that the five populations analyzed are structured into four groups, which are highly heterogeneous because they share common allele individuals. The analysis of the genetic structure by AMOVA showed a low degree of differentiation between the populations (6%), in agreement with the genetic differentiation index (Fst = 0.059). The heterogeneity of studied populations implies a genetic flow over time, which may have existed between the original populations. The overall negative Tajima D values and low genetic differentiation indicate an excess of rare mutations in the populations studied, resulting from a recent population expansion from a limited number of initial breeders isolated in locale hatcheries. Thus, further studies with a much larger panel of markers are required to better differentiate the strains and identify the most efficient ones for sustainable local aquaculture production.
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