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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