Use of microsatellites and a combinatorial optimization approach in the acquisition of gilthead seabream ( Sparus aurata L.) broodstocks for hatcheries

Abstract

The acquisition of a stock should be considered the single most important aspect of broodstock management because it determines the maximum amount of genetic variance and how much inbreeding will be produced via future matings. Using a set of eleven microsatellite markers, we have screened two samples from a captive sea bream population ( Sparus aurata) ( n = 661) from which three hatchery broodstocks will be established. We have estimated the relatedness coefficients between all the possible candidates to form those new broodstocks (− 0.3803 < r < + 0.8450) and finally we have used a stochastic search technique to solve, using a combinatorial optimization approach, the problem of ensuring that the three new broodstocks will contain the maximum possible genetic variance. The two starting samples revealed high levels of genetic variation ( H e ≈ 0.800 and N A > 17) and the microsatellite loci showed high PIC values (over 0.700). The searching method was not only appropriate but also very efficient. All three new broodstocks (60 individuals each) keep almost all the genetic variance previously assessed. Means of 17 alleles per locus, values of 0.80 as expected heterozygosities and, in addition, higher PIC values (0.84 as a mean) in these groups with respect to the original samples ensuring long term genetic response if necessary and guarantees a minimal inbreeding risk under our culture conditions since we have limited the relatedness distributions to − 0.3416 < r < + 0.1604.