Gilthead sea bream (Sparus aurata L.) is one of the most important species in the Mediterranean aquaculture. In the last quinquennium, implementation of genetic improvement programs has drawn the attention of gilthead sea bream producers to maintain a sustained growth in a competitive way. Although the organization of the industrial production based on genetic criteria increases the production costs, and at the beginning shows low genetic progress rate in short term, the genetic improvements provide a tool for a continuous, cumulative and permanent growth in the industry. Thus, the main objective of the current study was to determine the additive genetic variability for biological traits (growth and carcass) in a F2 generation of PROGENSA II project (National project in Spain; Improving the competitiveness of the sector of the gilthead sea bream through genetic selection). The data provided represent an important source of information for the design and establishment of genetic breeding programs in this species.
In order to study the existence of additive genetic variability, between carcass traits and their estimated counterparts by engineering technologies or technological traits, progenies obtained from the selected bloodstocks in two research centers (PCTM –ULPGC; Canary Island, and IFAPA; Andalusia, Spain), belonging to the second generation of the genetic improvement program PROGENSA II, were tagged by Passive Integrated Transponder (PIT), and mixed at the two research centers and two Spanish companies (ADSA; Canary Island and PIMSA; Andalusia, Spain). At harvest size, fish were sampled for growth, carcass, and technological traits, these last by IMAFISH software. Pieces of caudal fin were taken and conserved in ethanol for pedigree analysis. Genotyping and parental assignment were inferred by breeders and offspring, by using the SMsa-1 multiplex PCR (Super Multiplex Sparus aurata), containing 11 specific microsatellite markers. Genetic parameters (heritability and genetic and phenotypic correlations) for carcass and morphology traits were estimated. Genotype–environment interactions (GxE), at harvest size, were estimated by genetic correlation between two facilities (ADSA and PIMSA).
Heritability estimates ranged from 0.09 to 0.22 for growth traits, from 0.04 to 0.35 for carcass traits, and the highest were reported by technological traits from 0.09 to 0.40 (table1). The genetic correlations for growth traits were mainly high, for carcass traits were medium, and for the technological traits were high. GxE interactions for all traits, at harvest size, were measured considering two facilities, and they were mainly medium-high for all traits, except for FHA and FHB, which were low. These data suggest that GxE interactions cannot be discarded as morphological aspects, and the new non-invasive technological traits present better additive genetic variation than biological traits, and that could lead a faster selection response to improve growth and morphology of the fish through increased accuracy of breeding values and selection response rates.