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The potential of genomic selection (GS) to improve production traits has been widely demonstrated in many aquaculture species. Atlantic salmon breeding programmes typically consist of sibling testing schemes, where traits that cannot be measured on the selection candidates are measured on the candidates’ siblings. While annual testing on close relatives is effective, it is expensive due to high genotyping and phenotyping costs. Accurate prediction of breeding values in distant relatives could significantly reduce the cost of GS. This study aimed to evaluate the impact of decreasing the genomic relationship between the training and validation populations on the accuracy of genomic prediction for two key traits; body weight and resistance to sea lice; and to assess the interaction of genetic relationship with SNP density. Phenotype and genotype data from two year classes of a commercial breeding population of Atlantic salmon were used. The accuracy of genomic predictions were close to zero when the prediction was performed across year class, albeit this may reflect a lack of genetic correlation between the same traits measured in the different year classes. Within a year class, systematically reducing the relatedness between the training and validation populations resulted in decreasing accuracy of genomic prediction; when the training and validation populations were set up to contain no relatives with genomic relationships > 0.3, the accuracies decreased by 44% for sea lice count and by 53% for body weight. Less related training and validation populations also tended to result in highly biased predictions. No clear interaction between decreasing SNP density and relatedness between training and validation population was found. These results confirm the importance of close genetic relationships between training and selection populations in salmon breeding programmes, and suggests that prediction across generations using existing approaches would severely compromise the efficacy of GS.

The inclusion of genomic information became a reality in shrimp breeding and it is expected to accelerate the genetic gain over time. The decay of linkage disequilibrium (LD) between single nucleotide polymorphisms (SNPs) is an important measure to evaluate the feasibility of implementing genomic selection. The aim of this study was to evaluate the use of a novel 50 K SNP array tool to characterize the genomic diversity, LD and effective population size (Ne) in a farmed shrimp population. A total of 96 animals (40 sires and 56 dams) were genotyped using the novel Illumina AquaArray HD (50 K) vannamei®. Quality control (QC) of genomic data was performed and three different minor allele frequency (MAF) exclusion thresholds were applied: < 0.10 (QC1), < 0.05 (QC2) and < 0.01 (QC3). After QC, 34,425, 39,091 and 42,789 SNPs were retained for QC1, QC2 and QC3, respectively, validating the high informativeness of this SNP array to this particular shrimp breeding population. The population showed a considerable high overall heterozygosity in comparison to other aquaculture species meaning that genetic diversity is stable despite selection. The principal component analysis revealed three genetically distant groups with the first two principal components explaining 27.7 % of total variation. LD decayed rapidly in the first 30Kb of distance between markers from 0.20 to 0.07 and then decreased to 0.02 in the long-range distance. These results suggest a relatively recent incorporation of animals from different populations in the broodstock. Ne size reduced from 7,871 to 301 animals in 827 generations for QC1, 8,253 to 305 animals for QC2 and 8,957 to 315 animals for QC3, both in 899 generations. Contemporary Ne was close to 86 for all QCs. The level of LD estimated suggests that genomic selection and genome-wide association studies are feasible in shrimp by using this SNP array.

Tambaqui (Colossoma macropomum) is the main native fish produced in continental aquaculture from South America. However, its production has been negatively affected by significant economic losses due to frequent outbreaks caused by the parasite Ichthyophthirius multifiliis. Genetic selection for I. multifiliis resistance may represent a sustainable and effective alternative to reduce mortality and, therefore, improve production of tambaqui. The estimation of genetic parameters is needed to validate whether I. multifiliis resistance can be included in genetic improvement programs. The aim of this study was to estimate variance components and heritability for I. multifiliis resistance in tambaqui, through experimental challenge of 218 individuals from eight full-sib families. Survival status (SS), time of death (TD) and parasite load (PL) of fish presenting clinical signs of I. multifiliis infestation were recorded in the cohabitation experimental challenge. The total cumulative survival rate varied significantly among families (16 to 100%) and TD ranged from 217 to 254 hours post cohabitation, which indicates the presence of significant phenotypic variation related to resistance to I. multifiliis infestation. High values for heritability were estimated for SS and TD (0.46 ± 0.09 and 0.60 ± 0.18, respectively). However, differences among families and heritability value were not significant for PL. This study represents the first report on genetic parameters for disease resistance against the parasite I. multifiliis in a Neotropical fish species. The results presented here suggest that resistance to I. multifiliis in tambaqui can be improved through selective breeding.