Abstract
Aquaculture production is expected to increase with the help of genomic selection (GS). The possibility of performing GS using only a small number of SNPs has been examined in order to reduce genotyping costs; however, the practicality of this approach is still unclear. Here, we tested whether the effects of reducing the number of SNPs impaired the prediction accuracy of GS for standard length, body weight, and testes weight in the tiger pufferfish (Takifugu rubripes). High values for predictive ability (0.563–0.606) were obtained with 4000 SNPs for all traits under a genomic best linear unbiased predictor (GBLUP) model. These values were still within an acceptable range with 1200 SNPs (0.554–0.588). However, predictive abilities and prediction accuracies deteriorated using less than 1200 SNPs largely due to the reduced power in accurately estimating the genetic relationship among individuals; family structure could still be resolved with as few as 400 SNPs. This suggests that the SNPs informative for estimation of genetic relatedness among individuals differ from those for inference of family structure, and that non-random SNP selection based on the effects on family structure (e.g., site-FST, principal components, or random forest) is unlikely to increase the prediction accuracy for these traits.
Highlights
Aquaculture as an industry has taken root worldwide and has become the fastest growing in the food production sector[1]
We tested the feasibility of GP for testes weight (TW) standard length (SL), and body weight (BW) in cultured tiger pufferfish at harvest using the genomic best linear unbiased predictor (GBLUP) model and examined the effect of varying the number of SNPs on the estimations
Moderate heritability values were obtained for the three traits (0.538‒0.686) (Fig. 3), within the range of those estimated in previous studies where genomic information was used, e.g. Atlantic salmon (Salmo salar; length: 0.61, weight: 0.60)[29], common carp (Cyprinus carpio; length: 0.33)[30], Nile tilapia (Oreochromis niloticus; weight: 0.36)[31], channel catfish (Ictalurus punctatus; weight: 0.34)[32], large yellow croaker (Larimichthys crocea; length: 0.59, weight: 0.60, gonad weight: 0.37)[33,34], yellowtail kingfish (Seriola lalandi; length: 0.43, weight: 0.47)[35], and the tiger pufferfish[22]
Summary
Aquaculture as an industry has taken root worldwide and has become the fastest growing in the food production sector[1]. Genomic selection is advantageous for aquaculture species because many of economically important traits are polygenic (e.g., growth and disease resistance), and cultured populations often consist of many full-sib/half-sib families resulting in highly accurate GP6. A selective breeding program for this species is still in its infancy[17], the possibility of using GS for SL, BW, and for resistance against the monogenean parasite, Heterobothrium okamotoi, has already been tested[22] Precociousness is another important economic trait in this s pecies[23]. As precociousness is a polygenic t rait[23,25] TW at harvest can potentially be improved by GS To test this possibility, we raised an experimental population and applied GP for TW, SL, and BW using a genome-wide medium density SNP panel. We examined the effect of reducing the number of SNPs (from 4075 to 200) on the prediction accuracy and estimation of genetic relatedness among individuals to test the feasibility of using a low-density SNP panel for GS
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