Genetic diversity and candidate gene association analysis for growth in the South African Yellowtail (Seriola lalandi)
Yellowtail (Seriola lalandi) is regarded as an important line fishing species in South Africa and is important for economic trade. Due to their high fecundity, fast growth rate, robustness and ability to adapt to tank culture, Yellowtail is an excellent candidate for aquaculture. South Africa still relies on wild individuals as broodstock population to produce offspring through mass spawning to produce individuals for the market. Conventional selective breeding strategies are not as effective as they are supposed to be, leading to a loss of genetic diversity. This is further compounded by skewed broodstock success and inconsistencies regarding phenotypic performance and size between families. Research has also focused on growth as a trait of interest. The genetic resources for the commercially important Yellowtail kingfish are still relatively sparse but is growing considerably. Therefore, this study aimed to validate five growth related SNPs previously identified in Nguyen et.al., 2018 in a commercial South African cohort. First, using nine microsatellite markers, genetic diversity estimates and family structure of the cohorts were assessed. Comparisons between broodstock (n = 22) and progeny (n = 479) detected a genetic bottleneck between generations, likely as a result of the low number of contributing individuals (n = 4). Pairwise FST estimates of North Blinder, Yzerfontein, Cape Point, Gqeberha and Struis Bay indicate no significant differentiation between the wild coastal shelf populations, which could be regarded as one single population (coastal shelf P-values: 0.056 - 0.480). Results from the DAPC showed three genetic clusters, the coastal shelf population, a seamount population and the commercial broodstock population all clustering separately from each other, with overlap seen between the populations. Broodstock contributions to the F1-offspting cohorts were skewed, with one half-sib family consisting of up to 81.64% of the progeny population. This study demonstrates that the mass spawning method in conventional breeding methods is not sufficient. Two of the SNPs from Nguyen et al., 2018, the SNP found in ASCC1 (A > T), and the SNP found in CELF4 (T > G) were found to be monomorphic in the South African population (ASCC1: T, CELF4: T). The original SNP found in PXDN (C > T) could not be reliably genotyped in the South African population. The original SNP located in DRP2 (C >A) was found to be monomorphic (DRP2: C) and original SNP located in CRYBG1a (A >G) was confirmed to be segregating in the South African population (CRYBG1a: G >A). An additional 37 SNPs were identified located in CRYBG1a, DRP2 and PXDN. A case-control association analysis was performed to detect and validate variants linked to growth. Furthermore, a quantitative analysis was conducted using weight, length and Fulton’s conditioning factor as continuous response variables to pinpoint SNPs significantly associated with growth. To control for potential confounding factors, a regression model incorporating family and tank number as categorical covariates was applied. None of the original SNPs showed an association with growth in the South African population. However, four additional SNPs were found to be significantly associated with growth, one located in CRYBG1a and three located in PXDN. No significant haplotype blocks or epistatic effects were observed. This research revealed population-specific SNPs in genes related to growth.
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