BackgroundGenomic prediction using Diversity Arrays Technology (DArT) genotype by sequencing platform has not been reported in yellowtail kingfish (Seriola lalandi). The principal aim of this study was to address this knowledge gap and to assess predictive ability of genomic Best Linear Unbiased Prediction (gBLUP) for traits of commercial importance in a yellowtail kingfish population comprising 752 individuals that had DNA sequence and phenotypic records for growth traits (body weight, fork length and condition index). The gBLUP method was used due to its computational efficiency and it showed similar predictive performance to other approaches, especially for traits whose variation is of polygenic nature, such as body traits analysed in this study. The accuracy or predictive ability of the gBLUP model was estimated for three growth traits: body weight, folk length and condition index.ResultsThe prediction accuracy was moderate to high (0.44 to 0.69) for growth-related traits. The predictive ability for body weight increased by 17.0% (from 0.69 to 0.83) when missing genotype was imputed. Within population prediction using five-fold across validation approach showed that the gBLUP model performed well for growth traits (weight, length and condition factor), with the coefficient of determination (R2) from linear regression analysis ranging from 0.49 to 0.71.ConclusionsCollectively our results demonstrated, for the first time in yellowtail kingfish, the potential application of genomic selection for growth-related traits in the future breeding program for this species, S. lalandi.Electronic supplementary materialThe online version of this article (10.1186/s12864-018-4493-4) contains supplementary material, which is available to authorized users.

Captive breeding programs and aquaculture production have commenced worldwide for the globally distributed yellowtail kingfish (Seriola lalandi), and captive bred fingerlings are being shipped from the Southern Hemisphere to be farmed in the Northern Hemisphere. It was recently proposed that Pacific S. lalandi comprise at least three distinct species that diverged more than 2 million years ago. Here, we tested the hypothesis of different “species” in the Pacific using novel genomic data (namely single nucleotide polymorphisms and diversity array technology markers), as well as mtDNA and DNA microsatellite variation. These new data support the hypothesis of population subdivision between the Northeast Pacific, Northwest Pacific and South Pacific, and genetic divergence indicates restriction to the gene flow between hemispheres. However, our estimates of maximum mtDNA and nuclear DNA divergences of 2.43% and 0.67%, respectively, were within the ranges more commonly observed for populations within species than species within genera. Accordingly our data support the more traditional view that S. lalandi in the Pacific comprises three distinct populations rather than the subdivisions into several species.

The genetic resources available for the commercially important fish species Yellowtail kingfish (YTK) (Seriola lalandi) are relative sparse. To overcome this, we aimed (1) to develop a linkage map for this species, and (2) to identify markers/variants associated with economically important traits in kingfish (with an emphasis on body weight). Genetic and genomic analyses were conducted using 13,898 single nucleotide polymorphisms (SNPs) generated from a new high-throughput genotyping by sequencing platform, Diversity Arrays Technology (DArTseqTM) in a pedigreed population comprising 752 animals. The linkage analysis enabled to map about 4,000 markers to 24 linkage groups (LGs), with an average density of 3.4 SNPs per cM. The linkage map was integrated into a genome-wide association study (GWAS) and identified six variants/SNPs associated with body weight (P < 5e-8) when a multi-locus mixed model was used. Two out of the six significant markers were mapped to LGs 17 and 23, and collectively they explained 5.8% of the total genetic variance. It is concluded that the newly developed linkage map and the significantly associated markers with body weight provide fundamental information to characterize genetic architecture of growth-related traits in this population of YTK S. lalandi.

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