Genomic prediction using DArT-Seq technology for yellowtail kingfish Seriola lalandi

Genomic 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 (g...

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Bibliographic Details
Published in:BMC genomics 2018-01, Vol.19 (1), p.107-107, Article 107
Main Authors: Nguyen, Nguyen H, Premachandra, H K A, Kilian, Andrzej, Knibb, Wayne
Format: Article
Language:English
Subjects:
Animal development
Genetic aspects
Genetic improvement
Genomic prediction
Genomic selection and genotype by sequencing
Genotype
Identification and classification
Kingfish
Perciformes
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Summary:Genomic 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. The 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 (R ) from linear regression analysis ranging from 0.49 to 0.71. Collectively 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.
ISSN:1471-2164
1471-2164
DOI:10.1186/s12864-018-4493-4