Prediction Accuracies of Genomic Selection for Nine Commercially Important Traits in the Portuguese Oyster (Crassostrea angulata) Using DArT-Seq Technology

Genes

Cedric Gondro¹  Wayne Knibb²  SangV. Vu²  Wayne O’Connor²  LeDuy Khuong³  Michael Dove⁴  InVan Vu⁵  NgocT. H. Nguyen⁵  Rick Tearle⁶  ArthurR. Gilmour⁷ 

[1] Department of Animal Science, College of Agriculture and Natural Resources, Michigan State University, East Lansing, MI 48824, USA;GeneCology Research Centre, University of the Sunshine Coast, 90 Sippy Downs Dr., Sippy Downs QLD 4556, Australia;Ha Long University, Uong Bi 200000, Quang Ninh, Vietnam;NSW Department of Primary Industries, Port Stephens Fisheries Institute, Taylors Beach, New South Wales 2316, Australia;Northern National Broodstock Centre for Mariculture, RIA1, Catba Islands, Hai Phong 180000, Vietnam;School of Animal and Veterinary Science, The University of Adelaide, Adelaide 5005, Australia;Statistical and ASReml Consultant, Orange New South Wales 2800, Australia;

关键词: genomic selection;    prediction accuracy;    analysis methods;    SNP marker density;    genomic parameters;   

DOI  :  10.3390/genes12020210

来源: DOAJ

【 摘 要 】

Genomic selection has been widely used in terrestrial animals but has had limited application in aquaculture due to relatively high genotyping costs. Genomic information has an important role in improving the prediction accuracy of breeding values, especially for traits that are difficult or expensive to measure. The purposes of this study were to (i) further evaluate the use of genomic information to improve prediction accuracies of breeding values from, (ii) compare different prediction methods (BayesA, BayesCπ and GBLUP) on prediction accuracies in our field data, and (iii) investigate the effects of different SNP marker densities on prediction accuracies of traits in the Portuguese oyster (Crassostrea angulata). The traits studied are all of economic importance and included morphometric traits (shell length, shell width, shell depth, shell weight), edibility traits (tenderness, taste, moisture content), and disease traits (Polydora sp. and Marteilioides chungmuensis). A total of 18,849 single nucleotide polymorphisms were obtained from genotyping by sequencing and used to estimate genetic parameters (heritability and genetic correlation) and the prediction accuracy of genomic selection for these traits. Multi-locus mixed model analysis indicated high estimates of heritability for edibility traits; 0.44 for moisture content, 0.59 for taste, and 0.72 for tenderness. The morphometric traits, shell length, shell width, shell depth and shell weight had estimated genomic heritabilities ranging from 0.28 to 0.55. The genomic heritabilities were relatively low for the disease related traits: Polydora sp. prevalence (0.11) and M. chungmuensis (0.10). Genomic correlations between whole weight and other morphometric traits were from moderate to high and positive (0.58–0.90). However, unfavourably positive genomic correlations were observed between whole weight and the disease traits (0.35–0.37). The genomic best linear unbiased prediction method (GBLUP) showed slightly higher accuracy for the traits studied (0.240–0.794) compared with both BayesA and BayesCπ methods but these differences were not significant. In addition, there is a large potential for using low-density SNP markers for genomic selection in this population at a number of 3000 SNPs. Therefore, there is the prospect to improve morphometric, edibility and disease related traits using genomic information in this species.

【 授权许可】

Unknown