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Genomic prediction using low density marker panels in aquaculture: performance across species, traits, and genotyping platforms

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Original languageEnglish
JournalFrontiers in genetics
DOIs
Publication statusPublished - 27 Feb 2020

Abstract

Genomic selection increases the rate of genetic gain in breeding programmes, which results 16 in significant cumulative improvements in commercially important traits such as disease 17 resistance. Genomic selection currently relies on collecting genome-wide genotype data 18 accross a large number of individuals which requires substantial economic investment. 19 However, global aquaculture production predominantly occurs in small and medium sized 20 enterprises for whom this technology can be prohibitively expensive. For genomic selection 21 to benefit these aquaculture sectors more cost-efficient genotyping is necessary. In this study 22 the utility of low and medium density SNP panels (ranging from 100 to 9000 SNPs) to 23 accurate predict breeding values was tested and compared in four aquaculture datasets with 24 different characteristics (species, genome size, genotyping platform, family number and size, 25 total population size, and target trait). The traits show heritabilities between 0.198-0.493, and 26 genomic prediction accuracies using the full density panel of 0.5549-0.817. A consistent 27 pattern of genomic prediction accuracy was observed across species, with little or no 28 accuracy reduction until SNP density was reduced below 1,000 SNPs (prediction accuracies 29 of 0.44-0.75). Below this SNP density, heritability estimates and genomic prediction 30 accuracies tended to be lower and more variable (93 % of maximum accuracy achieved with 31 1,000 SNPs, 89 % with 500 SNPs, and 70% with 100 SNPs). A notable drop in accuracy was 32 observed between 200 SNP panels (0.44-0.75) and 100 SNP panels (0.39-0.66). Now that a 33 multitude of studies have highlighted the benefits of genomic over pedigree-based prediction 34 of breeding values in aquaculture species, the results of the current study highlight that these 35 benefits can be achieved at lower SNP densities and at lower cost, raising the possibility of a 36 broader application of genetic improvement in smaller and more fragmented aquaculture 37 settings. 38

    Research areas

  • breeding, disease resistance, growth, GBLUP, fish, oyster, salmon

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