Genome-Wide Association Study and Cost-Efficient Genomic Predictions for Growth and Fillet Yield in Nile Tilapia (Oreochromis niloticus)

Abstract

Fillet yield (FY) and harvest weight (HW) are economically important traits in Nile tilapia production. Genetic improvement of these traits, especially for FY, are lacking, due to the absence of efficient methods to measure the traits without sacrificing fish and the use of information from relatives to selection. However, genomic information could be used by genomic selection to improve traits that are difficult to measure directly in selection candidates, as in the case of FY. The objectives of this study were: (i) to perform genome-wide association studies (GWAS) to dissect the genetic architecture of FY and HW, (ii) to evaluate the accuracy of genotype imputation and (iii) to assess the accuracy of genomic selection using true and imputed low-density (LD) single nucleotide polymorphism (SNP) panels to determine a cost-effective strategy for practical implementation of genomic information in tilapia breeding programs. The data set consisted of 5,866 phenotyped animals and 1,238 genotyped animals (108 parents and 1,130 offspring) using a 50K SNP panel. The GWAS were performed using all genotyped and phenotyped animals. The genotyped imputation was performed from LD panels (LD0.5K, LD1K and LD3K) to high-density panel (HD), using information from parents and 20% of offspring in the reference set and the remaining 80% in the validation set. In addition, we tested the accuracy of genomic selection using true and imputed genotypes comparing the accuracy obtained from pedigree-based best linear unbiased prediction (PBLUP) and genomic predictions. The results from GWAS supports evidence of the polygenic nature of FY and HW. The accuracy of imputation ranged from 0.90 to 0.98 for LD0.5K and LD3K, respectively. The accuracy of genomic prediction outperformed the estimated breeding value from PBLUP. The use of imputation for genomic selection resulted in an increased relative accuracy independent of the trait and LD panel analyzed. The present results suggest that genotype imputation could be a cost-effective strategy for genomic selection in Nile tilapia breeding programs.

Keywords: GWAS; GenPred; Oreochromis niloticus; Shared Data Resources; complex traits; cost-efficient; genomic prediction; genotype imputation; low-density panel.

Figure 1

Manhattan plot of genetic variance explained by 20-SNP windows for fillet yield in the 2^nd iteration of wssGBLUP.

Figure 2

Manhattan plot of genetic variance explained by 20-SNP windows for harvest weight in the 2^nd iteration of wssGBLUP.

Figure 3

Imputation accuracy from low-density (LD3K, LD1K and LD0.5K) to high-density (HD) panel in Nile tilapia using parents (n = 108) and 20% of offspring (n = 226) genotyped with the HD panel as the reference set and 80% of offspring (n = 904) as the validation set.

Figure 4

Relative increase in accuracy of different genomic selection methods for fillet yield, harvest weight and waste weight compared to PBLUP in Nile tilapia using true and imputed genotypes.