Multi-trait GWAS using high-density genotypes identifies genes associated with body traits in Nile tilapia

Abstract

Background: Body traits are generally controlled by several genes in vertebrates (i.e. polygenes), which in turn make them difficult to identify through association mapping. Increasing the power of association studies by combining approaches such as genotype imputation and multi-trait analysis improves the ability to detect quantitative trait loci associated with polygenic traits, such as body traits. Results: A multi-trait genome-wide association study (mtGWAS) was performed to identify quantitative trait loci (QTL) and genes associated with body traits in Nile tilapia (Oreochromos niloticus) using genotypes imputed to whole-genome sequence (WGS). To increase the statistical power of mtGWAS for the detection of genetic associations, summary statistics from single-trait genome-wide association studies (stGWAS) for eight different body traits recorded in 1,309 animals were used. The mtGWAS increased the statistical power from the original sample size from 13% to 44%, depending on the trait analyzed. The better resolution of the WGS data combined with the increased power of the mtGWAS approach, allowed the detection of significant markers not previously found in the stGWAS. Some lead single nucleotide polymorphisms (SNPs) were found within important functional candidate genes previously associated with growth-related traits. For instance, we identified SNP within the α1,6-fucosyltransferase (FUT8), solute carrier family 4 member 2 (SLC4A2), A disintegrin and metalloproteinase with thrombospondin motifs 9 (ADAMTS9) and heart development protein with EGF like domains 1 (HEG1) genes, which have been associated with average daily gain in sheep, osteopetrosis in cattle, chest size in goats, and growth and meat quality in sheep, respectively. Conclusions: The high-resolution mtGWAS presented, allowed identification of significant SNPs, linked to strong functional candidate genes, associated with body traits in Nile tilapia. These results provide further insights about the genetic variants and genes underlying body trait variation in cichlid fish with high accuracy and strong statistical support.

Increased accuracy of genomic predictions for growth under chronic thermal stress in rainbow trout by prioritizing variants from GWAS using imputed sequence data

“…genomic selection or marker‐assisted selection). Most GWASs have identified the polygenic nature of growth traits in fish, as in Atlantic salmon (Gutierrez et al, 2015 ; Tsai et al, 2015 ; Yoshida et al, 2017 ), rainbow trout (Gonzalez‐Pena et al, 2016 ; Reis Neto et al, 2019 ; Wringe et al, 2010 ), Nile tilapia (Yoshida, Carvalheiro et al, 2019 , Yoshida, Lhorente et al, 2019 ; Yoshida & Yáñez, 2020 ) and catfish (Li et al, 2018 ). We increased the number of variants from low density to 1.39 million SNPs through genotype imputation aimed to achieve a better GWAS resolution.…”