Genomics to accelerate genetic improvement in tilapia

Abstract

Summary Selective breeding of tilapia populations started in the early 1990s and over the past three decades tilapia has become one of the most important farmed freshwater species, being produced in more than 125 countries around the globe. Although genome assemblies have been available since 2011, most of the tilapia industry still depends on classical selection techniques using mass spawning or pedigree information to select for growth traits with reported genetic gains of up to 20% per generation. The involvement of international breeding companies and research institutions has resulted in the rapid development and application of genomic resources in the last few years. GWAS and genomic selection are expected to contribute to uncovering the genetic variants involved in economically relevant traits and increasing the genetic gain in selective breeding programs, respectively. Developments over the next few years will probably focus on achieving a deep understanding of genetic architecture of complex traits, as well as accelerating genetic progress in the selection for growth‐, quality‐ and robustness‐related traits. Novel phenotyping technologies (i.e. phenomics), lower‐cost whole‐genome sequencing approaches, functional genomics and gene editing tools will be crucial in future developments for the improvement of tilapia aquaculture.

Multi-trait GWAS using imputed high-density genotypes from whole-genome sequencing identifies genes associated with body traits in Nile tilapia

“…Previous studies have estimated high values of genetic correlations between harvest weight and fillet weight (> 0.96) and moderate to high values between harvest weight and fillet yield (0.21 to 0.74) [7,9,10], suggesting that is not possible to improve fillet traits independently of body weight [11]. Although, previous reports have also identified negative or null genetic correlation between harvest weight and fillet yield [12], which suggests the importance of assessing these relationships on each particular population. Other body traits which have been proposed as selection criteria to generate more profitable commercial fish populations, are reduced waste (sum of bones, viscera, head, and fins) and carcass weight, due to their higher heritability values, less correlation to body weight, compared to fillet weight, and null or even favourable impact on fillet yield [13,14].…”

Multi-trait GWAS using imputed high-density genotypes from whole-genome sequencing identifies genes associated with body traits in Nile tilapia

“…Previous studies have estimated high values of genetic correlation between harvest weight and fillet weight (>0.96) and moderate to high values between harvest weight and fillet yield (0.21 to 0.74) [7,9,10], suggesting that is not possible to improve fillet traits independently of weight [11]. Although, previous reports have also identified negative or null genetic correlation between harvest weight and fillet yield [12], which suggests the importance of assessing these relationships on each particular population. Other body traits which have been proposed as selection criteria, to generate more profitable commercial fish populations, are reduced waste (sum of bones, viscera, head, and fins) and carcass weight, due to their higher heritability values, less correlation to body weight, compared to fillet weight, and null or even negative impact on fillet yield [13,14].…”

Genomic Selection and Genome-wide Association Study for Feed-Efficiency Traits in a Farmed Nile Tilapia (Oreochromis niloticus) Population

“…Farmed across a wide range of production systems, this species is considered a critical protein source for human consumption in undeveloped and developing countries ( Miao and Wang, 2020 ). Recently, a wide variety of genomic tools have been developed for Nile tilapia (reviewed in Yáñez et al, 2020 ). These genomic tools have facilitated studies to unravel the relationships among improved strains ( Hamilton et al, 2020 ), to detect regions associated with important traits ( Cáceres et al, 2019 ; Yoshida et al, 2019 ; Taslima et al, 2020 ; Barria et al, 2021 ), and to assess the accuracy of prediction of breeding values using genomic selection (GS) models, compared with pedigree-based models ( Yoshida et al, 2019 ; Joshi et al, 2020 ).…”

“…Previous work has aimed to assess body weight related traits (e.g. harvest weight, head weight, body length, fillet yield), as has been reviewed in Yáñez et al (2020) . Therefore, the aims of this study were to 1 ) dissect the genetic architecture of feed-efficiency traits in a Nile tilapia breeding population, 2 ) map the genomic regions associated with these traits and identify candidate genes, 3 ) evaluate the accuracy of prediction of breeding values using genomic data, and 4 ) assess the impact of the SNP density on the genomic prediction accuracies.…”