Genomic prediction for commercial traits using univariate and multivariate approaches in Nile tilapia (Oreochromis niloticus)

Joshi, Rajesh; Skaarud, Anders; Vera, M. de; Alvarez, Alejandro Tola; Ødegård, Jørgen

doi:10.1016/j.aquaculture.2019.734641

Cited by 41 publications

(32 citation statements)

References 33 publications

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“…We found moderate to high heritability values for ADG, BWH, WW, HW, HON, BLH, FW and FY, which is consistent with previous estimates for Nile tilapia calculated using pedigree and genomic methods [8,9,19,20]. The additive genetic variance and heritability estimated for BWH using genotypes imputed to high-density genotypes increased about 15% in comparison to the value previously estimated for the same population using a 50K SNP panel [19].…”

Section: Discussionsupporting

confidence: 89%

“…The availability of a chromosome-level reference genome assembly [14] and highthroughput whole-genome sequencing (WGS) methods [15,16], has allowed for the assessment of genetic variation of different Nile tilapia populations at a genome-wide level and the recent development of single nucleotide polymorphism (SNP) panels [17,18]. The availability of Nile tilapia SNP panels made it possible to use modern molecular breeding approaches; including mapping of quantitative trait loci (QTL) through genome-wide association studies (GWAS), marker-assisted selection (MAS) and genomic selection [19,20]. The GWAS approach evaluates the association between the genotype and the phenotype of interest, with both sources of information available for a large number of individuals.…”

Section: Introductionmentioning

confidence: 99%

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

Yoshida¹,

Yáñez²

2020

Preprint

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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.

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Section: Discussionsupporting

confidence: 89%

Section: Introductionmentioning

confidence: 99%

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

Yoshida¹,

Yáñez²

2020

Preprint

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“…One of the platforms was designed based on the analysis of the GenoMar Supreme Tilapia (GST) strain (Joshi et al 2018), whereas the other platform derived from the evaluation of two strains belonging to Aquacorporación Internacional (Costa Rica) and a GIFT population from AquaAmerica (Brazil) (Yáñez et al 2020). These SNP arrays have been shown to be highly effective in the discovery populations, and have been used to generate high-density linkage maps and perform tests of genomic selection (Joshi et al 2020;Yoshida et al 2019a). However, while all of these commercial strains are related to the GIFT strain (which underpins a large proportion of global tilapia aquaculture), their utility and performance in other farmed tilapia strains, especially those inhabiting Asia and Africa, is unknown.…”

mentioning

confidence: 99%

Development and Validation of an Open Access SNP Array for Nile Tilapia (Oreochromis niloticus)

Peñaloza

Robledo

Barría

et al. 2020

G3 Genes|Genomes|Genetics

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Tilapia are amongst the most important farmed fish species worldwide, and are fundamental for the food security of many developing countries. Several genetically improved Nile tilapia (Oreochromis niloticus) strains exist, such as the iconic Genetically Improved Farmed Tilapia (GIFT), and breeding programmes typically follow classical pedigree-based selection. The use of genome-wide single-nucleotide polymorphism (SNP) data can enable an understanding of the genetic architecture of economically important traits and the acceleration of genetic gain via genomic selection. Due to the global importance and diversity of Nile tilapia, an open access SNP array with known utility across multiple tilapia strains would be beneficial for aquaculture research and production. In the current study, a ~65K SNP array was designed based on SNPs discovered from whole-genome sequence data from a GIFT breeding nucleus population and the overlap with SNP datasets from several other farmed and wild Nile tilapia strains. The SNP array was applied to clearly distinguish between different tilapia populations across Asia and Africa, with at least ~30,000 SNPs segregating in each of the diverse population samples tested. It is anticipated that this SNP array will be an enabling tool for population genetics and tilapia breeding research, facilitating consistency and comparison of results across studies.

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“…Furthermore, univariate and multivariate genomic selection approaches have also been tested using dense SNP genotypes for growth-and disease resistancerelated traits (e.g. Streptococcus resistance), showing an increase in prediction accuracy, when compared with conventional pedigree-based genetic evaluation methods (Joshi et al, 2020c(Joshi et al, , 2019. These results indicate the benefits of genomic evaluations for the genetic improvement of these populations.…”

Section: Qtl Mapping Gwas and Genomic Selectionmentioning

confidence: 99%

Genomics to accelerate genetic improvement in tilapia

2020

Self Cite

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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.

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Genomic prediction for commercial traits using univariate and multivariate approaches in Nile tilapia (Oreochromis niloticus)

Cited by 41 publications

References 33 publications

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

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

Development and Validation of an Open Access SNP Array for Nile Tilapia (Oreochromis niloticus)

Genomics to accelerate genetic improvement in tilapia

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