Applications of genotyping by sequencing in aquaculture breeding and genetics.
TLDR
Direct genotyping by sequencing (GBS) techniques have underpinned many of the advances in aquaculture genetics and breeding to date, and have been extensively applied to generate population‐level SNP genotype data.Abstract:
Selective breeding is increasingly recognized as a key component of sustainable production of aquaculture species. The uptake of genomic technology in aquaculture breeding has traditionally lagged behind terrestrial farmed animals. However, the rapid development and application of sequencing technologies has allowed aquaculture to narrow the gap, leading to substantial genomic resources for all major aquaculture species. While high-density single-nucleotide polymorphism (SNP) arrays for some species have been developed recently, direct genotyping by sequencing (GBS) techniques have underpinned many of the advances in aquaculture genetics and breeding to date. In particular, restriction-site associated DNA sequencing (RAD-Seq) and subsequent variations have been extensively applied to generate population-level SNP genotype data. These GBS techniques are not dependent on prior genomic information such as a reference genome assembly for the species of interest. As such, they have been widely utilized by researchers and companies focussing on nonmodel aquaculture species with relatively small research communities. Applications of RAD-Seq techniques have included generation of genetic linkage maps, performing genome-wide association studies, improvements of reference genome assemblies and, more recently, genomic selection for traits of interest to aquaculture like growth, sex determination or disease resistance. In this review, we briefly discuss the history of GBS, the nuances of the various GBS techniques, bioinformatics approaches and application of these techniques to various aquaculture species.read more
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Harnessing genomics to fast-track genetic improvement in aquaculture.
Ross D. Houston,Tim P. Bean,Daniel J. Macqueen,Manu Kumar Gundappa,Ye Hwa Jin,Tom L. Jenkins,Sarah Louise C Selly,Samuel A.M. Martin,Jamie R. Stevens,Eduarda M. Santos,Andrew Davie,Diego Robledo +11 more
TL;DR: The authors review how genomics is being applied to aquaculture species at all stages of the domestication process to optimize selective breeding and how combining genomic selection with biotechnological innovations, such as genome editing and surrogate broodstock technologies, may further expedite genetic improvement in Aquaculture.
Genotyping-in-Thousands By Sequencing (GT-seq): A Cost Effective SNP Genotyping Method Based on Custom Amplicon Sequencing - Rainbow Trout
TL;DR: In this paper, the authors demonstrate that amplicon sequencing with GT-seq greatly reduces the cost of genotyping hundreds of targeted SNPs relative to existing methods by utilizing a simple library preparation method and massive efficiency of scale.
Journal ArticleDOI
Genomic Selection in Aquaculture: Application, Limitations and Opportunities With Special Reference to Marine Shrimp and Pearl Oysters.
Kyall R. Zenger,Mehar S. Khatkar,David B. Jones,Nima Khalilisamani,Nima Khalilisamani,Dean R. Jerry,Herman W. Raadsma,Herman W. Raadsma +7 more
TL;DR: The technical advances, practical requirements, and commercial applications that have made genomic selection feasible in a range of aquaculture industries are discussed, with a particular focus on molluscs and marine shrimp.
Journal ArticleDOI
Potential of Genome Editing to Improve Aquaculture Breeding and Production
TL;DR: The high fecundity and external fertilization of most aquaculture species can facilitate genome editing for research and application at a scale that is not possible in farmed terrestrial animals.
Journal ArticleDOI
Genomic Predictions and Genome-Wide Association Study of Resistance Against Piscirickettsia salmonis in Coho Salmon (Oncorhynchus kisutch) Using ddRAD Sequencing
Andres Barria,Andres Barria,Kris A. Christensen,Grazyella Massako Yoshida,Grazyella Massako Yoshida,Katharina Correa,Ana Jedlicki,Jean P. Lhorente,William S. Davidson,José M. Yáñez +9 more
TL;DR: Genomic selection models showed higher accuracies than the traditional pedigree-based best linear unbiased prediction (PBLUP) method, for both DD and BIN, and showed an improvement of up to 95% and 155% respectively over PBLUP.
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