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Genomic Prediction for Whole Weight, Body Shape, Meat Yield, and Color Traits in the Portuguese Oyster Crassostrea angulata1.38 MB
Published VersionCC BY V4.0, Open Access
Journal article
Genomic Prediction for Whole Weight, Body Shape, Meat Yield, and Color Traits in the Portuguese Oyster Crassostrea angulata
Frontiers in Genetics, Vol.12, pp.1-10
2021
Abstract
Genetic improvement for quality traits, especially color and meat yield, has been limited in aquaculture because the assessment of these traits requires that the animals be slaughtered first. Genotyping technologies do, however, provide an opportunity to improve the selection efficiency for these traits. The main purpose of this study is to assess the potential for using genomic information to improve meat yield (soft tissue weight and condition index), body shape (cup and fan ratios), color (shell and mantle), and whole weight traits at harvest in the Portuguese oyster,
Crassostrea angulata
. The study consisted of 647 oysters: 188 oysters from 57 full-sib families from the first generation and 459 oysters from 33 full-sib families from the second generation. The number per family ranged from two to eight oysters for the first and 12–15 oysters for the second generation. After quality control, a set of 13,048 markers were analyzed to estimate the genetic parameters (heritability and genetic correlation) and predictive accuracy of the genomic selection for these traits. The multi-locus mixed model analysis indicated high estimates of heritability for meat yield traits: 0.43 for soft tissue weight and 0.77 for condition index. The estimated genomic heritabilities were 0.45 for whole weight, 0.24 for cup ratio, and 0.33 for fan ratio and ranged from 0.14 to 0.54 for color traits. The genetic correlations among whole weight, meat yield, and body shape traits were favorably positive, suggesting that the selection for whole weight would have beneficial effects on meat yield and body shape traits. Of paramount importance is the fact that the genomic prediction showed moderate to high accuracy for the traits studied (0.38–0.92). Therefore, there are good prospects to improve whole weight, meat yield, body shape, and color traits using genomic information. A multi-trait selection program using the genomic information can boost the genetic gain and minimize inbreeding in the long-term for this population.
Details
- Title
- Genomic Prediction for Whole Weight, Body Shape, Meat Yield, and Color Traits in the Portuguese Oyster Crassostrea angulata
- Authors
- Sang V Vu (Corresponding Author) - GeneCology Research Centre, University of the Sunshine CoastWayne Knibb (Author) - University of the Sunshine Coast, Queensland, School of Science and Engineering - LegacyCedric Gondro (Author) - Michigan State UniversitySankar Subramanian (Author) - University of the Sunshine Coast, Queensland, GeneCology Research Centre - LegacyNgoc T. H Nguyen (Author) - Research Institute for Aquaculture No1Mobashwer Alam (Author) - The University of QueenslandMichael Dove (Author) - New South Wales Department of Primary IndustriesArthur R Gilmour (Author) - ConsultantIn Van Vu (Author) - Research Institute for Aquaculture No1Salma Bhyan (Author) - University of the Sunshine Coast, Queensland, School of Health and Behavioural Sciences - LegacyRick Tearle (Author) - The University of AdelaideLe Duy Khuong (Author) - Ha Long University (Vietnam)Tuan Son Le (Author) - Research Institute for Marine FisheriesWayne O’Connor (Author) - GeneCology Research Centre, University of the Sunshine Coast
- Publication details
- Frontiers in Genetics, Vol.12, pp.1-10
- Publisher
- Frontiers Research Foundation
- Date published
- 2021
- DOI
- 10.3389/fgene.2021.661276
- ISSN
- 1664-8021
- Copyright note
- Copyright © 2021 Vu, Knibb, Gondro, Subramanian, Nguyen, Alam, Dove, Gilmour, Vu, Bhyan, Tearle, Khuong, Le and O’Connor. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
- Organisation Unit
- School of Health - Biomedicine; School of Science and Engineering - Legacy; University of the Sunshine Coast, Queensland; GeneCology Research Centre - Legacy; Library Services; School of Science, Technology and Engineering; Centre for Bioinnovation; School of Health and Behavioural Sciences - Legacy
- Language
- English
- Record Identifier
- 99579408502621
- Output Type
- Journal article
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