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Effects of common full-sib families on accuracy of genomic prediction for tagging weight in striped catfish Pangasianodon hypophthalmus

Common full-sib families (c ( 2 )) make up a substantial proportion of total phenotypic variation in traits of commercial importance in aquaculture species and omission or inclusion of the c ( 2 ) resulted in possible changes in genetic parameter estimates and re-ranking of estimated breeding values...

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Autores principales: Vu, Nguyen Thanh, Phuc, Tran Huu, Nguyen, Nguyen Hong, Van Sang, Nguyen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9845282/
https://www.ncbi.nlm.nih.gov/pubmed/36685869
http://dx.doi.org/10.3389/fgene.2022.1081246
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author Vu, Nguyen Thanh
Phuc, Tran Huu
Nguyen, Nguyen Hong
Van Sang, Nguyen
author_facet Vu, Nguyen Thanh
Phuc, Tran Huu
Nguyen, Nguyen Hong
Van Sang, Nguyen
author_sort Vu, Nguyen Thanh
collection PubMed
description Common full-sib families (c ( 2 )) make up a substantial proportion of total phenotypic variation in traits of commercial importance in aquaculture species and omission or inclusion of the c ( 2 ) resulted in possible changes in genetic parameter estimates and re-ranking of estimated breeding values. However, the impacts of common full-sib families on accuracy of genomic prediction for commercial traits of economic importance are not well known in many species, including aquatic animals. This research explored the impacts of common full-sib families on accuracy of genomic prediction for tagging weight in a population of striped catfish comprising 11,918 fish traced back to the base population (four generations), in which 560 individuals had genotype records of 14,154 SNPs. Our single step genomic best linear unbiased prediction (ssGLBUP) showed that the accuracy of genomic prediction for tagging weight was reduced by 96.5%–130.3% when the common full-sib families were included in statistical models. The reduction in the prediction accuracy was to a smaller extent in multivariate analysis than in univariate models. Imputation of missing genotypes somewhat reduced the upward biases in the prediction accuracy for tagging weight. It is therefore suggested that genomic evaluation models for traits recorded during the early phase of growth development should account for the common full-sib families to minimise possible biases in the accuracy of genomic prediction and hence, selection response.
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spelling pubmed-98452822023-01-19 Effects of common full-sib families on accuracy of genomic prediction for tagging weight in striped catfish Pangasianodon hypophthalmus Vu, Nguyen Thanh Phuc, Tran Huu Nguyen, Nguyen Hong Van Sang, Nguyen Front Genet Genetics Common full-sib families (c ( 2 )) make up a substantial proportion of total phenotypic variation in traits of commercial importance in aquaculture species and omission or inclusion of the c ( 2 ) resulted in possible changes in genetic parameter estimates and re-ranking of estimated breeding values. However, the impacts of common full-sib families on accuracy of genomic prediction for commercial traits of economic importance are not well known in many species, including aquatic animals. This research explored the impacts of common full-sib families on accuracy of genomic prediction for tagging weight in a population of striped catfish comprising 11,918 fish traced back to the base population (four generations), in which 560 individuals had genotype records of 14,154 SNPs. Our single step genomic best linear unbiased prediction (ssGLBUP) showed that the accuracy of genomic prediction for tagging weight was reduced by 96.5%–130.3% when the common full-sib families were included in statistical models. The reduction in the prediction accuracy was to a smaller extent in multivariate analysis than in univariate models. Imputation of missing genotypes somewhat reduced the upward biases in the prediction accuracy for tagging weight. It is therefore suggested that genomic evaluation models for traits recorded during the early phase of growth development should account for the common full-sib families to minimise possible biases in the accuracy of genomic prediction and hence, selection response. Frontiers Media S.A. 2023-01-04 /pmc/articles/PMC9845282/ /pubmed/36685869 http://dx.doi.org/10.3389/fgene.2022.1081246 Text en Copyright © 2023 Vu, Phuc, Nguyen and Van Sang. https://creativecommons.org/licenses/by/4.0/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.
spellingShingle Genetics
Vu, Nguyen Thanh
Phuc, Tran Huu
Nguyen, Nguyen Hong
Van Sang, Nguyen
Effects of common full-sib families on accuracy of genomic prediction for tagging weight in striped catfish Pangasianodon hypophthalmus
title Effects of common full-sib families on accuracy of genomic prediction for tagging weight in striped catfish Pangasianodon hypophthalmus
title_full Effects of common full-sib families on accuracy of genomic prediction for tagging weight in striped catfish Pangasianodon hypophthalmus
title_fullStr Effects of common full-sib families on accuracy of genomic prediction for tagging weight in striped catfish Pangasianodon hypophthalmus
title_full_unstemmed Effects of common full-sib families on accuracy of genomic prediction for tagging weight in striped catfish Pangasianodon hypophthalmus
title_short Effects of common full-sib families on accuracy of genomic prediction for tagging weight in striped catfish Pangasianodon hypophthalmus
title_sort effects of common full-sib families on accuracy of genomic prediction for tagging weight in striped catfish pangasianodon hypophthalmus
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9845282/
https://www.ncbi.nlm.nih.gov/pubmed/36685869
http://dx.doi.org/10.3389/fgene.2022.1081246
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