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Estimation of breeding values for uniformity of growth in Atlantic salmon (Salmo salar) using pedigree relationships or single-step genomic evaluation

BACKGROUND: In farmed Atlantic salmon, heritability for uniformity of body weight is low, indicating that the accuracy of estimated breeding values (EBV) may be low. The use of genomic information could be one way to increase accuracy and, hence, obtain greater response to selection. Genomic informa...

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Autores principales: Sae-Lim, Panya, Kause, Antti, Lillehammer, Marie, Mulder, Han A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5439168/
https://www.ncbi.nlm.nih.gov/pubmed/28270100
http://dx.doi.org/10.1186/s12711-017-0308-3
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author Sae-Lim, Panya
Kause, Antti
Lillehammer, Marie
Mulder, Han A.
author_facet Sae-Lim, Panya
Kause, Antti
Lillehammer, Marie
Mulder, Han A.
author_sort Sae-Lim, Panya
collection PubMed
description BACKGROUND: In farmed Atlantic salmon, heritability for uniformity of body weight is low, indicating that the accuracy of estimated breeding values (EBV) may be low. The use of genomic information could be one way to increase accuracy and, hence, obtain greater response to selection. Genomic information can be merged with pedigree information to construct a combined relationship matrix ([Formula: see text] matrix) for a single-step genomic evaluation (ssGBLUP), allowing realized relationships of the genotyped animals to be exploited, in addition to numerator pedigree relationships ([Formula: see text] matrix). We compared the predictive ability of EBV for uniformity of body weight in Atlantic salmon, when implementing either the [Formula: see text] or [Formula: see text] matrix in the genetic evaluation. We used double hierarchical generalized linear models (DHGLM) based either on a sire-dam (sire-dam DHGLM) or an animal model (animal DHGLM) for both body weight and its uniformity. RESULTS: With the animal DHGLM, the use of [Formula: see text] instead of [Formula: see text] significantly increased the correlation between the predicted EBV and adjusted phenotypes, which is a measure of predictive ability, for both body weight and its uniformity (41.1 to 78.1%). When log-transformed body weights were used to account for a scale effect, the use of [Formula: see text] instead of [Formula: see text] produced a small and non-significant increase (1.3 to 13.9%) in predictive ability. The sire-dam DHGLM had lower predictive ability for uniformity compared to the animal DHGLM. CONCLUSIONS: Use of the combined numerator and genomic relationship matrix ([Formula: see text] ) significantly increased the predictive ability of EBV for uniformity when using the animal DHGLM for untransformed body weight. The increase was only minor when using log-transformed body weights, which may be due to the lower heritability of scaled uniformity, the lower genetic correlation of transformed body weight with its uniformity compared to the untransformed traits, and the small number of genotyped animals in the reference population. This study shows that ssGBLUP increases the accuracy of EBV for uniformity of body weight and is expected to increase response to selection in uniformity. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12711-017-0308-3) contains supplementary material, which is available to authorized users.
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spelling pubmed-54391682017-05-23 Estimation of breeding values for uniformity of growth in Atlantic salmon (Salmo salar) using pedigree relationships or single-step genomic evaluation Sae-Lim, Panya Kause, Antti Lillehammer, Marie Mulder, Han A. Genet Sel Evol Research Article BACKGROUND: In farmed Atlantic salmon, heritability for uniformity of body weight is low, indicating that the accuracy of estimated breeding values (EBV) may be low. The use of genomic information could be one way to increase accuracy and, hence, obtain greater response to selection. Genomic information can be merged with pedigree information to construct a combined relationship matrix ([Formula: see text] matrix) for a single-step genomic evaluation (ssGBLUP), allowing realized relationships of the genotyped animals to be exploited, in addition to numerator pedigree relationships ([Formula: see text] matrix). We compared the predictive ability of EBV for uniformity of body weight in Atlantic salmon, when implementing either the [Formula: see text] or [Formula: see text] matrix in the genetic evaluation. We used double hierarchical generalized linear models (DHGLM) based either on a sire-dam (sire-dam DHGLM) or an animal model (animal DHGLM) for both body weight and its uniformity. RESULTS: With the animal DHGLM, the use of [Formula: see text] instead of [Formula: see text] significantly increased the correlation between the predicted EBV and adjusted phenotypes, which is a measure of predictive ability, for both body weight and its uniformity (41.1 to 78.1%). When log-transformed body weights were used to account for a scale effect, the use of [Formula: see text] instead of [Formula: see text] produced a small and non-significant increase (1.3 to 13.9%) in predictive ability. The sire-dam DHGLM had lower predictive ability for uniformity compared to the animal DHGLM. CONCLUSIONS: Use of the combined numerator and genomic relationship matrix ([Formula: see text] ) significantly increased the predictive ability of EBV for uniformity when using the animal DHGLM for untransformed body weight. The increase was only minor when using log-transformed body weights, which may be due to the lower heritability of scaled uniformity, the lower genetic correlation of transformed body weight with its uniformity compared to the untransformed traits, and the small number of genotyped animals in the reference population. This study shows that ssGBLUP increases the accuracy of EBV for uniformity of body weight and is expected to increase response to selection in uniformity. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12711-017-0308-3) contains supplementary material, which is available to authorized users. BioMed Central 2017-03-07 /pmc/articles/PMC5439168/ /pubmed/28270100 http://dx.doi.org/10.1186/s12711-017-0308-3 Text en © The Author(s) 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Sae-Lim, Panya
Kause, Antti
Lillehammer, Marie
Mulder, Han A.
Estimation of breeding values for uniformity of growth in Atlantic salmon (Salmo salar) using pedigree relationships or single-step genomic evaluation
title Estimation of breeding values for uniformity of growth in Atlantic salmon (Salmo salar) using pedigree relationships or single-step genomic evaluation
title_full Estimation of breeding values for uniformity of growth in Atlantic salmon (Salmo salar) using pedigree relationships or single-step genomic evaluation
title_fullStr Estimation of breeding values for uniformity of growth in Atlantic salmon (Salmo salar) using pedigree relationships or single-step genomic evaluation
title_full_unstemmed Estimation of breeding values for uniformity of growth in Atlantic salmon (Salmo salar) using pedigree relationships or single-step genomic evaluation
title_short Estimation of breeding values for uniformity of growth in Atlantic salmon (Salmo salar) using pedigree relationships or single-step genomic evaluation
title_sort estimation of breeding values for uniformity of growth in atlantic salmon (salmo salar) using pedigree relationships or single-step genomic evaluation
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5439168/
https://www.ncbi.nlm.nih.gov/pubmed/28270100
http://dx.doi.org/10.1186/s12711-017-0308-3
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