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Possibilities to improve the genetic evaluation of a rare breed using limited genomic information and multivariate BLUP

The use of molecular genetic information in the evaluation of livestock has become more common. This study looks at the efficacy of using such information to improve the genetic evaluation of a rare breed of dual-purpose cattle. Data were available in the form of pedigree information on the Gloucest...

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Autores principales: Pollott, G. E., Charlesworth, A., Wathes, D. C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cambridge University Press 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4000164/
https://www.ncbi.nlm.nih.gov/pubmed/24739347
http://dx.doi.org/10.1017/S1751731114000330
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author Pollott, G. E.
Charlesworth, A.
Wathes, D. C.
author_facet Pollott, G. E.
Charlesworth, A.
Wathes, D. C.
author_sort Pollott, G. E.
collection PubMed
description The use of molecular genetic information in the evaluation of livestock has become more common. This study looks at the efficacy of using such information to improve the genetic evaluation of a rare breed of dual-purpose cattle. Data were available in the form of pedigree information on the Gloucester cattle breed in the United Kingdom and recorded milk and beef performance on a small number of animals. In addition, molecular genetic information in the form of multi-marker, multiple regression results converted to a 1 to 10 score (Igenity scores) and 123 single nucleotide polymorphism (SNP) genotypes for 199 non-recorded animals were available. Appropriate mixed-animal models were explored for the recorded traits and these were used to calculate estimated breeding values (EBV), and their accuracies, for 6527 animals in the breed’s pedigree file. Various ways to improve the accuracy of these EBV were explored. This involved using multivariate BLUP analyses, genomic estimated breeding values (GEBV) and combining Igenity scores with recorded traits in a series of bivariate genetic analyses. Using the milk recording traits as an example, the accuracy of a number of traits could be improved using multivariate analyses by up to 14%, depending on the combination of traits used. The level of increase in accuracy largely corresponded to the absolute difference between the genetic and residual correlations between two traits, but this was not always symmetrical. The use of GEBV did not increase the accuracy of milk trait EBV owing to the low proportion of variance explained by the 101 SNPs used. Using Igenity scores in bivariate analyses with the recorded data was more successful in increasing EBV accuracy. The largest increases were found in genotyped animals with no recorded performance (e.g. a 58% increase in fat weight in milk); however, the size of the increase depended on the level of the genetic correlation between the recorded trait and the Igenity score for that trait. Lower levels of improvements in accuracy were seen in animals that were recoded but not genotyped, and ancestors which were neither genotyped nor recorded. This study demonstrated that it was possible to improve the accuracy of EBV estimation by including Igenity score information in genetic analyses but it also concluded that increasing the level of performance recording in the breed would be beneficial.
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spelling pubmed-40001642014-05-02 Possibilities to improve the genetic evaluation of a rare breed using limited genomic information and multivariate BLUP Pollott, G. E. Charlesworth, A. Wathes, D. C. Animal Full Paper The use of molecular genetic information in the evaluation of livestock has become more common. This study looks at the efficacy of using such information to improve the genetic evaluation of a rare breed of dual-purpose cattle. Data were available in the form of pedigree information on the Gloucester cattle breed in the United Kingdom and recorded milk and beef performance on a small number of animals. In addition, molecular genetic information in the form of multi-marker, multiple regression results converted to a 1 to 10 score (Igenity scores) and 123 single nucleotide polymorphism (SNP) genotypes for 199 non-recorded animals were available. Appropriate mixed-animal models were explored for the recorded traits and these were used to calculate estimated breeding values (EBV), and their accuracies, for 6527 animals in the breed’s pedigree file. Various ways to improve the accuracy of these EBV were explored. This involved using multivariate BLUP analyses, genomic estimated breeding values (GEBV) and combining Igenity scores with recorded traits in a series of bivariate genetic analyses. Using the milk recording traits as an example, the accuracy of a number of traits could be improved using multivariate analyses by up to 14%, depending on the combination of traits used. The level of increase in accuracy largely corresponded to the absolute difference between the genetic and residual correlations between two traits, but this was not always symmetrical. The use of GEBV did not increase the accuracy of milk trait EBV owing to the low proportion of variance explained by the 101 SNPs used. Using Igenity scores in bivariate analyses with the recorded data was more successful in increasing EBV accuracy. The largest increases were found in genotyped animals with no recorded performance (e.g. a 58% increase in fat weight in milk); however, the size of the increase depended on the level of the genetic correlation between the recorded trait and the Igenity score for that trait. Lower levels of improvements in accuracy were seen in animals that were recoded but not genotyped, and ancestors which were neither genotyped nor recorded. This study demonstrated that it was possible to improve the accuracy of EBV estimation by including Igenity score information in genetic analyses but it also concluded that increasing the level of performance recording in the breed would be beneficial. Cambridge University Press 2014-05 /pmc/articles/PMC4000164/ /pubmed/24739347 http://dx.doi.org/10.1017/S1751731114000330 Text en © The Animal Consortium 2014 The online version of this article is published within an Open Access environment subject to the conditions of the Creative Commons Attribution-NonCommercial-ShareAlike licence <http://creativecommons.org/licenses/by-ncsa/3.0/>. The written permission of Cambridge University Press must be obtained for commercial re-use.
spellingShingle Full Paper
Pollott, G. E.
Charlesworth, A.
Wathes, D. C.
Possibilities to improve the genetic evaluation of a rare breed using limited genomic information and multivariate BLUP
title Possibilities to improve the genetic evaluation of a rare breed using limited genomic information and multivariate BLUP
title_full Possibilities to improve the genetic evaluation of a rare breed using limited genomic information and multivariate BLUP
title_fullStr Possibilities to improve the genetic evaluation of a rare breed using limited genomic information and multivariate BLUP
title_full_unstemmed Possibilities to improve the genetic evaluation of a rare breed using limited genomic information and multivariate BLUP
title_short Possibilities to improve the genetic evaluation of a rare breed using limited genomic information and multivariate BLUP
title_sort possibilities to improve the genetic evaluation of a rare breed using limited genomic information and multivariate blup
topic Full Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4000164/
https://www.ncbi.nlm.nih.gov/pubmed/24739347
http://dx.doi.org/10.1017/S1751731114000330
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