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Dissecting genetic trends to understand breeding practices in livestock: a maternal pig line example

BACKGROUND: Understanding whether genomic selection has been effective in livestock and when the results of genomic selection became visible are essential questions which we have addressed in this paper. Three criteria were used to identify practices of breeding programs over time: (1) the point of...

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Autores principales: Abdollahi-Arpanahi, Rostam, Lourenco, Daniela, Legarra, Andres, Misztal, Ignacy
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8627101/
https://www.ncbi.nlm.nih.gov/pubmed/34837954
http://dx.doi.org/10.1186/s12711-021-00683-6
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author Abdollahi-Arpanahi, Rostam
Lourenco, Daniela
Legarra, Andres
Misztal, Ignacy
author_facet Abdollahi-Arpanahi, Rostam
Lourenco, Daniela
Legarra, Andres
Misztal, Ignacy
author_sort Abdollahi-Arpanahi, Rostam
collection PubMed
description BACKGROUND: Understanding whether genomic selection has been effective in livestock and when the results of genomic selection became visible are essential questions which we have addressed in this paper. Three criteria were used to identify practices of breeding programs over time: (1) the point of divergence of estimated genetic trends based on pedigree-based best linear unbiased prediction (BLUP) versus single-step genomic BLUP (ssGBLUP), (2) the point of divergence of realized Mendelian sampling (RMS) trends based on BLUP and ssGBLUP, and (3) the partition of genetic trends into that contributed by genotyped and non-genotyped individuals and by males and females. METHODS: We used data on 282,035 animals from a commercial maternal line of pigs, of which 32,856 were genotyped for 36,612 single nucleotide polymorphisms (SNPs) after quality control. Phenotypic data included 228,427, 101,225, and 11,444 records for birth weight, average daily gain in the nursery, and feed intake, respectively. Breeding values were predicted in a multiple-trait framework using BLUP and ssGBLUP. RESULTS: The points of divergence of the genetic and RMS trends estimated by BLUP and ssGBLUP indicated that genomic selection effectively started in 2019. Partitioning the overall genetic trends into that for genotyped and non-genotyped individuals revealed that the contribution of genotyped animals to the overall genetic trend increased rapidly from ~ 74% in 2016 to 90% in 2019. The contribution of the female pathway to the genetic trend also increased since genomic selection was implemented in this pig population, which reflects the changes in the genotyping strategy in recent years. CONCLUSIONS: Our results show that an assessment of breeding program practices can be done based on the point of divergence of genetic and RMS trends between BLUP and ssGBLUP and based on the partitioning of the genetic trend into contributions from different selection pathways. However, it should be noted that genetic trends can diverge before the onset of genomic selection if superior animals are genotyped retroactively. For the pig population example, the results showed that genomic selection was effective in this population.
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spelling pubmed-86271012021-11-30 Dissecting genetic trends to understand breeding practices in livestock: a maternal pig line example Abdollahi-Arpanahi, Rostam Lourenco, Daniela Legarra, Andres Misztal, Ignacy Genet Sel Evol Research Article BACKGROUND: Understanding whether genomic selection has been effective in livestock and when the results of genomic selection became visible are essential questions which we have addressed in this paper. Three criteria were used to identify practices of breeding programs over time: (1) the point of divergence of estimated genetic trends based on pedigree-based best linear unbiased prediction (BLUP) versus single-step genomic BLUP (ssGBLUP), (2) the point of divergence of realized Mendelian sampling (RMS) trends based on BLUP and ssGBLUP, and (3) the partition of genetic trends into that contributed by genotyped and non-genotyped individuals and by males and females. METHODS: We used data on 282,035 animals from a commercial maternal line of pigs, of which 32,856 were genotyped for 36,612 single nucleotide polymorphisms (SNPs) after quality control. Phenotypic data included 228,427, 101,225, and 11,444 records for birth weight, average daily gain in the nursery, and feed intake, respectively. Breeding values were predicted in a multiple-trait framework using BLUP and ssGBLUP. RESULTS: The points of divergence of the genetic and RMS trends estimated by BLUP and ssGBLUP indicated that genomic selection effectively started in 2019. Partitioning the overall genetic trends into that for genotyped and non-genotyped individuals revealed that the contribution of genotyped animals to the overall genetic trend increased rapidly from ~ 74% in 2016 to 90% in 2019. The contribution of the female pathway to the genetic trend also increased since genomic selection was implemented in this pig population, which reflects the changes in the genotyping strategy in recent years. CONCLUSIONS: Our results show that an assessment of breeding program practices can be done based on the point of divergence of genetic and RMS trends between BLUP and ssGBLUP and based on the partitioning of the genetic trend into contributions from different selection pathways. However, it should be noted that genetic trends can diverge before the onset of genomic selection if superior animals are genotyped retroactively. For the pig population example, the results showed that genomic selection was effective in this population. BioMed Central 2021-11-27 /pmc/articles/PMC8627101/ /pubmed/34837954 http://dx.doi.org/10.1186/s12711-021-00683-6 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Abdollahi-Arpanahi, Rostam
Lourenco, Daniela
Legarra, Andres
Misztal, Ignacy
Dissecting genetic trends to understand breeding practices in livestock: a maternal pig line example
title Dissecting genetic trends to understand breeding practices in livestock: a maternal pig line example
title_full Dissecting genetic trends to understand breeding practices in livestock: a maternal pig line example
title_fullStr Dissecting genetic trends to understand breeding practices in livestock: a maternal pig line example
title_full_unstemmed Dissecting genetic trends to understand breeding practices in livestock: a maternal pig line example
title_short Dissecting genetic trends to understand breeding practices in livestock: a maternal pig line example
title_sort dissecting genetic trends to understand breeding practices in livestock: a maternal pig line example
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8627101/
https://www.ncbi.nlm.nih.gov/pubmed/34837954
http://dx.doi.org/10.1186/s12711-021-00683-6
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