Cargando…
Optimizing the Construction and Update Strategies for the Genomic Selection of Pig Reference and Candidate Populations in China
Optimizing the construction and update strategies for reference and candidate populations is the basis of the application of genomic selection (GS). In this study, we first simulated1200-purebred-pigs population that have been popular in China for 20 generations to study the effects of different pop...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9213789/ https://www.ncbi.nlm.nih.gov/pubmed/35754832 http://dx.doi.org/10.3389/fgene.2022.938947 |
_version_ | 1784730916066689024 |
---|---|
author | Wei, Xia Zhang, Tian Wang, Ligang Zhang, Longchao Hou, Xinhua Yan, Hua Wang, Lixian |
author_facet | Wei, Xia Zhang, Tian Wang, Ligang Zhang, Longchao Hou, Xinhua Yan, Hua Wang, Lixian |
author_sort | Wei, Xia |
collection | PubMed |
description | Optimizing the construction and update strategies for reference and candidate populations is the basis of the application of genomic selection (GS). In this study, we first simulated1200-purebred-pigs population that have been popular in China for 20 generations to study the effects of different population sizes and the relationship between individuals of the reference and candidate populations. The results showed that the accuracy was positively correlated with the size of the reference population within the same generation (r = 0.9366, p < 0.05), while was negatively correlated with the number of generation intervals between the reference and candidate populations (r = −0.9267, p < 0.01). When the reference population accumulated more than seven generations, the accuracy began to decline. We then simulated the population structure of 1200 purebred pigs for five generations and studied the effects of different heritabilities (0.1, 0.3, and 0.5), genotyping proportions (20, 30, and 50%), and sex ratios on the accuracy of the genomic estimate breeding value (GEBV) and genetic progress. The results showed that if the proportion of genotyping individuals accounts for 20% of the candidate population, the traits with different heritabilities can be genotyped according to the sex ratio of 1:1male to female. If the proportion is 30% and the traits are of low heritability (0.1), the sex ratio of 1:1 male to female is the best. If the traits are of medium or high heritability, the male-to-female ratio is 1:1, 1:2, or 2:1, which may achieve higher genetic progress. If the genotyping proportion is up to 50%, for low heritability traits (0.1), the proportion of sows from all genotyping individuals should not be less than 25%, and for the medium and high heritability traits, the optimal choice for the male-to-female ratio is 1:1, which may obtain the greatest genetic progress. This study provides a reference for determining a construction and update plan for the reference population of breeding pigs. |
format | Online Article Text |
id | pubmed-9213789 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-92137892022-06-23 Optimizing the Construction and Update Strategies for the Genomic Selection of Pig Reference and Candidate Populations in China Wei, Xia Zhang, Tian Wang, Ligang Zhang, Longchao Hou, Xinhua Yan, Hua Wang, Lixian Front Genet Genetics Optimizing the construction and update strategies for reference and candidate populations is the basis of the application of genomic selection (GS). In this study, we first simulated1200-purebred-pigs population that have been popular in China for 20 generations to study the effects of different population sizes and the relationship between individuals of the reference and candidate populations. The results showed that the accuracy was positively correlated with the size of the reference population within the same generation (r = 0.9366, p < 0.05), while was negatively correlated with the number of generation intervals between the reference and candidate populations (r = −0.9267, p < 0.01). When the reference population accumulated more than seven generations, the accuracy began to decline. We then simulated the population structure of 1200 purebred pigs for five generations and studied the effects of different heritabilities (0.1, 0.3, and 0.5), genotyping proportions (20, 30, and 50%), and sex ratios on the accuracy of the genomic estimate breeding value (GEBV) and genetic progress. The results showed that if the proportion of genotyping individuals accounts for 20% of the candidate population, the traits with different heritabilities can be genotyped according to the sex ratio of 1:1male to female. If the proportion is 30% and the traits are of low heritability (0.1), the sex ratio of 1:1 male to female is the best. If the traits are of medium or high heritability, the male-to-female ratio is 1:1, 1:2, or 2:1, which may achieve higher genetic progress. If the genotyping proportion is up to 50%, for low heritability traits (0.1), the proportion of sows from all genotyping individuals should not be less than 25%, and for the medium and high heritability traits, the optimal choice for the male-to-female ratio is 1:1, which may obtain the greatest genetic progress. This study provides a reference for determining a construction and update plan for the reference population of breeding pigs. Frontiers Media S.A. 2022-06-08 /pmc/articles/PMC9213789/ /pubmed/35754832 http://dx.doi.org/10.3389/fgene.2022.938947 Text en Copyright © 2022 Wei, Zhang, Wang, Zhang, Hou, Yan and Wang. 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 Wei, Xia Zhang, Tian Wang, Ligang Zhang, Longchao Hou, Xinhua Yan, Hua Wang, Lixian Optimizing the Construction and Update Strategies for the Genomic Selection of Pig Reference and Candidate Populations in China |
title | Optimizing the Construction and Update Strategies for the Genomic Selection of Pig Reference and Candidate Populations in China |
title_full | Optimizing the Construction and Update Strategies for the Genomic Selection of Pig Reference and Candidate Populations in China |
title_fullStr | Optimizing the Construction and Update Strategies for the Genomic Selection of Pig Reference and Candidate Populations in China |
title_full_unstemmed | Optimizing the Construction and Update Strategies for the Genomic Selection of Pig Reference and Candidate Populations in China |
title_short | Optimizing the Construction and Update Strategies for the Genomic Selection of Pig Reference and Candidate Populations in China |
title_sort | optimizing the construction and update strategies for the genomic selection of pig reference and candidate populations in china |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9213789/ https://www.ncbi.nlm.nih.gov/pubmed/35754832 http://dx.doi.org/10.3389/fgene.2022.938947 |
work_keys_str_mv | AT weixia optimizingtheconstructionandupdatestrategiesforthegenomicselectionofpigreferenceandcandidatepopulationsinchina AT zhangtian optimizingtheconstructionandupdatestrategiesforthegenomicselectionofpigreferenceandcandidatepopulationsinchina AT wangligang optimizingtheconstructionandupdatestrategiesforthegenomicselectionofpigreferenceandcandidatepopulationsinchina AT zhanglongchao optimizingtheconstructionandupdatestrategiesforthegenomicselectionofpigreferenceandcandidatepopulationsinchina AT houxinhua optimizingtheconstructionandupdatestrategiesforthegenomicselectionofpigreferenceandcandidatepopulationsinchina AT yanhua optimizingtheconstructionandupdatestrategiesforthegenomicselectionofpigreferenceandcandidatepopulationsinchina AT wanglixian optimizingtheconstructionandupdatestrategiesforthegenomicselectionofpigreferenceandcandidatepopulationsinchina |