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Genetic gain and inbreeding from simulation of different genomic mating schemes for pig improvement

BACKGROUND: Genomic selection involves choosing as parents those elite individuals with the higher genomic estimated breeding values (GEBV) to accelerate the speed of genetic improvement in domestic animals. But after multi-generation selection, the rate of inbreeding and the occurrence of homozygou...

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Autores principales: Zhao, Fuping, Zhang, Pengfei, Wang, Xiaoqing, Akdemir, Deniz, Garrick, Dorian, He, Jun, Wang, Lixian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10262571/
https://www.ncbi.nlm.nih.gov/pubmed/37309010
http://dx.doi.org/10.1186/s40104-023-00872-x
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author Zhao, Fuping
Zhang, Pengfei
Wang, Xiaoqing
Akdemir, Deniz
Garrick, Dorian
He, Jun
Wang, Lixian
author_facet Zhao, Fuping
Zhang, Pengfei
Wang, Xiaoqing
Akdemir, Deniz
Garrick, Dorian
He, Jun
Wang, Lixian
author_sort Zhao, Fuping
collection PubMed
description BACKGROUND: Genomic selection involves choosing as parents those elite individuals with the higher genomic estimated breeding values (GEBV) to accelerate the speed of genetic improvement in domestic animals. But after multi-generation selection, the rate of inbreeding and the occurrence of homozygous harmful alleles might increase, which would reduce performance and genetic diversity. To mitigate the above problems, we can utilize genomic mating (GM) based upon optimal mate allocation to construct the best genotypic combinations in the next generation. In this study, we used stochastic simulation to investigate the impact of various factors on the efficiencies of GM to optimize pairing combinations after genomic selection of candidates in a pig population. These factors included: the algorithm used to derive inbreeding coefficients; the trait heritability (0.1, 0.3 or 0.5); the kind of GM scheme (focused average GEBV or inbreeding); the approach for computing the genomic relationship matrix (by SNP or runs of homozygosity (ROH)). The outcomes were compared to three traditional mating schemes (random, positive assortative or negative assortative matings). In addition, the performance of the GM approach was tested on real datasets obtained from a Large White pig breeding population. RESULTS: Genomic mating outperforms other approaches in limiting the inbreeding accumulation for the same expected genetic gain. The use of ROH-based genealogical relatedness in GM achieved faster genetic gains than using relatedness based on individual SNPs. The G(ROH)-based GM schemes with the maximum genetic gain resulted in 0.9%–2.6% higher rates of genetic gain ΔG, and 13%–83.3% lower ΔF than positive assortative mating regardless of heritability. The rates of inbreeding were always the fastest with positive assortative mating. Results from a purebred Large White pig population, confirmed that GM with ROH-based GRM was more efficient than traditional mating schemes. CONCLUSION: Compared with traditional mating schemes, genomic mating can not only achieve sustainable genetic progress but also effectively control the rates of inbreeding accumulation in the population. Our findings demonstrated that breeders should consider using genomic mating for genetic improvement of pigs. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40104-023-00872-x.
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spelling pubmed-102625712023-06-15 Genetic gain and inbreeding from simulation of different genomic mating schemes for pig improvement Zhao, Fuping Zhang, Pengfei Wang, Xiaoqing Akdemir, Deniz Garrick, Dorian He, Jun Wang, Lixian J Anim Sci Biotechnol Research BACKGROUND: Genomic selection involves choosing as parents those elite individuals with the higher genomic estimated breeding values (GEBV) to accelerate the speed of genetic improvement in domestic animals. But after multi-generation selection, the rate of inbreeding and the occurrence of homozygous harmful alleles might increase, which would reduce performance and genetic diversity. To mitigate the above problems, we can utilize genomic mating (GM) based upon optimal mate allocation to construct the best genotypic combinations in the next generation. In this study, we used stochastic simulation to investigate the impact of various factors on the efficiencies of GM to optimize pairing combinations after genomic selection of candidates in a pig population. These factors included: the algorithm used to derive inbreeding coefficients; the trait heritability (0.1, 0.3 or 0.5); the kind of GM scheme (focused average GEBV or inbreeding); the approach for computing the genomic relationship matrix (by SNP or runs of homozygosity (ROH)). The outcomes were compared to three traditional mating schemes (random, positive assortative or negative assortative matings). In addition, the performance of the GM approach was tested on real datasets obtained from a Large White pig breeding population. RESULTS: Genomic mating outperforms other approaches in limiting the inbreeding accumulation for the same expected genetic gain. The use of ROH-based genealogical relatedness in GM achieved faster genetic gains than using relatedness based on individual SNPs. The G(ROH)-based GM schemes with the maximum genetic gain resulted in 0.9%–2.6% higher rates of genetic gain ΔG, and 13%–83.3% lower ΔF than positive assortative mating regardless of heritability. The rates of inbreeding were always the fastest with positive assortative mating. Results from a purebred Large White pig population, confirmed that GM with ROH-based GRM was more efficient than traditional mating schemes. CONCLUSION: Compared with traditional mating schemes, genomic mating can not only achieve sustainable genetic progress but also effectively control the rates of inbreeding accumulation in the population. Our findings demonstrated that breeders should consider using genomic mating for genetic improvement of pigs. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40104-023-00872-x. BioMed Central 2023-06-13 /pmc/articles/PMC10262571/ /pubmed/37309010 http://dx.doi.org/10.1186/s40104-023-00872-x Text en © The Author(s) 2023 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
Zhao, Fuping
Zhang, Pengfei
Wang, Xiaoqing
Akdemir, Deniz
Garrick, Dorian
He, Jun
Wang, Lixian
Genetic gain and inbreeding from simulation of different genomic mating schemes for pig improvement
title Genetic gain and inbreeding from simulation of different genomic mating schemes for pig improvement
title_full Genetic gain and inbreeding from simulation of different genomic mating schemes for pig improvement
title_fullStr Genetic gain and inbreeding from simulation of different genomic mating schemes for pig improvement
title_full_unstemmed Genetic gain and inbreeding from simulation of different genomic mating schemes for pig improvement
title_short Genetic gain and inbreeding from simulation of different genomic mating schemes for pig improvement
title_sort genetic gain and inbreeding from simulation of different genomic mating schemes for pig improvement
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10262571/
https://www.ncbi.nlm.nih.gov/pubmed/37309010
http://dx.doi.org/10.1186/s40104-023-00872-x
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