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Molecular Design-Based Breeding: A Kinship Index-Based Selection Method for Complex Traits in Small Livestock Populations
Genomic selection (GS) techniques have improved animal breeding by enhancing the prediction accuracy of breeding values, particularly for traits that are difficult to measure and have low heritability, as well as reducing generation intervals. However, the requirement to establish genetic reference...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10137344/ https://www.ncbi.nlm.nih.gov/pubmed/37107565 http://dx.doi.org/10.3390/genes14040807 |
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author | Gu, Jiamin Guo, Jianwei Zhang, Zhenyang Xu, Yuejin Qadri, Qamar Raza Zhang, Zhe Wang, Zhen Wang, Qishan Pan, Yuchun |
author_facet | Gu, Jiamin Guo, Jianwei Zhang, Zhenyang Xu, Yuejin Qadri, Qamar Raza Zhang, Zhe Wang, Zhen Wang, Qishan Pan, Yuchun |
author_sort | Gu, Jiamin |
collection | PubMed |
description | Genomic selection (GS) techniques have improved animal breeding by enhancing the prediction accuracy of breeding values, particularly for traits that are difficult to measure and have low heritability, as well as reducing generation intervals. However, the requirement to establish genetic reference populations can limit the application of GS in pig breeds with small populations, especially when small populations make up most of the pig breeds worldwide. We aimed to propose a kinship index based selection (KIS) method, which defines an ideal individual with information on the beneficial genotypes for the target trait. Herein, the metric for assessing selection decisions is a beneficial genotypic similarity between the candidate and the ideal individual; thus, the KIS method can overcome the need for establishing genetic reference groups and continuous phenotype determination. We also performed a robustness test to make the method more aligned with reality. Simulation results revealed that compared to conventional genomic selection methods, the KIS method is feasible, particularly, when the population size is relatively small. |
format | Online Article Text |
id | pubmed-10137344 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-101373442023-04-28 Molecular Design-Based Breeding: A Kinship Index-Based Selection Method for Complex Traits in Small Livestock Populations Gu, Jiamin Guo, Jianwei Zhang, Zhenyang Xu, Yuejin Qadri, Qamar Raza Zhang, Zhe Wang, Zhen Wang, Qishan Pan, Yuchun Genes (Basel) Article Genomic selection (GS) techniques have improved animal breeding by enhancing the prediction accuracy of breeding values, particularly for traits that are difficult to measure and have low heritability, as well as reducing generation intervals. However, the requirement to establish genetic reference populations can limit the application of GS in pig breeds with small populations, especially when small populations make up most of the pig breeds worldwide. We aimed to propose a kinship index based selection (KIS) method, which defines an ideal individual with information on the beneficial genotypes for the target trait. Herein, the metric for assessing selection decisions is a beneficial genotypic similarity between the candidate and the ideal individual; thus, the KIS method can overcome the need for establishing genetic reference groups and continuous phenotype determination. We also performed a robustness test to make the method more aligned with reality. Simulation results revealed that compared to conventional genomic selection methods, the KIS method is feasible, particularly, when the population size is relatively small. MDPI 2023-03-27 /pmc/articles/PMC10137344/ /pubmed/37107565 http://dx.doi.org/10.3390/genes14040807 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Gu, Jiamin Guo, Jianwei Zhang, Zhenyang Xu, Yuejin Qadri, Qamar Raza Zhang, Zhe Wang, Zhen Wang, Qishan Pan, Yuchun Molecular Design-Based Breeding: A Kinship Index-Based Selection Method for Complex Traits in Small Livestock Populations |
title | Molecular Design-Based Breeding: A Kinship Index-Based Selection Method for Complex Traits in Small Livestock Populations |
title_full | Molecular Design-Based Breeding: A Kinship Index-Based Selection Method for Complex Traits in Small Livestock Populations |
title_fullStr | Molecular Design-Based Breeding: A Kinship Index-Based Selection Method for Complex Traits in Small Livestock Populations |
title_full_unstemmed | Molecular Design-Based Breeding: A Kinship Index-Based Selection Method for Complex Traits in Small Livestock Populations |
title_short | Molecular Design-Based Breeding: A Kinship Index-Based Selection Method for Complex Traits in Small Livestock Populations |
title_sort | molecular design-based breeding: a kinship index-based selection method for complex traits in small livestock populations |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10137344/ https://www.ncbi.nlm.nih.gov/pubmed/37107565 http://dx.doi.org/10.3390/genes14040807 |
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