Molecular Design-Based Breeding: A Kinship Index-Based Selection Method for Complex Traits in Small Livestock Populations

Autor: Jiamin Gu, Jianwei Guo, Zhenyang Zhang, Yuejin Xu, Qamar Raza Qadri, Zhe Zhang, Zhen Wang, Qishan Wang, Yuchun Pan
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Genes; Volume 14; Issue 4; Pages: 807
ISSN: 2073-4425
DOI: 10.3390/genes14040807
Popis: 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.
Databáze: OpenAIRE