Zhao Qingbo, Liu Huiming, Zhang Qian, Qadri Qamar Raza, Pan Yuchun, Su Guosheng, Li Pinghua, Huang Ruihua
Key Laboratory (Nanjing) for Evaluation and Utilization of Pigs Resources, College of Animal Science & Technology, Nanjing Agricultural University, Nanjing, People's Republic of China.
Center for Quantitative Genetics and Genomics, Faculty of Science and Technology, Aarhus University, Tjele, Denmark.
J Anim Breed Genet. 2025 Jul;142(4):444-453. doi: 10.1111/jbg.12917. Epub 2024 Dec 18.
Both selection and mating systems are essential tools for breeders to conserve the genetic variance and improve the performance of livestock animals. How to effectively balance the genetic gain and inbreeding has always been an important issue in quantitative genetics research. In this study, a total of 11 selection methods, including random and truncation selection, six conventional selection methods, three different optimal contribution selection (OCS) methods and three mating strategies including random mating, minimum-coancestry mating based on pedigree (MCPed) and genomic information (MCmarker), were performed using stochastic simulations. The long-term effects of different combinations of selection and mating strategies on the genetic gain, the rate of inbreeding and genetic diversity in the small-scale pig conservation populations were investigated. The results showed that different strategies of selection and mating methods had different effects on genetic gain and inbreeding rate. For maintaining additive genetic variance, the optimal strategy was random selection with random mating, followed by SIREhalf-DAMfullRandom selection (which means selecting dams randomly from each full-sib family) and random mating. For mainting the number of common ancestors, the optimal strategy was SIREhalf-DAMfull selection (which means selecting dams with the highest estimated breeding value within each full-sib family) and random mating, followed by SIREhalf-DAMfullRandom selection and random mating, OCS and MCPed mating. For genetic diversity metrics, taking He and Ho as an example, the optimal strategy was GOCS (optimal contribution selection based on genomic information) with MCmarker mating. For genetic gain, the optimal strategy was truncation selection and MCmarker mating, followed by POCS (optimal contribution selection based on pedigree information) and MCmarker mating, truncation selection and MCPed mating. For the rate of inbreeding, the optimal strategy was SIREhalf-DAMfull selection and MCPed mating. Our findings can help breeding managers and farmers choose a more suitable and sustainable strategy for maintaining the genetic diversity and improving the genetic gain of local pig breeds.
选择和交配系统都是育种者保护遗传变异和提高家畜性能的重要工具。如何有效平衡遗传进展和近亲繁殖一直是数量遗传学研究中的重要问题。在本研究中，使用随机模拟执行了总共11种选择方法，包括随机选择和截断选择、六种传统选择方法、三种不同的最优贡献选择（OCS）方法，以及三种交配策略，包括随机交配、基于系谱的最小亲缘关系交配（MCPed）和基于基因组信息的最小亲缘关系交配（MCmarker）。研究了不同选择和交配策略组合对小规模猪保种群中遗传进展、近亲繁殖率和遗传多样性的长期影响。结果表明，不同的选择和交配方法策略对遗传进展和近亲繁殖率有不同影响。为保持加性遗传方差，最优策略是随机选择与随机交配，其次是父本半同胞-母本全同胞随机选择（即从每个全同胞家系中随机选择母本）和随机交配。为保持共同祖先数量，最优策略是父本半同胞-母本全同胞选择（即从每个全同胞家系中选择估计育种值最高的母本）和随机交配，其次是父本半同胞-母本全同胞随机选择和随机交配、OCS和MCPed交配。对于遗传多样性指标，以杂合度（He）和观察杂合度（Ho）为例，最优策略是基于基因组信息的最优贡献选择（GOCS）与MCmarker交配。对于遗传进展，最优策略是截断选择和MCmarker交配，其次是基于系谱信息的最优贡献选择（POCS）和MCmarker交配、截断选择和MCPed交配。对于近亲繁殖率，最优策略是父本半同胞-母本全同胞选择和MCPed交配。我们的研究结果可以帮助育种管理者和养殖户选择更合适和可持续的策略来维持地方猪种的遗传多样性并提高其遗传进展。
