Oh S-H
Asian-Australas J Anim Sci. 2012 Mar;25(3):299-303. doi: 10.5713/ajas.2011.11315.
Inbreeding is the mating of relatives that produce progeny having more homozygous alleles than non-inbred animals. Inbreeding increases numbers of recessive alleles, which is often associated with decreased performance known as inbreeding depression. The magnitude of inbreeding depression depends on the level of inbreeding in the animal. Level of inbreeding is expressed by the inbreeding coefficient. One breeding goal in livestock is uniform productivity while maintaining acceptable inbreeding levels, especially keeping inbreeding less than 20%. However, in closed herds without the introduction of new genetic sources high levels of inbreeding over time are unavoidable. One method that increases selection response and minimizes inbreeding is selection of individuals by weighting estimated breeding values with average relationships among individuals. Optimum genetic contribution theory (OGC) uses relationships among individuals as weighting factors. The algorithm is as follows: i) Identify the individual having the best EBV; ii) Calculate average relationships ( [Formula: see text]) between selected and candidates; iii) Select the individual having the best EBV adjusted for average relationships using the weighting factor k, [Formula: see text]. iv) Repeat process until the number of individuals selected equals number required. The objective of this study was to compare simulated results based on OGC selection under different conditions over 30 generations. Individuals (n = 110) were generated for the base population with pseudo random numbers of N~ (0, 3), ten were assumed male, and the remainder female. Each male was mated to ten females, and every female was assumed to have 5 progeny resulting in 500 individuals in the following generation. Results showed the OGC algorithm effectively controlled inbreeding and maintained consistent increases in selection response. Difference in breeding values between selection with OGC algorithm and by EBV only was 8%, however, rate of inbreeding was controlled by 47% after 20 generation. These results indicate that the OGC algorithm can be used effectively in long-term selection programs.
近亲繁殖是指亲属之间的交配，其产生的后代比非近亲繁殖动物具有更多的纯合等位基因。近亲繁殖会增加隐性等位基因的数量，这通常与被称为近亲繁殖衰退的性能下降有关。近亲繁殖衰退的程度取决于动物的近亲繁殖水平。近亲繁殖水平由近亲繁殖系数表示。家畜育种的一个目标是在保持可接受的近亲繁殖水平的同时实现均匀的生产力，特别是将近亲繁殖率保持在20%以下。然而，在没有引入新基因源的封闭畜群中，随着时间的推移，高水平的近亲繁殖是不可避免的。一种增加选择反应并使近亲繁殖最小化的方法是通过个体间平均亲缘关系对估计育种值进行加权来选择个体。最优遗传贡献理论（OGC）将个体间的亲缘关系用作加权因子。算法如下：i）识别具有最佳估计育种值（EBV）的个体；ii）计算所选个体与候选个体之间的平均亲缘关系（[公式：见原文]）；iii）使用加权因子k，[公式：见原文]，选择经平均亲缘关系调整后具有最佳EBV的个体。iv）重复该过程，直到所选个体数量等于所需数量。本研究的目的是比较基于OGC选择在30代不同条件下的模拟结果。使用服从N~（0,3）的伪随机数为基础群体生成个体（n = 110），假定其中10个为雄性，其余为雌性。每个雄性与10个雌性交配，假定每个雌性有5个后代，从而在下一代产生500个个体。结果表明，OGC算法有效地控制了近亲繁殖，并使选择反应持续增加。使用OGC算法选择与仅通过EBV选择之间的育种值差异为8%，然而，20代后近亲繁殖率得到了47%的控制。这些结果表明，OGC算法可有效地用于长期选择计划。
