Estimation of realized rates of genetic gain and indicators for breeding program assessment
Estimation of realized rates of genetic gain and indicators for breeding program assessment
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遗传增益实现率估算和育种计划评估指标
DOI：
10.1101/409342
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
Jessica Rutkoski
中科院分区：
文献类型：
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作者：
Jessica Rutkoski
已提出对育种计划实现的遗传增益率 (ΔGt) 进行常规估计作为监测其有效性的一种手段。其他研究中已经使用了几种实现 ΔGt 估计的方法，但没有一种方法在植物育种背景下得到客观评估。对 28 年来 80 个水稻 (Oryza sativa) 育种计划进行了随机模拟，生成数据，用于评估已实现的 ΔGt 估计的五种方法的误差、精度、效率以及真实与预测的年平均育种值之间的相关性。描述和评估了 ΔGt 的两个指标，即预期 ΔGt 和等效完整世代的平均数 (EqCg)。考虑到所有 28 年和过去 15 年的育种，实现的 ΔGt 估计最多分别高估或低估了 15% 和 27%。最好的方法是对照种群、估计育种值和ERA试验方法。其中，真实ΔGt与估计ΔGt之间的相关性最多为0.59，表明这些方法不能非常准确地根据实现的ΔGt对育种计划进行排名。预期 ΔGt 和平均 EqCg 被证明是确定是否预期非零遗传增益的有用指标。确定评估的三种最佳实现的 ΔGt 估计方法（如果有）中的哪一种适合任何给定的育种计划，应仔细考虑目标、资源、种子库存和可用数据的结构。
Routine estimation of the rate of genetic gain (ΔGt) realized by a breeding program has been proposed as a means to monitor its effectiveness. Several methods of realized ΔGt estimation have been utilized in other studies, but none have been objectively evaluated in a plant breeding context. Stochastic simulations of 80 rice (Oryza sativa) breeding programs over 28 years were done to generate data used to evaluate five methods of realized ΔGt estimation in terms of error, precision, efficiency and correlation between true and predicted annual mean breeding values. Two indicators of ΔGt, the expected ΔGt and the average number of equivalent complete generations (EqCg), were described and evaluated. At best, estimates of realized ΔGt were over or underestimated by 15% and 27% when considering all 28 years and the past 15 years of breeding respectively. The best methods were the control population, estimated breeding value, and ERA trial methods. Among these, correlations between true and estimated ΔGt were at best 0.59, indicating that these methods cannot very accurately rank breeding programs in terms of realized ΔGt. The expected ΔGt and the average EqCg were shown to be useful indicators for determining if a non-zero genetic gain is expected. Determining which of the three best realized ΔGt estimation methods evaluated, if any, would be appropriate for any given breeding program should be done with careful consideration of the objectives, resources, seed stocks, and structure of the data available.