Yabe Shiori, Iwata Hiroyoshi, Jannink Jean-Luc
Dep. of Agricultural and Environmental Biology, Graduate School of Agricultural and Life Science, The Univ. of Tokyo, Bunkyo, Tokyo 113-8657, Japan.
USDA-ARS, Robert W. Holley Center for Agriculture and Health, and Cornell Univ. Section of Plant Breeding and Genetics, Ithaca, NY 14853.
Crop Sci. 2018 Jul-Aug;58:1470-1480. doi: 10.2135/cropsci2017.07.0442. Epub 2018 Jun 21.
In plant breeding, humans occasionally make mistakes. Genomic selection is particularly prone to human error because it involves more steps than conventional phenotypic selection. The impact of human mistakes should be determined to evaluate the cost effectiveness of controlling human error in plant breeding. We used simulation to evaluate the impact of mislabeling, where marker scores from one plant are associated with the performance records of another plant in cassava ( Crantz) breeding. Results showed that, although selection with mislabeling reduced genetic gains, scenarios including six levels of mislabeling (from 5 to 50%) persisted in achieving gain because mislabeling decreased the genetic variance lost from the population. Breeding populations with higher rates of mislabeling experienced lower selection intensity, resulting in higher genetic variance, which partially compensated for the mislabeling. For low mislabeling rates (10% or less), the increased genetic variance observed under mislabeling led to improved accuracy of the prediction model in later selection cycles. Large-scale mislabeling should therefore be prevented, but the value of preventing small-scale mislabeling depends on the effort already being invested in preventing the loss of genetic variance during the course of selection. In a program, such as the one we simulated, that makes no effort to avoid loss of genetic variance, small-scale mislabeling has a less negative effect than expected. We assume that negative effects would be greater if best practices to avoid genetic variance loss were already implemented.
在植物育种中,人类偶尔会犯错。基因组选择特别容易出现人为错误,因为它比传统的表型选择涉及更多步骤。应该确定人为错误的影响,以评估控制植物育种中人为错误的成本效益。我们通过模拟来评估错误标记的影响,即在木薯(Crantz)育种中,将一株植物的标记分数与另一株植物的性能记录相关联。结果表明,尽管存在错误标记的选择会降低遗传增益,但包括六个错误标记水平(从5%到50%)的情况仍能实现增益,因为错误标记减少了群体中损失的遗传方差。错误标记率较高的育种群体经历的选择强度较低,导致遗传方差较高,这部分补偿了错误标记的影响。对于低错误标记率(10%或更低),在错误标记情况下观察到的遗传方差增加导致后期选择周期中预测模型的准确性提高。因此,应防止大规模错误标记,但防止小规模错误标记的价值取决于在选择过程中已经投入的防止遗传方差损失的努力。在一个像我们模拟的那样不努力避免遗传方差损失的项目中,小规模错误标记的负面影响比预期的要小。我们假设,如果已经实施了避免遗传方差损失的最佳做法,负面影响会更大。