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Quantile regression in genomic selection for oligogenic traits in autogamous plants: A simulation study
PLOS ONE ( IF 3.7 ) Pub Date : 2021-01-05 , DOI: 10.1371/journal.pone.0243666
Gabriela França Oliveira , Ana Carolina Campana Nascimento , Moysés Nascimento , Isabela de Castro Sant'Anna , Juan Vicente Romero , Camila Ferreira Azevedo , Leonardo Lopes Bhering , Eveline Teixeira Caixeta Moura

This study assessed the efficiency of Genomic selection (GS) or genome‐wide selection (GWS), based on Regularized Quantile Regression (RQR), in the selection of genotypes to breed autogamous plant populations with oligogenic traits. To this end, simulated data of an F2 population were used, with traits with different heritability levels (0.10, 0.20 and 0.40), controlled by four genes. The generations were advanced (up to F6) at two selection intensities (10% and 20%). The genomic genetic value was computed by RQR for different quantiles (0.10, 0.50 and 0.90), and by the traditional GWS methods, specifically RR-BLUP and BLASSO. A second objective was to find the statistical methodology that allows the fastest fixation of favorable alleles. In general, the results of the RQR model were better than or equal to those of traditional GWS methodologies, achieving the fixation of favorable alleles in most of the evaluated scenarios. At a heritability level of 0.40 and a selection intensity of 10%, RQR (0.50) was the only methodology that fixed the alleles quickly, i.e., in the fourth generation. Thus, it was concluded that the application of RQR in plant breeding, to simulated autogamous plant populations with oligogenic traits, could reduce time and consequently costs, due to the reduction of selfing generations to fix alleles in the evaluated scenarios.



中文翻译:

配子体寡聚性状基因组选择的分位数回归:模拟研究

这项研究基于正则化分位数回归(RQR)评估了基因组选择(GS)或全基因组选择(GWS)的效率,以选择基因型来繁殖具有寡聚性状的自生植物种群。为此,使用了F 2种群的模拟数据,这些特征具有不同的遗传水平(0.10、0.20和0.40),由四个基因控制。几代人都进步了(直到F 6)在两个选择强度下(10%和20%)。通过RQR计算不同分位数(0.10、0.50和0.90)的基因组遗传值,并通过传统的GWS方法,特别是RR-BLUP和BLASSO计算得出。第二个目标是找到可以最快固定有利等位基因的统计方法。一般而言,RQR模型的结果优于或等于传统GWS方法的结果,从而在大多数评估方案中实现了有利等位基因的固定。在遗传水平为0.40和选择强度为10%的情况下,RQR(0.50)是唯一可以快速固定等位基因的方法,即在第四代中。因此,可以得出结论,RQR在植物育种中对具有寡聚性状的模拟自生植物种群的应用可以减少时间,从而降低成本,

更新日期:2021-01-06
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