Department of Crop and Soil Sciences, North Carolina State University, Raleigh, NC 27695, USA.
Department of Plant and Soil Sciences, University of Delaware, Newark, DE 19716, USA.
G3 (Bethesda). 2023 Aug 30;13(9). doi: 10.1093/g3journal/jkad141.
Tropical maize can be used to diversify the genetic base of temperate germplasm and help create climate-adapted cultivars. However, tropical maize is unadapted to temperate environments, in which sensitivities to long photoperiods and cooler temperatures result in severely delayed flowering times, developmental defects, and little to no yield. Overcoming this maladaptive syndrome can require a decade of phenotypic selection in a targeted, temperate environment. To accelerate the incorporation of tropical diversity in temperate breeding pools, we tested if an additional generation of genomic selection can be used in an off-season nursery where phenotypic selection is not very effective. Prediction models were trained using flowering time recorded on random individuals in separate lineages of a heterogenous population grown at two northern U.S. latitudes. Direct phenotypic selection and genomic prediction model training was performed within each target environment and lineage, followed by genomic prediction of random intermated progenies in the off-season nursery. Performance of genomic prediction models was evaluated on self-fertilized progenies of prediction candidates grown in both target locations in the following summer season. Prediction abilities ranged from 0.30 to 0.40 among populations and evaluation environments. Prediction models with varying marker effect distributions or spatial field effects had similar accuracies. Our results suggest that genomic selection in a single off-season generation could increase genetic gains for flowering time by more than 50% compared to direct selection in summer seasons only, reducing the time required to change the population mean to an acceptably adapted flowering time by about one-third to one-half.
热带玉米可以用来丰富温带种质的遗传基础，并有助于培育适应气候的品种。然而，热带玉米不适应温带环境，在温带环境中，对长光照期和较低温度的敏感性导致开花时间严重延迟、发育缺陷，几乎没有产量。克服这种适应不良的综合征可能需要在有针对性的温带环境中进行十年的表型选择。为了加速将热带多样性纳入温带育种群体，我们测试了在非季节性苗圃中是否可以使用额外一代的基因组选择，而在非季节性苗圃中，表型选择效果不佳。使用在两个美国北部纬度种植的异质群体的随机个体记录的开花时间来训练预测模型。在每个目标环境和谱系中进行直接表型选择和基因组预测模型训练，然后在非季节性苗圃中对随机互交后代进行基因组预测。在接下来的夏季，在两个目标地点种植预测候选者的自交后代，评估基因组预测模型的性能。在不同的群体和评估环境中，预测能力的范围从 0.30 到 0.40。具有不同标记效应分布或空间场效应的预测模型具有相似的准确性。我们的结果表明，与仅在夏季进行直接选择相比，在一个非季节性世代中进行基因组选择可以使开花时间的遗传增益增加 50%以上，将群体平均值改变为可接受的适应开花时间所需的时间减少约三分之一到一半。
