Zhang Xuehai, Huang Chenglong, Wu Di, Qiao Feng, Li Wenqiang, Duan Lingfeng, Wang Ke, Xiao Yingjie, Chen Guoxing, Liu Qian, Xiong Lizhong, Yang Wanneng, Yan Jianbing
National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research (X.Z., F.Q., W.L., Y.X., L.X., W.Y., J.Y.), College of Engineering (C.H., D.W., L.D., K.W., W.Y.), and Ministry of Agriculture Key Laboratory of Crop Ecophysiology and Farming System in the Middle Reaches of the Yangtze River (G.C.), Huazhong Agricultural University, Wuhan 430070, People's Republic of China; and.
Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, and Key Laboratory of the Ministry of Education for Biomedical Photonics, Department of Biomedical Engineering, Huazhong University of Science and Technology, Wuhan 430074, People's Republic of China (Q.L.).
Plant Physiol. 2017 Mar;173(3):1554-1564. doi: 10.1104/pp.16.01516. Epub 2017 Jan 30.
With increasing demand for novel traits in crop breeding, the plant research community faces the challenge of quantitatively analyzing the structure and function of large numbers of plants. A clear goal of high-throughput phenotyping is to bridge the gap between genomics and phenomics. In this study, we quantified 106 traits from a maize () recombinant inbred line population ( = 167) across 16 developmental stages using the automatic phenotyping platform. Quantitative trait locus (QTL) mapping with a high-density genetic linkage map, including 2,496 recombinant bins, was used to uncover the genetic basis of these complex agronomic traits, and 988 QTLs have been identified for all investigated traits, including three QTL hotspots. Biomass accumulation and final yield were predicted using a combination of dissected traits in the early growth stage. These results reveal the dynamic genetic architecture of maize plant growth and enhance ideotype-based maize breeding and prediction.
随着作物育种中对新性状的需求不断增加,植物研究界面临着对大量植物的结构和功能进行定量分析的挑战。高通量表型分析的一个明确目标是弥合基因组学和表型组学之间的差距。在本研究中,我们使用自动表型分析平台,对一个玉米重组自交系群体(n = 167)在16个发育阶段的106个性状进行了量化。利用包含2496个重组 bins 的高密度遗传连锁图谱进行数量性状位点(QTL)定位,以揭示这些复杂农艺性状的遗传基础,已为所有研究性状鉴定出988个QTL,包括三个QTL热点。利用早期生长阶段解析出的性状组合预测生物量积累和最终产量。这些结果揭示了玉米植株生长的动态遗传结构,并加强了基于理想型的玉米育种和预测。