| Literature DB >> 28153923 |
Xuehai Zhang1,2, Chenglong Huang1,2, Di Wu1,2, Feng Qiao1,2, Wenqiang Li1,2, Lingfeng Duan1,2, Ke Wang1,2, Yingjie Xiao1,2, Guoxing Chen1,2, Qian Liu1,2, Lizhong Xiong1,2, Wanneng Yang3,4, Jianbing Yan3,4.
Abstract
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 (Zea mays) recombinant inbred line population (n = 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.Entities:
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Year: 2017 PMID： 28153923 PMCID： PMC5338669 DOI： 10.1104/pp.16.01516
Source DB: PubMed Journal: Plant Physiol ISSN： 0032-0889 Impact factor: 8.340