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High-Throughput Phenotyping and QTL Mapping Reveals the Genetic Architecture of Maize Plant Growth
Author(s) -
Xuehai Zhang,
Chenglong Huang,
Di Wu,
Feng Qiao,
Wenqiang Li,
Lingfeng Duan,
Ke Wang,
Yingjie Xiao,
Guoxing Chen,
Qian Liu,
Lizhong Xiong,
Wanneng Yang,
Jianbing Yan
Publication year - 2017
Publication title -
plant physiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.554
H-Index - 312
eISSN - 1532-2548
pISSN - 0032-0889
DOI - 10.1104/pp.16.01516
Subject(s) - quantitative trait locus , genetic architecture , biology , throughput , computational biology , microbiology and biotechnology , genetics , gene , computer science , telecommunications , wireless
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.

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