4.8 Article

Comparative analysis of metabolome of rice seeds at three developmental stages using a recombinant inbred line population

Journal

PLANT JOURNAL
Volume 100, Issue 5, Pages 908-922

Publisher

WILEY
DOI: 10.1111/tpj.14482

Keywords

rice seeds; metabolome; seeds during grain filling; mature seeds; germinating seeds; metabolic quantitative trait loci

Categories

Funding

  1. National Science Fund for Distinguished Young Scholars [31625021]
  2. State Key Program of National Natural Science Foundation of China [31530052]
  3. National Natural Science Foundation of China [31800250, 31960063]
  4. Hainan University Startup Fund [KYQD (ZR) 1866, KYQD(ZR) 1824]

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Plants are considered an important food and nutrition source for humans. Despite advances in plant seed metabolomics, knowledge about the genetic and molecular bases of rice seed metabolomes at different developmental stages is still limited. Here, using Zhenshan 97 (ZS97) and Minghui 63 (MH63), we performed a widely targeted metabolic profiling in seeds during grain filling, mature seeds and germinating seeds. The diversity between MH63 and ZS97 was characterized in terms of the content of metabolites and the metabolic shifting across developmental stages. Taking advantage of the ultra-high-density genetic map of a population of 210 recombinant inbred lines (RILs) derived from a cross between ZS97 and MH63, we identified 4681 putative metabolic quantitative trait loci (mQTLs) in seeds across the three stages. Further analysis of the mQTLs for the codetected metabolites across the three stages revealed that the genetic regulation of metabolite accumulation was closely related to developmental stage. Using in silico analyses, we characterized 35 candidate genes responsible for 30 structurally identified or annotated compounds, among which LOC_Os07g04970 and LOC_Os06g03990 were identified to be responsible for feruloylserotonin and l-asparagine content variation across populations, respectively. Metabolite-agronomic trait association and colocation between mQTLs and phenotypic quantitative trait loci (pQTLs) revealed the complexity of the metabolite-agronomic trait relationship and the corresponding genetic basis.

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