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Rice metabolic regulatory network spanning the entire life cycle

Authors :
Yuanyuan Lyu
Xuemei Liu
Yufei Li
Chenkun Yang
Qianqian Zhou
Jie Luo
Xianqing Liu
Longxu An
Wei Chen
Lianghuan Qu
Junjie Zhou
Yuyuan Mao
Wenju Peng
Shen Zhou
Shuangqian Shen
Shouchuang Wang
Yuheng Shi
Alisdair R. Fernie
Source :
Molecular Plant
Publication Year :
2022
Publisher :
Elsevier BV, 2022.

Abstract

As one of the most important crops in the world, rice (Oryza sativa) is a model plant for metabolome research. Although many studies have focused on the analysis of specific tissues, the changes in metabolite abundance across the entire life cycle have not yet been determined. In this study, combining both targeted and nontargeted metabolite profiling methods, a total of 825 annotated metabolites were quantified in rice samples from different tissues covering the entire life cycle. The contents of metabolites in different tissues of rice were significantly different, with various metabolites accumulating in the plumule and radicle during seed germination. Combining these data with transcriptome data obtained from the same time period, we constructed the Rice Metabolic Regulation Network. The metabolites and co-expressed genes were further divided into 12 clusters according to their accumulation patterns, with members within each cluster displaying a uniform and clear pattern of abundance across development. Using this dataset, we established a comprehensive metabolic profile of the rice life cycle and used two independent strategies to identify novel transcription factors—namely the use of known regulatory genes as bait to screen for new networks underlying lignin metabolism and the unbiased identification of new glycerophospholipid metabolism regulators on the basis of tissue specificity. This study thus demonstrates how guilt-by-association analysis of metabolome and transcriptome data spanning the entire life cycle in cereal crops provides novel resources and tools to aid in understanding the mechanisms underlying important agronomic traits.

Details

ISSN :
16742052
Volume :
15
Database :
OpenAIRE
Journal :
Molecular Plant
Accession number :
edsair.doi.dedup.....93dcb470bf0cbd7612e8a70d4546a4d4
Full Text :
https://doi.org/10.1016/j.molp.2021.10.005