ArticleBMC systems biology2018
Transcriptomic and metabolic flux analyses reveal shift of metabolic patterns during rice grain development.
Article in BMC systems biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed, 17 citations in OpenAlex.
- Gene expression variations and allele-specific expression of two rice and their hybrid in caryopses at single-nucleus resolution.Frontiers in plant science · 2023Article
- Exploring synergies between plant metabolic modelling and machine learning.Computational and structural biotechnology journal · 2022Review
- Differentiation of the High Night Temperature Response in Leaf Segments of Rice Cultivars with Contrasting Tolerance.International journal of molecular sciences · 2021Article
- Metabolomics Analysis in Different Development Stages on SP0 Generation of Rice Seeds After Spaceflight.Frontiers in plant science · 2021Article
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Authors and funding
8 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundRice (Oryza sativa) is one of the most important grain crops, which serves as food source for nearly half of the world population. The study of rice development process as well as related strategies for production has made significant progress. However, the comprehensive study on development of different rice tissues at both transcriptomic and metabolic flux level across different stages was lacked.
resultsIn this study, we performed RNA-Seq and characterized the expression profiles of differentiated tissues from Oryza sativa Zhonghua 11, including leaves, sheath, stamen, pistil, lemma and palea of the booting stage, and embryo, endosperm, lemma and palea of the mature grain stage. By integrating this set of transcriptome data of different rice tissues at different stages with a genome-scale rice metabolic model, we generated tissue-specific models and investigated the shift of metabolic patterns, and the discrepancy between transcriptomic and metabolic level. We found although the flux patterns are not very similar with the gene expression pattern, the tissues at booting stage and mature grain stage can be separately clustered by primary metabolism at either level. While the gene expression and flux distribution of secondary metabolism is more diverse across tissues and stages. The critical rate-limiting reactions and pathways were also identified. In addition, we compared the patterns of the same tissue at different stages and the different tissues at same stage. There are more altered pathways at gene expression level than metabolic level, which indicate the metabolism is more robust to reflect the phenotype, and might largely because of the complex post-transcriptional modification.
conclusionsThe tissue-specific models revealed more detail metabolic pattern shift among different tissues and stages, which is of great significance to uncover mechanism of rice grain development and further improve production and quality of rice.
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