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Transcriptomic and metabolic flux analyses reveal shift of metabolic patterns during rice grain development

Overview of attention for article published in BMC Systems Biology, April 2018
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Title
Transcriptomic and metabolic flux analyses reveal shift of metabolic patterns during rice grain development
Published in
BMC Systems Biology, April 2018
DOI 10.1186/s12918-018-0574-x
Pubmed ID
Authors

Fangzhou Shen, Xueting Wu, Luoxi Shi, Hang Zhang, Yangmin Chen, Xiaoquan Qi, Zhuo Wang, Xuan Li

Abstract

Rice (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. In 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. The 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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Mendeley readers

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Geographical breakdown

Country Count As %
Unknown 27 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 22%
Student > Bachelor 4 15%
Student > Ph. D. Student 3 11%
Student > Doctoral Student 2 7%
Student > Master 2 7%
Other 5 19%
Unknown 5 19%
Readers by discipline Count As %
Agricultural and Biological Sciences 9 33%
Biochemistry, Genetics and Molecular Biology 7 26%
Medicine and Dentistry 2 7%
Unknown 9 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 11 May 2018.
All research outputs
#22,767,715
of 25,382,440 outputs
Outputs from BMC Systems Biology
#1,004
of 1,132 outputs
Outputs of similar age
#299,700
of 339,945 outputs
Outputs of similar age from BMC Systems Biology
#34
of 47 outputs
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