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Identification of Key Genes for the Ultrahigh Yield of Rice Using Dynamic Cross-tissue Network Analysis

文献类型： 外文期刊

作者： Hu, Jihong 1 ; Zeng, Tao 3 ; Xia, Qiongmei 5 ; Huang, Liyu 6 ; Zhang, Yesheng 1 ; Zhang, Chuanchao 3 ; Zeng, Yan 1 ; Liu, 1 ;

作者机构： 1.Chinese Acad Sci, Kunming Inst Zool, State Key Lab Genet Resources & Evolut, Kunming 650223, Yunnan, Peoples R China

2.Wuhan Univ, Coll Life Sci, State Key Lab Hybrid Rice, Wuhan 430072, Peoples R China

3.Chinese Acad Sci, Shanghai Inst Biol Sci, Inst Biochem & Cell Biol, Ctr Excellence Mol Cell Sci,CAS Key Lab Syst Biol, Shanghai 200031, Peoples R China

4.Inst Brain Intelligence Technol, Zhangjiang Lab, Shanghai 201210, Peoples R China

5.Yunnan Acad Agr Sci, Inst Food Crop, Kunming 650205, Yunnan, Peoples R China

6.Yunnan Univ, Sch Agr, Kunming 650500, Yunnan, Peoples R China

7.BGI Baoshan, Baoshan 678004, Peoples R China

8.Northwestern Polytech Univ, Ctr Ecol & Environm Sci, Xian 710072, Peoples R China

9.ShanghaiTech Univ, Sch Life Sci & Technol, Shanghai 201210, Peoples R China

关键词： Dynamic cross-tissue (DCT); Systems biology; RNA-seq; Ultrahigh yield; Rice

期刊名称：GENOMICS PROTEOMICS & BIOINFORMATICS （ 影响因子：7.691； 五年影响因子：11.12 ）

ISSN： 1672-0229

年卷期： 2020 年 18 卷 3 期

页码：

收录情况： SCI

摘要： Significantly increasing crop yield is a major and worldwide challenge for food supply and security. It is well-known that rice cultivated at Taoyuan in Yunnan of China can produce the highest yield worldwide. Yet, the gene regulatory mechanism underpinning this ultrahigh yield has been a mystery. Here, we systematically collected the transcriptome data for seven key tissues at different developmental stages using rice cultivated both at Taoyuan as the case group and at another regular rice planting place Jinghong as the control group. We identified the top 24 candidate high-yield genes with their network modules from these well-designed datasets by developing a novel computational systems biology method, i.e., dynamic cross-tissue (DCT) network analysis. We used one of the candidate genes, OsSPL4, whose function was previously unknown, for gene editing experimental validation of the high yield, and confirmed that OsSPL4 significantly affects panicle branching and increases the rice yield. This study, which included extensive field phenotyping, cross-tissue systems biology analyses, and functional validation, uncovered the key genes and gene regulatory networks underpinning the ultrahigh yield of rice. The DCT method could be applied to other plant or animal systems if different phenotypes under various environments with the common genome sequences of the examined sample. DCT can be downloaded from https://github.com/zt-pub DCT.

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