State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China; State Key Laboratory of Hybrid Rice, College of Life Sciences, Wuhan University, Wuhan 430072, China.
CAS Key Laboratory of Systems Biology, Center for Excellence in Molecular Cell Science, Institute of Biochemistry and Cell Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China; Institute of Brain-Intelligence Technology, Zhangjiang Laboratory, Shanghai 201210, China.
Genomics Proteomics Bioinformatics. 2020 Jun;18(3):256-270. doi: 10.1016/j.gpb.2019.11.007. Epub 2020 Jul 28.
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/ztpub/DCT.
大幅提高作物产量是全球粮食供应和安全面临的主要挑战。众所周知，中国云南桃园种植的水稻可以达到全球最高的产量。然而，支撑这种超高产量的基因调控机制一直是个谜。在这里，我们系统地收集了来自桃园和另一个常规水稻种植地景洪的水稻在不同发育阶段的七个关键组织的转录组数据。我们通过开发一种新的计算系统生物学方法，即动态跨组织（DCT）网络分析，从这些精心设计的数据集确定了前 24 个候选高产基因及其网络模块。我们使用候选基因之一 OsSPL4 进行了高产的基因编辑实验验证，该基因的功能以前未知，并证实 OsSPL4 显著影响穗分枝并增加了水稻产量。这项研究包括广泛的田间表型分析、跨组织系统生物学分析和功能验证，揭示了水稻超高产的关键基因和基因调控网络。如果有共同的基因组序列，DCT 方法可以应用于其他植物或动物系统，用于研究不同环境下的不同表型。DCT 可从 https://github.com/ztpub/DCT 下载。
