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.
农作物产量的显著提升是关系到全世界食物供给和粮食安全的重大问题。在中国云南涛源地区，发现在自然条件下的水稻种植能获得超高的产量，然而，这种超高产水稻的调控机理一直是个尚未可知。为揭示这个谜团，本研究在持续4年大大田实验基础上，同时收集涛源和景洪（对照）地区影响水稻产量和生长发育的7个关键组织，进行转录组测序。利用自主开发的计算系统生物学算法，动态跨组织隐变量网络整合分析(dynamic cross-tissue，DCT) 对转录组数据进行系统的生物信息学分析，鉴定到了24个候选高产基因以及相关网络模块。与此同时，我们对其中一个未知功能的候选基因 OsSPL4，进行了基因编辑（CRISPR/Cas9）转基因实验，验证其确实能够显著增加幼穗分枝，进而提高水稻产量。本研究通过大量的田间实验，跨组织的系统生物学分析，功能验证，综合揭示了涛源水稻超高产的关键基因和关键调控网络。我们开发的DCT模型与算法将能广泛应用于其他动植物在相同基因组情况下，由于环境条件不同而引起表型显著差异的分子机理研究。DCT的程序包可以在https://github.com/ztpub/DCT获得。





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