Tea plants adjust development and metabolism by integrating environmental and endogenous signals in complex but poorly defined gene networks. Here, we present an integrative analysis framework for the identification of conserved modules controlling important agronomic traits using a comprehensive collection of RNA-seq datasets in Camellia plants including 189 samples. In total, 212 secondary metabolism, 182 stress response, and 182 tissue development-related coexpressed modules were revealed. Functional modules (e.g., drought response, theobromine biosynthesis, and new shoot development-related modules) and potential regulators that were highly conserved across diverse genetic backgrounds and/or environmental conditions were then identified by cross-experiment comparisons and consensus clustering. Moreover, we investigate the preservation of gene networks between Camellia sinensis and other Camellia species. This revealed that the coexpression patterns of several recently evolved modules related to secondary metabolism and environmental adaptation were rewired and showed higher connectivity in tea plants. These conserved modules are excellent candidates for modeling the core mechanism of tea plant development and secondary metabolism and should serve as a great resource for hypothesis generation and tea quality improvement.

茶树通过将环境信号和内源信号整合到复杂但并不明确的基因网络中来调节发育和代谢。本文利用189份山茶属植物的RNA-seq数据集，提出了一个综合分析框架，用于鉴定重要农艺性状的保守模组。共发现212个次级代谢、182个应激反应和182个组织发育相关的共表达模块。然后，通过交叉实验比较和共识聚类，鉴定在不同遗传背景和/或环境条件下高度保守的功能模块(如干旱响应、可可碱生物合成和新茎发育相关模块)和潜在调控因子。此外，我们还研究了茶树与其他山茶植物之间基因网络的保守情况。结果表明，茶树中与次生代谢和环境适应有关的几个最近进化的模块的共表达模式被重新排列并显示出更高的连通性。这些保守模块是构建茶树发育和次生代谢核心机制的优良候选模型，可以作为假说提出和茶叶品质改良的重要资源。【百度翻译，仅供参考】