Department of Genomics, Branch for Northwest & West Region, Agricultural Biotechnology Research Institute of Iran (ABRII), Agricultural Research, Education and Extension Organization (AREEO), Tabriz, Iran.
PLoS One. 2024 Aug 22;19(8):e0307248. doi: 10.1371/journal.pone.0307248. eCollection 2024.
In the current study, systems biology approach was applied to get a deep insight regarding the regulatory mechanisms of Chromochloris zofingiensis under overall stress conditions. Meta-analysis was performed using p-values combination of differentially expressed genes. To identify the informative models related to stress conditions, two distinct weighted gene co-expression networks were constructed and preservation analyses were performed using medianRankand Zsummary algorithms. Moreover, functional enrichment analysis of non-preserved modules was performed to shed light on the biological performance of underlying genes in the non-preserved modules. In the next step, the gene regulatory networks between top hub genes of non-preserved modules and transcription factors were inferred using ensemble of trees algorithm. Results showed that the power of beta = 7 was the best soft-thresholding value to ensure a scale-free network, leading to the determination of 12 co-expression modules with an average size of 128 genes. Preservation analysis showed that the connectivity pattern of the six modules including the blue, black, yellow, pink, greenyellow, and turquoise changed during stress condition which defined as non-preserved modules. Examples of enriched pathways in non-preserved modules were Oxidative phosphorylation", "Vitamin B6 metabolism", and "Arachidonic acid metabolism". Constructed regulatory network between identified TFs and top hub genes of non-preserved module such as Cz06g10250, Cz03g12130 showed that some specific TFs such as C3H and SQUAMOSA promoter binding protein (SBP) specifically regulates the specific hubs. The current findings add substantially to our understanding of the stress responsive underlying mechanism of C. zofingiensis for future studies and metabolite production programs.
在当前的研究中,采用系统生物学方法深入了解 Chromochloris zofingiensis 在整体应激条件下的调控机制。使用差异表达基因的 p 值组合进行荟萃分析。为了识别与应激条件相关的信息模型,构建了两个不同的加权基因共表达网络,并使用 medianRank 和 Zsummary 算法进行保存分析。此外,对非保存模块进行了功能富集分析,以揭示非保存模块中潜在基因的生物学性能。在下一步中,使用集成树算法推断非保存模块的顶级枢纽基因和转录因子之间的基因调控网络。结果表明,β=7 的幂是确保无标度网络的最佳软阈值值,导致确定了 12 个具有平均大小为 128 个基因的共表达模块。保存分析表明,包括蓝色、黑色、黄色、粉红色、黄绿色和绿松石色在内的六个模块的连接模式在应激条件下发生了变化,被定义为非保存模块。非保存模块中富集途径的示例包括“氧化磷酸化”、“维生素 B6 代谢”和“花生四烯酸代谢”。鉴定的 TFs 和非保存模块的顶级枢纽基因之间构建的调控网络,如 Cz06g10250、Cz03g12130,表明一些特定的 TFs,如 C3H 和 SQUAMOSA 启动子结合蛋白(SBP),特异性调节特定的枢纽。当前的发现极大地增加了我们对 C. zofingiensis 应激响应潜在机制的理解,为未来的研究和代谢产物生产计划提供了依据。