Transcriptomic and phylogenetic analysis of a bacterial cell cycle reveals strong associations between gene co-expression and evolution
Transcriptomic and phylogenetic analysis of a bacterial cell cycle reveals strong associations between gene co-expression and evolution
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DOI：
10.1186/1471-2164-14-450
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发表时间：
2013-07-05
期刊：
影响因子：
4.4
通讯作者：
Jacobs-Wagner, Christine
中科院分区：
文献类型：
--
作者：
Fang, Gang;Passalacqua, Karla D.;Jacobs-Wagner, Christine
背景资料：参与细菌细胞周期的遗传网络知之甚少，尽管它支撑着细菌非凡的增殖能力。这种网络如何演变甚至不太清楚。本研究的主要目的是鉴定和分析新月柄杆菌细胞周期中差异表达的基因和途径，并分析细胞周期网络的进化特征。crescentus细胞周期阶段，每个阶段有三个生物学重复。我们发现，1,586个基因（超过基因组的三分之一）在不同阶段之间显示出显著的差异表达。这个基因列表，其中包含许多基因以前未知的细胞周期调控，包括几乎一半的基因参与初级代谢，这表明这些“管家”基因不是组成型转录在细胞周期中，因为通常假设。基因和模块共表达聚类揭示了共调节途径，并建议功能耦合的基因。此外，对细胞周期网络的进化分析表明，共表达和共进化之间存在高度相关性。大多数共表达模块具有强烈的系统发育信号，广泛保守的基因和进化枝特异性基因主导细胞周期共表达网络的不同亚结构。我们还发现，保守的基因往往决定其module.Conclusion的表达谱：我们描述了第一个系统发育和单核苷酸分辨率的转录组学分析的细菌细胞周期网络。此外，该研究还表明了进化如何塑造了这个网络，并提供了直接的生物网络支持，即选择压力不是在单个基因上，而是在基因之间的关系上，这突出了将系统发育分析整合到生物网络研究中的重要性。
Background: The genetic network involved in the bacterial cell cycle is poorly understood even though it underpins the remarkable ability of bacteria to proliferate. How such network evolves is even less clear. The major aims of this work were to identify and examine the genes and pathways that are differentially expressed during the Caulobacter crescentus cell cycle, and to analyze the evolutionary features of the cell cycle network.Results: We used deep RNA sequencing to obtain high coverage RNA-Seq data of five C. crescentus cell cycle stages, each with three biological replicates. We found that 1,586 genes (over a third of the genome) display significant differential expression between stages. This gene list, which contains many genes previously unknown for their cell cycle regulation, includes almost half of the genes involved in primary metabolism, suggesting that these "house-keeping" genes are not constitutively transcribed during the cell cycle, as often assumed. Gene and module co-expression clustering reveal co-regulated pathways and suggest functionally coupled genes. In addition, an evolutionary analysis of the cell cycle network shows a high correlation between co-expression and co-evolution. Most co-expression modules have strong phylogenetic signals, with broadly conserved genes and clade-specific genes predominating different substructures of the cell cycle co-expression network. We also found that conserved genes tend to determine the expression profile of their module.Conclusion: We describe the first phylogenetic and single-nucleotide-resolution transcriptomic analysis of a bacterial cell cycle network. In addition, the study suggests how evolution has shaped this network and provides direct biological network support that selective pressure is not on individual genes but rather on the relationship between genes, which highlights the importance of integrating phylogenetic analysis into biological network studies.