Meta-analysis reveals conserved cell cycle transcriptional network across multiple human cell types.
Meta-analysis reveals conserved cell cycle transcriptional network across multiple human cell types.
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DOI：
10.1186/s12864-016-3435-2
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发表时间：
2017-01-05
期刊：
影响因子：
4.4
通讯作者：
Freeman TC
中科院分区：
文献类型：
--
作者：
Giotti B;Joshi A;Freeman TC
细胞分裂是所有真核生物生理学和病理学的核心。支持细胞周期的分子机制已经在许多物种中进行了广泛的研究，并且已经发现其核心方面是高度保守的。类似地，在不同生物体和不同细胞类型中研究了与该途径相关的转录变化。据报道，在每种情况下，都有数百个基因受到调控，然而，在不同研究中鉴定的基因似乎很少有共识。在最近对不同人类细胞类型的细胞周期的转录组学研究的比较中，只有96个细胞周期基因被报道在所有研究中是相同的。在这里，我们使用基于网络的方法对已发表的人类细胞周期表达数据进行系统的重新检查，以识别具有相似表达谱的基因组，从而确定功能。特别是包含298个转录本的两个簇，显示出与评估的四种人类细胞类型的细胞周期发生一致的表达模式。我们的分析表明，在人类细胞类型中，细胞周期相关基因表达的保守性比以前报道的要大得多，这可以分为与细胞周期的G1/S-S和G2-M期相关的两个不同的转录网络。这项工作还强调了对组合数据集进行重新分析的好处。本文的在线版本（doi：10.1186/s12864-016-3435-2）包含补充材料，可供授权用户使用。
Cell division is central to the physiology and pathology of all eukaryotic organisms. The molecular machinery underpinning the cell cycle has been studied extensively in a number of species and core aspects of it have been found to be highly conserved. Similarly, the transcriptional changes associated with this pathway have been studied in different organisms and different cell types. In each case hundreds of genes have been reported to be regulated, however there seems to be little consensus in the genes identified across different studies. In a recent comparison of transcriptomic studies of the cell cycle in different human cell types, only 96 cell cycle genes were reported to be the same across all studies examined. Here we perform a systematic re-examination of published human cell cycle expression data by using a network-based approach to identify groups of genes with a similar expression profile and therefore function. Two clusters in particular, containing 298 transcripts, showed patterns of expression consistent with cell cycle occurrence across the four human cell types assessed. Our analysis shows that there is a far greater conservation of cell cycle-associated gene expression across human cell types than reported previously, which can be separated into two distinct transcriptional networks associated with the G1/S-S and G2-M phases of the cell cycle. This work also highlights the benefits of performing a re-analysis on combined datasets. The online version of this article (doi:10.1186/s12864-016-3435-2) contains supplementary material, which is available to authorized users.
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影响因子：
14.9
作者：
Gauthier NP;Larsen ME;Wernersson R;de Lichtenberg U;Jensen LJ;Brunak S;Jensen TS
通讯作者：
Jensen TS
WGCNA：用于加权相关网络分析的 R 包。
影响因子：
3
作者：
Langfelder P;Horvath S
通讯作者：
Horvath S
DOI：
10.1126/science.1245075
发表时间：
2015-05-15
期刊：
Science (New York, N.Y.)
影响因子：
--
作者：
Ginzberg MB;Kafri R;Kirschner M
通讯作者：
Kirschner M
影响因子：
16
作者：
Cho, RJ;Campbell, MJ;Davis, RW
通讯作者：
Davis, RW
影响因子：
64.8
作者：
BROOKS, RF
通讯作者：
BROOKS, RF