Nature：从转录组水平系统分析炎症后的基因组反应机制

生物谷

　生物谷报道：最新由美国32个研究单位参与的一项大型研究，以转录组水平为核心，全面揭示从基因组的表达，转录组水平，表型之间的相互关系。

　我们知道，基因芯片目前常用于肿瘤等疾病的检测。然而，最大的困难不是检测本身，而是芯片等高通量检测后得到的大量数据，如何分析和认识这些数据，从中发现最有价值的资料，这是面对研究者的最大挑战。本期Nature发表了由美国３２家研究单位共同参与的一项大型研究，首次基因结构性网络知识全面从基因组水平分析人体的蛋白质，小分子和表型与疾病之间的关系。他们选择了内毒素炎症作为模型，研究了血液中的淋巴细胞对炎症的反应，全面揭示了淋巴细胞对急性系统性炎症的反应，包括淋巴细胞的生物代谢的紊乱、基因转录地调节等。这篇研究成果提供了全面揭示了淋巴细胞与内在免疫系统的关系，为人类更深入地了解从基因表达到表型，以及疾病之间的分子网络机制提供依据。

A prototypical inflammatory cell was constructed from 292 representative genes involved in inflammation and innate immunity. Genes for which the expression statistically increased from baseline are coloured red, those for which expression decreased are shown in blue. a, Composite changes in apparent expression over 24 h, identifying nodes and interactions. b, Temporal changes in apparent expression. The response to endotoxin administration in blood leukocytes can be viewed as an integrated cell-wide response, propagating and resolving over time.

a, The network consists of 1,214 genes showing perturbed expression, and 342 genes highly interconnected to this group (red, increased; blue, decreased expression). b, Selected regions of the network, highlighting several groups of genes. Group 1, mitochondrial respiratory chain complex I (NDUF genes). Group 2, mitochondrial respiratory chain complex III (UQCR genes). Group 3, ATP synthase complex (ATP5 genes). Group 4, pyruvate dehydrogenase complex. Group 5, mitochondrial permeability transition pore complex. Group 6, elongation initiation factor complex (EIF3 genes). Group 7, ribosomal proteins (RPL, RPS genes). Group 8, COP9 signallosome (COPS genes). Group 9, proteasome (PSM genes).

原始来源：

Steve E. Calvano, Wenzhong Xiao, Daniel R. Richards, Ramon M. Felciano, Henry V. Baker, Raymond J. Cho, Richard O. Chen, Bernard H. Brownstein, J. Perren Cobb, S. Kevin Tschoeke, Carol Miller-Graziano, Lyle L. Moldawer, Michael N. Mindrinos, Ronald W. Davis, Ronald G. Tompkins, Stephen F. Lowry and Inflamm and Host Response to Injury Large Scale Collab. Res. Program. A network-based analysis of systemic inflammation in humans. Nature 437, 1032-1037
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