Pancaldi Vera, Schubert Falk, Bähler Jürg
Department of Genetics, Evolution and Environment and UCL Cancer Institute, University College London, Darwin Building, Gower Street, London, UK WC1E 6BT.
Mol Biosyst. 2010 Mar;6(3):543-52. doi: 10.1039/b913876p. Epub 2009 Dec 15.
Genome-wide gene expression is re-programmed in response to external or internal factors such as environmental stress or genetic mutation, respectively, or as a function of endogenous processes such as cell proliferation or differentiation. Here we integrate expression profiling data that have been collected by our laboratory since 2001 and that interrogate more than 900 different experimental conditions. We take advantage of this large data set to rank all genes based on their variability in gene expression across the different conditions. The most variable genes were enriched for functions such as stress response, carbohydrate metabolism and trans-membrane transport, and these genes were underrepresented for introns and tended to be close to telomeres. We then compared how overall gene regulation and variability of gene expression across conditions is affected by environmental or genetic perturbations, and by endogenous programmes. Meiotic differentiation and environmental perturbations led to substantially greater gene expression variability and overall regulation than did genetic perturbations and the transcriptional programme accompanying cell proliferation. We also used the integrated data to identify gene regulation modules using two different clustering approaches. Two major clusters, containing growth- and metabolism-related genes on one hand and stress- and differentiation-related genes on the other, were reciprocally regulated across conditions. We discuss these findings with respect to other recent reports on the regulation and evolution of gene expression.
全基因组基因表达会分别响应外部或内部因素（如环境压力或基因突变），或作为内源性过程（如细胞增殖或分化）的函数而重新编程。在这里，我们整合了自2001年以来由我们实验室收集的表达谱数据，这些数据涉及900多种不同的实验条件。我们利用这个大数据集，根据所有基因在不同条件下基因表达的变异性对它们进行排名。变异性最大的基因在应激反应、碳水化合物代谢和跨膜运输等功能方面富集，并且这些基因的内含子较少，且倾向于靠近端粒。然后，我们比较了环境或基因扰动以及内源性程序如何影响跨条件的整体基因调控和基因表达变异性。减数分裂分化和环境扰动导致的基因表达变异性和整体调控比基因扰动以及伴随细胞增殖的转录程序要大得多。我们还使用整合数据，通过两种不同的聚类方法来识别基因调控模块。两个主要的聚类，一方面包含与生长和代谢相关的基因，另一方面包含与应激和分化相关的基因，在不同条件下相互调控。我们结合其他近期关于基因表达调控和进化的报告来讨论这些发现。
