Elkon Ran, Rashi-Elkeles Sharon, Lerenthal Yaniv, Linhart Chaim, Tenne Tamar, Amariglio Ninette, Rechavi Gideon, Shamir Ron, Shiloh Yosef
The David and Inez Myers Laboratory for Genetic Research, Department of Human Genetics, Sackler School of Medicine, Tel Aviv University, Tel Aviv, 69978, Israel.
Genome Biol. 2005;6(5):R43. doi: 10.1186/gb-2005-6-5-r43. Epub 2005 Apr 13.
Gene-expression microarrays and RNA interferences (RNAi) are among the most prominent techniques in functional genomics. The combination of the two holds promise for systematic, large-scale dissection of transcriptional networks. Recent studies, however, raise the concern that nonspecific responses to small interfering RNAs (siRNAs) might obscure the consequences of silencing the gene of interest, throwing into question the ability of this experimental strategy to achieve precise network dissections.
We used microarrays and RNAi to dissect a transcriptional network induced by DNA damage in a human cellular system. We recorded expression profiles with and without exposure of the cells to a radiomimetic drug that induces DNA double-strand breaks (DSBs). Profiles were measured in control cells and in cells knocked-down for the Rel-A subunit of NFkappaB and for p53, two pivotal stress-induced transcription factors, and for the protein kinase ATM, the major transducer of the cellular responses to DSBs. We observed that NFkappaB and p53 mediated most of the damage-induced gene activation; that they controlled the activation of largely disjoint sets of genes; and that ATM was required for the activation of both pathways. Applying computational promoter analysis, we demonstrated that the dissection of the network into ATM/NFkappaB and ATM/p53-mediated arms was highly accurate.
Our results demonstrate that the combined experimental strategy of expression arrays and RNAi is indeed a powerful method for the dissection of complex transcriptional networks, and that computational promoter analysis can provide a strong complementary means for assessing the accuracy of this dissection.
基因表达微阵列和RNA干扰(RNAi)是功能基因组学中最突出的技术。两者结合有望对转录网络进行系统的大规模剖析。然而,最近的研究引发了人们的担忧,即对小干扰RNA(siRNA)的非特异性反应可能会掩盖沉默目标基因的后果,从而使这种实验策略能否实现精确的网络剖析受到质疑。
我们使用微阵列和RNAi剖析了人类细胞系统中由DNA损伤诱导的转录网络。我们记录了细胞暴露于诱导DNA双链断裂(DSB)的放射模拟药物前后的表达谱。在对照细胞以及敲低NFκB的Rel-A亚基、p53(两种关键的应激诱导转录因子)和蛋白激酶ATM(细胞对DSB反应的主要转导器)的细胞中测量了表达谱。我们观察到,NFκB和p53介导了大部分损伤诱导的基因激活;它们控制着大量不相交基因集的激活;并且ATM是两条通路激活所必需的。通过应用计算启动子分析,我们证明将网络剖析为ATM/NFκB和ATM/p53介导的分支是高度准确的。
我们的结果表明,表达阵列和RNAi的联合实验策略确实是剖析复杂转录网络的有力方法,并且计算启动子分析可以为评估这种剖析的准确性提供强有力的补充手段。