TRANSCRIPTIONAL NETWORK DISSECTION USING A COMBINATION OF MICROARRAYS, RANi AMD COMPUTATIONAL PROMOTER ANALYSIS

Ran Elkon1*, Sharon Rashi-Elkeles1*, Yaniv Lerenthal1, Chaim Linhart2, Tamar Tenne1, Ninette Amariglio3, Gideon Rechavi3, Ron Shamir2, and Yosef Shiloh1

1The David and Inez Myers Laboratory for Genetic Research, Department of Human Genetics, Sackler School of Medicine, 2School of Computer Science, 3Department of Pediatric

Hemato-Oncology and Functional Genomics, The Chaim Sheba Medical Center and Sackler School of Medicine, Tel-Aviv University, Israel.

The combination of microarrays and RNAi techniques holds promise for systematic, wide-scale dissection of transcriptional networks. However, recent studies raised the concern that nonspecific responses to siRNA might obscure the consequences of silencing the gene of interest. In this work, we assessed the ability to precisely dissect transcriptional networks by this combined experimental approach. Focusing on a DNA damage-induced transcriptional network as a test case, we recorded expression profiles with and without exposure of human cells to a radiomimetic drug that induces double strand breaks in the DNA (DSBs). Profiles were measured in control cells and in cells knocked-down for the Rel-A subunit of NF-kB and for p53, two pivotal stress-induced transcription factors, and for ATM, the major transducer of the cellular responses to DSBs. We observed that NF-kB 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 demonstrate that the dissection of the network into ATM/NF-kB- and ATM/p53-mediated arms was highly accurate. Thus, we demonstrate that this combined strategy is indeed a powerful method for the dissection of complex transcriptional networks.