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Dissection of a DNA-damage-induced transcriptional network using a combination of microarrays, RNA interference and computational promoter analysis

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

The David and Inez Myers Laboratory for Genetic Research, Department of Human Genetics, Sackler School of Medicine, Tel Aviv University, Tel Aviv, 69978, Israel

School of Computer Science, The Chaim Sheba Medical Center and Sackler School of Medicine, Tel Aviv University, Tel Aviv, 69978, Israel

Department of Pediatric Hemato-Oncology and Functional Genomics, The Chaim Sheba Medical Center and Sackler School of Medicine, Tel Aviv University, Tel Aviv, 69978, Israel

author email corresponding author email* Contributed equally

Genome Biology 2005, 6:R43doi:10.1186/gb-2005-6-5-r43

Published: 13 April 2005

Subject areas: Molecular biology, Genome studies, Genetics


Additional files

Additional File 1:

Two figures showing the microarray results and their analysis. Supplementary Figure 1. Perfect-match (PM) and mismatch (MM) probe signals measured prior to and 4 hours after treatment with NCS. These signals are shown for four genes that were induced by the NCS treatment. As can be seen, mismatch signals were increased as well, pointing that they too contain information on gene expression level. Supplementary Figure 2. Comparison between RMA and MAS 5 computed signals. M vs. A plots (as introduced by Speed's lab http://stat-www.berkeley.edu/users/terry/zarray/Html/normspie.html webcite) based on expression levels that were computed by MAS5 or RMA for comparison between: (i) two replicated chips (C0a vs. C0b) (ii) post-treatment vs. pre-treatment chips (C0a vs. C4a), and (iii) same as (ii) but expression levels were averaged on triplicate chips at both time points. In all comparisons, the fold induction distributions (represented by the Y-axis) were markedly narrower when expression levels were computed by RMA. Distributions based on MAS5 were especially noisy in the low intensity genes.

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Additional File 2:

Tables showing GO categories of affected genes, comparison between MAS5 and RMA computation of expression levels, primers used for real-time RT-PCR and the sequences of the shRNAs use in this study. Supplementary Table B. GO categories of the genes that were upregulated in response to infection of the cells with shRNA-expressing retroviral vectors. Supplementary Table C. GO categories of the genes that were downregulated in response to infection of the cells with the shRNA-expressing retroviral vectors. Supplementary Table E. Comparison between MAS 5 and RMA computation of expression levels. Supplementary Table F. Primers used for quantitative real-time RT-PCR assays. Supplementary Table G. Sequences of shRNAs used in this study.

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Additional File 3:

A table listing genes whose expression was affected by infection of the cells with the shRNA-expressing retroviral vectors. Supplementary Table A. Genes whose expression was affected by infection of the cells with the shRNA-expressing retroviral vectors.

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This file can be viewed with: Microsoft Excel Viewer

Additional File 4:

A table listing the genes induced in both controls in in response to NCS treatment, and their assignment into the four clusters. Supplementary Table D. List of the 112 genes that were induced in both controls in response to NCS treatment, and their assignment into the four clusters.

Format: XLS Size: 34KB Download file

This file can be viewed with: Microsoft Excel Viewer


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