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. 2009 Jul 31;35(2):228-39.
doi: 10.1016/j.molcel.2009.06.021.

A genome-wide siRNA screen reveals diverse cellular processes and pathways that mediate genome stability

Renee D Paulsen  1 , Deena V Soni, Roy Wollman, Angela T Hahn, Muh-Ching Yee, Anna Guan, Jayne A Hesley, Steven C Miller, Evan F Cromwell, David E Solow-Cordero, Tobias Meyer, Karlene A Cimprich
Affiliations

A genome-wide siRNA screen reveals diverse cellular processes and pathways that mediate genome stability

Renee D Paulsen et al. Mol Cell. .

Abstract

Signaling pathways that respond to DNA damage are essential for the maintenance of genome stability and are linked to many diseases, including cancer. Here, a genome-wide siRNA screen was employed to identify additional genes involved in genome stabilization by monitoring phosphorylation of the histone variant H2AX, an early mark of DNA damage. We identified hundreds of genes whose downregulation led to elevated levels of H2AX phosphorylation (gammaH2AX) and revealed links to cellular complexes and to genes with unclassified functions. We demonstrate a widespread role for mRNA-processing factors in preventing DNA damage, which in some cases is caused by aberrant RNA-DNA structures. Furthermore, we connect increased gammaH2AX levels to the neurological disorder Charcot-Marie-Tooth (CMT) syndrome, and we find a role for several CMT proteins in the DNA-damage response. These data indicate that preservation of genome stability is mediated by a larger network of biological processes than previously appreciated.

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Figures

Figure 1
Figure 1. siRNA screen for genes suppressing H2AX phosphorylation
Images of siControl (A) or siChk1 (B) transfected cells stained with anti-γH2AX antibodies and PI acquired on the Isocyte™. (C) Scatter plot of the raw γH2AX and PI intensity for negative (siControl, blue) and positive (siChk, red) controls. Each dot represents the γH2AX intensity of a single cell as a function of PI intensity. (D) The same cells from panel C shown after normalization. Right portion shows the histograms of each population. The dotted horizontal line reflects the adjusted γH2AX intensity cutoff used to designate a cell as γH2AX positive. (E) Deviation between duplicates of the screen is shown by plotting the first replicate against the second for each siRNA tested. Individual colors indicate the day in which the siRNA pool was tested. Inset shows the histogram of correlation coefficients for all plates analyzed. (F) The Z’ factor for each plate.
Figure 2
Figure 2. Functional classification of statistically significant gene set
(A) Genes identified by statistical methods described in the text were grouped by biological process using PANTHER (http://www.pantherdb.org). (B) Detailed protein categorization of the nucleoside, nucleotide, and nucleic acid metabolism category from (A). (C) Classification enrichment was determined using the David bioinformatic database and Ingenuity Pathway Analysis, and the right-tailed Fisher’s exact test. The threshold of significance was applied for —log (p=0.05).
Figure 3
Figure 3. Screening validation
(A) A representative well showing the γH2AX signal as a function of PI intensity for siControl- and siChk1-transfected cells. The percentage of γH2AX positive cells per well was calculated by applying a γH2AX intensity cutoff (horizontal line). (B) Table representing the effects of the four individual siRNAs tested during deconvolution. siRNAs were considered positive if the percentage of γH2AX+ cells was siControl-transfected wells. (C) Table demonstrating the retest rate for genes chosen from the primary screening significance groups. (D) Bar graph showing the effect of targeting genes involved in DNA replication and checkpoint activation. Each bar represents an individual siRNA tested, and error bars indicate variation between duplicates.
Figure 4
Figure 4. Network modeling of screen hits identifies new functional groups linked to genome maintenance
Networks of interacting proteins identified using DAVID Bioinformatics Database and Ingenuity Pathway Analysis. Color indicates strength of statistical significance (green) or strength of deconvolution results (red). If a statistically significant gene was deconvoluted, the deconvolution result is preferentially shown.
Figure 5
Figure 5. Functional assays for mRNA processing genes affecting γH2AX
(A) Effect on γH2AX after targeting genes involved in mRNA processing. (B) Percent of cells exhibiting greater than five 53BP1 foci after siRNA treatment. (C) Representative images of change in γH2AX signal following RNaseH expression. (D) Quantitation of effect represented in C for the indicated genes. Inset shows RNaseH-HA protein expression. (E) G2/M checkpoint assay after knockdown of the indicated genes and IR treatment. Fold increase of the mitotic index (% mitotic cells post-IR / % mitotic cells nontreated) in cells transfected with targeting siRNA relative to control is shown. (F) HR repair frequency at an induced double-strand break after knockdown of indicated gene. Samples were normalized to the HR frequency in the siControl-transfected cells. All graphs shown are mean ± SE for n=3. Duplicate bars indicate the effects of two different siRNAs.
Figure 6
Figure 6. Loss of Charcot-Marie-Tooth disease genes leads to increased DNA damage and repair defects
(A) Percentage of γH2AX+ cells after knockdown of the indicated genes. Duplicate bars indicate effects of individual siRNAs tested. (B) Images of γH2AX signal 72h after knockdown of the indicated gene. Scale bar indicates 50μm. (C) Sensitivity to aphidicolin (100nM) or IR treatment (2Gy). Samples were corrected for the effect of the indicated siRNA on growth rate and then normalized to the siLuciferase-transfected sample. Details can be found in the supplemental methods. (D) HR repair frequency at an induced double-strand break after knockdown of the indicated gene. Samples were normalized to the HR frequency in the siLuciferase-transfected cells. (E) p-Chk1 and γH2AX response in GJB1 patient cell lines. Samples were collected 24 hrs after drug addition. BrdU plots indicate there is no significant difference in the cell cycle distribution of the mock treated cells. All graphs shown are mean ± SE for n=3.
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