Lejeune et al. BMC Genomics 2012, 13:91 http://www.biomedcentral.com/1471-2164/13/91 other abnormalities such as morphological abnormalities (2243 RNAi clones) were excluded from further analysis. For RNAi clones that did not alter nematode growth and morphology, the two P0 animals (old and dark nematodes) initially incubated in the well were manually removed from the plate and young adults (F1 progeny) were assayed for light touch response as previously described [13]. Briefly, touch tests involved scoring for the response to light touch at the tail by using a fine hair. Touch test were performed by scoring 5 touches at the tail of the animal for 70-90 animals/RNAi clone/test. Ordinarily, wild-type animals will respond by backing away from the touch. The responses were recorded for every animal such that, for example, 4 responses out of 5 at the tail is given as 80% responsiveness, and the mean values for responsiveness were retained for further analysis of the data. A score for change in touch response (S) was calculated as [(Percent response - mean baseline)/mean baseline]. Using this formula, the maximally-achievable score is 4.55 (maximal suppression of 128Q cytotoxicity, i.e. 100% responsiveness) and the minimally-achievable score is -1 (maximal aggravation of 128Q cytotoxicity). The baseline in the assay was monitored across the entire time of the screening from the incubation of the animals treated with the empty vector L4440 in all of the 96-well plates assayed. The cumulated baseline over the entire time of the screening was observed to be stable (20.6 ± 3%) and the cumu- lated baseline/month was used to calculate S scores. Sta- tistical analysis was performed using one-way ANOVA and the Tukey’s Multiple Comparison Test. To decrease the risk for false positives, RNAi clones were scored as positive hits (suppressors or enhancers) if the S ± SD value was outside the baseline ± (SD*2.6). Initial hits (suppressors, enhancers) were tested for confirmation or invalidation of effect on touch response and the result- ing data were retained for biological content analysis. All of the screening assays were performed by investiga- tors that were trained to score touch response of 128Q animals in a similar way using blind assays. Prior to performing the RNAi screen, the efficiency of gene inactivation in touch receptor neurons was tested by incubating ID447 L1 larvae in 96-well plates (1 lar- vae/well) with bacteria expressing either RNAi against GFP (plasmid pL4417) or empty vector (plasmid pL4440). Incubation was performed as described above until F1 young adults are produced. At the end of incu- bation, 70-90 animals/genotype were moved to agar plates and mounted on slides, and YFP levels in touch cells (mec-7p target cells) were measured at high (63X) magnification using a fluorescence microscope (Zeiss Axioplan Imaging II) and image analysis software (Image J). Additionally, YFP mRNA levels were mea- sured by qRT-PCR from whole animals using standard Page 3 of 14 methods. All of the nematode experiments were per- formed at least three times. Student’s t-tests were used for statistical analysis of YFP mRNA levels and YFP expression levels. Data analysis The final screening results were initially classified using Gene Ontology (GO) annotations for Biological Process, Molecular Function and Cellular Component http:// www.geneontology.org/[21]. GO enrichment tests were performed using Ontologizer v 2.0 [22]. Additionally, we used hypergeometric tests to test for gene set enrich- ment [23,24]. The gene sets used for enrichment analy- sis were established using core components of (i) canonical pathways based on Wormbook http://www. wormbook.org, KEGG http://www.genome.ad.jp/kegg/ [25] and Panther http://www.pantherdb.org/pathway/. To analyze further the biological content of RNAi clones confirmed to modulate 128Q toxicity, we per- formed network-boosted data analysis. To this end, we subjected the RNAi data to spectral decomposition ana- lysis using the integrated C. elegans network Wormnet v.2 [26]. This large-coverage network contains gene interaction data that were established according to sev- eral types of evidences derived from multiple organisms, including several types of gene interactions based on gene co-expression (microarray measurements of the expression of C. elegans mRNAs), protein-protein inter- actions including genome-wide yeast two-hybrid interac- tions between C. elegans proteins and protein-protein interactions from the Worm Interactome database [27], genetic interactions from WormBase [28], human and fly ‘interologs’ i.e. human and fly protein interactions [29,30], Yeast ‘associalogs’ i.e. functional interactions transferred from the yeast functional gene network [31], phylogenic profiles (comparative genomics linkages derived from the analysis of bacterial and archaeal gen- omes), gene neighbors and co-citation (literature-mined C. elegans gene associations). To increase the power of spectral decomposition analysis in detecting pathways, we also used a more homogenous network containing high confidence interactions, namely Core Wormnet [26] in which we omitted co-expression and co-citation links. To perform spectral decomposition analysis, we developed an enhanced version of the previously described [32] Fourier-like analysis. This approach is based on the spectral decomposition of gene activity profiles with respect to the connectivity of the reference network. S scores in the RNAi screen are considered as a ‘signal’ and the Fourier transformation decomposes the signal as a superposition of signals at different fre- quencies, with 40 successive attenuations performed [32]. The aim of these transformations is to keep the low-frequency signals and discard the high frequency