RNA interference (RNAi) represents a powerful method to systematically study loss-of-function phenotypes on a large scale with a wide variety of biological assays, constituting a rich source for the assignment of gene function. The GenomeRNAi database (http://www.genomernai.org) makes available RNAi phenotype data extracted from the literature for human and Drosophila. It also provides RNAi reagent information, along with an assessment as to their efficiency and specificity. This manuscript describes an update of the database previously featured in the NAR Database Issue. The new version has undergone a complete re-design of the user interface, providing an intuitive, flexible framework for additional functionalities. Screen information and gene-reagent-phenotype associations are now available for download. The integration with other resources has been improved by allowing in-links via GenomeRNAi screen IDs, or external gene or reagent identifiers. A distributed annotation system (DAS) server enables the visualization of the phenotypes and reagents in the context of a genome browser. We have added a page listing ‘frequent hitters’, i.e. genes that show a phenotype in many screens, which might guide on-going RNAi studies. Structured annotation guidelines have been established to facilitate consistent curation, and a submission template for direct submission by data producers is available for download.

Tumor necrosis factor alpha (TNF-α) is a potent inflammatory cytokine secreted upon cellular stress as well as immunological stimuli and is implicated in the pathology of inflammatory diseases and cancer. The therapeutic potential of modifying TNF-α pathway activity has been realized in several diseases, and antagonists of TNF-α have reached clinical applications. While much progress in the understanding of signaling downstream of the TNF-α receptor complex has been made, the compendium of factors required for signal transduction is still not complete. In order to find novel regulators of proinflammatory signaling induced by TNF-α, we conducted a genome-wide small interfering RNA screen in human cells. We identified several new candidate modulators of TNF-α signaling, which were confirmed in independent experiments. Specifically, we show that caspase 4 is required for the induction of NF-κB activity, while it appears to be dispensable for the activation of the Jun N-terminal protein kinase signaling branch. Taken together, our experiments identify caspase 4 as a novel regulator of TNF-α-induced NF-κB signaling that is required for the activation of IκB kinase. We further provide the genome-wide RNA interference data set as a compendium in a format compliant with minimum information about an interfering RNA experiment (MAIRE).

Proteins with long, pathogenic polyglutamine (polyQ) sequences have an enhanced propensity to spontaneously misfold and self-assemble into insoluble protein aggregates. Here, we have identified 21 human proteins that influence polyQ-induced ataxin-1 misfolding and proteotoxicity in cell model systems. By analyzing the protein sequences of these modifiers, we discovered a recurrent presence of coiled-coil (CC) domains in ataxin-1 toxicity enhancers, while such domains were not present in suppressors. This suggests that CC domains contribute to the aggregation- and toxicity-promoting effects of modifiers in mammalian cells. We found that the ataxin-1–interacting protein MED15, computationally predicted to possess an N-terminal CC domain, enhances spontaneous ataxin-1 aggregation in cell-based assays, while no such effect was observed with the truncated protein MED15ΔCC, lacking such a domain. Studies with recombinant proteins confirmed these results and demonstrated that the N-terminal CC domain of MED15 (MED15CC) per se is sufficient to promote spontaneous ataxin-1 aggregation in vitro. Moreover, we observed that a hybrid Pum1 protein harboring the MED15CC domain promotes ataxin-1 aggregation in cell model systems. In strong contrast, wild-type Pum1 lacking a CC domain did not stimulate ataxin-1 polymerization. These results suggest that proteins with CC domains are potent enhancers of polyQ-mediated protein misfolding and aggregation in vitro and in vivo.

Author Summary

Spinocerebellar ataxias (SCAs) are a group of inherited neurodegenerative diseases with around 30 subtypes, which are characterized by a progressive loss of cerebellar neurons. Neuronal death has been linked to the aggregation of mutated disease-causing proteins, such as ataxin-1 (ATXN1). Pathogenic ATXN1 contains an elongated glutamine stretch, which triggers spontaneous misfolding and self-assembly of the protein into aggregates. Earlier studies in lower organisms have discovered many non-human proteins that alter aggregation and/or toxicity of mutant ATXN1. Here, we combine an experimental screening approach with bioinformatics to find human proteins that modulate aggregation and toxicity of ATXN1. We identified 21 proteins affecting mutant ATXN1 in mammalian cells. Further characterization revealed that enhancers of ATXN1-mediated toxicity contain α-helical coiled-coil domains as structural motifs, while suppressors do not. Detailed studies with the ATXN1 interacting proteins MED15 and Pum1 finally demonstrated that coiled-coil domains are indeed critical for the aggregation and toxicity promoting effects of human proteins. Our study contributes to a deeper understanding of ATXN1 aggregation and SCA1 pathogenesis and highlights potential therapeutic targets for further investigations.

The planarian Schmidtea mediterranea is a powerful model organism for studying stem cell biology due to its extraordinary regenerative ability mediated by neoblasts, a population of adult somatic stem cells. Elucidation of the S. mediterranea transcriptome and the dynamics of transcript expression will increase our understanding of the gene regulatory programs that regulate stem cell function and differentiation. Here, we have used RNA-Seq to characterize the S. mediterranea transcriptome in sexual and asexual animals and in purified neoblast and differentiated cell populations. Our analysis identified many uncharacterized genes, transcripts, and alternatively spliced isoforms that are differentially expressed in a strain or cell type-specific manner. Transcriptome profiling of purified neoblasts and differentiated cells identified neoblast-enriched transcripts, many of which likely play important roles in regeneration and stem cell function. Strikingly, many of the neoblast-enriched genes are orthologs of genes whose expression is enriched in human embryonic stem cells, suggesting that a core set of genes that regulate stem cell function are conserved across metazoan species.

Wnt/β-catenin signaling is fundamental in embryogenesis and tissue homeostasis in metazoans. Upon Wnt stimulation, cognate coreceptors LRP5 and LRP6 ([LRP5/6] low-density lipoprotein receptor-related proteins 5 and 6) are activated via phosphorylation at key residues. Although several kinases have been implicated, the LRP5/6 activation mechanism remains unclear. Here, we report that transmembrane protein 198 (TMEM198), a previously uncharacterized seven-transmembrane protein, is able to specifically activate LRP6 in transducing Wnt signaling. TMEM198 associates with LRP6 and recruits casein kinase family proteins, via the cytoplasmic domain, to phosphorylate key residues important for LRP6 activation. In mammalian cells, TMEM198 is required for Wnt signaling and casein kinase 1-induced LRP6 phosphorylation. During Xenopus embryogenesis, maternal and zygotic tmem198 mRNAs are widely distributed in the ectoderm and mesoderm. TMEM198 is required for Wnt-mediated neural crest formation, antero-posterior patterning, and particularly engrailed-2 expression in Xenopus embryos. Thus, our results identified TMEM198 as a membrane scaffold protein that promotes LRP6 phosphorylation and Wnt signaling activation.

Malignant astrocytomas are highly aggressive brain tumours with poor prognosis. While a number of structural genomic changes and dysregulation of signalling pathways in gliomas have been described, the identification of biomarkers and druggable targets remains an important task for novel diagnostic and therapeutic approaches. Here, we show that the Wnt-specific secretory protein Evi (also known as GPR177/Wntless/Sprinter) is overexpressed in astrocytic gliomas. Evi/Wls is a core Wnt signalling component and a specific regulator of pan-Wnt protein secretion, affecting both canonical and non-canonical signalling. We demonstrate that its depletion in glioma and glioma-derived stem-like cells led to decreased cell proliferation and apoptosis. Furthermore, Evi/Wls silencing in glioma cells reduced cell migration and the capacity to form tumours in vivo. We further show that Evi/Wls overexpression is sufficient to promote downstream Wnt signalling. Taken together, our study identifies Evi/Wls as an essential regulator of glioma tumourigenesis, identifying a pathway-specific protein trafficking factor as an oncogene and offering novel therapeutic options to interfere with the aberrant regulation of growth factors at the site of production.

Cell-based high-throughput RNAi screening has become a powerful research tool in addressing a variety of biological questions. In RNAi screening, one of the most commonly applied assay system is measuring the fitness of cells that is usually quantified using fluorescence, luminescence and absorption-based readouts. These methods, typically implemented and scaled to large-scale screening format, however often only yield limited information on the cell fitness phenotype due to evaluation of a single and indirect physiological indicator. To address this problem, we have established a cell fitness multiplexing assay which combines a biochemical approach and two fluorescence-based assaying methods. We applied this assay in a large-scale RNAi screening experiment with siRNA pools targeting the human kinome in different modified HEK293 cell lines. Subsequent analysis of ranked fitness phenotypes assessed by the different assaying methods revealed average phenotype intersections of 50.7±2.3%–58.7±14.4% when two indicators were combined and 40–48% when a third indicator was taken into account. From these observations we conclude that combination of multiple fitness measures may decrease false-positive rates and increases confidence for hit selection. Our robust experimental and analytical method improves the classical approach in terms of time, data comprehensiveness and cost.

p24 proteins are required for secretion of Wnt ligands

Wnt proteins are signalling molecules that follow a dedicated secretory pathway. The authors here identify novel components of this pathway, providing evidence that p24 proteins act as cargo receptors in an anterograde secretory route for Wnts.

During development and disease, the exocytosis of signalling molecules, such as Wnt ligands, is essential to orchestrate cellular programs in multicellular organisms. However, it remains a largely unresolved question whether signalling molecules follow specialized transport routes through the exocytic pathway. Here we identify several Drosophila p24 proteins that are required for Wnt signalling. We demonstrate that one of these p24 proteins, namely Opossum, shuttles in the early secretory pathway, and that the Drosophila Wnt proteins are retained in the absence of p24 proteins. Our results indicate that Wnt secretion relies on a specialized anterograde secretion route with p24 proteins functioning as conserved cargo receptors.

Short interference RNA (siRNA) is widely used in mammalian cells. In insects, however, reports concerning the suitablility of siRNA in vivo is very limited compared with that of long dsRNA, which is thought to be more effective. There is insufficient information on the essential rules of siRNA design in insects, as very few siRNAs have been tested in this context. To establish an effective method of gene silencing using siRNA in vivo in insects, we determined the effects of siRNA on seven target genes. We designed siRNAs according to a new guideline and injected them into eggs of Bombyx mori. At the mRNA level, the expression of most of these genes was successfully silenced, down to less than half the constitutive level, which in some cases led to the development of distinctive phenotypes. In addition, we observed stronger effect of siRNA both on the mRNA level and the phenotype than that of long dsRNA under comparable conditions. These results indicate that direct injection of siRNA is an effective reverse-genetics tool for the analysis of embryogenesis in vivo in insects.

Background

Systematic measurement of genetic interactions by combinatorial RNAi (co-RNAi) is a powerful tool for mapping functional modules and discovering components. It also provides insights into the role of epistasis on the way from genotype to phenotype. The interpretation of co-RNAi data requires computational and statistical analysis in order to detect interactions reliably and sensitively.

Results

We present a comprehensive approach to the analysis of univariate phenotype measurements, such as cell growth. The method is based on a quantitative model and is demonstrated on two example Drosophila cell culture data sets. We discuss adjustments for technical variability, data quality assessment, model parameter fitting and fit diagnostics, choice of scale, and assessment of statistical significance.

Conclusions

As a result, we obtain quantitative genetic interactions and interaction networks reflecting known biological relationships between target genes. The reliable extraction of presence, absence, and strength of interactions provides insights into molecular mechanisms.

Background

Planarian flatworms can regenerate their head, including a functional brain, within less than a week. Despite the enormous potential of these animals for medical research and regenerative medicine, the mechanisms of regeneration and the molecules involved remain largely unknown.

Results

To identify genes that are differentially expressed during early stages of planarian head regeneration, we generated a de novo transcriptome assembly from more than 300 million paired-end reads from planarian fragments regenerating the head at 16 different time points. The assembly yielded 26,018 putative transcripts, including very long transcripts spanning multiple genomic supercontigs, and thousands of isoforms. Using short-read data from two platforms, we analyzed dynamic gene regulation during the first three days of head regeneration. We identified at least five different temporal synexpression classes, including genes specifically induced within a few hours after injury. Furthermore, we characterized the role of a conserved Runx transcription factor, smed-runt-like1. RNA interference (RNAi) knockdown and immunofluorescence analysis of the regenerating visual system indicated that smed-runt-like1 encodes a transcriptional regulator of eye morphology and photoreceptor patterning.

Conclusions

Transcriptome sequencing of short reads allowed for the simultaneous de novo assembly and differential expression analysis of transcripts, demonstrating highly dynamic regulation during head regeneration in planarians.

Background

In Drosophila, the early secretory apparatus comprises discrete paired Golgi stacks in close proximity to exit sites from the endoplasmic reticulum (tER sites), thus forming tER-Golgi units. Although many components involved in secretion have been identified, the structural components sustaining its organisation are less known. Here we set out to identify novel ER resident proteins involved in the of tER-Golgi unit organisation.

Results

To do so, we designed a novel screening strategy combining a bioinformatics pre-selection with an RNAi screen. We first selected 156 proteins exhibiting known or related ER retention/retrieval signals from a list of proteins predicted to have a signal sequence. We then performed a microscopy-based primary and confirmation RNAi screen in Drosophila S2 cells directly scoring the organisation of the tER-Golgi units. We identified 49 hits, most of which leading to an increased number of smaller tER-Golgi units (MG for “more and smaller Golgi”) upon depletion. 16 of them were validated and characterised, showing that this phenotype was not due to an inhibition in secretion, a block in G2, or ER stress. Interestingly, the MG phenotype was often accompanied by an increase in the cell volume. Out of 6 proteins, 4 were localised to the ER.

Conclusions

This work has identified novel proteins involved in the organisation of the Drosophila early secretory pathway. It contributes to the effort of assigning protein functions to gene annotation in the secretory pathway, and analysis of the MG hits revealed an enrichment of ER proteins. These results suggest a link between ER localisation, aspects of cell metabolism and tER-Golgi structural organisation.

Transcription factors of the RUNX and GATA families play key roles in the control of cell fate choice and differentiation, notably in the hematopoietic system. During Drosophila hematopoiesis, the RUNX factor Lozenge and the GATA factor Serpent cooperate to induce crystal cell differentiation. We used Serpent/Lozenge-activated transcription as a paradigm to identify modulators of GATA/RUNX activity by a genome-wide RNA interference screen in cultured Drosophila blood cells. Among the 129 factors identified, several belong to the Mediator complex. Mediator is organized in three modules plus a regulatory “CDK8 module,” composed of Med12, Med13, CycC, and Cdk8, which has long been thought to behave as a single functional entity. Interestingly, our data demonstrate that Med12 and Med13 but not CycC or Cdk8 are essential for Serpent/Lozenge-induced transactivation in cell culture. Furthermore, our in vivo analysis of crystal cell development show that, while the four CDK8 module subunits control the emergence and the proliferation of this lineage, only Med12 and Med13 regulate its differentiation. We thus propose that Med12/Med13 acts as a coactivator for Serpent/Lozenge during crystal cell differentiation independently of CycC/Cdk8. More generally, we suggest that the set of conserved factors identified herein may regulate GATA/RUNX activity in mammals.

Colorectal cancer (CRC) is a complex disease related to environmental and genetic risk factors. Several studies have shown that susceptibility to complex diseases can be mediated by ancestral alleles. Using RNAi screening, CTNNBL1 was identified as a putative regulator of the Wnt signaling pathway, which plays a key role in colorectal carcinogenesis. Recently, single nucleotide polymorphisms (SNPs) in CTNNBL1 have been associated with obesity, a known risk factor for CRC. We investigated whether genetic variation in CTNNBL1 affects susceptibility to CRC and tested for signals of recent selection. We applied a tagging SNP approach that cover all known common variation in CTNNBL1 (allele frequency >5%; r2>0.8). A case-control study was carried out using two well-characterized study populations: a hospital-based Czech population composed of 751 sporadic cases and 755 controls and a family/early onset-based German population (697 cases and 644 controls). Genotyping was performed using allele specific PCR based TaqMan® assays (Applied Biosystems, Weiterstadt, Germany). In the Czech cohort, containing sporadic cases, the ancestral alleles of three SNPs showed evidence of association with CRC: rs2344481 (OR 1.44, 95%CI 1.06-1.95, dominant model), rs2281148 (OR 0.59, 95%CI 0.36-0.96, dominant model) and rs2235460 (OR 1.38, 95%CI 1.01-1.89, AA vs. GG). The associations were less prominent in the family/early onset-based German cohort. Data derived from several databases and statistical tests consistently pointed to a likely shaping of CTNNBL1 by positive selection. Further studies are needed to identify the actual function of CTNNBL1 and to validate the association results in other populations.

RNA interference (RNAi) screens have enabled the systematic analysis of many biological processes in cultured cells and whole organisms. The success of such screens and the interpretation of the data depend on the stringent design of RNAi libraries. We describe and validate NEXT-RNAi, a software for the automated design and evaluation of RNAi sequences on a genome-wide scale. NEXT-RNAi is implemented as open-source software and is accessible at http://www.nextrnai.org/.

How to predict gene function from phenotypic cues is a longstanding question in biology.Using quantitative multiparametric imaging, RNAi-mediated cell phenotypes were measured on a genome-wide scale.On the basis of phenotypic ‘neighbourhoods', we identified previously uncharacterized human genes as mediators of the DNA damage response pathway and the maintenance of genomic integrity.The phenotypic map is provided as an online resource at http://www.cellmorph.org for discovering further functional relationships for a broad spectrum of biological module

Genetic screens for phenotypic similarity have made key contributions for associating genes with biological processes. Aggregating genes by similarity of their loss-of-function phenotype has provided insights into signalling pathways that have a conserved function from Drosophila to human (Nusslein-Volhard and Wieschaus, 1980; Bier, 2005). Complex visual phenotypes, such as defects in pattern formation during development, greatly facilitated the classification of genes into pathways, and phenotypic similarities in many cases predicted molecular relationships. With RNA interference (RNAi), highly parallel phenotyping of loss-of-function effects in cultured cells has become feasible in many organisms whose genome have been sequenced (Boutros and Ahringer, 2008). One of the current challenges is the computational categorization of visual phenotypes and the prediction of gene function and associated biological processes. With large parts of the genome still being in unchartered territory, deriving functional information from large-scale phenotype analysis promises to uncover novel gene–gene relationships and to generate functional maps to explore cellular processes.

In this study, we developed an automated approach using RNAi-mediated cell phenotypes, multiparametric imaging and computational modelling to obtain functional information on previously uncharacterized genes. To generate broad, computer-readable phenotypic signatures, we measured the effect of RNAi-mediated knockdowns on changes of cell morphology in human cells on a genome-wide scale. First, the several million cells were stained for nuclear and cytoskeletal markers and then imaged using automated microscopy. On the basis of fluorescent markers, we established an automated image analysis to classify individual cells (Figure 1A). After cell segmentation for determining nuclei and cell boundaries (Figure 1C), we computed 51 cell descriptors that quantified intensities, shape characteristics and texture (Figure 1F). Individual cells were categorized into 1 of 10 classes, which included cells showing protrusion/elongation, cells in metaphase, large cells, condensed cells, cells with lamellipodia and cellular debris (Figure 1D and E). Each siRNA knockdown was summarized by a phenotypic profile and differences between RNAi knockdowns were quantified by the similarity between phenotypic profiles. We termed the vector of scores a phenoprint (Figure 3C) and defined the phenotypic distance between a pair of perturbations as the distance between their corresponding phenoprints.

To visualize the distribution of all phenoprints, we plotted them in a genome-wide map as a two-dimensional representation of the phenotypic similarity relationships (Figure 3A). The complete data set and an interactive version of the phenotypic map are available at http://www.cellmorph.org. The map identified phenotypic ‘neighbourhoods', which are characterized by cells with lamellipodia (WNK3, ANXA4), cells with prominent actin fibres (ODF2, SOD3), abundance of large cells (CA14), many elongated cells (SH2B2, ELMO2), decrease in cell number (TPX2, COPB1, COPA), increase in number of cells in metaphase (BLR1, CIB2) and combinations of phenotypes such as presence of large cells with protrusions and bright nuclei (PTPRZ1, RRM1; Figure 3B).

To test whether phenotypic similarity might serve as a predictor of gene function, we focused our further analysis on two clusters that contained genes associated with the DNA damage response (DDR) and genomic integrity (Figure 3A and C). The first phenotypic cluster included proteins with kinetochore-associated functions such as NUF2 (Figure 3B) and SGOL1. It also contained the centrosomal protein CEP164 that has been described as an important mediator of the DNA damage-activated signalling cascade (Sivasubramaniam et al, 2008) and the largely uncharacterized genes DONSON and SON. A second phenotypically distinct cluster included previously described components of the DDR pathway such as RRM1 (Figure 3A–C), CLSPN, PRIM2 and SETD8. Furthermore, this cluster contained the poorly characterized genes CADM1 and CD3EAP.

Cells activate a signalling cascade in response to DNA damage induced by exogenous and endogenous factors. Central are the kinases ATM and ATR as they serve as sensors of DNA damage and activators of further downstream kinases (Harper and Elledge, 2007; Cimprich and Cortez, 2008). To investigate whether DONSON, SON, CADM1 and CD3EAP, which were found in phenotypic ‘neighbourhoods' to known DDR components, have a role in the DNA damage signalling pathway, we tested the effect of their depletion on the DDR on γ irradiation. As indicated by reduced CHEK1 phosphorylation, siRNA knock down of DONSON, SON, CD3EAP or CADM1 resulted in impaired DDR signalling on γ irradiation. Furthermore, knock down of DONSON or SON reduced phosphorylation of downstream effectors such as NBS1, CHEK1 and the histone variant H2AX on UVC irradiation. DONSON depletion also impaired recruitment of RPA2 onto chromatin and SON knockdown reduced RPA2 phosphorylation indicating that DONSON and SON presumably act downstream of the activation of ATM. In agreement to their phenotypic profile, these results suggest that DONSON, SON, CADM1 and CD3EAP are important mediators of the DDR. Further experiments demonstrated that they are also required for the maintenance of genomic integrity.

In summary, we show that genes with similar phenotypic profiles tend to share similar functions. The power of our computational and experimental approach is demonstrated by the identification of novel signalling regulators whose phenotypic profiles were found in proximity to known biological modules. Therefore, we believe that such phenotypic maps can serve as a resource for functional discovery and characterization of unknown genes. Furthermore, such approaches are also applicable for other perturbation reagents, such as small molecules in drug discovery and development. One could also envision combined maps that contain both siRNAs and small molecules to predict target–small molecule relationships and potential side effects.

Genetic screens for phenotypic similarity have made key contributions to associating genes with biological processes. With RNA interference (RNAi), highly parallel phenotyping of loss-of-function effects in cells has become feasible. One of the current challenges however is the computational categorization of visual phenotypes and the prediction of biological function and processes. In this study, we describe a combined computational and experimental approach to discover novel gene functions and explore functional relationships. We performed a genome-wide RNAi screen in human cells and used quantitative descriptors derived from high-throughput imaging to generate multiparametric phenotypic profiles. We show that profiles predicted functions of genes by phenotypic similarity. Specifically, we examined several candidates including the largely uncharacterized gene DONSON, which shared phenotype similarity with known factors of DNA damage response (DDR) and genomic integrity. Experimental evidence supports that DONSON is a novel centrosomal protein required for DDR signalling and genomic integrity. Multiparametric phenotyping by automated imaging and computational annotation is a powerful method for functional discovery and mapping the landscape of phenotypic responses to cellular perturbations.

The design of RNA interference (RNAi) reagents is an essential step for performing loss-of-function studies in many experimental systems. The availability of sequenced and annotated genomes greatly facilitates RNAi experiments in an increasing number of organisms that were previously not genetically tractable. The E-RNAi web-service, accessible at http://www.e-rnai.org/, provides a computational resource for the optimized design and evaluation of RNAi reagents. The 2010 update of E-RNAi now covers 12 genomes, including Drosophila, Caenorhabditis elegans, human, emerging model organisms such as Schmidtea mediterranea and Acyrthosiphon pisum, as well as the medically relevant vectors Anopheles gambiae and Aedes aegypti. The web service calculates RNAi reagents based on the input of target sequences, sequence identifiers or by visual selection of target regions through a genome browser interface. It identifies optimized RNAi target-sites by ranking sequences according to their predicted specificity, efficiency and complexity. E-RNAi also facilitates the design of secondary RNAi reagents for validation experiments, evaluation of pooled siRNA reagents and batch design. Results are presented online, as a downloadable HTML report and as tab-delimited files.

Background

The analysis of high-throughput screening data sets is an expanding field in bioinformatics. High-throughput screens by RNAi generate large primary data sets which need to be analyzed and annotated to identify relevant phenotypic hits. Large-scale RNAi screens are frequently used to identify novel factors that influence a broad range of cellular processes, including signaling pathway activity, cell proliferation, and host cell infection. Here, we present a web-based application utility for the end-to-end analysis of large cell-based screening experiments by cellHTS2.

Results

The software guides the user through the configuration steps that are required for the analysis of single or multi-channel experiments. The web-application provides options for various standardization and normalization methods, annotation of data sets and a comprehensive HTML report of the screening data analysis, including a ranked hit list. Sessions can be saved and restored for later re-analysis. The web frontend for the cellHTS2 R/Bioconductor package interacts with it through an R-server implementation that enables highly parallel analysis of screening data sets. web cellHTS2 further provides a file import and configuration module for common file formats.

Conclusions

The implemented web-application facilitates the analysis of high-throughput data sets and provides a user-friendly interface. web cellHTS2 is accessible online at http://web-cellHTS2.dkfz.de. A standalone version as a virtual appliance and source code for platforms supporting Java 1.5.0 can be downloaded from the web cellHTS2 page. web cellHTS2 is freely distributed under GPL.

Summary: EBImage provides general purpose functionality for reading, writing, processing and analysis of images. Furthermore, in the context of microscopy-based cellular assays, EBImage offers tools to segment cells and extract quantitative cellular descriptors. This allows the automation of such tasks using the R programming language and use of existing tools in the R environment for signal processing, statistical modeling, machine learning and data visualization.

Availability: EBImage is free and open source, released under the LGPL license and available from the Bioconductor project (http://www.bioconductor.org/packages/release/bioc/html/EBImage.html).

Contact: gregoire.pau@ebi.ac.uk

Dishevelled (Dsh) is a cytoplasmic multidomain protein that is required for all known branches of the Wnt signalling pathway1–3. The Frizzled/planar cell polarity (Fz/PCP) signalling branch requires an asymmetric cortical localization of Dsh, but this process remains poorly understood. Using a genome-wide RNA interference (RNAi) screen in Drosophila melanogaster cells, we show that Dsh membrane localization is dependent on the Na+/H+ exchange activity of the plasma membrane exchanger Nhe2. Manipulating Nhe2 expression levels in the eye causes PCP defects, and Nhe2 interacts genetically with Fz. Our data show that the binding and surface recruitment of Dsh by Fz is pH- and charge-dependent. We identify a polybasic stretch within the Dsh DEP domain that binds to negatively charged phospholipids and appears to be mechanistically important. Dsh recruitment by Fz can be abolished by converting these basic amino-acid residues into acidic ones, as in the mutant, DshKR/E. In vivo, the DshKR/E(2×) mutant with two substituted residues fails to associate with the membrane during active PCP signalling but rescues canonical Wnt signalling defects in a dsh-background. These results suggest that direct interaction between Fz and Dsh is stabilized by a pH and charge-dependent interaction of the DEP domain with phospholipids. This stabilization is particularly important for the PCP signalling branch and, thus, promotes specific pathway selection in Wnt signalling.

The GenomeRNAi database (http://www.genomernai.org/) contains phenotypes from published cell-based RNA interference (RNAi) screens in Drosophila and Homo sapiens. The database connects observed phenotypes with annotations of targeted genes and information about the RNAi reagent used for the perturbation experiment. The availability of phenotypes from Drosophila and human screens also allows for phenotype searches across species. Besides reporting quantitative data from genome-scale screens, the new release of GenomeRNAi also enables reporting of data from microscopy experiments and curated phenotypes from published screens. In addition, the database provides an updated resource of RNAi reagents and their predicted quality that are available for the Drosophila and the human genome. The new version also facilitates the integration with other genomic data sets and contains expression profiling (RNA-Seq) data for several cell lines commonly used in RNAi experiments.

During a genome-wide RNAi screen, we isolated CG8580 as a gene involved in the innate immune response of Drosophila. CG8580, which we named Akirin, acts in parallel with the NF-κB transcription factor downstream of the Imd pathway and was required for defense against Gram-negative bacteria. Akirin is highly conserved and the human genome contains two homologues, one of which was able to rescue the loss of function phenotype in Drosophila cells. Akirins had a strict nuclear localization. Knockout of both Akirin homologues in mice revealed that one had an essential function downstream of Toll-like receptor, tumor necrosis factor and interleukin 1-β (IL-1β) signaling pathways leading to the production of IL-6. Thus, Akirin is a conserved nuclear factor required for innate immune responses.

While many core JAK/STAT pathway components have been discovered in Drosophila via classical genetic approaches, the identification of pathway regulators has been more challenging. Recently two cell-based RNAi screens for JAK/STAT pathway regulators have been undertaken using libraries of double-stranded RNAs targeting a large proportion of the predicted Drosophila transcriptome. While both screens identified multiple regulators, only relatively few loci are common to both data sets. Here we compare the two screens and discuss these differences. Although many factors are likely to be contributory, differences in the assay design are of key importance. Low levels of stimulation favouring the identification of negative pathway regulators and high levels of stimulation favouring the identification of positively acting factors. Ultimately, the results from both screens are likely to be largely complementary and have identified a range of novel candidate regulators of JAK/STAT pathway activity as a starting point for new research directions in the future.

RNA interference (RNAi) has emerged as a powerful tool to generate loss-of-function phenotypes in a variety of organisms. Combined with the sequence information of almost completely annotated genomes, RNAi technologies have opened new avenues to conduct systematic genetic screens for every annotated gene in the genome. As increasing large datasets of RNAi-induced phenotypes become available, an important challenge remains the systematic integration and annotation of functional information. Genome-wide RNAi screens have been performed both in Caenorhabditis elegans and Drosophila for a variety of phenotypes and several RNAi libraries have become available to assess phenotypes for almost every gene in the genome. These screens were performed using different types of assays from visible phenotypes to focused transcriptional readouts and provide a rich data source for functional annotation across different species. The GenomeRNAi database provides access to published RNAi phenotypes obtained from cell-based screens and maps them to their genomic locus, including possible non-specific regions. The database also gives access to sequence information of RNAi probes used in various screens. It can be searched by phenotype, by gene, by RNAi probe or by sequence and is accessible at

cellHTS is a new method for the analysis and documentation of RNAi screens.

RNA interference (RNAi) screening is a powerful technology for functional characterization of biological pathways. Interpretation of RNAi screens requires computational and statistical analysis techniques. We describe a method that integrates all steps to generate a scored phenotype list from raw data. It is implemented in an open-source Bioconductor/R package, cellHTS (). The method is useful for the analysis and documentation of individual RNAi screens. Moreover, it is a prerequisite for the integration of multiple experiments.