GenomeRNAi: a database for cell-based and in vivo RNAi phenotypes, 2013 update

Regulation of TORC1 in response to amino acid starvation via lysosomal recruitment of TSC2

TOR complex 1 (TORC1) is a potent anabolic regulator of cellular growth and metabolism. When cells have sufficient amino acids, TORC1 is active due to its lysosomal localization mediated via the Rag GTPases. Upon amino acid removal, the Rag GTPases release TORC1, causing it to become cytoplasmic and inactive. We show here that, upon amino acid removal, the Rag GTPases also recruit TSC2 to the lysosome, where it can act on Rheb. Only when both the Rag GTPases and Rheb are inactive is TORC1 fully released from the lysosome. Upon amino acid withdrawal, cells lacking TSC2 fail to completely release TORC1 from the lysosome, fail to completely inactivate TORC1, and fail to adjust physiologically to amino acid starvation. These data suggest that regulation of TSC2 subcellular localization may be a general mechanism to control its activity and place TSC2 in the amino-acid-sensing pathway to TORC1.

Resources for functional genomics studies in Drosophila melanogaster

Drosophila melanogaster has become a system of choice for functional genomic studies. Many resources, including online databases and software tools, are now available to support design or identification of relevant fly stocks and reagents or analysis and mining of existing functional genomic, transcriptomic, proteomic, etc. datasets. These include large community collections of fly stocks and plasmid clones, "meta" information sites like FlyBase and FlyMine, and an increasing number of more specialized reagents, databases, and online tools. Here, we introduce key resources useful to plan large-scale functional genomics studies in Drosophila and to analyze, integrate, and mine the results of those studies in ways that facilitate identification of highest-confidence results and generation of new hypotheses. We also discuss ways in which existing resources can be used and might be improved and suggest a few areas of future development that would further support large- and small-scale studies in Drosophila and facilitate use of Drosophila information by the research community more generally.

Specific inhibition of diverse pathogens in human cells by synthetic microRNA-like oligonucleotides inferred from RNAi screens

Systematic genetic perturbation screening in human cells remains technically challenging. Typically, large libraries of chemically synthesized siRNA oligonucleotides are used, each designed to degrade a specific cellular mRNA via the RNA interference (RNAi) mechanism. Here, we report on data from three genome-wide siRNA screens, conducted to uncover host factors required for infection of human cells by two bacterial and one viral pathogen. We find that the majority of phenotypic effects of siRNAs are unrelated to the intended "on-target" mechanism, defined by full complementarity of the 21-nt siRNA sequence to a target mRNA. Instead, phenotypes are largely dictated by "off-target" effects resulting from partial complementarity of siRNAs to multiple mRNAs via the "seed" region (i.e., nucleotides 2-8), reminiscent of the way specificity is determined for endogenous microRNAs. Quantitative analysis enabled the prediction of seeds that strongly and specifically block infection, independent of the intended on-target effect. This prediction was confirmed experimentally by designing oligos that do not have any on-target sequence match at all, yet can strongly reproduce the predicted phenotypes. Our results suggest that published RNAi screens have primarily, and unintentionally, screened the sequence space of microRNA seeds instead of the intended on-target space of protein-coding genes. This helps to explain why previously published RNAi screens have exhibited relatively little overlap. Our analysis suggests a possible way of identifying "seed reagents" for controlling phenotypes of interest and establishes a general strategy for extracting valuable untapped information from past and future RNAi screens.

Stable RNA interference rules for silencing

RNA interference has become an indispensable tool for loss-of-function studies across eukaryotes. By enabling stable and reversible gene silencing, shRNAs provide a means to study long-term phenotypes, perform pool-based forward genetic screens and examine the consequences of temporary target inhibition in vivo. However, efficient implementation in vertebrate systems has been hindered by technical difficulties affecting potency and specificity. Focusing on these issues, we analyse current strategies to obtain maximal knockdown with minimal off-target effects.

RNAi screening in Drosophila cells and in vivo

Here, I discuss how RNAi screening can be used effectively to uncover gene function. Specifically, I discuss the types of high-throughput assays that can be done in Drosophila cells and in vivo, RNAi reagent design and available reagent collections, automated screen pipelines, analysis of screen results, and approaches to RNAi results verification.

A synthetic lethal screen identifies FAT1 as an antagonist of caspase-8 in extrinsic apoptosis

The extrinsic apoptosis pathway is initiated by binding of death ligands to death receptors resulting in the formation of the death-inducing signaling complex (DISC). Activation of procaspase-8 within the DISC and its release from the signaling complex is required for processing executor caspases and commiting cell death. Here, we report that the atypical cadherin FAT1 interacts with caspase-8 preventing the association of caspase-8 with the DISC. We identified FAT1 in a genome-wide siRNA screen for synthetic lethal interactions with death receptor-mediated apoptosis. Knockdown of FAT1 sensitized established and patient-derived glioblastoma cell lines for apoptosis transduced by cell death ligands. Depletion of FAT1 resulted in enhanced procaspase-8 recruitment to the DISC and increased formation of caspase-8 containing secondary signaling complexes. In addition, FAT1 knockout cell lines generated by CRISPR/Cas9-mediated genome engineering were more susceptible for death receptor-mediated apoptosis. Our findings provide evidence for a mechanism to control caspase-8-dependent cell death by the atypical cadherin FAT1. These results contribute towards the understanding of effector caspase regulation in physiological conditions.

In Vivo RNAi-Based Screens: Studies in Model Organisms

RNA interference (RNAi) is a technique widely used for gene silencing in organisms and cultured cells, and depends on sequence homology between double-stranded RNA (dsRNA) and target mRNA molecules. Numerous cell-based genome-wide screens have successfully identified novel genes involved in various biological processes, including signal transduction, cell viability/death, and cell morphology. However, cell-based screens cannot address cellular processes such as development, behavior, and immunity. Drosophila and Caenorhabditis elegans are two model organisms whose whole bodies and individual body parts have been subjected to RNAi-based genome-wide screening. Moreover, Drosophila RNAi allows the manipulation of gene function in a spatiotemporal manner when it is implemented using the Gal4/UAS system. Using this inducible RNAi technique, various large-scale screens have been performed in Drosophila, demonstrating that the method is straightforward and valuable. However, accumulated results reveal that the results of RNAi-based screens have relatively high levels of error, such as false positives and negatives. Here, we review in vivo RNAi screens in Drosophila and the methods that could be used to remove ambiguity from screening results.

Predicting functional gene interactions with the hierarchical interaction score

Systems biology aims to unravel the vast network of functional interactions that govern biological systems. To date, the inference of gene interactions from large-scale 'omics data is typically achieved using correlations. We present the hierarchical interaction score (HIS) and show that the HIS outperforms commonly used methods in the inference of functional interactions between genes measured in large-scale experiments, making it a valuable statistic for systems biology.

E-TALEN: a web tool to design TALENs for genome engineering

Use of transcription activator-like effector nucleases (TALENs) is a promising new technique in the field of targeted genome engineering, editing and reverse genetics. Its applications span from introducing knockout mutations to endogenous tagging of proteins and targeted excision repair. Owing to this wide range of possible applications, there is a need for fast and user-friendly TALEN design tools. We developed E-TALEN (http://www.e-talen.org), a web-based tool to design TALENs for experiments of varying scale. E-TALEN enables the design of TALENs against a single target or a large number of target genes. We significantly extended previously published design concepts to consider genomic context and different applications. E-TALEN guides the user through an end-to-end design process of de novo TALEN pairs, which are specific to a certain sequence or genomic locus. Furthermore, E-TALEN offers a functionality to predict targeting and specificity for existing TALENs. Owing to the computational complexity of many of the steps in the design of TALENs, particular emphasis has been put on the implementation of fast yet accurate algorithms. We implemented a user-friendly interface, from the input parameters to the presentation of results. An additional feature of E-TALEN is the in-built sequence and annotation database available for many organisms, including human, mouse, zebrafish, Drosophila and Arabidopsis, which can be extended in the future.

MalaCards: an integrated compendium for diseases and their annotation

Comprehensive disease classification, integration and annotation are crucial for biomedical discovery. At present, disease compilation is incomplete, heterogeneous and often lacking systematic inquiry mechanisms. We introduce MalaCards, an integrated database of human maladies and their annotations, modeled on the architecture and strategy of the GeneCards database of human genes. MalaCards mines and merges 44 data sources to generate a computerized card for each of 16 919 human diseases. Each MalaCard contains disease-specific prioritized annotations, as well as inter-disease connections, empowered by the GeneCards relational database, its searches and GeneDecks set analyses. First, we generate a disease list from 15 ranked sources, using disease-name unification heuristics. Next, we use four schemes to populate MalaCards sections: (i) directly interrogating disease resources, to establish integrated disease names, synonyms, summaries, drugs/therapeutics, clinical features, genetic tests and anatomical context; (ii) searching GeneCards for related publications, and for associated genes with corresponding relevance scores; (iii) analyzing disease-associated gene sets in GeneDecks to yield affiliated pathways, phenotypes, compounds and GO terms, sorted by a composite relevance score and presented with GeneCards links; and (iv) searching within MalaCards itself, e.g. for additional related diseases and anatomical context. The latter forms the basis for the construction of a disease network, based on shared MalaCards annotations, embodying associations based on etiology, clinical features and clinical conditions. This broadly disposed network has a power-law degree distribution, suggesting that this might be an inherent property of such networks. Work in progress includes hierarchical malady classification, ontological mapping and disease set analyses, striving to make MalaCards an even more effective tool for biomedical research. Database URL: http://www.malacards.org/

Go retro and get a GRIP

Gene retrocopy insertions are a source of new genes and new gene functions, and can now be identified using paired-end whole genome sequencing data.

See related Research article: http://genomebiology.com/2013/14/3/R22