FlyRNAi.org-the database of the Drosophila RNAi screening center and transgenic RNAi project: 2017 update.

The FlyRNAi database of the Drosophila RNAi Screening Center (DRSC) and Transgenic RNAi Project (TRiP) at Harvard Medical School and associated DRSC/TRiP Functional Genomics Resources website (http://fgr.hms.harvard.edu) serve as a reagent production tracking system, screen data repository, and portal to the community. Through this portal, we make available protocols, online tools, and other resources useful to researchers at all stages of high-throughput functional genomics screening, from assay design and reagent identification to data analysis and interpretation. In this update, we describe recent changes and additions to our website, database and suite of online tools. Recent changes reflect a shift in our focus from a single technology (RNAi) and model species (Drosophila) to the application of additional technologies (e.g. CRISPR) and support of integrated, cross-species approaches to uncovering gene function using functional genomics and other approaches.

Controllability analysis of the directed human protein interaction network identifies disease genes and drug targets.

The protein-protein interaction (PPI) network is crucial for cellular information processing and decision-making. With suitable inputs, PPI networks drive the cells to diverse functional outcomes such as cell proliferation or cell death. Here, we characterize the structural controllability of a large directed human PPI network comprising 6,339 proteins and 34,813 interactions. This network allows us to classify proteins as "indispensable," "neutral," or "dispensable," which correlates to increasing, no effect, or decreasing the number of driver nodes in the network upon removal of that protein. We find that 21% of the proteins in the PPI network are indispensable. Interestingly, these indispensable proteins are the primary targets of disease-causing mutations, human viruses, and drugs, suggesting that altering a network's control property is critical for the transition between healthy and disease states. Furthermore, analyzing copy number alterations data from 1,547 cancer patients reveals that 56 genes that are frequently amplified or deleted in nine different cancers are indispensable. Among the 56 genes, 46 of them have not been previously associated with cancer. This suggests that controllability analysis is very useful in identifying novel disease genes and potential drug targets.

Integrating protein-protein interaction networks with phenotypes reveals signs of interactions.

A major objective of systems biology is to organize molecular interactions as networks and to characterize information flow within networks. We describe a computational framework to integrate protein-protein interaction (PPI) networks and genetic screens to predict the 'signs' of interactions (i.e., activation-inhibition relationships). We constructed a Drosophila melanogaster signed PPI network consisting of 6,125 signed PPIs connecting 3,352 proteins that can be used to identify positive and negative regulators of signaling pathways and protein complexes. We identified an unexpected role for the metabolic enzymes enolase and aldo-keto reductase as positive and negative regulators of proteolysis, respectively. Characterization of the activation-inhibition relationships between physically interacting proteins within signaling pathways will affect our understanding of many biological functions, including signal transduction and mechanisms of disease.

Optimized gene editing technology for Drosophila melanogaster using germ line-specific Cas9.

The ability to engineer genomes in a specific, systematic, and cost-effective way is critical for functional genomic studies. Recent advances using the CRISPR-associated single-guide RNA system (Cas9/sgRNA) illustrate the potential of this simple system for genome engineering in a number of organisms. Here we report an effective and inexpensive method for genome DNA editing in Drosophila melanogaster whereby plasmid DNAs encoding short sgRNAs under the control of the U6b promoter are injected into transgenic flies in which Cas9 is specifically expressed in the germ line via the nanos promoter. We evaluate the off-targets associated with the method and establish a Web-based resource, along with a searchable, genome-wide database of predicted sgRNAs appropriate for genome engineering in flies. Finally, we discuss the advantages of our method in comparison with other recently published approaches.

Genomic signatures of disease resistance in endangered staghorn corals.

White band disease (WBD) has caused unprecedented declines in the Caribbean Acropora corals, which are now listed as critically endangered species. Highly disease-resistant Acropora cervicornis genotypes exist, but the genetic underpinnings of disease resistance are not understood. Using transmission experiments, a newly assembled genome, and whole-genome resequencing of 76 A. cervicornis genotypes from Florida and Panama, we identified 10 genomic regions and 73 single-nucleotide polymorphisms that are associated with disease resistance and that include functional protein-coding changes in four genes involved in coral immunity and pathogen detection. Polygenic scores calculated from 10 genomic loci indicate that genetic screens can detect disease resistance in wild and nursery stocks of A. cervicornis across the Caribbean.

Transcriptomics reveals specific molecular mechanisms underlying transgenerational immunity in Manduca sexta.

The traditional view of innate immunity in insects is that every exposure to a pathogen triggers an identical and appropriate immune response and that prior exposures to pathogens do not confer any protective (i.e., adaptive) effect against subsequent exposure to the same pathogen. This view has been challenged by experiments demonstrating that encounters with sublethal doses of a pathogen can prime the insect's immune system and, thus, have protective effects against future lethal doses. Immune priming has been reported across several insect species, including the red flour beetle, the honeycomb moth, the bumblebee, and the European honeybee, among others. Immune priming can also be transgenerational where the parent's pathogenic history influences the immune response of its offspring. Phenotypic evidence of transgenerational immune priming (TGIP) exists in the tobacco moth Manduca sexta where first-instar progeny of mothers injected with the bacterium Serratia marcescens exhibited a significant increase of in vivo bacterial clearance. To identify the gene expression changes underlying TGIP in M. sexta, we performed transcriptome-wide, transgenerational differential gene expression analysis on mothers and their offspring after mothers were exposed to S. marcescens. We are the first to perform transcriptome-wide analysis of the gene expression changes associated with TGIP in this ecologically relevant model organism. We show that maternal exposure to both heat-killed and live S. marcescens has strong and significant transgenerational impacts on gene expression patterns in their offspring, including upregulation of peptidoglycan recognition protein, toll-like receptor 9, and the antimicrobial peptide cecropin.

Differential gene expression analysis of symbiotic and aposymbiotic Exaiptasia anemones under immune challenge with Vibrio coralliilyticus.

Anthozoans are a class of Cnidarians that includes scleractinian corals, anemones, and their relatives. Despite a global rise in disease epizootics impacting scleractinian corals, little is known about the immune response of this key group of invertebrates. To better characterize the anthozoan immune response, we used the model anemone Exaiptasia pallida to explore the genetic links between the anthozoan-algal symbioses and immunity in a two-factor RNA-Seq experiment using both symbiotic and aposymbiotic (menthol-bleached) Exaiptasia pallida exposed to the bacterial pathogen Vibrio coralliilyticus. Multivariate and univariate analyses of Exaiptasia gene expression demonstrated that exposure to live Vibrio coralliilyticus had strong and significant impacts on transcriptome-wide gene expression for both symbiotic and aposymbiotic anemones, but we did not observe strong interactions between symbiotic state and Vibrio exposure. There were 4,164 significantly differentially expressed (DE) genes for Vibrio exposure, 1,114 DE genes for aposymbiosis, and 472 DE genes for the additive combinations of Vibrio and aposymbiosis. KEGG enrichment analyses identified 11 pathways-involved in immunity (5), transport and catabolism (4), and cell growth and death (2)-that were enriched due to both Vibrio and/or aposymbiosis. Immune pathways showing strongest differential expression included complement, coagulation, nucleotide-binding, and oligomerization domain (NOD), and Toll for Vibrio exposure and coagulation and apoptosis for aposymbiosis.

Identification of potential drug targets for tuberous sclerosis complex by synthetic screens combining CRISPR-based knockouts with RNAi.

The tuberous sclerosis complex (TSC) family of tumor suppressors, TSC1 and TSC2, function together in an evolutionarily conserved protein complex that is a point of convergence for major cell signaling pathways that regulate mTOR complex 1 (mTORC1). Mutation or aberrant inhibition of the TSC complex is common in various human tumor syndromes and cancers. The discovery of novel therapeutic strategies to selectively target cells with functional loss of this complex is therefore of clinical relevance to patients with nonmalignant TSC and those with sporadic cancers. We developed a CRISPR-based method to generate homogeneous mutant Drosophila cell lines. By combining TSC1 or TSC2 mutant cell lines with RNAi screens against all kinases and phosphatases, we identified synthetic interactions with TSC1 and TSC2. Individual knockdown of three candidate genes (mRNA-cap, Pitslre, and CycT; orthologs of RNGTT, CDK11, and CCNT1 in humans) reduced the population growth rate of Drosophila cells lacking either TSC1 or TSC2 but not that of wild-type cells. Moreover, individual knockdown of these three genes had similar growth-inhibiting effects in mammalian TSC2-deficient cell lines, including human tumor-derived cells, illustrating the power of this cross-species screening strategy to identify potential drug targets.

Protein complex-based analysis framework for high-throughput data sets.

Analysis of high-throughput data increasingly relies on pathway annotation and functional information derived from Gene Ontology. This approach has limitations, in particular for the analysis of network dynamics over time or under different experimental conditions, in which modules within a network rather than complete pathways might respond and change. We report an analysis framework based on protein complexes, which are at the core of network reorganization. We generated a protein complex resource for human, Drosophila, and yeast from the literature and databases of protein-protein interaction networks, with each species having thousands of complexes. We developed COMPLEAT (http://www.flyrnai.org/compleat), a tool for data mining and visualization for complex-based analysis of high-throughput data sets, as well as analysis and integration of heterogeneous proteomics and gene expression data sets. With COMPLEAT, we identified dynamically regulated protein complexes among genome-wide RNA interference data sets that used the abundance of phosphorylated extracellular signal-regulated kinase in cells stimulated with either insulin or epidermal growth factor as the output. The analysis predicted that the Brahma complex participated in the insulin response.

UP-TORR: online tool for accurate and Up-to-Date annotation of RNAi Reagents.

RNA interference (RNAi) is a widely adopted tool for loss-of-function studies but RNAi results only have biological relevance if the reagents are appropriately mapped to genes. Several groups have designed and generated RNAi reagent libraries for studies in cells or in vivo for Drosophila and other species. At first glance, matching RNAi reagents to genes appears to be a simple problem, as each reagent is typically designed to target a single gene. In practice, however, the reagent-gene relationship is complex. Although the sequences of oligonucleotides used to generate most types of RNAi reagents are static, the reference genome and gene annotations are regularly updated. Thus, at the time a researcher chooses an RNAi reagent or analyzes RNAi data, the most current interpretation of the RNAi reagent-gene relationship, as well as related information regarding specificity (e.g., predicted off-target effects), can be different from the original interpretation. Here, we describe a set of strategies and an accompanying online tool, UP-TORR (for Updated Targets of RNAi Reagents; www.flyrnai.org/up-torr), useful for accurate and up-to-date annotation of cell-based and in vivo RNAi reagents. Importantly, UP-TORR automatically synchronizes with gene annotations daily, retrieving the most current information available, and for Drosophila, also synchronizes with the major reagent collections. Thus, UP-TORR allows users to choose the most appropriate RNAi reagents at the onset of a study, as well as to perform the most appropriate analyses of results of RNAi-based studies.