The Drosophila MSL complex mediates dosage compensation by increasing transcription of the single X chromosome in males approximately two-fold. This is accomplished through recognition of the X chromosome and subsequent acetylation of histone H4K16 on X-linked genes. Initial binding to the X is thought to occur at "entry sites" that contain a consensus sequence motif ("MSL recognition element" or MRE). However, this motif is only ∼2 fold enriched on X, and only a fraction of the motifs on X are initially targeted. Here we ask whether chromatin context could distinguish between utilized and non-utilized copies of the motif, by comparing their relative enrichment for histone modifications and chromosomal proteins mapped in the modENCODE project. Through a comparative analysis of the chromatin features in male S2 cells (which contain MSL complex) and female Kc cells (which lack the complex), we find that the presence of active chromatin modifications, together with an elevated local GC content in the surrounding sequences, has strong predictive value for functional MSL entry sites, independent of MSL binding. We tested these sites for function in Kc cells by RNAi knockdown of Sxl, resulting in induction of MSL complex. We show that ectopic MSL expression in Kc cells leads to H4K16 acetylation around these sites and a relative increase in X chromosome transcription. Collectively, our results support a model in which a pre-existing active chromatin environment, coincident with H3K36me3, contributes to MSL entry site selection. The consequences of MSL targeting of the male X chromosome include increase in nucleosome lability, enrichment for H4K16 acetylation and JIL-1 kinase, and depletion of linker histone H1 on active X-linked genes. Our analysis can serve as a model for identifying chromatin and local sequence features that may contribute to selection of functional protein binding sites in the genome.
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.
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.
Most studies of host-pathogen interactions have focused on pathogen-specific virulence determinants. Here, we report a genome-wide RNA interference screen to identify host factors required for intracellular bacterial pathogenesis. Using Drosophila cells and the cytosolic pathogen Listeria monocytogenes, we identified 305 double-stranded RNAs targeting a wide range of cellular functions that altered L. monocytogenes infection. Comparison to a similar screen with Mycobacterium fortuitum, a vacuolar pathogen, identified host factors that may play a general role in intracellular pathogenesis and factors that specifically affect access to the cytosol by L. monocytogenes.
Regulation of chromatin structure is critical in many fundamental cellular processes. Previous studies have suggested that the Rb tumor suppressor may recruit multiple chromatin regulatory proteins to repress E2F, a key regulator of cell proliferation and differentiation. Taking advantage of the evolutionary conservation of the E2F pathway, we have conducted a genome-wide RNAi screen in cultured Drosophila cells for genes required for repression of E2F activity. Among the genes identified are components of the putative Domino chromatin remodeling complex, as well as the Polycomb Group (PcG) protein-like fly tumor suppressor, L3mbt, and the related CG16975/dSfmbt. These factors are recruited to E2F-responsive promoters through physical association with E2F and are required for repression of endogenous E2F target genes. Surprisingly, their inhibitory activities on E2F appear to be independent of Rb. In Drosophila, domino mutation enhances cell proliferation induced by E2F overexpression and suppresses a loss-of-function cyclin E mutation. These findings suggest that potential chromatin regulation mediated by Domino and PcG-like factors plays an important role in controlling E2F activity and cell growth.
Multiple centrosomes in tumor cells create the potential for multipolar divisions that can lead to aneuploidy and cell death. Nevertheless, many cancer cells successfully divide because of mechanisms that suppress multipolar mitoses. A genome-wide RNAi screen in Drosophila S2 cells and a secondary analysis in cancer cells defined mechanisms that suppress multipolar mitoses. In addition to proteins that organize microtubules at the spindle poles, we identified novel roles for the spindle assembly checkpoint, cortical actin cytoskeleton, and cell adhesion. Using live cell imaging and fibronectin micropatterns, we found that interphase cell shape and adhesion pattern can determine the success of the subsequent mitosis in cells with extra centrosomes. These findings may identify cancer-selective therapeutic targets: HSET, a normally nonessential kinesin motor, was essential for the viability of certain extra centrosome-containing cancer cells. Thus, morphological features of cancer cells can be linked to unique genetic requirements for survival.
Biological networks are highly complex systems, consisting largely of enzymes that act as molecular switches to activate/inhibit downstream targets via post-translational modification. Computational techniques have been developed to perform signaling network inference using some high-throughput data sources, such as those generated from transcriptional and proteomic studies, but comparable methods have not been developed to use high-content morphological data, which are emerging principally from large-scale RNAi screens, to these ends. Here, we describe a systematic computational framework based on a classification model for identifying genetic interactions using high-dimensional single-cell morphological data from genetic screens, apply it to RhoGAP/GTPase regulation in Drosophila, and evaluate its efficacy. Augmented by knowledge of the basic structure of RhoGAP/GTPase signaling, namely, that GAPs act directly upstream of GTPases, we apply our framework for identifying genetic interactions to predict signaling relationships between these proteins. We find that our method makes mediocre predictions using only RhoGAP single-knockdown morphological data, yet achieves vastly improved accuracy by including original data from a double-knockdown RhoGAP genetic screen, which likely reflects the redundant network structure of RhoGAP/GTPase signaling. We consider other possible methods for inference and show that our primary model outperforms the alternatives. This work demonstrates the fundamental fact that high-throughput morphological data can be used in a systematic, successful fashion to identify genetic interactions and, using additional elementary knowledge of network structure, to infer signaling relations.
Wnt proteins are secreted, lipid-modified glycoproteins that control animal development and adult tissue homeostasis. Secretion of Wnt proteins is at least partly regulated by a dedicated machinery. Here, we report a genome-wide RNA interference screen for genes involved in the secretion of Wingless (Wg), a Drosophila Wnt. We identify three new genes required for Wg secretion. Of these, Emp24 and Eclair are required for proper export of Wg from the endoplasmic reticulum (ER). We propose that Emp24 and Eca act as specific cargo receptors for Wg to concentrate it in forming vesicles at sites of ER export.
Defects in miRNA biogenesis or activity are associated to development abnormalities and diseases. In Drosophila, miRNAs are predominantly loaded in Argonaute-1, which they guide for silencing of target RNAs. The miRNA pathway overlaps the RNAi pathway in this organism, as miRNAs may also associate with Argonaute-2, the mediator of RNAi. We set up a gene construct in which a single inducible promoter directs the expression of the GFP protein as well as two miRNAs perfectly matching the GFP sequences. We show that self-silencing of the resulting automiG gene requires Drosha, Pasha, Dicer-1, Dicer-2 and Argonaute-2 loaded with the anti-GFP miRNAs. In contrast, self-silencing of the automiG gene does not involve Argonaute-1. Thus, automiG reports in vivo for both miRNA biogenesis and Ago-2 mediated silencing, providing a powerful biosensor to identify situations where miRNA or siRNA pathways are impaired. As a proof of concept, we used automiG as a biosensor to screen a chemical library and identified 29 molecules that strongly inhibit miRNA silencing, out of which 5 also inhibit RNAi triggered by long double-stranded RNA. Finally, the automiG sensor is also self-silenced by the anti-GFP miRNAs in HeLa cells and might be easily used to identify factors involved in miRNA biogenesis and silencing guided by perfect target complementarity in mammals.
We present a resource of high quality lists of functionally related Drosophila genes, e.g. based on protein domains (kinases, transcription factors, etc.) or cellular function (e.g. autophagy, signal transduction). To establish these lists, we relied on different inputs, including curation from databases or the literature and mapping from other species. Moreover, as an added curation and quality control step, we asked experts in relevant fields to review many of the lists. The resource is available online for scientists to search and view, and is editable based on community input. Annotation of gene groups is an ongoing effort and scientific need will typically drive decisions regarding which gene lists to pursue. We anticipate that the number of lists will increase over time; that the composition of some lists will grow and/or change over time as new information becomes available; and that the lists will benefit the scientific community, e.g. at experimental design and data analysis stages. Based on this, we present an easily updatable online database, available at www.flyrnai.org/glad, at which gene group lists can be viewed, searched and downloaded.
Store-operated Ca2+ entry is mediated by Ca2+ release-activated Ca2+ (CRAC) channels following Ca2+ release from intracellular stores. We performed a genome-wide RNA interference (RNAi) screen in Drosophila cells to identify proteins that inhibit store-operated Ca2+ influx. A secondary patch-clamp screen identified CRACM1 and CRACM2 (CRAC modulators 1 and 2) as modulators of Drosophila CRAC currents. We characterized the human ortholog of CRACM1, a plasma membrane-resident protein encoded by gene FLJ14466. Although overexpression of CRACM1 did not affect CRAC currents, RNAi-mediated knockdown disrupted its activation. CRACM1 could be the CRAC channel itself, a subunit of it, or a component of the CRAC signaling machinery.
Eukaryotic gene expression requires export of messenger RNAs (mRNAs) from their site of transcription in the nucleus to the cytoplasm where they are translated. While mRNA export has been studied in yeast, the complexity of gene structure and cellular function in metazoan cells has likely led to increased diversification of these organisms' export pathways. Here we report the results of a genome-wide RNAi screen in which we identify 72 factors required for polyadenylated [poly-(A(+))] mRNA export from the nucleus in Drosophila cells. Using structural and functional conservation analysis of yeast and Drosophila mRNA export factors, we expose the evolutionary divergence of eukaryotic mRNA export pathways. Additionally, we demonstrate the differential export requirements of two endogenous heat-inducible transcripts--intronless heat-shock protein 70 (HSP70) and intron-containing HSP83--and identify novel export factors that participate in HSP83 mRNA splicing. We characterize several novel factors and demonstrate their participation in interactions with known components of the Drosophila export machinery. One of these factors, Drosophila melanogaster PCI domain-containing protein 2 (dmPCID2), associates with polysomes and may bridge the transition between exported messenger ribonucleoprotein particles (mRNPs) and polysomes. Our results define the global network of factors involved in Drosophila mRNA export, reveal specificity in the export requirements of different transcripts, and expose new avenues for future work in mRNA export.
Damage initiates a pleiotropic cellular response aimed at cellular survival when appropriate. To identify genes required for damage survival, we used a cell-based RNAi screen against the Drosophila genome and the alkylating agent methyl methanesulphonate (MMS). Similar studies performed in other model organisms report that damage response may involve pleiotropic cellular processes other than the central DNA repair components, yet an intuitive systems level view of the cellular components required for damage survival, their interrelationship, and contextual importance has been lacking. Further, by comparing data from different model organisms, identification of conserved and presumably core survival components should be forthcoming. We identified 307 genes, representing 13 signaling, metabolic, or enzymatic pathways, affecting cellular survival of MMS-induced damage. As expected, the majority of these pathways are involved in DNA repair; however, several pathways with more diverse biological functions were also identified, including the TOR pathway, transcription, translation, proteasome, glutathione synthesis, ATP synthesis, and Notch signaling, and these were equally important in damage survival. Comparison with genomic screen data from Saccharomyces cerevisiae revealed no overlap enrichment of individual genes between the species, but a conservation of the pathways. To demonstrate the functional conservation of pathways, five were tested in Drosophila and mouse cells, with each pathway responding to alkylation damage in both species. Using the protein interactome, a significant level of connectivity was observed between Drosophila MMS survival proteins, suggesting a higher order relationship. This connectivity was dramatically improved by incorporating the components of the 13 identified pathways within the network. Grouping proteins into "pathway nodes" qualitatively improved the interactome organization, revealing a highly organized "MMS survival network." We conclude that identification of pathways can facilitate comparative biology analysis when direct gene/orthologue comparisons fail. A biologically intuitive, highly interconnected MMS survival network was revealed after we incorporated pathway data in our interactome analysis.
BACKGROUND: The Notch signaling pathway regulates a diverse array of developmental processes, and aberrant Notch signaling can lead to diseases, including cancer. To obtain a more comprehensive understanding of the genetic network that integrates into Notch signaling, we performed a genome-wide RNAi screen in Drosophila cell culture to identify genes that modify Notch-dependent transcription. RESULTS: Employing complementary data analyses, we found 399 putative modifiers: 189 promoting and 210 antagonizing Notch activated transcription. These modifiers included several known Notch interactors, validating the robustness of the assay. Many novel modifiers were also identified, covering a range of cellular localizations from the extracellular matrix to the nucleus, as well as a large number of proteins with unknown function. Chromatin-modifying proteins represent a major class of genes identified, including histone deacetylase and demethylase complex components and other chromatin modifying, remodeling and replacement factors. A protein-protein interaction map of the Notch-dependent transcription modifiers revealed that a large number of the identified proteins interact physically with these core chromatin components. CONCLUSIONS: The genome-wide RNAi screen identified many genes that can modulate Notch transcriptional output. A protein interaction map of the identified genes highlighted a network of chromatin-modifying enzymes and remodelers that regulate Notch transcription. Our results open new avenues to explore the mechanisms of Notch signal regulation and the integration of this pathway into diverse cellular processes.
Reactive Oxygen Species (ROS) are a natural by-product of cellular growth and proliferation, and are required for fundamental processes such as protein-folding and signal transduction. However, ROS accumulation, and the onset of oxidative stress, can negatively impact cellular and genomic integrity. Signalling networks have evolved to respond to oxidative stress by engaging diverse enzymatic and non-enzymatic antioxidant mechanisms to restore redox homeostasis. The architecture of oxidative stress response networks during periods of normal growth, and how increased ROS levels dynamically reconfigure these networks are largely unknown. In order to gain insight into the structure of signalling networks that promote redox homeostasis we first performed genome-scale RNAi screens to identify novel suppressors of superoxide accumulation. We then infer relationships between redox regulators by hierarchical clustering of phenotypic signatures describing how gene inhibition affects superoxide levels, cellular viability, and morphology across different genetic backgrounds. Genes that cluster together are likely to act in the same signalling pathway/complex and thus make "functional interactions". Moreover we also calculate differential phenotypic signatures describing the difference in cellular phenotypes following RNAi between untreated cells and cells submitted to oxidative stress. Using both phenotypic signatures and differential signatures we construct a network model of functional interactions that occur between components of the redox homeostasis network, and how such interactions become rewired in the presence of oxidative stress. This network model predicts a functional interaction between the transcription factor Jun and the IRE1 kinase, which we validate in an orthogonal assay. We thus demonstrate the ability of systems-biology approaches to identify novel signalling events.