An automated, image-based RNAi screen for cell shape reveals roles for membrane secretion factors in cell spreading.
Recent technological advances in microscopy have enabled cell-based whole genome screens, but the analysis of the vast amount of image data generated by such screens usually proves to be rate limiting. In this study, we performed a whole genome RNA interference (RNAi) screen to uncover genes that affect spreading of Drosophila melanogaster S2 cells using several computational methods for analyzing the image data in an automated manner. Expected genes in the Scar-Arp2/3 actin nucleation pathway were identified as well as casein kinase I, which had a similar morphological RNAi signature. A distinct nonspreading morphological phenotype was identified for genes involved in membrane secretion or synthesis. In this group, we identified a new secretory peptide and investigated the functions of two poorly characterized endoplasmic reticulum proteins that have roles in secretion. Thus, this genome-wide screen succeeded in identifying known and unexpected proteins that are important for cell spreading, and the computational tools developed in this study should prove useful for other types of automated whole genome screens.
Parallel RNA interference screens and gene expression arrays in six Drosophila cell lines identified regulators of cell morphology, including a neuronal function for the kinase minibrain/DYRK1A in the regulation of protrusion morphology.
In recent years RNAi screening has proven a powerful tool for dissecting gene functions in animal cells in culture. However, to date, most RNAi screens have been performed in a single cell line, and results then extrapolated across cell types and systems.
Here, to dissect generic and cell type-specific mechanisms underlying cell morphology, we have performed identical kinome RNAi screens in six different Drosophila cell lines, derived from two distinct tissues of origin. This analysis identified a core set of kinases required for normal cell morphology in all lines tested, together with a number of kinases with cell type-specific functions. Most significantly, the screen identified a role for minibrain (mnb/DYRK1A), a kinase associated with Down's syndrome, in the regulation of actin-based protrusions in CNS-derived cell lines. This cell type-specific requirement was not due to the peculiarities in the morphology of CNS-derived cells and could not be attributed to differences in mnb expression. Instead, it likely reflects differences in gene expression that constitute the cell type-specific functional context in which mnb/DYRK1A acts.
Using parallel RNAi screens and gene expression analyses across cell types we have identified generic and cell type-specific regulators of cell morphology, which include mnb/DYRK1A in the regulation of protrusion morphology in CNS-derived cell lines. This analysis reveals the importance of using different cell types to gain a thorough understanding of gene function across the genome and, in the case of kinases, the difficulties of using the differential gene expression to predict function.
Here we describe a detailed methodology to study the function of genes whose products function during mitosis by dsRNA-mediated interference (RNAi) in cultured cells of Drosophila melanogaster. This procedure is particularly useful for the analysis of genes for which genetic mutations are not available or for the dissection of complicated phenotypes derived from the analysis of such mutants. With the advent of whole genome sequencing it is expected that RNAi-based screenings will be one method of choice for the identification and study of novel genes involved in particular cellular processes. In this paper we focused particularly on the procedures for the proper phenotypic analysis of cells after RNAi-mediated depletion of proteins required for mitosis, the process by which the genetic information is segregated equally between daughter cells. We use RNAi of the microtubule-associated protein MAST/Orbit as an example for the usefulness of the technique.
Mitosis; Microtubules; Kinetochores; Drosophila
Genome-scale RNA-interference (RNAi) screens are becoming ever more common gene discovery tools. However, whilst every screen identifies interacting genes, less attention has been given to how factors such as library design and post-screening bioinformatics may be effecting the data generated.
Here we present a new genome-wide RNAi screen of the Drosophila JAK/STAT signalling pathway undertaken in the Sheffield RNAi Screening Facility (SRSF). This screen was carried out using a second-generation, computationally optimised dsRNA library and analysed using current methods and bioinformatic tools. To examine advances in RNAi screening technology, we compare this screen to a biologically very similar screen undertaken in 2005 with a first-generation library. Both screens used the same cell line, reporters and experimental design, with the SRSF screen identifying 42 putative regulators of JAK/STAT signalling, 22 of which verified in a secondary screen and 16 verified with an independent probe design. Following reanalysis of the original screen data, comparisons of the two gene lists allows us to make estimates of false discovery rates in the SRSF data and to conduct an assessment of off-target effects (OTEs) associated with both libraries. We discuss the differences and similarities between the resulting data sets and examine the relative improvements in gene discovery protocols.
Our work represents one of the first direct comparisons between first- and second-generation libraries and shows that modern library designs together with methodological advances have had a significant influence on genome-scale RNAi screens.
Genome screening; RNAi; Off-target effect; JAK/STAT pathway; Functional genomics; dsRNA
The completion of the genome sequencing for several organisms has
created a great demand for genomic tools that can systematically
analyze the growing wealth of data. In contrast to the classical
reverse genetics approach of creating specific knockout cell lines
or animals that is time-consuming and expensive, RNA-mediated
interference (RNAi) has emerged as a fast, simple, and
cost-effective technique for gene knockdown in large scale. Since
its discovery as a gene silencing response to double-stranded RNA
(dsRNA) with homology to endogenous genes in
Caenorhabditis elegans (C elegans),
RNAi technology has been adapted to various high-throughput
screens (HTS) for genome-wide loss-of-function (LOF) analysis.
Biochemical insights into the endogenous mechanism of
RNAi have led to advances in RNAi methodology including RNAi
molecule synthesis, delivery, and sequence design. In this
article, we will briefly review these various RNAi library designs
and discuss the benefits and drawbacks of each library strategy.
In many eukaryotic cells, double-stranded RNA (dsRNA) triggers RNA interference (RNAi), the specific degradation of RNA of homologous sequence. RNAi is now a major tool for reverse-genetics projects, including large-scale high-throughput screens. Recent reports have questioned the specificity of RNAi, raising problems in interpretation of RNAi-based experiments.
Using the protozoan Trypanosoma brucei as a model, we designed a functional complementation assay to ascertain that phenotypic effect(s) observed upon RNAi were due to specific silencing of the targeted gene. This was applied to a cytoskeletal gene encoding the paraflagellar rod protein 2 (TbPFR2), whose product is essential for flagellar motility. We demonstrate the complementation of TbPFR2, silenced via dsRNA targeting its UTRs, through the expression of a tagged RNAi-resistant TbPFR2 encoding a protein that could be immunolocalized in the flagellum. Next, we performed a functional complementation of TbPFR2, silenced via dsRNA targeting its coding sequence, through heterologous expression of the TbPFR2 orthologue gene from Trypanosoma cruzi: the flagellum regained its motility.
This work shows that functional complementation experiments can be readily performed in order to ascertain that phenotypic effects observed upon RNAi experiments are indeed due to the specific silencing of the targetted gene. Further, the results described here are of particular interest when reverse genetics studies cannot be easily achieved in organisms not amenable to RNAi. In addition, our strategy should constitute a firm basis to elaborate functional-dissection studies of genes from other organisms.
The recently developed RNA interference (RNAi) technology has created an unprecedented opportunity which allows the function of individual genes in whole organisms or cell lines to be interrogated at genome-wide scale. However, multiple issues, such as off-target effects or low efficacies in knocking down certain genes, have produced RNAi screening results that are often noisy and that potentially yield both high rates of false positives and false negatives. Therefore, integrating RNAi screening results with other information, such as protein-protein interaction (PPI), may help to address these issues.
By analyzing 24 genome-wide RNAi screens interrogating various biological processes in Drosophila, we found that RNAi positive hits were significantly more connected to each other when analyzed within a protein-protein interaction network, as opposed to random cases, for nearly all screens. Based on this finding, we developed a network-based approach to identify false positives (FPs) and false negatives (FNs) in these screening results. This approach relied on a scoring function, which we termed NePhe, to integrate information obtained from both PPI network and RNAi screening results. Using a novel rank-based test, we compared the performance of different NePhe scoring functions and found that diffusion kernel-based methods generally outperformed others, such as direct neighbor-based methods. Using two genome-wide RNAi screens as examples, we validated our approach extensively from multiple aspects. We prioritized hits in the original screens that were more likely to be reproduced by the validation screen and recovered potential FNs whose involvements in the biological process were suggested by previous knowledge and mutant phenotypes. Finally, we demonstrated that the NePhe scoring system helped to biologically interpret RNAi results at the module level.
By comprehensively analyzing multiple genome-wide RNAi screens, we conclude that network information can be effectively integrated with RNAi results to produce suggestive FPs and FNs, and to bring biological insight to the screening results.
While genetic screens have identified many genes essential for neurite outgrowth, they have been limited in their ability to identify neural genes that also have earlier critical roles in the gastrula, or neural genes for which maternally contributed RNA compensates for gene mutations in the zygote. To address this, we developed methods to screen the Drosophila genome using RNA-interference (RNAi) on primary neural cells and present the results of the first full-genome RNAi screen in neurons. We used live-cell imaging and quantitative image analysis to characterize the morphological phenotypes of fluorescently labelled primary neurons and glia in response to RNAi-mediated gene knockdown. From the full genome screen, we focused our analysis on 104 evolutionarily conserved genes that when downregulated by RNAi, have morphological defects such as reduced axon extension, excessive branching, loss of fasciculation, and blebbing. To assist in the phenotypic analysis of the large data sets, we generated image analysis algorithms that could assess the statistical significance of the mutant phenotypes. The algorithms were essential for the analysis of the thousands of images generated by the screening process and will become a valuable tool for future genome-wide screens in primary neurons. Our analysis revealed unexpected, essential roles in neurite outgrowth for genes representing a wide range of functional categories including signalling molecules, enzymes, channels, receptors, and cytoskeletal proteins. We also found that genes known to be involved in protein and vesicle trafficking showed similar RNAi phenotypes. We confirmed phenotypes of the protein trafficking genes Sec61alpha and Ran GTPase using Drosophila embryo and mouse embryonic cerebral cortical neurons, respectively. Collectively, our results showed that RNAi phenotypes in primary neural culture can parallel in vivo phenotypes, and the screening technique can be used to identify many new genes that have important functions in the nervous system.
Development and function of the brain requires the coordinated action of thousands of genes, and currently we understand the roles of only a small fraction of them. Recent advances in genomics, such as the sequencing of entire genomes and the discovery of RNA-interference as a means of testing the effects of gene loss, have opened up the possibility to systematically analyze the function of all known and predicted genes in an organism. Until now, this type of functional genomics approach has not been applied to the study of very complex cells, such as the brain's neurons, on a full-genome scale. In this work, we developed techniques to test all genes, one by one in a rapid manner, for their potential role in neuronal development using neurons isolated from fruit fly embryos. These results yielded a global perspective of what types of genes are necessary for brain development; importantly, they show that a large variety of genes can be studied in this way.
Recently, High-content screening (HCS) has been combined with RNA interference (RNAi) to become an essential image-based high-throughput method for studying genes and biological networks through RNAi-induced cellular phenotype analyses. However, a genome-wide RNAi-HCS screen typically generates tens of thousands of images, most of which remain uncategorized due to the inadequacies of existing HCS image analysis tools. Until now, it still requires highly trained scientists to browse a prohibitively large RNAi-HCS image database and produce only a handful of qualitative results regarding cellular morphological phenotypes. For this reason we have developed intelligent interfaces to facilitate the application of the HCS technology in biomedical research. Our new interfaces empower biologists with computational power not only to effectively and efficiently explore large-scale RNAi-HCS image databases, but also to apply their knowledge and experience to interactive mining of cellular phenotypes using Content-Based Image Retrieval (CBIR) with Relevance Feedback (RF) techniques.
RNAi Screens in Drosophila and human cells for novel actin regulators revealed conserved roles for proteins involved in nuclear actin export, RNA splicing, and ubiquitination.
Although a large number of actin-binding proteins and their regulators have been identified through classical approaches, gaps in our knowledge remain. Here, we used genome-wide RNA interference as a systematic method to define metazoan actin regulators based on visual phenotype. Using comparative screens in cultured Drosophila and human cells, we generated phenotypic profiles for annotated actin regulators together with proteins bearing predicted actin-binding domains. These phenotypic clusters for the known metazoan “actinome” were used to identify putative new core actin regulators, together with a number of genes with conserved but poorly studied roles in the regulation of the actin cytoskeleton, several of which we studied in detail. This work suggests that although our search for new components of the core actin machinery is nearing saturation, regulation at the level of nuclear actin export, RNA splicing, ubiquitination, and other upstream processes remains an important but unexplored frontier of actin biology.
A second generation dsRNA library was used to re-assess factors that influence the outcome of transcriptional reporter-based whole-genome RNAi screens for the Wnt/Wingless (wg) and Hedgehog (hh)-signaling pathways.
Off-target effects have been demonstrated to be a major source of false-positives in RNA interference (RNAi) high-throughput screens. In this study, we re-assess the previously published transcriptional reporter-based whole-genome RNAi screens for the Wingless and Hedgehog signaling pathways using second generation double-stranded RNA libraries. Furthermore, we investigate other factors that may influence the outcome of such screens, including cell-type specificity, robustness of reporters, and assay normalization, which determine the efficacy of RNAi-knockdown of target genes.
The characteristic bipolar shape of the mitotic spindle is produced by the focusing of the minus ends of microtubules at the spindle poles. The focus is maintained by the centrosome, a microtubule-nucleating organelle, as well as by proteins that are capable of focusing kinetochore fibers (K fibers) even in the absence of a centrosome. Here, we have performed a small-scale RNA interference (RNAi) screen of known or suspected pole-related proteins in Drosophila S2 cells. An unexpected outcome of this screen was the finding that one of the four Drosophila Mob proteins (a family of kinase regulators) plays a role in spindle pole organization. Time-lapse microscopy of mitotic cells depleted of Drosophila Mob4 by RNAi revealed that the K fibers splay apart and do not maintain their focus either in the presence or absence of functional centrosomes. The Mob4 RNAi phenotype most closely resembles that observed after depletion of the protein encoded by abnormal spindle (Asp), although Asp localization is not substantially affected by Mob4 RNAi. Expression of a Drosophila Mob4-GFP fusion protein revealed its localization to the nucleus in interphase and to spindle poles and kinetochores during mitosis. We propose that Mob4 in Drosophila controls a mitotic kinase that in turn regulates downstream target proteins involved in K fiber focusing at the poles.
RNAi; Centrosome; Microtubule; Kinetochore; γ-tubulin
RNA interference (RNAi) is a powerful and widely used approach to investigate gene function, but a major limitation of the approach is the high incidence of non-specific phenotypes that arise due to off-target effects. We previously showed that RNAi-mediated knock-down of pico, which encodes the only member of the MRL family of adapter proteins in Drosophila, resulted in reduction in cell number and size leading to reduced tissue growth. In contrast, a recent study reported that pico knockdown leads to tissue dysmorphology, pointing to an indirect role for pico in the control of wing size. To understand the cause of this disparity we have utilised a synthetic RNAi-resistant transgene, which bears minimal sequence homology to the predicted dsRNA but encodes wild type Pico protein, to reanalyse the RNAi lines used in the two studies. We find that the RNAi lines from different sources exhibit different effects, with one set of lines uniquely resulting in a tissue dysmorphology phenotype when expressed in the developing wing. Importantly, the loss of tissue morphology fails to be complemented by co-overexpression of RNAi-resistant pico suggesting that this phenotype is the result of an off-target effect. This highlights the importance of careful validation of RNAi-induced phenotypes, and shows the potential of synthetic transgenes for their experimental validation.
Maintaining adequate proteasomal proteolytic activity is essential for eukaryotic cells. For metazoan cells, little is known about the composition of genes that are regulated in the proteasome network or the mechanisms that modulate the levels of proteasome genes. Previously, two distinct treatments have been observed to induce 26S proteasome levels in Drosophila melanogaster cell lines, RNA interference (RNAi)-mediated inhibition of the 26S proteasome subunit Rpn10/S5a and suppression of proteasome activity through treatment with active-site inhibitors. We have carried out genome array profiles from cells with decreased Rpn10/S5a levels using RNAi or from cells treated with proteasome inhibitor MG132 and have thereby identified candidate genes that are regulated as part of a metazoan proteasome network. The profiles reveal that the majority of genes that were identified to be under the control of the regulatory network consisted of 26S proteasome subunits. The 26S proteasome genes, including three new subunits, Ubp6p, Uch-L3, and Sem1p, were found to be up-regulated. A number of genes known to have proteasome-related functions, including Rad23, isopeptidase T, sequestosome, and the genes for the segregase complex TER94/VCP-Ufd1-Npl4 were also found to be up-regulated. RNAi-mediated inhibition against the segregase complex genes demonstrated pronounced stabilization of proteasome substrates throughout the Drosophila cell. Finally, transcriptional reporter assays and deletion mapping studies in Drosophila demonstrate that proteasome mRNA induction is dependent upon the 5′ untranslated regions (UTRs). Transfer of the 5′ UTR from the proteasome subunit Rpn1/S2 to a noninducible promoter was sufficient to confer transcriptional upregulation of the reporter mRNA after proteasome inhibition.
RNA interference (RNAi) is a process in which double-strand RNA (dsRNA) directs the specific degradation of a corresponding target mRNA. The mediators of this process are small dsRNAs, of ∼21 bp in length, called small interfering RNAs (siRNAs). siRNAs, which can be prepared in vitro in a number of ways and then transfected into cells, can direct the degradation of corresponding mRNAs inside these cells. Hence, siRNAs represent a powerful tool for studying gene functions, as well as having the potential of being highly specific pharmaceutical agents. Some limitations in using this technology exist because the preparation of siRNA in vitro and screening for siRNAs efficient in RNAi can be expensive and time-consuming processes. Here, we demonstrate that custom oligonucleotide arrays can be efficiently used for the preparation of defined mixtures of siRNAs for the silencing of exogenous and endogenous genes. The method is fast, inexpensive, does not require siRNA optimization and has a number of advantages over methods utilizing enzymatic preparation of siRNAs by digestion of longer dsRNAs, as well as methods based on chemical synthesis of individual siRNAs or their DNA templates.
Phenotypes are an important subject of biomedical research for which many repositories have already been created. Most of these databases are either dedicated to a single species or to a single disease of interest. With the advent of technologies to generate phenotypes in a high-throughput manner, not only is the volume of phenotype data growing fast but also the need to organize these data in more useful ways. We have created PhenomicDB (freely available at ), a multi-species genotype/phenotype database, which shows phenotypes associated with their corresponding genes and grouped by gene orthologies across a variety of species. We have enhanced PhenomicDB recently by additionally incorporating quantitative and descriptive RNA interference (RNAi) screening data, by enabling the usage of phenotype ontology terms and by providing information on assays and cell lines. We envision that integration of classical phenotypes with high-throughput data will bring new momentum and insights to our understanding. Modern analysis tools under development may help exploiting this wealth of information to transform it into knowledge and, eventually, into novel therapeutic approaches.
The majority of new drug approvals for cancer are based on existing therapeutic targets. One approach to the identification of novel targets is to perform high-throughput RNA interference (RNAi) cellular viability screens. We describe a novel approach combining RNAi screening in multiple cell lines with gene expression and genomic profiling to identify novel cancer targets. We performed parallel RNAi screens in multiple cancer cell lines to identify genes that are essential for viability in some cell lines but not others, suggesting that these genes constitute key drivers of cellular survival in specific cancer cells. This approach was verified by the identification of PIK3CA, silencing of which was selectively lethal to the MCF7 cell line, which harbours an activating oncogenic PIK3CA mutation. We combined our functional RNAi approach with gene expression and genomic analysis, allowing the identification of several novel kinases, including WEE1, that are essential for viability only in cell lines that have an elevated level of expression of this kinase. Furthermore, we identified a subset of breast tumours that highly express WEE1 suggesting that WEE1 could be a novel therapeutic target in breast cancer. In conclusion, this strategy represents a novel and effective strategy for the identification of functionally important therapeutic targets in cancer.
RNAi screens have, to date, identified many genes required for mitotic divisions of Drosophila tissue culture cells. However, the inventory of such genes remains incomplete. We have combined the powers of bioinformatics and RNAi technology to detect novel mitotic genes. We found that Drosophila genes involved in mitosis tend to be transcriptionally co-expressed. We thus constructed a co-expression–based list of 1,000 genes that are highly enriched in mitotic functions, and we performed RNAi for each of these genes. By limiting the number of genes to be examined, we were able to perform a very detailed phenotypic analysis of RNAi cells. We examined dsRNA-treated cells for possible abnormalities in both chromosome structure and spindle organization. This analysis allowed the identification of 142 mitotic genes, which were subdivided into 18 phenoclusters. Seventy of these genes have not previously been associated with mitotic defects; 30 of them are required for spindle assembly and/or chromosome segregation, and 40 are required to prevent spontaneous chromosome breakage. We note that the latter type of genes has never been detected in previous RNAi screens in any system. Finally, we found that RNAi against genes encoding kinetochore components or highly conserved splicing factors results in identical defects in chromosome segregation, highlighting an unanticipated role of splicing factors in centromere function. These findings indicate that our co-expression–based method for the detection of mitotic functions works remarkably well. We can foresee that elaboration of co-expression lists using genes in the same phenocluster will provide many candidate genes for small-scale RNAi screens aimed at completing the inventory of mitotic proteins.
Mitosis is the evolutionarily conserved process that enables a dividing cell to equally partition its genetic material between the two daughter cells. The fidelity of mitotic division is crucial for normal development of multicellular organisms and to prevent cancer or birth defects. Understanding the molecular mechanisms of mitosis requires the identification of genes involved in this process. Previous studies have shown that such genes can be readily identified by RNA interference (RNAi) in Drosophila tissue culture cells. Because the inventory of mitotic genes is still incomplete, we have undertaken an RNAi screen using a novel approach. We used a co-expression–based bioinformatic procedure to select a group of 1,000 genes enriched in mitotic functions from a dataset of 13,166 Drosophila genes. This group includes roughly half of the known mitotic genes, implying that it should contain half of all mitotic genes, including those that are currently unknown. We performed RNAi against each of the 1,000 genes in the group. By limiting the number of genes to be examined, we were able to perform a very detailed phenotypic analysis of RNAi cells. This analysis allowed the identification of 70 genes whose mitotic role was previously unknown; 30 are required for proper chromosome segregation and 40 are required to maintain chromosome integrity.
Until just a few years ago, RNA interference (RNAi) technology was restricted to the research fields of plants, C. elegans or Drosophila. The discovery of gene silencing by in vitro synthesized double-stranded RNA (dsRNA) in mammalian cells has made the use of RNAi possible in nearly the entire life science kingdom. DNA vectors delivering small interfering RNA (siRNA) directed by polymerase III or polymerase II promoters to persistently inhibit target genes expression have extended this technology to study in vivo function of these genes. Recently, RNAi has been used as a powerful tool in the functional analysis of nuclear receptors and their coregulators. This short review will cover studies in this area.
The introduction ten years ago of RNA interference (RNAi) as a tool for molecular exploration in Trypanosoma brucei has led to a surge in our understanding of the pathogenesis and biology of this human parasite. In particular, a genome-wide RNAi screen has recently been combined with next-generation Illumina sequencing to expose catalogues of genes associated with loss of fitness in distinct developmental stages. At present, this technology is restricted to RNAi-positive protozoan parasites, which excludes T. cruzi, Leishmania major, and Plasmodium falciparum. Therefore, elucidating the mechanism of RNAi and identifying the essential components of the pathway is fundamental for improving RNAi efficiency in T. brucei and for transferring the RNAi tool to RNAi-deficient pathogens. Here we used comparative genomics of RNAi-positive and -negative trypanosomatid protozoans to identify the repertoire of factors in T. brucei. In addition to the previously characterized Argonaute 1 (AGO1) protein and the cytoplasmic and nuclear Dicers, TbDCL1 and TbDCL2, respectively, we identified the RNA Interference Factors 4 and 5 (TbRIF4 and TbRIF5). TbRIF4 is a 3′-5′ exonuclease of the DnaQ superfamily and plays a critical role in the conversion of duplex siRNAs to the single-stranded form, thus generating a TbAGO1-siRNA complex required for target-specific cleavage. TbRIF5 is essential for cytoplasmic RNAi and appears to act as a TbDCL1 cofactor. The availability of the core RNAi machinery in T. brucei provides a platform to gain mechanistic insights in this ancient eukaryote and to identify the minimal set of components required to reconstitute RNAi in RNAi-deficient parasites.
RNA interference (RNAi), a naturally-occurring pathway whereby the presence of double-stranded RNA in a cell triggers the degradation of homologous mRNA, has been harnessed in many organisms as an invaluable molecular biology tool to interrogate gene function. Although this technology is widely used in the protozoan parasite Trypanosoma brucei, other parasites of considerable public health significance, such as Trypanosoma cruzi, Leishmania major, and Plasmodium falciparum do not perform RNAi. Since RNAi has recently been introduced into budding yeast, this opens up the possibility that RNAi can be reconstituted in these pathogens. The key to this is getting a handle on the essential RNAi factors in T. brucei. By applying comparative genomics we identified five genes that are present in the RNAi-proficient species, but not in RNAi-deficient species: three previously identified RNAi factors, and two novel ones, which are described here. This insight into the core T. brucei RNAi machinery represents a major step towards transferring this pathway to RNAi-deficient parasites.
Self-complementary RNA transcripts form a double-stranded RNA (dsRNA) that triggers a sequence-specific mRNA degradation, in a process known as RNA interference (RNAi), leading to gene silencing. In vascular plants, RNAi molecules trafficking occur between cells and systemically throughout the plant. RNAi signals can spread systemically throughout a plant, even across graft junctions from transgenic to non-transgenic stocks. There is also a great interest in applying RNAi to pathogenic fungi. Specific inhibition of gene expression by RNAi has been shown to be suitable for a multitude of phytopathogenic filamentous fungi. However, double-stranded (ds)RNA/small interfering (si)RNA silencing effect has not been observed in vivo.
This study demonstrates for the first time the in vivo interference phenomenon in the pathogenic fungus Fusarium verticillioides, in which expression of an individual fungal transgene was specifically abolished by inoculating mycelial cells in transgenic tobacco plants engineered to express siRNAs from a dsRNA corresponding to the particular transgene.
The results provide a powerful tool for further studies on molecular plant-microbe and symbiotic interactions. From a biotechnological perspective, silencing of fungal genes by generating siRNAs in the host provides a novel strategy for the development of broad fungi-resistance strategies in plants and other organisms.
RNA interference (RNAi) is an effective tool for genome-scale, high-throughput analysis of gene function. In the past five years, a number of genome-scale RNAi high-throughput screens (HTSs) have been done in both Drosophila and mammalian cultured cells to study diverse biological processes, including signal transduction, cancer biology, and host cell responses to infection. Results from these screens have led to the identification of new components of these processes and, importantly, have also provided insights into the complexity of biological systems, forcing new and innovative approaches to understanding functional networks in cells. Here, we review the main findings that have emerged from RNAi HTS and discuss technical issues that remain to be improved, in particular the verification of RNAi results and validation of their biological relevance. Furthermore, we discuss the importance of multiplexed and integrated experimental data analysis pipelines to RNAi HTS.
bioinformatics; cell biology; Drosophila; high-throughput screening
RNA interference (RNAi), an RNA-dependent gene silencing process that is initiated by double-stranded RNA (dsRNA) molecules, has been applied with variable success in lepidopteran insects, in contrast to the high efficiency achieved in the coleopteran Tribolium castaneum. To gain insight into the factors that determine the efficiency of RNAi, a survey was carried out to check the expression of factors that constitute the machinery of the small interfering RNA (siRNA) and microRNA (miRNA) pathways in different tissues and stages of the silkmoth, Bombyx mori. It was found that the dsRNA-binding protein R2D2, an essential component in the siRNA pathway in Drosophila, was expressed at minimal levels in silkmoth tissues. The silkmoth-derived Bm5 cell line was also deficient in expression of mRNA encoding full-length BmTranslin, an RNA-binding factor that has been shown to stimulate the efficiency of RNAi. However, despite the lack of expression of the RNA-binding proteins, silencing of a luciferase reporter gene was observed by co-transfection of luc dsRNA using a lipophilic reagent. In contrast, gene silencing was not detected when the cells were soaked in culture medium supplemented with dsRNA. The introduction of an expression construct for Tribolium R2D2 (TcR2D2) did not influence the potency of luc dsRNA to silence the luciferase reporter. Immunostaining experiments further showed that both TcR2D2 and BmTranslin accumulated at defined locations within the cytoplasm of transfected cells. Our results offer a first evaluation of the expression of the RNAi machinery in silkmoth tissues and Bm5 cells and provide evidence for a functional RNAi response to intracellular dsRNA in the absence of R2D2 and Translin. The failure of TcR2D2 to stimulate the intracellular RNAi pathway in Bombyx cells is discussed.
RNA interference (RNAi) is a well-conserved mechanism that uses small noncoding RNAs to silence gene expression posttranscriptionally. Gene regulation by RNAi is now recognized as one of the major regulatory pathways in eukaryotic cells. Although the main components of the RNAi/miRNA pathway have been identified, the molecular mechanisms regulating the activity of the RNAi/miRNA pathway have only begun to emerge within the last couple of years. Recently, high-throughput reporter assays to monitor the activity of the RNAi/miRNA pathway have been developed and used for proof-of-concept pilot screens. Both inhibitors and activators of the RNAi/miRNA pathway have been found. Although still in its infancy, a chemical biology approach using high-throughput chemical screens should open up a new avenue for dissecting the RNAi/miRNA pathway, as well as developing novel RNAi- or miRNA-based therapeutic interventions.
When recognized by the RNA interference (RNAi) pathway, double-stranded RNA (dsRNA) produced in eukaryotic cells results in posttranscriptional gene silencing. In addition, dsRNA can trigger the interferon response as part of the immune response in vertebrates. In this study, we show that dsRNA, but not short interfering RNA (siRNA), induces the expression of qde-2 (an Argonaute gene) and dcl-2 (a Dicer gene), two central components of the RNAi pathway in the filamentous fungus Neurospora crassa. The induction of QDE-2 by dsRNA is required for normal gene silencing, indicating that this is a regulatory mechanism that allows the optimal function of the RNAi pathway. In addition, we demonstrate that Dicer proteins (DCLs) regulate QDE-2 posttranscriptionally, suggesting a role for DCLs or siRNA in QDE-2 accumulation. Finally, a genome-wide search revealed that additional RNAi components and homologs of antiviral and interferon-stimulated genes are also dsRNA-activated genes in Neurospora. Together, our results suggest that the activation of the RNAi components is part of a broad ancient host defense response against viral and transposon infections.