Large-scale RNAi-based screens are playing a critical role in defining sets of genes that regulate specific cellular processes. Numerous screens have been completed and in some cases more than one screen has examined the same cellular process, enabling a direct comparison of the genes identified in separate screens. Surprisingly, the overlap observed between the results of similar screens is low, suggesting that RNAi screens have relatively high levels of false positives, false negatives, or both.
We re-examined genes that were identified in two previous RNAi-based cell cycle screens to identify potential false positives and false negatives. We were able to confirm many of the originally observed phenotypes and to reveal many likely false positives. To identify potential false negatives from the previous screens, we used protein interaction networks to select genes for re-screening. We demonstrate cell cycle phenotypes for a significant number of these genes and show that the protein interaction network is an efficient predictor of new cell cycle regulators. Combining our results with the results of the previous screens identified a group of validated, high-confidence cell cycle/cell survival regulators. Examination of the subset of genes from this group that regulate the G1/S cell cycle transition revealed the presence of multiple members of three structurally related protein complexes: the eukaryotic translation initiation factor 3 (eIF3) complex, the COP9 signalosome, and the proteasome lid. Using a combinatorial RNAi approach, we show that while all three of these complexes are required for Cdk2/Cyclin E activity, the eIF3 complex is specifically required for some other step that limits the G1/S cell cycle transition.
Our results show that false positives and false negatives each play a significant role in the lack of overlap that is observed between similar large-scale RNAi-based screens. Our results also show that protein network data can be used to minimize false negatives and false positives and to more efficiently identify comprehensive sets of regulators for a process. Finally, our data provides a high confidence set of genes that are likely to play key roles in regulating the cell cycle or cell survival.
Epigenetic information is frequently erased near the start of each new generation (1). In some cases, however, epigenetic information can be transmitted from parent to progeny (epigenetic inheritance) (2). A particularly striking example of epigenetic inheritance is dsRNA-mediated gene silencing (RNAi) in C. elegans, which can be inherited for more than five generations (3–8). To understand this process we conducted a genetic screen for animals defective for transmitting RNAi silencing signals to future generations. This screen identified the gene heritable RNAi defective (hrde)-1.
hrde-1 encodes an Argonaute (Ago) that associates with small interfering (si)RNAs in germ cells of the progeny of animals exposed to dsRNA. In nuclei of these germ cells, HRDE-1 engages the Nrde nuclear RNAi pathway to direct H3K9me3 at RNAi targeted genomic loci and promote RNAi inheritance. Under normal growth conditions, HRDE-1 associates with endogenously expressed siRNAs, which direct nuclear gene silencing in germ cells. In hrde-1 or nuclear RNAi deficient animals, germline silencing is lost over generational time. Concurrently, these animals exhibit steadily worsening defects in gamete formation and function that ultimately lead to sterility. These results establish that the Ago HRDE-1 directs gene-silencing events in germ cell nuclei, which drive multi-generational RNAi inheritance and promote immortality of the germ cell lineage. We propose that C. elegans uses the RNAi inheritance machinery to transmit epigenetic information, accrued by past generations, into future generations to regulate important biological processes.
Polarized microtubule (MT) growth in the leading edge is critical to directed cell migration, and is mediated by Rac1 GTPase. To find downstream targets of Rac1 that affect MT assembly dynamics, we performed an RNAi screen of 23 MT binding and regulatory factors and identified RNAi treatments that suppressed changes in MT dynamics induced by constitutively activated Rac1. By analyzing fluorescent EB3 dynamics with automated tracking, we found that RNAi treatments targeting p150glued, APC2, spastin, EB1, Op18, or MARK2 blocked Rac1-mediated MT growth in lamellipodia. MARK2 was the only protein whose RNAi targeting additionally suppressed Rac1 effects on MT orientation in lamellipodia, and thus became the focus of further study. We show that GFP-MARK2 rescued effects of MARK2 depletion on MT growth lifetime and orientation, and GFP-MARK2 localized in lamellipodia in a Rac1-activity-dependent manner. In a wound-edge motility assay, MARK2-depleted cells failed to polarize their centrosomes or exhibit oriented MT growth in the leading edge, and displayed defects in directional cell migration. Thus, automated image analysis of MT assembly dynamics identified MARK2 as a target regulated downstream of Rac1 that promotes oriented MT growth in the leading edge to mediate directed cell migration.
Radial glial progenitor cells (RGPCs), have been long known to exhibit a striking form of bidirectional nuclear migration. The purpose and underlying mechanism for this unusual cell cycle-dependent “interkinetic” nuclear migration has remained poorly understood. We investigated the basis for this behavior by live imaging of nuclei, centrosomes, and microtubules in embryonic rat brain slices, coupled with blebbistatin and RNAi. We observed nuclei to migrate independent of centrosomes and unidirectionally away from or toward the ventricular surface along microtubules, which we found to be uniformly oriented from the ventricular to the pial surfaces of the brain. Cytoplasmic dynein RNAi specifically inhibited apically-directed nuclear movement. An RNAi screen for kinesin genes identified KIF1A, a member of the kinesin 3 family, as the motor for basally-directed nuclear movement. These observations provide the first direct evidence for a role for kinesins in nuclear migration and neurogenesis, and suggest that a novel cell cycle-dependent switch between distinct microtubule motors drives INM.
RNAi screening holds the promise of systemizing the search for combination therapeutic strategies. Here we performed a pooled shRNA library screen to look for promising targets to inhibit in combination with inhibition of the mitotic regulator polo-like kinase (PLK1). The library contained ~4,500 shRNAs targeting various signaling and cancer-related genes and was screened in four lung cancer cell lines using both high (IC80) and low (IC20) amounts of the PLK1 inhibitor GSK461364. The relative abundance of cells containing individual shRNAs following drug treatment was determined by microarray analysis, using the mock treatment replicates as the normalizing reference. Overall, the inferred influences of individual shRNAs in both high and low drug treatment were remarkably similar in all four cell lines and involved a large percentage of the library. To investigate which functional categories of shRNAs were most prominent in influencing drug response, we used statistical analysis of microarrays (SAM) in combination with a filter for genes that had two or more concordant shRNAs. The most significant functional categories that came out of this analysis included receptor tyrosine kinases and nuclear hormone receptors. Through individual validation experiments, we determined that the two shRNAs from the library targeting the nuclear retinoic acid receptor gene RARA did indeed silence RARA expression and as predicted conferred resistance to GSK461364. This led us to test whether activation of RARA receptor with retinoids could sensitize cells to GSK461364. We found that retinoids did increase the drug sensitivity and enhanced the ability of PLK1 inhibition to induce mitotic arrest and apoptosis. These results suggest that retinoids could be used to enhance the effectiveness of GSK461364 and provide further evidence that RNAi screens can be effective tools to identify combination target strategies.
Polo-like kinase 1; shRNA library screening; retinoids; combination therapy strategies
Because off-target effects hamper interpretation and validation of RNAi screens, we developed a bioinformatics method, Genome-wide Enrichment of Seed Sequence matches (GESS), to identify candidate off-targeted transcripts from direct analysis of primary screening data. GESS identified a prominent off-targeted transcript in several screens, including MAD2 in a screen for components of the spindle assembly checkpoint. We demonstrate how incorporation of the results of GESS analysis can enhance the validation rate in RNAi screens.
FLIGHT (http://flight.icr.ac.uk/) is an online resource compiling data from high-throughput Drosophila in vivo and in vitro RNAi screens. FLIGHT includes details of RNAi reagents and their predicted off-target effects, alongside RNAi screen hits, scores and phenotypes, including images from high-content screens. The latest release of FLIGHT is designed to enable users to upload, analyze, integrate and share their own RNAi screens. Users can perform multiple normalizations, view quality control plots, detect and assign screen hits and compare hits from multiple screens using a variety of methods including hierarchical clustering. FLIGHT integrates RNAi screen data with microarray gene expression as well as genomic annotations and genetic/physical interaction datasets to provide a single interface for RNAi screen analysis and datamining in Drosophila.
RNAi; database; integration; bioinformatics; phenotype
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.
RNA interference (RNAi) leads to sequence-specific knockdown of gene function. The approach can be used in large-scale screens to interrogate function in various model organisms and an increasing number of other species. Genome-scale RNAi screens are routinely performed in cultured or primary cells or in vivo in organisms such as C. elegans. High-throughput RNAi screening is benefitting from the development of sophisticated new instrumentation and software tools for collecting and analyzing data, including high-content image data. The results of large-scale RNAi screens have already proved useful, leading to new understandings of gene function relevant to topics such as infection, cancer, obesity and aging. Nevertheless, important caveats apply and should be taken into consideration when developing or interpreting RNAi screens. Some level of false discovery is inherent to high-throughput approaches and specific to RNAi screens, false discovery due to off-target effects (OTEs) of RNAi reagents remains a problem. The need to improve our ability to use RNAi to elucidate gene function at large scale and in additional systems continues to be addressed through improved RNAi library design, development of innovative computational and analysis tools and other approaches.
RNAi; high-throughput screens; high-content imaging; cell-based assays
Adenovirus virus-associated (VA) RNAs are processed to functional viral miRNAs or mivaRNAs. mivaRNAs are important for virus production, suggesting that they may target cellular or viral genes that affect the virus cell cycle. To look for cellular targets of mivaRNAs, we first identified genes downregulated in the presence of VA RNAs by microarray analysis. These genes were then screened for mivaRNA target sites using several bioinformatic tools. The combination of microarray analysis and bioinformatics allowed us to select the splicing and translation regulator TIA-1 as a putative mivaRNA target. We show that TIA-1 is downregulated at mRNA and protein levels in infected cells expressing functional mivaRNAs and in transfected cells that express mivaRNAI-138, one of the most abundant adenoviral miRNAs. Also, reporter assays show that TIA-1 is downregulated directly by mivaRNAI-138. To determine whether mivaRNAs could target other cellular genes we analyzed 50 additional putative targets. Thirty of them were downregulated in infected or transfected cells expressing mivaRNAs. Some of these genes are important for cell growth, transcription, RNA metabolism and DNA repair. We believe that a mivaRNA-mediated fine tune of the expression of some of these genes could be important in adenovirus cell cycle.
Although many critical roles of the RUNX family proteins have already been identified, little attention has been given to how these proteins interact with other factors. Elucidating RUNX protein interactions will help extend our understanding of their roles in normal development and tumorigenesis. In this study, we performed large-scale RNAi screening to identify genes that genetically interact with rnt-1, the sole homolog of RUNX protein in the nematode Caenorhabditis elegans. To this end, we took advantage of the fact that C. elegans can survive a severe loss of RNT-1 function with only mild phenotypes, and we looked for genes that caused a synthetic phenotype in the rnt-1 mutant background. We identified seven genes, three of which (cdk-8, cic-1, and sur-2) are involved in transcription, two of which (pgp-2 and cct-5) are involved in stress response, and two of which (D2045.7 and W09D10.4) are involved in signaling cascades, according to their functional gene ontology terms. We further confirmed that the CDK8-containing mediator complex genetically interacts with RNT-1 by showing that knockdown of each component of the CDK8 mediator complex caused a synthetic phenotype, that is, the exploded intestine through the vulva (Eiv) phenotype, in the rnt-1 mutant background. We also identified a putative target gene, acs-4, which is regulated by the RNT-1 and CDK8 mediator complex. Our results strengthen the notion that the CDK8 mediator complex may also act together with RUNX proteins in mammals.
RNAi; RUNX; CDK8; mediator; genetic interaction
The phenomenon that is known as RNA mediated interference (RNAi) was first observed in the nematode C. elegans. The application of RNAi has now been widely disseminated and the mechanisms underlying the pathway have been uncovered using both genetics and biochemistry. In the worm, it has been demonstrated that RNAi is easily adapted to high throughput analysis and screening protocols. Hence, given the availability of whole genome sequences, RNAi has been used extensively as a tool for annotating gene function. Genetic screens performed with C. elegans have also led to the identification of genes that are essential for RNAi or that modulate the RNAi process. The identification of such genes has made it possible to manipulate and enhance the RNAi response. Moreover, many of the genes identified in C. elegans have been conserved in other organisms. Thus, opportunities are available for researchers to take advantage of the insights gained from the worm and apply them to their own systems in order to improve the efficiency and potency of the RNAi response.
C. elegans; RdRP; RNA interference; siRNA; systemic RNAi
FlyRNAi (http://www.flyrnai.org), the database and website of the Drosophila RNAi Screening Center (DRSC) at Harvard Medical School, serves a dual role, tracking both production of reagents for RNA interference (RNAi) screening in Drosophila cells and RNAi screen results. The database and website is used as a platform for community availability of protocols, tools, and other resources useful to researchers planning, conducting, analyzing or interpreting the results of Drosophila RNAi screens. Based on our own experience and user feedback, we have made several changes. Specifically, we have restructured the database to accommodate new types of reagents; added information about new RNAi libraries and other reagents; updated the user interface and website; and added new tools of use to the Drosophila community and others. Overall, the result is a more useful, flexible and comprehensive website and database.
An RNAi screen in Drosophila cells has identified about 100 TANGO proteins, which may regulate protein exocytosis or secretion.
Although the organization and functions of the constitutive secretory pathway have been intensively studied for decades, a recent genome-wide RNAi screen in Drosophila cells has identified about 100 genes encoding novel so-called TANGO proteins (for transport and Golgi organization) that may be direct regulators of various aspects of protein exocytosis or secretion.
The Drosophila circadian oscillator is comprised of transcriptional feedback loops that are activated by CLOCK (CLK) and CYCLE (CYC) and repressed by PERIOD (PER) and TIMELESS (TIM) . The timing of CLK-CYC activation and PER-TIM repression is regulated post-translationally, in part through rhythmic phosphorylation of CLK, PER and TIM [2–4]. Although kinases that control PER and TIM levels and subcellular localization have been identified [5–10], additional kinases are predicted to target PER, TIM and/or CLK to promote time-specific transcriptional repression. We screened for kinases that alter circadian behavior via clock cell directed RNA interference (RNAi) and identified the proline-directed kinase nemo (nmo) as a novel component of the circadian oscillator. Both nmo RNAi knock down and a nmo hypomorphic mutant shorten circadian period, whereas nmo overexpression lengthens circadian period. CLK levels increase when nmo expression is knocked down in clock cells, whereas CLK levels decrease and PER and TIM accumulation is delayed when nmo is overexpressed in clock cells. These data suggest that nmo slows the pace of the circadian oscillator by altering CLK, PER and TIM expression, thereby contributing to the generation of a ~24-hour circadian period.
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.
RNA interference (RNAi) provides a powerful reverse genetics approach to analyze gene functions both in tissue culture and in vivo. Because of its widespread applicability and effectiveness it has become an essential part of the tool box kits of model organisms such as Caenorhabditis elegans, Drosophila, and the mouse. In addition, the use of RNAi in animals in which genetic tools are either poorly developed or nonexistent enables a myriad of fundamental questions to be asked. Here, we review the methods and applications of in vivo RNAi to characterize gene functions in model organisms and discuss their impact to the study of developmental as well as evolutionary questions. Further, we discuss the applications of RNAi technologies to crop improvement, pest control and RNAi therapeutics, thus providing an appreciation of the potential for phenomenal applications of RNAi to agriculture and medicine.
In vivo RNAi technology is replacing classical genetics in screens and conditional targeting of gene function. It also has applications in crop improvement, pest control, and medicine.
Targeted gene silencing by RNA interference allows the study of gene function in plants and animals. In cell culture and small animal models, genetic screens can be performed—even tissue-specifically in Drosophila—with genome-wide RNAi libraries. However, a major problem with the use of RNAi approaches is the unavoidable false-positive error caused by off-target effects. Until now, this is minimized by computational RNAi design, comparing RNAi to the mutant phenotype if known, and rescue with a presumed ortholog. The ultimate proof of specificity would be to restore expression of the same gene product in vivo. Here, we present a simple and efficient method to rescue the RNAi-mediated knockdown of two independent genes in Drosophila. By exploiting the degenerate genetic code, we generated Drosophila
RNAi Escape Strategy Construct (RESC) rescue proteins containing frequent silent mismatches in the complete RNAi target sequence. RESC products were no longer efficiently silenced by RNAi in cell culture and in vivo. As a proof of principle, we rescue the RNAi-induced loss of function phenotype of the eye color gene white and tracheal defects caused by the knockdown of the heparan sulfate proteoglycan syndecan. Our data suggest that RESC is widely applicable to rescue and validate ubiquitous or tissue-specific RNAi and to perform protein structure–function analysis.
High-throughput screening using RNAi is a powerful gene discovery method but is often complicated by false positive and false negative results. Whereas false positive results associated with RNAi reagents has been a matter of extensive study, the issue of false negatives has received less attention.
We performed a meta-analysis of several genome-wide, cell-based Drosophila RNAi screens, together with a more focused RNAi screen, and conclude that the rate of false negative results is at least 8%. Further, we demonstrate how knowledge of the cell transcriptome can be used to resolve ambiguous results and how the number of false negative results can be reduced by using multiple, independently-tested RNAi reagents per gene.
RNAi reagents that target the same gene do not always yield consistent results due to false positives and weak or ineffective reagents. False positive results can be partially minimized by filtering with transcriptome data. RNAi libraries with multiple reagents per gene also reduce false positive and false negative outcomes when inconsistent results are disambiguated carefully.
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
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
RNA interference (RNAi) has become a powerful technique for reverse genetics and drug discovery and, in both of these areas, large-scale high-throughput RNAi screens are commonly performed. The statistical techniques used to analyze these screens are frequently borrowed directly from small-molecule screening; however small-molecule and RNAi data characteristics differ in meaningful ways. We examine the similarities and differences between RNAi and small-molecule screens, highlighting particular characteristics of RNAi screen data that must be addressed during analysis. Additionally, we provide guidance on selection of analysis techniques in the context of a sample workflow.
RNA-mediated interference (RNAi)-based functional genomics is a systems-level approach to identify novel genes that control biological phenotypes. Existing computational approaches can identify individual genes from RNAi datasets that regulate a given biological process. However, currently available methods cannot identify which RNAi screen "hits" are novel components of well-characterized biological pathways known to regulate the interrogated phenotype. In this study, we describe a method to identify genes from RNAi datasets that are novel components of known biological pathways. We experimentally validate our approach in the context of a recently completed RNAi screen to identify novel regulators of melanogenesis.
In this study, we utilize a PPI network topology-based approach to identify targets within our RNAi dataset that may be components of known melanogenesis regulatory pathways. Our computational approach identifies a set of screen targets that cluster topologically in a human PPI network with the known pigment regulator Endothelin receptor type B (EDNRB). Validation studies reveal that these genes impact pigment production and EDNRB signaling in pigmented melanoma cells (MNT-1) and normal melanocytes.
We present an approach that identifies novel components of well-characterized biological pathways from functional genomics datasets that could not have been identified by existing statistical and computational approaches.
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.
RNA-mediated interference (RNAi) is a method to inhibit gene function by introduction of double-stranded RNA (dsRNA). Recently, an RNAi library was constructed that consists of bacterial clones expressing dsRNA, corresponding to nearly 90% of the 19,427 predicted genes of C. elegans. Feeding of this RNAi library to the standard wild-type laboratory strain Bristol N2 detected phenotypes for approximately 10% of the corresponding genes. To increase the number of genes for which a loss-of-function phenotype can be detected, we undertook a genome-wide RNAi screen using the rrf-3 mutant strain, which we found to be hypersensitive to RNAi. Feeding of the RNAi library to rrf-3 mutants resulted in additional loss-of-function phenotypes for 393 genes, increasing the number of genes with a phenotype by 23%. These additional phenotypes are distributed over different phenotypic classes. We also studied interexperimental variability in RNAi results and found persistent levels of false negatives. In addition, we used the RNAi phenotypes obtained with the genome-wide screens to systematically clone seven existing genetic mutants with visible phenotypes. The genome-wide RNAi screen using rrf-3 significantly increased the functional data on the C. elegans genome. The resulting dataset will be valuable in conjunction with other functional genomics approaches, as well as in other model organisms.
The screen suggested functions for 393 genes for which no RNAi-mediated phenotype was known. The comparison with similar screens in worms has general implications for RNAi experiments