Genome-wide RNAi as a route to gene function in Drosophila.

With the sequencing of the human genome and the genomes of most major model organisms completed, the systematic characterisation of gene functions remains a key challenge. During the past few years, RNA interference (RNAi) has become a powerful tool to silence the expression of genes and analyse their loss-of-function phenotype when mutant alleles are not available. Genome-wide RNAi screens against all predicted genes have been successfully used to dissect a variety of biological processes in Caenorhabditis elegans. Recently, a genome-wide library of double-stranded RNAs, that target every gene in the Drosophila genome and that is suitable for high throughput cell-based assays, was published. In this paper, recent advances will be summarised. Screening strategies and applications as a route to comprehensively characterising gene function will be discussed.     

Using Functional Genetics to Understand Breast Cancer Biology

Genetic screens were for long the prerogative of those that studied model organisms. The discovery in 2001 that gene silencing through RNA interference (RNAi) can also be brought about in mammalian cells paved the way for large scale loss-of-function genetic screens in higher organisms. In this article, we describe how functional genetic studies can help us understand the biology of breast cancer, how it can be used to identify novel targets for breast cancer therapy, and how it can help in the identification of those patients that are most likely to respond to a given therapy.Much remains to be learned regarding the function of mammalian genes. Only some quarter of all human genes have well-described functions. It is likely that quite a few of these currently unannotated genes will turn out to play key parts in cancer biology. For example, a 70-gene gene signature that can discriminate breast tumors of good and poor prognosis contained some 20 genes of currently unknown function (van ‘t Veer et al. 2002). The fact that these genes of unknown function foretell breast cancer prognosis hints at a role for at least some of these genes in breast cancer biology. The unbiased search for genes that contribute to breast cancer development is therefore likely to yield a rich harvest of new insights. RNA interference allows us to suppress genes systematically on a large scale and study the effects of gene suppression on specific cellular processes or signaling pathways. Consequently, RNA interference-based genetic screens have the potential to deepen our understanding of the molecular events that cause breast cancer, to find novel targets for therapy and to find biomarkers of drug responsiveness. In this article, we will describe the technologies available to perform both gain-of-function and loss-of-function genetic screens and will illustrate how such functional genetic screens have been used in the recent past to study a variety of outstanding questions in the biology of breast cancer.     

RNAi screens in Caenorhabditis elegans in a 96-well liquid format and their application to the systematic identification of genetic interactions

We describe a protocol for performing RNA interference (RNAi) screens in Caenorhabditis elegans in liquid culture in 96-well plates. The procedure allows a single researcher to set-up and score RNAi experiments at approximately 2,000 genes per day. By comparing RNAi phenotypes between wild-type worms and worms carrying a defined genetic mutation, we have used this protocol to identify synthetic lethal interactions between genes systematically. We also describe how the protocol can be adapted to target two genes simultaneously by combinatorial RNAi.     

药物基因组学对癌症化疗的启示

药物基因组学的研究任务是阐明个体差异的遗传基础,并利用这些遗传信息来预测药物的疗效、毒性和安全性。绝大多数的癌症化疗药物在治疗效果及正常组织毒性上的个体差异一直广为关注。不仅诸多临床因素(如年龄、性别、饮食、药物相互作用等)与药物反应和治疗效果有关,而且药物分布(转运和代谢)和药物靶标的遗传变异同样可导致癌症治疗上的差异。本篇综述主要讨论当前和将来药物基因组学在临床癌症治疗和抗癌药物研制方面的应用。     

Commercial potential of RNAi

The commercial potential of RNAi is assessed on the basis of successful translation of technology into applications in three areas: (1) drug discovery and research-currently the biggest segment; (2) potential therapeutic applications; and (3) the role of microRNA in molecular diagnostics. RNAi is an important method for analyzing gene function and identifying new drug targets that use dsRNA to knock down or silence specific genes. Sets of siRNAs focused on a specific gene class (siRNA libraries) have the capacity to greatly increase the pace of pathway analysis and functional genomics. RNAi plays an important role in drug discovery by facilitating target validation. The discovery of the role of microRNA (miRNAs) in various pathological processes opens up possible applications in molecular diagnostics, particularly that of cancer. The advantages of RNAi-based therapeutics over traditional pharmaceuticals include the capability for more specific therapies with small molecule siRNA. Drawbacks include the development of resistance in cancer and viral infections as well as the interferon effect. RNAi is closely related to gene therapy and the vectors developed for gene therapy are also being used for delivery of siRNAs. RNAi, along with other related technologies, will contribute to the development of personalised medicine. Although none of the RNAi-based drugs is in the market yet, some are in clinical trials. By the year 2010 the market for RNAi-based drugs is expected to be worth 3.5 billion dollars and is expected to expand to 10.5 billion dollars by the year 2015.     

Measuring error rates in genomic perturbation screens: gold standards for human functional genomics

Technological advancement has opened the door to systematic genetics in mammalian cells. Genome‐scale loss‐of‐function screens can assay fitness defects induced by partial gene knockdown, using RNA interference, or complete gene knockout, using new CRISPR techniques. These screens can reveal the basic blueprint required for cellular proliferation. Moreover, comparing healthy to cancerous tissue can uncover genes that are essential only in the tumor; these genes are targets for the development of specific anticancer therapies. Unfortunately, progress in this field has been hampered by off‐target effects of perturbation reagents and poorly quantified error rates in large‐scale screens. To improve the quality of information derived from these screens, and to provide a framework for understanding the capabilities and limitations of CRISPR technology, we derive gold‐standard reference sets of essential and nonessential genes, and provide a Bayesian classifier of gene essentiality that outperforms current methods on both RNAi and CRISPR screens. Our results indicate that CRISPR technology is more sensitive than RNAi and that both techniques have nontrivial false discovery rates that can be mitigated by rigorous analytical methods.     

RNAi mechanisms and applications

Within the past two decades we have become increasingly aware of the roles that RNAs play in regulation of gene expression. The RNA world was given a booster shot with the discovery of RNA interference (RNAi), a compendium of mechanisms involving small RNAs (less than 30 bases long) that regulate the expression of genes in a variety of eukaryotic organisms. Rapid progress in our understanding of RNAi-based mechanisms has led to applications of this powerful process in studies of gene function as well as in therapeutic applications for the treatment of disease. RNAi-based therapies involve two-dimensional drug designs using only identification of good Watson-Crick base pairing between the RNAi guide strand and the target, thereby resulting in rapid design and testing of RNAi triggers. To date there are several clinical trials using RNAi, and we should expect the list of new applications to grow at a phenomenal rate. This article summarizes our current knowledge about the mechanisms and applications of RNAi.     

In vivo self-assembled small RNAs as a new generation of RNAi therapeutics

RNAi therapy has undergone two stages of development, direct injection of synthetic siRNAs and delivery with artificial vehicles or conjugated ligands; both have not solved the problem of efficient in vivo siRNA delivery. Here, we present a proof-of-principle strategy that reprogrammes host liver with genetic circuits to direct the synthesis and self-assembly of siRNAs into secretory exosomes and facilitate the in vivo delivery of siRNAs through circulating exosomes. By combination of different genetic circuit modules, in vivo assembled siRNAs are systematically distributed to multiple tissues or targeted to specific tissues (e.g., brain), inducing potent target gene silencing in these tissues. The therapeutic value of our strategy is demonstrated by programmed silencing of critical targets associated with various diseases, including EGFR/KRAS in lung cancer, EGFR/TNC in glioblastoma and PTP1B in obesity. Overall, our strategy represents a next generation RNAi therapeutics, which makes RNAi therapy feasible.Subject terms: RNAi, siRNAs     

Genome-scale loss-of-function screening with a lentiviral RNAi library

The discovery that RNA interference (RNAi) is functional in mammalian cells led us to form The RNAi Consortium (TRC) with the goal of enabling large-scale loss-of-function screens through the development of genome-scale RNAi libraries and methodologies for their use. These resources form the basis of a loss-of-function screening platform created at the Broad Institute. Our human and mouse libraries currently contain >135,000 lentiviral clones targeting 27,000 genes. Initial screening efforts have demonstrated that these libraries and methods are practical and powerful tools for high-throughput lentivirus RNAi screens.     

The CONJUDOR pipeline for multiplexed knockdown of gene pairs identifies RBBP-5 as a germ cell reprogramming barrier in C. elegans

Multiple gene activities control complex biological processes such as cell fate specification during development and cellular reprogramming. Investigating the manifold gene functions in biological systems requires also simultaneous depletion of two or more gene activities. RNA interference-mediated knockdown (RNAi) is commonly used in Caenorhabditis elegans to assess essential genes, which otherwise lead to lethality or developmental arrest upon full knockout. RNAi application is straightforward by feeding worms with RNAi plasmid-containing bacteria. However, the general approach of mixing bacterial RNAi clones to deplete two genes simultaneously often yields poor results. To address this issue, we developed a bacterial conjugation-mediated double RNAi technique ‘CONJUDOR’. It allows combining RNAi bacteria for robust double RNAi with high-throughput. To demonstrate the power of CONJUDOR for large scale double RNAi screens we conjugated RNAi against the histone chaperone gene lin-53 with more than 700 other chromatin factor genes. Thereby, we identified the Set1/MLL methyltransferase complex member RBBP-5 as a novel germ cell reprogramming barrier. Our findings demonstrate that CONJUDOR increases efficiency and versatility of RNAi screens to examine interconnected biological processes in C. elegans with high-throughput.     

RNA干扰在肿瘤基因治疗中的应用策略

运用RNA干扰（RNAi）技术可以通过以下策略进行肿瘤的靶向治疗：抑制癌基因、生长因子及其受体的过表达,从而抑制细胞生长;干扰细胞周期蛋白及其相关基因的表达,从而抑制细胞增殖;抵抗致癌病毒的入侵;抑制抗凋亡基因的表达;上调和恢复抑癌基因的功能;抑制肿瘤发生过程中的关键酶;抑制与肿瘤转移有关的血管生成;靶向端粒酶;靶向耐药基因。尽管目前RNAi已经较为广泛地应用于基因功能研究和肿瘤疾病的基因治疗研究中,但其在应用过程中还有许多亟待解决的问题。我们就RNAi及其在肿瘤疾病基因治疗中的应用策略和存在的问题做一综述。     

Bcl-2/C-Raf双基因“敲低”抑制人结肠癌细胞增殖

 RNA干扰是一种具有序列特异性的基因沉默,能够触发具有相应序列的mRNA的降解.构建具有双靶点的RNAi质粒表达载体,与单靶点表达载体比较,探讨其对结肠癌细胞增殖的抑 制作用.本研究分别构建了针对Bcl-2、C-Raf 和Bcl-2/C-Raf靶基因的质粒表达载体,通过Lipofectamine TM2000介导转染人结肠癌细胞系HCT-8后,检测相应转染组靶基因的mRNA和蛋白质表达量,测定各组细胞活性,研究RNAi对各组癌细胞增殖的抑制率.结果表明,分别转染3种质粒表达载体后,3组结肠癌细胞中相应靶基因的mRNA和蛋白质表达量均降低;转染双靶点干扰质粒的试验组;其细胞活性低于单靶点组;对于针对Bcl-2, C-Raf和Bcl-2/C-Raf基因的3组干扰实验,RNAi对结肠癌细胞增殖的抑制率分别为43.87%,40.64% 和63.85%.RNAi是结肠癌细胞中的一种功能途径,以质粒作为表达载体,同时具备Bcl-2/C-Raf双靶点的表达载体,对结肠癌细胞增殖的抑制作用要明显优于单靶点表达载体,双靶点质粒表达载体在结肠癌的基因治疗中是有潜力的.     

Simultaneous analysis of large-scale RNAi screens for pathogen entry

Background

Large-scale RNAi screening has become an important technology for identifying genes involved in biological processes of interest. However, the quality of large-scale RNAi screening is often deteriorated by off-targets effects. In order to find statistically significant effector genes for pathogen entry, we systematically analyzed entry pathways in human host cells for eight pathogens using image-based kinome-wide siRNA screens with siRNAs from three vendors. We propose a Parallel Mixed Model (PMM) approach that simultaneously analyzes several non-identical screens performed with the same RNAi libraries.

Results

We show that PMM gains statistical power for hit detection due to parallel screening. PMM allows incorporating siRNA weights that can be assigned according to available information on RNAi quality. Moreover, PMM is able to estimate a sharedness score that can be used to focus follow-up efforts on generic or specific gene regulators. By fitting a PMM model to our data, we found several novel hit genes for most of the pathogens studied.

Conclusions

Our results show parallel RNAi screening can improve the results of individual screens. This is currently particularly interesting when large-scale parallel datasets are becoming more and more publicly available. Our comprehensive siRNA dataset provides a public, freely available resource for further statistical and biological analyses in the high-content, high-throughput siRNA screening field.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-1162) contains supplementary material, which is available to authorized users.     

RNAi for plant functional genomics

A major challenge in the post-genome era of plant biology is to determine the functions of all the genes in the plant genome. A straightforward approach to this problem is to reduce or knock out expression of a gene with the hope of seeing a phenotype that is suggestive of its function. Insertional mutagenesis is a useful tool for this type of study, but it is limited by gene redundancy, lethal knock-outs, nontagged mutants and the inability to target the inserted element to a specific gene. RNA interference (RNAi) of plant genes, using constructs encoding self-complementary 'hairpin' RNA, largely overcomes these problems. RNAi has been used very effectively in Caenorhabditis elegans functional genomics, and resources are currently being developed for the application of RNAi to high-throughput plant functional genomics.     

SANTA: Quantifying the Functional Content of Molecular Networks

Linking networks of molecular interactions to cellular functions and phenotypes is a key goal in systems biology. Here, we adapt concepts of spatial statistics to assess the functional content of molecular networks. Based on the guilt-by-association principle, our approach (called SANTA) quantifies the strength of association between a gene set and a network, and functionally annotates molecular networks like other enrichment methods annotate lists of genes. As a general association measure, SANTA can (i) functionally annotate experimentally derived networks using a collection of curated gene sets and (ii) annotate experimentally derived gene sets using a collection of curated networks, as well as (iii) prioritize genes for follow-up analyses. We exemplify the efficacy of SANTA in several case studies using the S. cerevisiae genetic interaction network and genome-wide RNAi screens in cancer cell lines. Our theory, simulations, and applications show that SANTA provides a principled statistical way to quantify the association between molecular networks and cellular functions and phenotypes. SANTA is available from http://bioconductor.org/packages/release/bioc/html/SANTA.html.     

Effective RNA interference in cultured silkworm cells mediated by overexpression of Caenorhabditis elegans SID-1

RNA interference (RNAi) is a conserved mechanism that catalyzes sequence-specific gene silencing and has been used for loss-of-function genetic screens in many organisms. Here, we demonstrated that the expression of Caenorhabditis elegans SID-1 (CeSID-1) could trigger effective gene silencing in the cultured silkworm cell line, BmN4 (BmN4-SID1). Soaking the BmN4-SID1 in dsRNA corresponding to endogenous target genes induced a significant decrease of the amount of mRNA or protein. A small amount of dsRNA was enough to silence the target gene in a few days. Overexpression of CeSID-1 did not affect the cell viability. Our results suggest that BmN4-SID1 can be used in many applications in silkworm cells and will become a valuable resource for gene analysis.