siRNAdb: a database of siRNA sequences

A Graph Neural Network Approach for the Analysis of siRNA-Target Biological Networks

Many biological systems are characterised by biological entities, as well as their relationships. These interaction networks can be modelled as graphs, with nodes representing bio-entities, such as molecules, and edges representing relations among them, such as interactions. Due to the current availability of a huge amount of biological data, it is very important to consider in silico analysis methods based on, for example, machine learning, that could take advantage of the inner graph structure of the data in order to improve the quality of the results. In this scenario, graph neural networks (GNNs) are recent computational approaches that directly deal with graph-structured data. In this paper, we present a GNN network for the analysis of siRNA-mRNA interaction networks. siRNAs, in fact, are small RNA molecules that are able to bind to target genes and silence them. These events make siRNAs key molecules as RNA interference agents in many biological interaction networks related to severe diseases such as cancer. In particular, our GNN approach allows for the prediction of the siRNA efficacy, which measures the siRNA's ability to bind and silence a gene target. Tested on benchmark datasets, our proposed method overcomes other machine learning algorithms, including the state-of-the-art predictor based on the convolutional neural network, reaching a Pearson correlation coefficient of approximately 73.6%. Finally, we proposed a case study where the efficacy of a set of siRNAs is predicted for a gene of interest. To the best of our knowledge, GNNs were used for the first time in this scenario.

In Silico Methods for the Identification of Viral-Derived Small Interfering RNAs (vsiRNAs) and Their Application in Plant Genomics

The current era of high-throughput sequencing (HTS) technology has expedited the detection and diagnosis of viruses and viroids in the living system including plants. HTS data has become vital to study the etiology of the infection caused by both known as well as novel viral elements in planta, and their impact on overall crop health and productivity. Viral-derived small interfering RNAs are generated as a result of defence response by the host via RNAi machinery. They are immensely exploited for performing exhaustive viral investigations in plants using bioinformatics as well as experimental approaches.This chapter briefly presents the basics of virus-derived small interfering RNAs (vsiRNAs ) biology in plants and their applications in plant genomics and highlights in silico strategies exploited for virus/viroid detection. It gives a systematic pipeline for vsiRNAs identification using currently available bioinformatics tools and databases. This will surely work as a quick beginner's recipe for the in silico revelation of plant vsiRNAs as well as virus/viroid diagnosis using high-throughput sequencing data.

Identification and characterization of novel microRNAs in disease-resistant and disease-susceptible Penaeus monodon

MicroRNAs (miRNAs), known as a translational regulator, are evolutionary conserved, small, and noncoding RNA. They have played a vital role in disease biology through the host-virus-miRNA-interaction. In this study, novel miRNAs of naturally occurring, virus-free disease-resistant and disease-susceptible Penaeus monodon were identified and characterized. In disease-susceptible samples, 45 homologous mature miRNAs and 28 homologous precursor miRNAs were identified. In disease-resistant samples, 52 homologous mature miRNAs and 87 homologous precursor miRNAs were identified. In disease-susceptible samples, 33 novel mature miRNAs and 33 novel precursor miRNAs were identified. In disease-resistant samples, 523 novel mature miRNAs and 141 novel precursor miRNAs were identified. Differential expression study revealed the up-regulated and down-regulated miRNAs in disease-resistant and disease-susceptible P. monodon. Gene ontology pathway of known and novel miRNAs revealed that P. monodon miRNAs might have a potential and specific role in signal transduction, cell-to-cell signaling, innate immune response and defense response to different pathogens.

PVsiRNAPred: Prediction of plant exclusive virus-derived small interfering RNAs by deep convolutional neural network

Plant exclusive virus-derived small interfering RNAs (vsiRNAs) regulate various biological processes, especially important in antiviral immunity. The identification of plant vsiRNAs is important for understanding the biogenesis and function mechanisms of vsiRNAs and further developing anti-viral plants. In this study, we extracted plant vsiRNA sequences from the PVsiRNAdb database. We then utilized deep convolutional neural network (CNN) to develop a deep learning algorithm for predicting plant vsiRNAs based on vsiRNA sequence composition, known as PVsiRNAPred. The key part of PVsiRNAPred is the CNN module, which automatically learns hierarchical representations of vsiRNA sequences related to vsiRNA profiles in plants. When evaluated using an independent testing dataset, the accuracy of the model was 65.70%, which was higher than those of five conventional machine learning method-based classifiers. In addition, PVsiRNAPred obtained a sensitivity of 67.11%, specificity of 64.26% and Matthews correlation coefficient (MCC) of 0.31, and the area under the receiver operating characteristic (ROC) curve (AUC) of PVsiRNAPred was 0.71 in the independent test. The permutation test with 1000 shuffles resulted in a p value of<0.001. The above results reveal that PVsiRNAPred has favorable generalization capabilities. We hope PVsiRNAPred, the first bioinformatics algorithm for predicting plant vsiRNAs, will allow efficient discovery of new vsiRNAs.

Noncoding RNAs Databases: Current Status and Trends

One of the most important resources for researchers of noncoding RNAs is the information available in public databases spread over the internet. However, the effective exploration of this data can represent a daunting task, given the large amount of databases available and the variety of stored data. This chapter describes a classification of databases based on information source, type of RNA, source organisms, data formats, and the mechanisms for information retrieval, detailing the relevance of each of these classifications and its usability by researchers. This classification is used to update a 2012 review, indexing now more than 229 public databases. This review will include an assessment of the new trends for ncRNA research based on the information that is being offered by the databases. Additionally, we will expand the previous analysis focusing on the usability and application of these databases in pathogen and disease research. Finally, this chapter will analyze how currently available database schemas can help the development of new and improved web resources.

SiRNA silencing efficacy prediction based on a deep architecture

Background

Small interfering RNA (siRNA) can be used to post-transcriptional gene regulation by knocking down targeted genes. In functional genomics, biomedical research and cancer therapeutics, siRNA design is a critical research topic. Various computational algorithms have been developed to select the most effective siRNA, whereas the efficacy prediction accuracy is not so satisfactory. Many existing computational methods are based on feature engineering, which may lead to biased and incomplete features. Deep learning utilizes non-linear mapping operations to detect potential feature pattern and has been considered perform better than existing machine learning method.

Results

In this paper, to further improve the prediction accuracy and facilitate gene functional studies, we developed a new powerful siRNA efficacy predictor based on a deep architecture. First, we extracted hidden feature patterns from two modalities, including sequence context features and thermodynamic property. Then, we constructed a deep architecture to implement the prediction. On the available largest siRNA database, the performance of our proposed method was measured with 0.725 PCC and 0.903 AUC value. The comparative experiment showed that our proposed architecture outperformed several siRNA prediction methods.

Conclusions

The results demonstrate that our deep architecture is stable and efficient to predict siRNA silencing efficacy. The method could help select candidate siRNA for targeted mRNA, and further promote the development of RNA interference.

RNA interference: new mechanistic and biochemical insights with application in oral cancer therapy

Over the last few decades, the incidence of oral cancer has gradually increased, due to the negative influence of environmental factors and also abnormalities within the genome. The main issues in oral cancer treatment consist in surpassing resistance and recurrence. However, continuous discovery of altered signaling pathways in these tumors provides valuable information for the identification of novel gene candidates targeted in personalized therapy. RNA interference (RNAi) is a natural mechanism that involves small interfering RNA (siRNA); this can be exploited in biomedical research by using natural or synthetic constructs for activation of the mechanism. Synthetic siRNA transcripts were developed as a versatile class of molecular tools that have a diverse range of programmable roles, being involved in the regulation of several biological processes, thereby providing the perspective of an alternative option to classical treatment. In this review, we summarize the latest information related to the application of siRNA in oral malignancy together with molecular aspects of the technology and also the perspective upon the delivery system. Also, the emergence of newer technologies such as clustered regularly interspaced short palindromic repeats/Cas9 or transcription activator-like effector nucleases in comparison with the RNAi approach is discussed in this paper.

A comprehensive review of web-based resources of non-coding RNAs for plant science research

Non-coding RNAs (ncRNAs) are transcribed from genome but not translated into proteins. Many ncRNAs are key regulators of plants growth and development, metabolism and stress tolerance. In order to make the web-based ncRNA resources for plant science research be more easily accessible and understandable, we made a comprehensive review for 83 web-based resources of three types, including genome databases containing ncRNA data, microRNA (miRNA) databases and long non-coding RNA (lncRNA) databases. To facilitate effective usage of these resources, we also suggested some preferred resources of miRNAs and lncRNAs for performing meaningful analysis.

saRNAdb: Resource of Small Activating RNAs for Up-regulating the Gene Expression

RNA activation (RNAa) is the process of enhancing selective gene expression at transcriptional level using double-stranded RNAs, targeting gene promoter. These RNA molecules are usually 21 nucleotides long and termed as small activating RNAs (saRNAs). They are involved in gene regulation, epigenetics, gain-of-function studies and have potential therapeutic applications for various diseases especially cancer. RNAa is opposite to RNA interference in functionality; however, both processes share some protein machinery. There are many RNA interference centered online resources but no one for saRNAs; therefore, we developed "saRNAdb" database (http://bioinfo.imtech.res.in/manojk/sarna/). It contains 2150 manually curated saRNA entries with detailed information about their nucleotide sequences, activities, corresponding target gene, promoter and other experimental data. Besides, saRNA-promoter binding location, predicted saRNA features, tools (off-target, map) and RNAa-related proteins with their interacting partners are provided. saRNAdb is expected to assist in RNA research especially for nucleic acid-based therapeutics development.

PVsiRNAdb: a database for plant exclusive virus-derived small interfering RNAs

Ribonucleic acids (RNA) interference mechanism has been proved to be an important regulator of both transcriptional and post-transcription controls of gene expression during biotic and abiotic stresses in plants. Virus-derived small interfering RNAs (vsiRNAs) are established components of the RNA silencing mechanism for incurring anti-viral resistance in plants. Some databases like siRNAdb, HIVsirDB and VIRsiRNAdb are available online pertaining to siRNAs as well as vsiRNAs generated during viral infection in humans; however, currently there is a lack of repository for plant exclusive vsiRNAs. We have developed `PVsiRNAdb (http://www.nipgr.res.in/PVsiRNAdb)', a manually curated plant-exclusive database harboring information related to vsiRNAs found in different virus-infected plants collected by exhaustive data mining of published literature so far. This database contains a total of 322 214 entries and 282 549 unique sequences of vsiRNAs. In PVsiRNAdb, detailed and comprehensive information is available for each vsiRNA sequence. Apart from the core information consisting of plant, tissue, virus name and vsiRNA sequence, additional information of each vsiRNAs (map position, length, coordinates, strand information and predicted structure) may be of high utility to the user. Different types of search and browse modules with three different tools namely BLAST, Smith-Waterman Align and Mapping are provided at PVsiRNAdb. Thus, this database being one of its kind will surely be of much use to molecular biologists for exploring the complex viral genetics and genomics, viral-host interactions and beneficial to the scientific community and can prove to be very advantageous in the field of agriculture for producing viral resistance transgenic crops.

A database of breast oncogenic specific siRNAs

Breast cancer is a serious problem causing the death of women across the world. At present, one of the major challenges is to design drugs to target breast cancer specific gene(s). RNA interference (RNAi) is an important technique for targeted gene silencing that may lead to promising novel therapeutic strategies for breast cancer. Therefore, identification of such molecules having high oncogene specificity is the need of the hour. Here, we have developed a database named as Breast Oncogenic Specific siRNAs (BOSS, http://bioinformatics.cimap.res.in/sharma/boss/) on the basis of the current research status on siRNA-mediated repression of oncogenes in different breast cancer cell lines. BOSS is a resource of experimentally validated breast oncogenic siRNAs, collected from research articles and patents published yet. The present database contains information on 865 breast oncogenic siRNA entries. Each entry provides comprehensive information of an siRNA that includes its name, sequence, target gene, type of cells, and inhibition value, etc. Additionally, some useful tools like siRNAMAP and BOSS BLAST were also developed and linked with the database. siRNAMAP can be used for the selection of best siRNA against a target gene while BOSS BLAST tool helps to locate the siRNA sequences in deferent oncogenes.

MicroRNAs associated with drought response in the pulse crop common bean (Phaseolus vulgaris L.)

Drought stress significantly reduces common bean yields. Recently, some drought-related miRNAs were found in various plants. However, reports of miRNAs involved in drought stress in common bean are limited. Here, we obtained four sRNA samples from drought-tolerant and -sensitive cultivars of common bean that experienced with or without drought treatment. A total of 49 novel miRNAs and 120 known miRNAs were detected. Under drought treatment, 9 and 7 known miRNAs were down and up-regulated, respectively, and 5 and 3 of the novel miRNAs were increased and decreased, respectively. Among these miRNAs, four miRNAs shared the same pattern of expression between Long 22-0579 and Naihua. Target genes of these miRNAs included transcription factors, protein kinases, and nuclear transcription factors. Finally, we verified all of the differentially expressed miRNAs by RT-qPCR, and we identified 16 miRNAs that are potentially associated with the drought stress response. These miRNAs and target genes will be useful in future basic studies and in applied studies investigating how miRNA regulation can be used to enhance drought resistance in plant species.

siRNAmod: A database of experimentally validated chemically modified siRNAs

Small interfering RNA (siRNA) technology has vast potential for functional genomics and development of therapeutics. However, it faces many obstacles predominantly instability of siRNAs due to nuclease digestion and subsequently biologically short half-life. Chemical modifications in siRNAs provide means to overcome these shortcomings and improve their stability and potency. Despite enormous utility bioinformatics resource of these chemically modified siRNAs (cm-siRNAs) is lacking. Therefore, we have developed siRNAmod, a specialized databank for chemically modified siRNAs. Currently, our repository contains a total of 4894 chemically modified-siRNA sequences, comprising 128 unique chemical modifications on different positions with various permutations and combinations. It incorporates important information on siRNA sequence, chemical modification, their number and respective position, structure, simplified molecular input line entry system canonical (SMILES), efficacy of modified siRNA, target gene, cell line, experimental methods, reference etc. It is developed and hosted using Linux Apache MySQL PHP (LAMP) software bundle. Standard user-friendly browse, search facility and analysis tools are also integrated. It would assist in understanding the effect of chemical modifications and further development of stable and efficacious siRNAs for research as well as therapeutics. siRNAmod is freely available at: http://crdd.osdd.net/servers/sirnamod.

An introduction to RNA databases

We present an introduction to RNA databases. The history and technology behind RNA databases are briefly discussed. We examine differing methods of data collection and curation and discuss their impact on both the scope and accuracy of the resulting databases. Finally, we demonstrate these principles through detailed examination of four leading RNA databases: Noncode, miRBase, Rfam, and SILVA.

Unraveling siRNA unzipping kinetics with graphene

Using all atom molecular dynamics simulations, we report spontaneous unzipping and strong binding of small interfering RNA (siRNA) on graphene. Our dispersion corrected density functional theory based calculations suggest that nucleosides of RNA have stronger attractive interactions with graphene as compared to DNA residues. These stronger interactions force the double stranded siRNA to spontaneously unzip and bind to the graphene surface. Unzipping always nucleates at one end of the siRNA and propagates to the other end after few base-pairs get unzipped. While both the ends get unzipped, the middle part remains in double stranded form because of torsional constraint. Unzipping probability distributions fitted to single exponential function give unzipping time (τ) of the order of few nanoseconds which decrease exponentially with temperature. From the temperature variation of unzipping time we estimate the energy barrier to unzipping.

de novo analysis and functional classification of the transcriptome of the root lesion nematode, Pratylenchus thornei, after 454 GS FLX sequencing

The migratory endoparasitic root lesion nematode Pratylenchus thornei is a major pest of the cereals wheat and barley. In what we believe to be the first global transcriptome analysis for P. thornei, using Roche GS FLX sequencing, 787,275 reads were assembled into 34,312 contigs using two assembly programs, to yield 6,989 contigs common to both. These contigs were annotated, resulting in functional assignments for 3,048. Specific transcripts studied in more detail included carbohydrate active enzymes potentially involved in cell wall degradation, neuropeptides, putative plant nematode parasitism genes, and transcripts that could be secreted by the nematode. Transcripts for cell wall degrading enzymes were similar to bacterial genes, suggesting that they were acquired by horizontal gene transfer. Contigs matching 14 parasitism genes found in sedentary endoparasitic nematodes were identified. These genes are thought to function in suppression of host defenses and in feeding site development, but their function in P. thornei may differ. Comparison of the common contigs from P. thornei with other nematodes showed that 2,039 were common to sequences of the Heteroderidae, 1,947 to the Meloidogynidae, 1,218 to Radopholus similis, 1,209 matched expressed sequence tags (ESTs) of Pratylenchus penetrans and Pratylenchus vulnus, and 2,940 to contigs of Pratylenchus coffeae. There were 2,014 contigs common to Caenarhabditis elegans, with 15.9% being common to all three groups. Twelve percent of contigs with matches to the Heteroderidae and the Meloidogynidae had no homology to any C. elegans protein. Fifty-seven percent of the contigs did not match known sequences and some could be unique to P. thornei. These data provide substantial new information on the transcriptome of P. thornei, those genes common to migratory and sedentary endoparasitic nematodes, and provide additional understanding of genes required for different forms of parasitism. The data can also be used to identify potential genes to study host interactions and for crop protection.

VIRsiRNAdb: a curated database of experimentally validated viral siRNA/shRNA

RNAi technology has been emerging as a potential modality to inhibit viruses during past decade. In literature a few siRNA databases have been reported that focus on targeting human and mammalian genes but experimentally validated viral siRNA databases are lacking. We have developed VIRsiRNAdb, a manually curated database having comprehensive details of 1358 siRNA/shRNA targeting viral genome regions. Further, wherever available, information regarding alternative efficacies of above 300 siRNAs derived from different assays has also been incorporated. Important fields included in the database are siRNA sequence, virus subtype, target genome region, cell type, target object, experimental assay, efficacy, off-target and siRNA matching with reference viral sequences. Database also provides the users with facilities of advance search, browsing, data submission, linking to external databases and useful siRNA analysis tools especially siTarAlign which align the siRNA with reference viral genomes or user defined sequences. VIRsiRNAdb contains extensive details of siRNA/shRNA targeting 42 important human viruses including influenza virus, hepatitis B virus, HPV and SARS Corona virus. VIRsiRNAdb would prove useful for researchers in picking up the best viral siRNA for antiviral therapeutics development and also for developing better viral siRNA design tools. The database is freely available at http://crdd.osdd.net/servers/virsirnadb.

HIVsirDB: a database of HIV inhibiting siRNAs

BACKGROUND

Human immunodeficiency virus (HIV) is responsible for millions of deaths every year. The current treatment involves the use of multiple antiretroviral agents that may harm patients due to their toxic nature. RNA interference (RNAi) is a potent candidate for the future treatment of HIV, uses short interfering RNA (siRNA/shRNA) for silencing HIV genes. In this study, attempts have been made to create a database HIVsirDB of siRNAs responsible for silencing HIV genes.

DESCRIPTIONS

HIVsirDB is a manually curated database of HIV inhibiting siRNAs that provides comprehensive information about each siRNA or shRNA. Information was collected and compiled from literature and public resources. This database contains around 750 siRNAs that includes 75 partially complementary siRNAs differing by one or more bases with the target sites and over 100 escape mutant sequences. HIVsirDB structure contains sixteen fields including siRNA sequence, HIV strain, targeted genome region, efficacy and conservation of target sequences. In order to facilitate user, many tools have been integrated in this database that includes; i) siRNAmap for mapping siRNAs on target sequence, ii) HIVsirblast for BLAST search against database, iii) siRNAalign for aligning siRNAs.

CONCLUSION

HIVsirDB is a freely accessible database of siRNAs which can silence or degrade HIV genes. It covers 26 types of HIV strains and 28 cell types. This database will be very useful for developing models for predicting efficacy of HIV inhibiting siRNAs. In summary this is a useful resource for researchers working in the field of siRNA based HIV therapy. HIVsirDB database is accessible at http://crdd.osdd.net/raghava/hivsir/.

Databases and resources for human small non-coding RNAs

Recent advances in high-throughput sequencing have facilitated the genome-wide studies of small non-coding RNAs (sRNAs). Numerous studies have highlighted the role of various classes of sRNAs at different levels of gene regulation and disease. The fast growth of sequence data and the diversity of sRNA species have prompted the need to organise them in annotation databases. There are currently several databases that collect sRNA data. Various tools are provided for access, with special emphasis on the well-characterised family of micro-RNAs. The striking heterogeneity of the new classes of sRNAs and the lack of sufficient functional annotation, however, make integration of these datasets a difficult task. This review describes the currently available databases for human sRNAs that are accessible via the internet, and some of the large datasets for human sRNAs from high-throughput sequencing experiments that are so far only available as supplementary data in publications. Some of the main issues related to the integration and annotation of sRNA datasets are also discussed.

The construction of transgenic and gene knockout/knockin mouse models of human disease

The genetic and physiological similarities between mice and humans have focused considerable attention on rodents as potential models of human health and disease. Together with the wealth of resources, knowledge, and technologies surrounding the mouse as a model system, these similarities have propelled this species to the forefront of biomedical research. The advent of genomic manipulation has quickly led to the creation and use of genetically engineered mice as powerful tools for cutting edge studies of human disease research including the discovery, refinement, and utility of many currently available therapeutic regimes. In particular, the creation of genetically modified mice as models of human disease has remarkably changed our ability to understand the molecular mechanisms and cellular pathways underlying disease states. Moreover, the mouse models resulting from gene transfer technologies have been important components correlating an individual's gene expression profile to the development of disease pathologies. The objective of this review is to provide physician-scientists with an expansive historical and logistical overview of the creation of mouse models of human disease through gene transfer technologies. Our expectation is that this will facilitate on-going disease research studies and may initiate new areas of translational research leading to enhanced patient care.

Variables and strategies in development of therapeutic post-transcriptional gene silencing agents

Post-transcriptional gene silencing (PTGS) agents such as ribozymes, RNAi and antisense have substantial potential for gene therapy of human retinal degenerations. These technologies are used to knockdown a specific target RNA and its cognate protein. The disease target mRNA may be a mutant mRNA causing an autosomal dominant retinal degeneration or a normal mRNA that is overexpressed in certain diseases. All PTGS technologies depend upon the initial critical annealing event of the PTGS ligand to the target RNA. This event requires that the PTGS agent is in a conformational state able to support hybridization and that the target have a large and accessible single-stranded platform to allow rapid annealing, although such platforms are rare. We address the biocomplexity that currently limits PTGS therapeutic development with particular emphasis on biophysical variables that influence cellular performance. We address the different strategies that can be used for development of PTGS agents intended for therapeutic translation. These issues apply generally to the development of PTGS agents for retinal, ocular, or systemic diseases. This review should assist the interested reader to rapidly appreciate critical variables in PTGS development and facilitate initial design and testing of such agents against new targets of clinical interest.

Toward a complete in silico, multi-layered embryonic stem cell regulatory network

Recent efforts in systematically profiling embryonic stem (ES) cells have yielded a wealth of high-throughput data. Complementarily, emerging databases and computational tools facilitate ES cell studies and further pave the way toward the in silico reconstruction of regulatory networks encompassing multiple molecular layers. Here, we briefly survey databases, algorithms, and software tools used to organize and analyze high-throughput experimental data collected to study mammalian cellular systems with a focus on ES cells. The vision of using heterogeneous data to reconstruct a complete multi-layered ES cell regulatory network is discussed. This review also provides an accompanying manually extracted dataset of different types of regulatory interactions from low-throughput experimental ES cell studies available at http://amp.pharm.mssm.edu/iscmid/literature.

Telomerase inhibition strategies by siRNAs against either hTR or hTERT in oral squamous cell carcinoma

Human telomerase RNA (hTR) and human telomerase reverse transcriptase (hTERT) are considered effective molecular targets for current anticancer therapy. In this study, we investigated the therapeutic effects of targeting hTR and hTERT individually or in combination by recombinant adenovirus-delivered small interfering RNA (siRNA) in oral squamous cell carcinoma (OSCC) Tca8113. Further, we screened the optimal strategy for RNA interference. Our results show that these different recombinant adenoviruses specifically reduced the levels of hTR mRNA, hTERT mRNA, hTERT protein and telomerase activity in Tca8113 cells. Moreover, they successfully inhibited xenograft tumor growth in nude mice. The potency of their antitumor activities was ranked as follows: anti-hTR >anti-hTR+anti-hTERT >anti-hTERT. Therefore, we demonstrated that the siRNA-expressing recombinant adenoviruses were an effective anticancer tool for treatment of OSCC. Furthermore, the anticancer effect of solely targeting hTR was more direct and efficient, compared with the effect of targeting hTR and hTERT in combination, or hTERT exclusively. The mechanism of this anticancer effect in OSCC was not only related to the inhibition of cell proliferation and the induction of cell apoptosis, but might also involve the inhibition of tumor angiogenesis.

DNAzyme-mediated recovery of small recombinant RNAs from a 5S rRNA-derived chimera expressed in Escherichia coli

Background

Manufacturing large quantities of recombinant RNAs by overexpression in a bacterial host is hampered by their instability in intracellular environment. To overcome this problem, an RNA of interest can be fused into a stable bacterial RNA for the resulting chimeric construct to accumulate in the cytoplasm to a sufficiently high level. Being supplemented with cost-effective procedures for isolation of the chimera from cells and recovery of the recombinant RNA from stabilizing scaffold, this strategy might become a viable alternative to the existing methods of chemical or enzymatic RNA synthesis.

Results

Sequence encoding a 71-nucleotide recombinant RNA was inserted into a plasmid-borne deletion mutant of the Vibrio proteolyticus 5S rRNA gene in place of helix III - loop C segment of the original 5S rRNA. After transformation into Escherichia coli, the chimeric RNA (3×pen aRNA) was expressed constitutively from E. coli rrnB P1 and P2 promoters. The RNA chimera accumulated to levels that exceeded those of the host's 5S rRNA. A novel method relying on liquid-solid partitioning of cellular constituents was developed for isolation of total RNA from bacterial cells. This protocol avoids toxic chemicals, and is therefore more suitable for large scale RNA purification than traditional methods. A pair of biotinylated 8-17 DNAzymes was used to bring about the quantitative excision of the 71-nt recombinant RNA from the chimera. The recombinant RNA was isolated by sequence-specific capture on beads with immobilized complementary deoxyoligonucleotide, while DNAzymes were recovered by biotin affinity chromatography for reuse.

Conclusions

The feasibility of a fermentation-based approach for manufacturing large quantities of small RNAs in vivo using a "5S rRNA scaffold" strategy is demonstrated. The approach provides a route towards an economical method for the large-scale production of small RNAs including shRNAs, siRNAs and aptamers for use in clinical and biomedical research.

Silencing of gene expression in cultured cells using small interfering RNAs

The discovery of RNA interference (RNAi) and related small RNA-mediated regulatory pathways has significantly altered the understanding of gene regulation in eukaryotic cells. In the RNAi pathway, small interfering RNAs (siRNAs) approximately 21 to 23 nucleotides in length serve as the regulatory molecules that guide and induce sequence-specific gene silencing. The use of siRNA-mediated silencing as a tool for investigating gene function is well established in cultured mammalian cells. This unit provides basic approaches to explore the field of RNAi, and hopes to address the importance of optimizing transfection conditions after empirical determinations in order to understand various degrees of silencing efficiency.

Essential notes regarding the design of functional siRNAs for efficient mammalian RNAi

Short interfering RNAs (siRNAs) are widely used to bring about RNA interference (RNAi) in mammalian cells. Numerous siRNAs may be designed for any target gene though most of which would be incapable of efficiently inducing mammalian RNAi. Certain highly functional siRNAs designed for knockout of a particular gene may render unrelated endogenous genes nonfunctional. These major bottlenecks should be properly eliminated when RNAi technologies are employed for any experiment in mammalian functional genomics. This paper thus presents essential notes and findings regarding the proper choice of siRNA-sequence selection algorithms and web-based online software systems.

siRNAs: their potential as therapeutic agents--Part I. Designing of siRNAs

RNA interference (RNAi) is a novel and essential biological process, as well as a powerful experimental tool with the potential to be used in therapeutic development. RNAi-based strategies have the capability of being able to be driven from bench to bedside. It is very important to develop the precise tools for designing the siRNAs to get the most efficient knockdown of the target genes and to reduce any off-target effects. In this review we have discussed the strategies and parameters required for effective siRNA designing and synthesis, based on already published literature.

A construct with fluorescent indicators for conditional expression of miRNA

BACKGROUND

Transgenic RNAi holds promise as a simple, low-cost, and fast method for reverse genetics in mammals. It may be particularly useful for producing animal models for hypomorphic gene function. Inducible RNAi that permits spatially and temporally controllable gene silencing in vivo will enhance the power of transgenic RNAi approach. Furthermore, because microRNA (miRNA) targeting specific genes can be expressed simultaneously with protein coding genes, incorporation of fluorescent marker proteins can simplify the screening and analysis of transgenic RNAi animals.

RESULTS

We sought to optimally express a miRNA simultaneously with a fluorescent marker. We compared two construct designs. One expressed a red fluorescent protein (RFP) and a miRNA placed in its 3' untranslated region (UTR). The other expressed the same RFP and miRNA, but the precursor miRNA (pre-miRNA) coding sequence was placed in an intron that was inserted into the 3'-UTR. We found that the two constructs expressed comparable levels of miRNA. However, the intron-containing construct expressed a significantly higher level of RFP than the intron-less construct. Further experiments indicate that the 3'-UTR intron enhances RFP expression by its intrinsic gene-expression-enhancing activity and by eliminating the inhibitory effect of the pre-miRNA on the expression of RFP. Based on these findings, we incorporated the intron-embedded pre-miRNA design into a conditional expression construct that employed the Cre-loxP system. This construct initially expressed EGFP gene, which was flanked by loxP sites. After exposure to Cre recombinase, the transgene stopped EGFP expression and began expression of RFP and a miRNA, which silenced the expression of specific cellular genes.

CONCLUSION

We have designed and tested a conditional miRNA-expression construct and showed that this construct expresses both the marker genes strongly and can silence the target gene efficiently upon Cre-mediated induction of the miRNA expression. This construct can be used to increase the efficiency of making cell lines or transgenic animals that stably express miRNA targeting specific genes.

www.rnaworkbench.com: A new program for analyzing RNA interference

RNA interference (RNAi) has become an important tool to study and utilize gene silencing by introducing short interfering RNA (siRNA). In order to predict the most efficient siRNAs, a new software tool, RNA Workbench (RNAWB), has been designed and is freely available (after registration) on http://www.rnaworkbench.com. In addition to the standard selection rules, RNAWB includes the possibility of statistical analyses of the applied selection rules (criteria). The role of RNA secondary structures in the RNA interference process as well as the application of sequence rules are discussed to show the applicability of the software.

Focusing on RISC assembly in mammalian cells

RISC (RNA-induced silencing complex) is a central protein complex in RNAi, into which a siRNA strand is assembled to become effective in gene silencing. By using an in vitro RNAi reaction based on Drosophila embryo extract, an asymmetric model was recently proposed for RISC assembly of siRNA strands, suggesting that the strand that is more loosely paired at its 5' end is selectively assembled into RISC and results in target gene silencing. However, in the present study, we were unable to establish such a correlation in cell-based RNAi assays, as well as in large-scale RNAi data analyses. This suggests that the thermodynamic stability of siRNA is not a major determinant of gene silencing in mammalian cells. Further studies on fork siRNAs showed that mismatch at the 5' end of the siRNA sense strand decreased RISC assembly of the antisense strand, but surprisingly did not increase RISC assembly of the sense strand. More interestingly, measurements of melting temperature showed that the terminal stability of fork siRNAs correlated with the positions of the mismatches, but not gene silencing efficacy. In summary, our data demonstrate that there is no definite correlation between siRNA stability and gene silencing in mammalian cells, which suggests that instead of thermodynamic stability, other features of the siRNA duplex contribute to RISC assembly in RNAi.

Double-mismatched siRNAs enhance selective gene silencing of a mutant ALS-causing allele

AIM

Our previous study demonstrated an siRNA-mediated, allele-specific silencing of mutant genes that cause amyotrophic lateral sclerosis. To improve siRNA design for better therapeutic use of RNA interference, we systematically tested the base-pairing mismatch strategy in the design of asymmetric siRNA.

METHODS

A naturally symmetric siRNA that targets the human Cu Zn superoxide dismutase G85R mutant allele was modified by placing either 1 or 2 mismatches at the end of the siRNA from position 1 to 4 at each time. The target preference and silencing efficacy of modified siRNA were measured using a modified dual luciferase system.

RESULTS

The modification of single base-pairing mismatch successfully achieved the conversion of the siRNA that was originally favored to the antisense of the mutant allele to the one that was favored to the sense strand of the gene. Compared to the single-mismatched siRNA, those with double-mismatch at one end demonstrated an increased asymmetry, and thus, an enhanced specificity and efficacy of gene silencing. In addition, the siRNA with double-mismatch at both ends remained in symmetry.

CONCLUSION

Our results suggest the effectiveness of converting a symmetric siRNA to an asymmetric one by introducing mismatches into its structure, and the superiority of double-mismatched siRNA to single-mismatched siRNA in producing selective gene silencing resulting from the disruption of siRNA symmetry. The double-mismatch strategy is an improvement of the single-mismatch method and could be useful in the design of effective siRNAs for the treatment of diseases caused by dominant, gain-of-function gene mutations, such as ALS.

Asymmetrically designed siRNAs and shRNAs enhance the strand specificity and efficacy in RNAi

RNAi can mediate allele-specific silencing, and offers an attractive approach for treatment of human diseases caused by dominant, gain-of-function gene mutations. However, allele-specific silencing requires that the RNAi target the mutated region of the mRNA, limiting the choices of the target sequences. This often results in the use of a suboptimal siRNAs or shRNAs. Unfavorable strand asymmetry, which leads to the sense strand rather than the antisense strand to be incorporated into RNA-induced silencing complex (RISC), can cause poor RNAi efficacy. We systematically tested an approach that places mismatches at or near the 5' of the antisense strand to create favorable strand asymmetry. Here we show that this approach can enhance the RNAi efficacy of not only siRNAs but also shRNAs synthesized from genes, which can be placed in various viral vectors. Thus, this design of asymmetric shRNAs could be potentially used in silencing dominant, gain-of-function gene mutations for gene therapy.

siRNA selection criteria--statistical analyses of applicability and significance

RNA interference is a powerful tool for gene silencing, which is mediated by introducing siRNA. In the present study, statistical analyses of published siRNA selection criteria, the interpretation of some criteria and systematic searching for new criteria have been carried out for CGB siRNA and siRecords databases. The results of the analyses are as follows: (i) Our study supports the two-state model of the RNA-induced silencing complex (RISC). (ii) Stable 5'-S ends of a siRNA sequence, higher stability of the whole siRNA, and low breaking energy of siRNA duplex occurs in effective siRNA sequences. Also low internal stability of the 5'-AS terminus is preferred. (iii) Secondary structure can be successfully used as an RNAi selection criterion. (iv) Several published sequence criteria have been confirmed and also new criteria have been developed. (v) Also a Target Patterns criterion, which is comparable or better than the best known criteria, has been created.

Long-term XPC silencing reduces DNA double-strand break repair

To study the relationships between different DNA repair pathways, we established a set of clones in which one specific DNA repair gene was silenced using long-term RNA interference in HeLa cell line. We focus here on genes involved in either nucleotide excision repair (XPA and XPC) or nonhomologous end joining (NHEJ; DNA-PKcs and XRCC4). As expected, XPA(KD) (knock down) and XPC(KD) cells were highly sensitive to UVC. DNA-PKcs(KD) and XRCC4(KD) cells presented an increased sensitivity to various inducers of double-strand breaks (DSBs) and a 70% to 80% reduction of in vitro NHEJ activity. Long-term silencing of XPC gene expression led to an increased sensitivity to etoposide, a topoisomerase II inhibitor that creates DSBs through the progression of DNA replication forks. XPC(KD) cells also showed intolerance toward acute gamma-ray irradiation. We showed that XPC(KD) cells exhibited an altered spectrum of NHEJ products with decreased levels of intramolecular joined products. Moreover, in both XPC(KD) and DNA-PKcs(KD) cells, XRCC4 and ligase IV proteins were mobilized on damaged nuclear structures at lower doses of DSB inducer. In XPC-proficient cells, XPC protein was released from nuclear structures after induction of DSBs. By contrast, silencing of XPA gene expression did not have any effect on sensitivity to DSB or NHEJ. Our results suggest that XPC deficiency, certainly in combination with other genetic defects, may contribute to impair DSB repair.

Genetic regulation by non-coding RNAs

Large scale cDNA sequencing and genome tiling array studies have shown that around 50% of genomic DNA in humans is transcribed, of which 2% is translated into proteins and the remaining 98% is non-coding RNAs (ncRNAs). There is mounting evidence that these ncRNAs play critical roles in regulating DNA structure, RNA expression, protein translation and protein functions through multiple genetic mechanisms, and thus affect normal development of organisms at all levels. Today, we know very little about the regulatory mechanisms and functions of these ncRNAs, which is clearly essential knowledge for understanding the secret of life. To promote this emerging research subject of critical importance, in this paper we review (1) ncRNAs' past and present, (2) regulatory mechanisms and their functions, (3) experimental strategies for identifying novel ncRNAs, (4) experimental strategies for investigating their functions, and (5) methodologies and examples of the application of ncRNAs.

On the art of identifying effective and specific siRNAs

Small interfering RNAs (siRNAs) have been widely exploited for sequence-specific gene knockdown, predominantly to investigate gene function in cultured vertebrate cells, and also hold promise as therapeutic agents. Because not all siRNAs that are cognate to a given target mRNA are equally effective, computational tools have been developed based on experimental data to increase the likelihood of selecting effective siRNAs. Furthermore, because target-complementary siRNAs can also target other mRNAs containing sequence segments that are partially complementary to the siRNA, most computational tools include ways to reduce potential off-target effects in the siRNA selection process. Though these methods facilitate selection of functional siRNAs, they do not yet alleviate the need for experimental validation. This perspective provides a practical guide based on current wisdom for selecting siRNAs.

PPD v1.0--an integrated, web-accessible database of experimentally determined protein pKa values

The Protein pK(a) Database (PPD) v1.0 provides a compendium of protein residue-specific ionization equilibria (pK(a) values), as collated from the primary literature, in the form of a web-accessible postgreSQL relational database. Ionizable residues play key roles in the molecular mechanisms that underlie many biological phenomena, including protein folding and enzyme catalysis. The PPD serves as a general protein pK(a) archive and as a source of data that allows for the development and improvement of pK(a) prediction systems. The database is accessed through an HTML interface, which offers two fast, efficient search methods: an amino acid-based query and a Basic Local Alignment Search Tool search. Entries also give details of experimental techniques and links to other key databases, such as National Center for Biotechnology Information and the Protein Data Bank, providing the user with considerable background information. The database can be found at the following URL: http://www.jenner.ac.uk/PPD.

DSTHO: database of siRNAs targeted at human oncogenes: a statistical analysis

Existing treatments of human cancer, which is characterized by abnormal proliferation of cells often lead to fatal outcomes. Sequence selective silencing of oncogene expression using siRNA technology is emerging as a potential solution for cancer treatment. The exclusive selectivity and easy application to virtually any therapeutic target including intracellular factors and transcription factors renders siRNA oligonucleotide applications very promising. However, synthesis of siRNA having sufficient knockdown efficiency is laborious and cost intensive. The database is designed in order to aid the synthesis of siRNAs, which target human oncogenes (OsiRNAs). It provides OsiRNAs of known efficacy from previous experiments with links to published literature and theoretically pre-generated putative target sequences. In addition, links to available theoretical tools, databases and literature corresponding to siRNAs in general are also provided. The links to literature provide information about role of siRNA in therapeutics, chemical properties and transfection methods. Statistical analysis of mono-, di- and tri- mers located in OsiRNAs of known efficacies is performed to identify positional preferences and screen specific motifs. This analysis aids the design and synthesis of effective siRNAs, which particularly target human oncogenes. The database can be accessed at .

Comparison of test systems for RNAinterference

RNAinterference (RNAi) has developed within a short time from an area of basic research occupied by a few experts to a widely used technical tool for reverse genetics, which is expected to have a broad utility not only in research, but also in medical and diagnostic applications. Despite its widespread use, the application of RNAi is often hampered because a difference of only a few nucleotides in the sequence of the target RNA can change the efficiency of a small interfering RNA (siRNA) from high to zero, and publicly available design tools for siRNAs are not yet perfect. We therefore developed and compared RNAi test systems based on different promoters, reporters, and target sequences. Here, we show that fluorescence-based test systems have obvious disadvantages compared to luciferase-based test systems and that some combinations of promoter, reporter, and target sequences, although currently in use, are not well suited for testing RNAi effects.

Small regulatory RNAs in mammals

Mammalian cells harbor numerous small non-protein-coding RNAs, including small nucleolar RNAs (snoRNAs), microRNAs (miRNAs), short interfering RNAs (siRNAs) and small double-stranded RNAs, which regulate gene expression at many levels including chromatin architecture, RNA editing, RNA stability, translation, and quite possibly transcription and splicing. These RNAs are processed by multistep pathways from the introns and exons of longer primary transcripts, including protein-coding transcripts. Most show distinctive temporal- and tissue-specific expression patterns in different tissues, including embryonal stem cells and the brain, and some are imprinted. Small RNAs control a wide range of developmental and physiological pathways in animals, including hematopoietic differentiation, adipocyte differentiation and insulin secretion in mammals, and have been shown to be perturbed in cancer and other diseases. The extent of transcription of non-coding sequences and the abundance of small RNAs suggests the existence of an extensive regulatory network on the basis of RNA signaling which may underpin the development and much of the phenotypic variation in mammals and other complex organisms and which may have different genetic signatures from sequences encoding proteins.