Reconsideration of in-silico siRNA design based on feature selection: a cross-platform data integration perspective

Protection of animals against devastating RNA viruses using CRISPR-Cas13s

The intrinsic nature of CRISPR-Cas in conferring immunity to bacteria and archaea has been repurposed to combat pathogenic agents in mammalian and plant cells. In this regard, CRISPR-Cas13 systems have proved their remarkable potential for single-strand RNA viruses targeting. Here, different types of Cas13 orthologs were applied to knockdown foot-and-mouth disease virus (FMDV), a highly contagious disease of a wide variety of species with genetically diverse strains and is widely geographically distributed. Using programmable CRISPR RNAs capable of targeting conserved regions of the viral genome, all Cas13s from CRISPR system type VI (subtype A/B/D) could comprehensively target and repress different serotypes of FMDV virus. This approach has the potential to destroy all strains of a virus as targets the ultra-conserved regions of genome. We experimentally compared the silencing efficiency of CRISPR and RNAi by designing the most effective short hairpin RNAs according to our developed scoring system and observed comparable results. This study showed successful usage of various Cas13 enzymes for suppression of FMDV, which provides a flexible strategy to battle with other animal infectious RNA viruses, an underdeveloped field in the biotechnology scope.

In Silico Design of siRNAs for Silencing CLEC5A Receptor as a Potential Therapeutic Approach Against Dengue and Japanese Encephalitis Virus Infection in Human

Dengue and Japanese encephalitis virus (JEV) are mosquito-borne RNA viruses that can cause severe illness leading to death in the tropics and subtropics. Both of these viruses interact directly with the C-type lectin domain family 5, member A receptor (CLEC5A) on human macrophages which stimulates the release of proinflammatory cytokines. Since blockade of this interaction has been shown to suppress the secretion of cytokines, CLEC5A is considered a potential target for the development of new treatments to reduce virus-induced brain damage. Developing a vaccine against dengue is challenging because this virus can cause disease through 4 different serotypes. Therefore, the vaccine must immunize against all 4 serotypes to be effective, while unvaccinated people still contract JEV and suffer from its complications. Small interfering RNAs (siRNAs) play an important role in regulating gene expression by causing the degradation of target mRNAs. In this study, we attempted to rationally design potential siRNA molecules using various software, targeting the CLEC5A gene. In total, 3 siRNAs were found to be potential candidates for CLEC5A silencing. They showed good target accessibility, optimum guanine-cytosine (GC) content, the least chance of off-target effects, positive energy of folding, and strong interaction with Argonaute2 protein as denoted by a negative docking energy score. In addition, molecular dynamics simulation of the siRNA-Ago2-docked complexes showed the stability of the complexes over 1.5 nanoseconds. These predicted siRNAs might effectively downregulate the expression of the CLEC5A receptor and thus prove vital in the treatment of dengue and JEV infections.

Therapeutic RNA interference: A novel approach to the treatment of primary hyperoxaluria

RNA interference (RNAi) is a natural biological pathway that inhibits gene expression by targeted degradation or translational inhibition of cytoplasmic mRNA by the RNA induced silencing complex. RNAi has long been exploited in laboratory research to study the biological consequences of the reduced expression of a gene of interest. More recently RNAi has been demonstrated as a therapeutic avenue for rare metabolic diseases. This review presents an overview of the cellular RNAi machinery as well as therapeutic RNAi design and delivery. As a clinical example we present primary hyperoxaluria, an ultrarare inherited disease of increased hepatic oxalate production which leads to recurrent calcium oxalate kidney stones. In the most common form of the disease (Type 1), end‐stage kidney disease occurs in childhood or young adulthood, often necessitating combined kidney and liver transplantation. In this context we discuss nedosiran (Dicerna Pharmaceuticals, Inc.) and lumasiran (Alnylam Pharmaceuticals), which are both novel RNAi therapies for primary hyperoxaluria that selectively reduce hepatic expression of lactate dehydrogenase and glycolate oxidase respectively, reducing hepatic oxalate production and urinary oxalate levels. Finally, we consider future optimizations advances in RNAi therapies.

Silencing efficacy prediction: a retrospective study on target mRNA features

Post-transcriptional gene silencing is a widely used method to suppress gene expression. Unfortunately only a portion of siRNAs do successfully reduce gene expression. Target mRNA secondary structures and siRNA-mRNA thermodynamic features are believed to contribute to the silencing activity. However, there is still an open discussion as to what determines siRNA efficacy. In this retrospective study, we analysed the target accessibility comparing very high (VH) compared with low (L) efficacy siRNA sequences obtained from the siRecords Database. We determined the contribution of mRNA target local secondary structures on silencing efficacy. Both the univariable and the multivariable logistic regression evidenced no relationship between siRNA efficacy and mRNA target secondary structures. Moreover, none of the thermodynamic and sequence-base parameters taken into consideration (H-b index, ΔG°_overall, ΔG°_duplex, ΔG°_break-target and GC%) was associated with siRNA efficacy. We found that features believed to be predictive of silencing efficacy are not confirmed to be so when externally evaluated in a large heterogeneous sample. Although it was proposed that silencing efficacy could be influenced by local target accessibility we show that this could be not generalizable because of the diversity of experimental setting that may not be representative of biological systems especially in view of the many local protein factors, usually not taken into consideration, which could hamper the silencing process.

We analysed several siRNA-mRNA target features involved in silencing efficacy. We found out that features believed to be predictive of silencing efficacy are not such when transferred to a larger dataset of experiments and different experimental settings.

Synthetic RNAs for Gene Regulation: Design Principles and Computational Tools

The use of synthetic non-coding RNAs for post-transcriptional regulation of gene expression has not only become a standard laboratory tool for gene functional studies but it has also opened up new perspectives in the design of new and potentially promising therapeutic strategies. Bioinformatics has provided researchers with a variety of tools for the design, the analysis, and the evaluation of RNAi agents such as small-interfering RNA (siRNA), short-hairpin RNA (shRNA), artificial microRNA (a-miR), and microRNA sponges. More recently, a new system for genome engineering based on the bacterial CRISPR-Cas9 system (Clustered Regularly Interspaced Short Palindromic Repeats), was shown to have the potential to also regulate gene expression at both transcriptional and post-transcriptional level in a more specific way. In this mini review, we present RNAi and CRISPRi design principles and discuss the advantages and limitations of the current design approaches.

High-throughput sequencing as an effective approach in profiling small RNAs derived from a hairpin RNA expression vector in woody plants

Hairpin RNA (hpRNA)-mediated gene silencing has proved to be an efficient approach to develop virus-resistant transgenic plants. To characterize small RNA molecules (sRNAs) derived from an hpRNA expression vector in transgenic cherry rootstock plants, we conducted small RNA sequencing of (1) a transgenic rootstock containing an inverted repeat of the partial coat protein of Prunus necrotic ring spot virus (PNRSV-hpRNA); (2) a nontransgenic rootstock; and (3) a PNRSV-infected sweet cherry plant. Analysis of the PNRSV sRNA pools indicated that 24-nt (nucleotide) small interfering RNAs (siRNAs) were the most prevalent sRNAs in the transgenic rootstock whereas the most abundant sRNAs in the PNRSV-infected nontransgenic rootstock were 21-nt siRNAs. In addition, the 24-nt siRNAs of the PNRSV-hpRNA were more abundant on the sense strand than those on the antisense strand in the transgenic rootstock. In contrast, preference in generating PNRSV sRNAs, ranging from 19-nt to 30-nt for sense and antisense strands, was not distinct in the PNRSV-infected nontransgenic sweet cherry. Taken together, this is the first report on profiling hpRNA-derived sRNAs in woody plants using high-throughput sequencing technology, which is an efficient way to verify the presence/absence, the abundance, and the sequence features of certain sRNAs.

Computational design of artificial RNA molecules for gene regulation

RNA interference (RNAi) is a powerful tool for the regulation of gene expression. Small exogenous noncoding RNAs (ncRNAs) such as siRNA and shRNA are the active silencing agents, intended to target and cleave complementary mRNAs in a specific way. They are widely and successfully employed in functional studies, and several ongoing and already completed siRNA-based clinical trials suggest encouraging results in the regulation of overexpressed genes in disease. siRNAs share many aspects of their biogenesis and function with miRNAs, small ncRNA molecules transcribed from endogenous genes which are able to repress the expression of target mRNAs by either inhibiting their translation or promoting their degradation. Although siRNA and artificial miRNA molecules can significantly reduce the expression of overexpressed target genes, cancer and other diseases can also be triggered or sustained by upregulated miRNAs. Thus, in the past recent years, molecular tools for miRNA silencing, such as antagomiRs and miRNA sponges, have been developed. These molecules have shown their efficacy in the derepression of genes downregulated by overexpressed miRNAs. In particular, while a single antagomiR is able to inhibit a single complementary miRNA, an artificial sponge construct usually contains one or more binding sites for one or more miRNAs and functions by competing with the natural targets of these miRNAs. As a consequence, natural miRNA targets are reexpressed at their physiological level. In this chapter we review the most successful methods for the computational design of siRNAs, antagomiRs, and miRNA sponges and describe the most popular tools that implement them.

Reconsideration of in silico siRNA design from a perspective of heterogeneous data integration: problems and solutions

The success of RNA interference (RNAi) depends on the interaction between short interference RNAs (siRNAs) and mRNAs. Design of highly efficient and specific siRNAs has become a challenging issue in applications of RNAi. Here, we present a detailed survey on the state-of-the-art siRNAs design, focusing on several key issues with the current in silico RNAi studies, including: (i) inconsistencies among the proposed guidelines for siRNAs design and the incomplete list of siRNAs features, (ii) improper integration of the heterogeneous cross-platform siRNAs data, (iii) inadequate consideration of the binding specificity of the target mRNAs and (iv) reduction in the 'off-target' effect in siRNAs design. With these considerations, the popular in silico siRNAs design rules are reexamined and several inconsistent viewpoints toward siRNAs feature identifications are clarified. In addition, novel computational models for siRNAs design using state-of-art machine learning techniques are discussed, which focus on heterogeneous data integration, joint feature selection and customized siRNAs screening toward highly specific targets. We believe that addressing such issues in siRNA study will provide new clues for further improved design of more efficient and specific siRNAs in RNAi.

In silico target-specific siRNA design based on domain transfer in heterogeneous data

RNA interference via exogenous small interference RNAs (siRNA) is a powerful tool in gene function study and disease treatment. Designing efficient and specific siRNA on target gene remains the key issue in RNAi. Although various in silico models have been proposed for rational siRNA design, most of them focus on the efficiencies of selected siRNAs, while limited effort has been made to improve their specificities targeted on specific mRNAs, which is related to reducing off-target effects (OTEs) in RNAi. In our study, we propose for the first time that the enhancement of target specificity of siRNA design can be achieved computationally by domain transfer in heterogeneous data sources from different siRNA targets. A transfer learning based method i.e., heterogeneous regression (HEGS) is presented for target-specific siRNA efficacy modeling and feature selection. Based on the model, (1) the target regression model can be built by extracting information from related data in other targets/experiments, thus increasing the target specificity in siRNA design with the help of information from siRNAs binding to other homologous genes, and (2) the potential features correlated to the current siRNA design can be identified even when there is lack of experimental validated siRNA affinity data on this target. In summary, our findings present useful instructions for a better target-specific siRNA design, with potential applications in genome-wide high-throughput screening of effective siRNA, and will provide further insights on the mechanism of RNAi.