Design of siRNAs producing unstructured guide-RNAs results in improved RNA interference efficiency

Petits ARN interférents : applications potentielles pour les néphrologues Small interfering RNA: potential applications for nephrologists

Small interfering RNA (siRNAs) are double-stranded RNAs of around 20 base pairs in length that trigger RNAi machinery, which promotes degradation of a target mRNA avoiding protein translation. SiRNAs are liver-targeted, using tris N-acetylgalactosamine (GalNAc) as the targeting ligand. This discovery received the Nobel Prize for medicine and physiology in 2006 and lead to substantial therapeutic advances. Application field and development of these siRNA has been very fast. Indeed, patisiran has been released in 2018 for hereditary transthyretin amyloidosis. This first treatment showed the security and efficacy of such a product. Since, treatments have been developed for acute hepatic porphyria and primary hyperoxaluria. The current pipeline for new siRNA development is ambitious; clinical trial are ongoing in nephrology, as in the IgA nephropathy. Frequent diseases are also targeted such as hypertension or hypercholesterolemia. © 2022 Published by Elsevier Masson SAS on behalf of Société francophone de néphrologie, dialyse et transplantation.

Cheminformatics Modeling of Gene Silencing for Both Natural and Chemically Modified siRNAs

In designing effective siRNAs for a specific mRNA target, it is critically important to have predictive models for the potency of siRNAs. None of the published methods characterized the chemical structures of individual nucleotides constituting a siRNA molecule; therefore, they cannot predict the potency of gene silencing by chemically modified siRNAs (cm-siRNA). We propose a new approach that can predict the potency of gene silencing by cm-siRNAs, which characterizes each nucleotide (NT) using 12 BCUT cheminformatics descriptors describing its charge distribution, hydrophobic and polar properties. Thus, a 21-NT siRNA molecule is described by 252 descriptors resulting from concatenating all the BCUT values of its composing nucleotides. Partial Least Square is employed to develop statistical models. The Huesken data (2431 natural siRNA molecules) were used to perform model building and evaluation for natural siRNAs. Our results were comparable with or superior to those from Huesken's algorithm. The Bramsen dataset (48 cm-siRNAs) was used to build and test the models for cm-siRNAs. The predictive r2 of the resulting models reached 0.65 (or Pearson r values of 0.82). Thus, this new method can be used to successfully model gene silencing potency by both natural and chemically modified siRNA molecules.

SARS-CoV-2 and the central nervous system: Emerging insights into hemorrhage-associated neurological consequences and therapeutic considerations

Coronavirus disease 2019 (COVID-19), caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) continues to impact our lives by causing widespread illness and death and poses a threat due to the possibility of emerging strains. SARS-CoV-2 targets angiotensin-converting enzyme 2 (ACE2) before entering vital organs of the body, including the brain. Studies have shown systemic inflammation, cellular senescence, and viral toxicity-mediated multi-organ failure occur during infectious periods. However, prognostic investigations suggest that both acute and long-term neurological complications, including predisposition to irreversible neurodegenerative diseases, can be a serious concern for COVID-19 survivors, especially the elderly population. As emerging studies reveal sites of SARS-CoV-2 infection in different parts of the brain, potential causes of chronic lesions including cerebral and deep-brain microbleeds and the likelihood of developing stroke-like pathologies increases, with critical long-term consequences, particularly for individuals with neuropathological and/or age-associated comorbid conditions. Our recent studies linking the blood degradation products to genome instability, leading to cellular senescence and ferroptosis, raise the possibility of similar neurovascular events as a result of SARS-CoV-2 infection. In this review, we discuss the neuropathological consequences of SARS-CoV-2 infection in COVID survivors, focusing on possible hemorrhagic damage in brain cells, its association to aging, and the future directions in developing mechanism-guided therapeutic strategies.

New Insights on the Integrated Management of Plant Diseases by RNA Strategies: Mycoviruses and RNA Interference

RNA-based strategies for plant disease management offer an attractive alternative to agrochemicals that negatively impact human and ecosystem health and lead to pathogen resistance. There has been recent interest in using mycoviruses for fungal disease control after it was discovered that some cause hypovirulence in fungal pathogens, which refers to a decline in the ability of a pathogen to cause disease. Cryphonectria parasitica, the causal agent of chestnut blight, has set an ideal model of management through the release of hypovirulent strains. However, mycovirus-based management of plant diseases is still restricted by limited approaches to search for viruses causing hypovirulence and the lack of protocols allowing effective and systemic virus infection in pathogens. RNA interference (RNAi), the eukaryotic cell system that recognizes RNA sequences and specifically degrades them, represents a promising. RNA-based disease management method. The natural occurrence of cross-kingdom RNAi provides a basis for host-induced gene silencing, while the ability of most pathogens to uptake exogenous small RNAs enables the use of spray-induced gene silencing techniques. This review describes the mechanisms behind and the potential of two RNA-based strategies, mycoviruses and RNAi, for plant disease management. Successful applications are discussed, as well as the research gaps and limitations that remain to be addressed.

Biotechnological Evolution of siRNA Molecules: From Bench Tool to the Refined Drug

The depth and versatility of siRNA technologies enable their use in disease targets that are undruggable by small molecules or that seek to achieve a refined turn-off of the genes for any therapeutic area. Major extracellular barriers are enzymatic degradation of siRNAs by serum endonucleases and RNAases, renal clearance of the siRNA delivery system, the impermeability of biological membranes for siRNA, activation of the immune system, plasma protein sequestration, and capillary endothelium crossing. To overcome the intrinsic difficulties of the use of siRNA molecules, therapeutic applications require nanometric delivery carriers aiming to protect double-strands and deliver molecules to target cells. This review discusses the history of siRNAs, siRNA design, and delivery strategies, with a focus on progress made regarding siRNA molecules in clinical trials and how siRNA has become a valuable asset for biopharmaceutical companies.

RNAs - a new frontier in crop protection

Small RNA (sRNA)-mediated RNA interference (RNAi) is a regulatory mechanism conserved in almost all eukaryotes. sRNAs play a critical role in host pathogen interactions either endogenously or by traveling between the interacting organisms and inducing 'cross-Kingdom RNAi' in the counterparty. Cross-kingdom RNAi is the mechanistic basis of host-induced gene silencing (HIGS), which relies on genetically expressing pathogen-gene targeting RNAs in crops, and has been successfully utilized against both microbial pathogens and pests. HIGS is limited by the need to produce genetically engineered crops. Recent studies have demonstrated that double-stranded RNAs and sRNAs can be efficiently taken up by many fungal pathogens, and induce gene silencing in fungal cells. This mechanism, termed 'environmental RNAi', allows direct application of pathogen-gene targeting RNAs onto crops to silence fungal virulence-related genes for plant protection. In this review, we will focus on how we can leverage cross-kingdom RNAi and environmental RNAi for crop disease control.

CRISPR/Cas13d-mediated efficient KDM5B mRNA knockdown in porcine somatic cells and parthenogenetic embryos

An efficient mRNA knockdown strategy is needed to explore gene function in cells and embryos, especially to understand the process of maternal mRNA decay during early embryo development. Cas13, a novel RNA-targeting CRISPR effector protein, could bind and cleave complementary single-strand RNA, which has been employed for mRNA knockdown in mouse and human cells and RNA-virus interference in plants. Cas13 has not yet been reported to be used in pigs. In the current study, we explored the feasibility of CRISPR/Cas13d-mediated endogenous RNA knockdown in pigs. KDM5B, a histone demethylase of H3K4me3, was downregulated at the transcriptional level by 50% with CRISPR/Cas13d in porcine fibroblast cells. Knockdown of KDM5B-induced H3K4me3 expression and decreased the abundance of H3K27me3, H3K9me3, H3K4ac, H4K8ac, and H4K12ac. These changes affected cell proliferation and cell cycle. Furthermore, stable integration of the CRISPR/Cas13d system into the porcine genome resulted in the continuous expression of Cas13d and persistent knockdown of KDM5B. Finally, the RNA-targeting potential of Cas13d was further validated in porcine parthenogenetic embryos. By microinjection of Cas13d mRNA and gRNA targeting KDM5B into porcine oocytes, the expression of KDM5B was downregulated, the abundance of H3K4me3 increased as expected, and the expression of embryonic development-related genes was changed accordingly. These results indicate that CRISPR/Cas13d provides an easily programmable platform for spatiotemporal transcriptional manipulation in pigs.

The architecture of the SARS-CoV-2 RNA genome inside virion

SARS-CoV-2 carries the largest single-stranded RNA genome and is the causal pathogen of the ongoing COVID-19 pandemic. How the SARS-CoV-2 RNA genome is folded in the virion remains unknown. To fill the knowledge gap and facilitate structure-based drug development, we develop a virion RNA in situ conformation sequencing technology, named vRIC-seq, for probing viral RNA genome structure unbiasedly. Using vRIC-seq data, we reconstruct the tertiary structure of the SARS-CoV-2 genome and reveal a surprisingly "unentangled globule" conformation. We uncover many long-range duplexes and higher-order junctions, both of which are under purifying selections and contribute to the sequential package of the SARS-CoV-2 genome. Unexpectedly, the D614G and the other two accompanying mutations may remodel duplexes into more stable forms. Lastly, the structure-guided design of potent small interfering RNAs can obliterate the SARS-CoV-2 in Vero cells. Overall, our work provides a framework for studying the genome structure, function, and dynamics of emerging deadly RNA viruses.

The mutual regulatory loop between TPTEP1 and miR-1303 in leukemogenesis of acute myeloid leukemia

Background

Non-coding RNAs (ncRNAs) have been identified as key regulators during the pathogenesis and development of cancers. However, most of ncRNAs have never been explored in acute myeloid leukemia (AML).

Methods

Gene expression was evaluated by quantitative real-time polymerase chain reaction (qRT-PCR) or western blot. Functional assays were performed to assess the cellular processes in AML cells. The relationship between genes was verified by means of a series of mechanism assays.

Results

Transmembrane phosphatase with tensin homology pseudogene 1 (TPTEP1) was notably downregulated in AML cells, and functionally acted as a proliferation-inhibitor. Additionally, TPTEP1 suppressed AML cell growth by inactivating c-Jun N-terminal kinase (JNK)/c-JUN signaling pathway. MicroRNA (MiR)-1303, as an oncogene, was predicted and validated as a target of c-JUN in AML cells. Also, TPTEP1 interacted with miR-1303 and they were mutually silenced by each other in AML cells. Furthermore, the effect of TPTEP1 overexpression on AML cell proliferation was counteracted under miR-1303 upregulation.

Conclusion

Our findings unmasked a feedback loop of TPTEP1/JNK/c-JUN/miR-1303 axis in AML cells, suggesting TPTEP1 and miR-1303 as potential targets for developing therapeutic strategies for AML patients.

Computational prediction of potential siRNA and human miRNA sequences to silence orf1ab associated genes for future therapeutics against SARS-CoV-2

The coronavirus disease 2019 (COVID-19) is an ongoing pandemic caused by an RNA virus termed as severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). SARS-CoV-2 possesses an almost 30kbp long genome. The genome contains open-reading frame 1ab (ORF1ab) gene, the largest one of SARS-CoV-2, encoding polyprotein PP1ab and PP1a responsible for viral transcription and replication. Several vaccines have already been approved by the respective authorities over the world to develop herd immunity among the population. In consonance with this effort, RNA interference (RNAi) technology holds the possibility to strengthen the fight against this virus. Here, we have implemented a computational approach to predict potential short interfering RNAs including small interfering RNAs (siRNAs) and microRNAs (miRNAs), which are presumed to be intrinsically active against SARS-CoV-2. In doing so, we have screened miRNA library and siRNA library targeting the ORF1ab gene. We predicted the potential miRNA and siRNA candidate molecules utilizing an array of bioinformatic tools. By extending the analysis, out of 24 potential pre-miRNA hairpins and 131 siRNAs, 12 human miRNA and 10 siRNA molecules were sorted as potential therapeutic agents against SARS-CoV-2 based on their GC content, melting temperature (Tm), heat capacity (Cp), hybridization and minimal free energy (MFE) of hybridization. This computational study is focused on lessening the extensive time and labor needed in conventional trial and error based wet lab methods and it has the potential to act as a decent base for future researchers to develop a successful RNAi therapeutic.

Small interfering RNAs (siRNAs) based gene silencing strategies for the treatment of glaucoma: Recent advancements and future perspectives

RNA-interference-based mechanisms, especially the use of small interfering RNAs (siRNAs), have been under investigation for the treatment of several ailments and have shown promising results for ocular diseases including glaucoma. The eye, being a confined compartment, serves as a good target for the delivery of siRNAs. This review focuses on siRNA-based strategies for gene silencing to treat glaucoma. We have discussed the ocular structures and barriers to gene therapy (tear film, corneal, conjunctival, vitreous, and blood ocular barriers), methods of administration for ocular gene delivery (topical instillation, periocular, intracameral, intravitreal, subretinal, and suprachoroidal routes) and various viral and non-viral vectors in siRNA-based therapy for glaucoma. The components and mechanism of siRNA-based gene silencing have been mentioned briefly followed by the basic strategies and challenges faced during siRNA therapeutics development. We have emphasized different therapeutic targets for glaucoma which have been under research by scientists and the current siRNA-based drugs used in glaucoma treatment. We also mention briefly strategies for siRNA-based treatment after glaucoma surgery.

[Application of simple Ilizarov ring external fixation technique in treatment of tibial plateau fracture complicated with osteofascial compartment syndrome]

OBJECTIVE

To explore the effectiveness of simple Ilizarov ring external fixation technique in treatment of tibial plateau fractures complicated with osteofascial compartment syndrome.

METHODS

Between September 2013 and March 2017, 30 patients with tibial plateau fractures complicated with osteofascial compartment syndrome were treated with simple Ilizarov ring external fixation technique. There were 23 males and 7 females, with an average age of 34.4 years (range, 23-43 years). The injuries were caused by traffic accident in 12 cases, by falling from height in 4 cases, by falling in 8 cases, and by a crashing object in 6 cases. The time from injury to admission was 1-12 hours (mean, 4.8 hours). According to the Schatzker classification, there was 1 case of type Ⅱ, 3 cases of type Ⅲ, 10 cases of type Ⅳ, 7 cases of type Ⅴ, and 9 cases of type Ⅵ. All patients underwent fasciotomy due to osteofascial compartment syndrome; the interval between fasciotomy and operation was 10-15 days (mean, 12.5 days). Knee Society Score (KSS) and Ilizarov Method Research and Application Association (ASAMI) protocol were used to evaluate knee function.

RESULTS

The operation time was 110-155 minutes (mean, 123.1 minutes); the intraoperative blood loss was 100-500 mL (mean, 245 mL); the postoperative hospital stay was 3-5 days (mean, 3.8 days). All patients were followed up 20-24 weeks (mean, 22.7 weeks). Except for 2 patients with signs of needle tract infection, no other complication occurred. X-ray films showed that the fractures healed, and the healing time was 10-20 weeks (mean, 14.6 weeks). At last follow-up, the KSS clinical score was 70- 95 with an average of 87.5; the functional score was 70-90 with an average of 79.0. According to ASAMI protocol evaluation, the effectiveness was rated as excellent in 24 cases, good in 3 cases, fair in 2 cases, and poor in 1 case.

CONCLUSION

For tibial plateau fractures complicated with osteofascial compartment syndrome, simple Ilizarov ring external fixation technique can basically restore joint function and has fewer complications. It is a relatively safe and effective treatment method.

A Therapeutic Approach Against Leishmania donovani by Predicting RNAi Molecules Against the Surface Protein, gp63

Background:

Leishmaniasis is a disease caused by the Leishmania sp. and can be classified into two major types: cutaneous and visceral leismaniasis. Visceral leishmaniasis is the deadlier type and is mediated by Leishmania donovani and involves the establishment of persistent infection and causes damage to the liver, spleen and bone marrow. With no vaccine yet available against leishmaniasis and the current therapeutic drugs of leishmaniasis being toxic and expensive; an alternative treatment is necessary.

Objective:

Surface glycocalyx protein gp63, plays a major role in the virulence and resulting pathogenicity associated with the disease. Henceforth, silencing the gp63 mRNA through the RNA interference system was the aim of this study.

Methods:

In this study two competent siRNAs and three miRNAs have been designed against gp63 for five different strains of L. donovani by using various computational methods. Target specific siRNAs were designed using siDirect 2.0 and to design possible miRNA, another tool named IDT (IntegratedDNA Technology). Screening for off-target similarity was done by BLAST and the GC contents and the secondary structures of the designed RNAs were determined. RNA-RNA interaction was calculated by RNAcofold and IntraRNA, followed by the determination of heat capacity and the concentration of duplex by DNAmelt web server.

Results:

The selected RNAi molecules; two siRNA and three miRNA had no off-target in human genome and the ones with lower GC content were selected for efficient RNAi function. The selected ones showed proper thermodynamic characteristics to suppress the expression of the pathogenic gene of gp63.

RNA Interference and Small RNA Analysis

Small silencing RNAs have provided powerful reverse genetics tools and have opened new areas of research. This introduction describes the use of RNAi to suppress expression of individual genes for loss-of-function analysis. It also summarizes methods for measuring specific and global changes in small RNA expression, as well as methods to inhibit the function of individual endogenous small RNA species such as miRNAs.

Nanomaterials-Based siRNA Delivery: Routes of Administration, Hurdles and Role of Nanocarriers

Ribonucleic acid interference (RNAi) is a potential alternative therapeutic approach to knock down the overexpression of genes in several disorders especially cancers with underlying genetic dysfunctions. For silencing of specific genes involved in cell cycle, small/short interfering ribonucleic acids (siRNAs) are being used clinically. The siRNA-based RNAi is more efficient, specific and safe antisense technology than other RNAi approaches. The route of siRNA administration for siRNA therapy depends on the targeted site. However, certain hurdles like poor stability of siRNA, saturation, off-target effect, immunogenicity, anatomical barriers and non-targeted delivery restrict the successful siRNA therapy. Thus, advancement of an effective, secure, and long-term delivery system is prerequisite to the medical utilization of siRNA. Polycationic nanocarriers mediated targeted delivery system is an ideal system to remove these hurdles and to increase the blood retention time and rate of intracellular permeability. In this chapter, we will mainly discuss the different biocompatible, biodegradable, non-toxic (organic, inorganic and hybrid) nanocarriers that encapsulate and shield the siRNA from the different harsh environment and provides the increased systemic siRNA delivery.

Advances in CRISPR-Cas systems for RNA targeting, tracking and editing

Clustered regularly interspaced short palindromic repeat (CRISPR)/CRISPR-associated protein (Cas) systems, especially type II (Cas9) systems, have been widely used in gene/genome targeting. Modifications of Cas9 enable these systems to become platforms for precise DNA manipulations. However, the utilization of CRISPR-Cas systems in RNA targeting remains preliminary. The discovery of type VI CRISPR-Cas systems (Cas13) shed light on RNA-guided RNA targeting. Cas13d, the smallest Cas13 protein, with a length of only ~930 amino acids, is a promising platform for RNA targeting compatible with viral delivery systems. Much effort has also been made to develop Cas9, Cas13a and Cas13b applications for RNA-guided RNA targeting. The discovery of new RNA-targeting CRISPR-Cas systems as well as the development of RNA-targeting platforms with Cas9 and Cas13 will promote RNA-targeting technology substantially. Here, we review new advances in RNA-targeting CRISPR-Cas systems as well as advances in applications of these systems in RNA targeting, tracking and editing. We also compare these Cas protein-based technologies with traditional technologies for RNA targeting, tracking and editing. Finally, we discuss remaining questions and prospects for the future.

In silico prediction of short hairpin RNA and in vitro silencing of activin receptor type IIB in chicken embryo fibroblasts by RNA interference

Gene silencing by RNA interference is extensively used reverse genetic approach to analyse the implications of any gene in mammalian systems. The silencing of the Activin type IIB receptor belonging to transforming growth factor beta superfamily has demonstrated increase in muscle growth in many species. We designed five short hairpin RNA constructs targeting coding region of chicken ACTRIIB. All the shRNAs were transfected into chicken embryo fibroblast cells and evaluated their silencing efficiency by real time PCR and western blotting. Initially the computational analysis of target region and shRNA constructs was undertaken to predict sequence based features (secondary structures, GC% and H-b index) and thermodynamic features (ΔG_overall, ΔG_duplex, ΔG_break-target, ΔG_{intra-oligomer}, ΔG_{inter-oligomer} and ΔΔG_ends). We determined that all these predicted features were associated with shRNA efficacy. The invitro analysis of shRNA constructs exhibited significant (P < 0.05) reduction in the levels of ACTRIIB at mRNA and protein level. The knock down efficiency of shRNAs varied significantly (P < 0.001) from 83% (shRNA 1) to 43% (shRNA 5). All the shRNAs up regulated the myogenic pathway associated genes (MyoD and MyoG) significantly (P < 0.05). There was significant (P < 0.05) up-regulation of IFNA, IFNB and MHCII transcripts. The ACTRIIB expression was inversely associated with the expression of myogenic pathway and immune response genes. The anti ACTRIIB shRNA construct 1 and 3 exhibited maximum knock down efficiency with minimal interferon response, and can be used for generating ACTRIIB knockdown chicken with higher muscle mass.

Capsule-like Safe Genetic Vectors-Cell-Penetrating Core-Shell Particles Selectively Release Functional Small RNA and Entrap Its Encoding DNA

The breakthrough of genetic therapy is set back by the lack of suitable genetic vector systems. We present the development of permeability-tunable, capsule-like, polymeric, micron-sized, core-shell particles for delivery of recombinant nucleic acids into target cells. These particles were demonstrated to effectively release rod-shaped small hairpin RNA and to selectively retain the RNA-encoding DNA template, which was designed to form a bulky tripartite structure. Thus, they can serve as delivery vectors preloaded with cargo RNA or alternatively as RNA-producing micro-bioreactors. The internalization of particles by human tissue culture cells inversely correlated with particle size and with the cell to particle ratio, although at a higher than stoichiometric excess of particles over cells, cell viability was impaired. Among primary human peripheral blood mononuclear cells, up to 50% of the monocytes displayed positive uptake of particles. Finally, these particles efficiently delivered siRNA into HEK293T cells triggering functional knockdown of the target gene lamin A/C. Particle-mediated knockdown was superior to that observed after conventional siRNA delivery via lipofection. Core-shell particles protect encapsulated nucleic acids from degradation and target cell genomes from direct contact with recombinant DNA, thus representing a promising delivery vector system that can be explored for genetic therapy and vaccination.

Nuclear receptor nhr-48 is required for pathogenicity of the second stage (J2) of the plant parasite Meloidogyne incognita

Nuclear receptors (NRs) are a diverse class of transcription factors, which are involved in regulating a large number of physiological events in metazoans. However, the function of NRs is poorly understood in plant-parasitic nematodes. Here, members of the NR1J+K group of NRs in nematodes, including the free-living and plant parasites, were examined and phylogenetically analyzed. We found that the number of members of the NR1J+K group in plant-parasitic nematodes was less than that in the free-living nematodes, suggesting this reduction of NR1J+K group members in plant parasites maybe arose during the separation of the free-living and intermediately plant parasitic nematodes (Bursaphelenchus xylophilus). Interestingly, the DNA-binding domain (DBD) and ligand-binding domain (LBD) of NR1J+K members were separated into two gene locations in the plant parasites. Knockdown of Meloidogyne incognita WBMinc13296, the ortholog of Caenorhabditis elegans nhr-48 DBD, reduced infectivity, delayed development, and decreased reproductivity. J2 of M. incognita subjected to silencing of WBMinc13295, the orthologs of B. xylophilus nhr-48 LBD, exhibited developmental lag within the host and reduced reproductivity. This study provides new insights into the function of NRs and suggests that NRs are potential targets for developing effective strategies for biological control of plant-parasitic nematodes.

Validation of RNAi Silencing Efficiency Using Gene Array Data shows 18.5% Failure Rate across 429 Independent Experiments

No independent cross-validation of success rate for studies utilizing small interfering RNA (siRNA) for gene silencing has been completed before. To assess the influence of experimental parameters like cell line, transfection technique, validation method, and type of control, we have to validate these in a large set of studies. We utilized gene chip data published for siRNA experiments to assess success rate and to compare methods used in these experiments. We searched NCBI GEO for samples with whole transcriptome analysis before and after gene silencing and evaluated the efficiency for the target and off-target genes using the array-based expression data. Wilcoxon signed-rank test was used to assess silencing efficacy and Kruskal–Wallis tests and Spearman rank correlation were used to evaluate study parameters. All together 1,643 samples representing 429 experiments published in 207 studies were evaluated. The fold change (FC) of down-regulation of the target gene was above 0.7 in 18.5% and was above 0.5 in 38.7% of experiments. Silencing efficiency was lowest in MCF7 and highest in SW480 cells (FC = 0.59 and FC = 0.30, respectively, P = 9.3E−06). Studies utilizing Western blot for validation performed better than those with quantitative polymerase chain reaction (qPCR) or microarray (FC = 0.43, FC = 0.47, and FC = 0.55, respectively, P = 2.8E−04). There was no correlation between type of control, transfection method, publication year, and silencing efficiency. Although gene silencing is a robust feature successfully cross-validated in the majority of experiments, efficiency remained insufficient in a significant proportion of studies. Selection of cell line model and validation method had the highest influence on silencing proficiency.

Principles for Predicting RNA Secondary Structure Design Difficulty

Designing RNAs that form specific secondary structures is enabling better understanding and control of living systems through RNA-guided silencing, genome editing and protein organization. Little is known, however, about which RNA secondary structures might be tractable for downstream sequence design, increasing the time and expense of design efforts due to inefficient secondary structure choices. Here, we present insights into specific structural features that increase the difficulty of finding sequences that fold into a target RNA secondary structure, summarizing the design efforts of tens of thousands of human participants and three automated algorithms (RNAInverse, INFO-RNA and RNA-SSD) in the Eterna massive open laboratory. Subsequent tests through three independent RNA design algorithms (NUPACK, DSS-Opt and MODENA) confirmed the hypothesized importance of several features in determining design difficulty, including sequence length, mean stem length, symmetry and specific difficult-to-design motifs such as zigzags. Based on these results, we have compiled an Eterna100 benchmark of 100 secondary structure design challenges that span a large range in design difficulty to help test future efforts. Our in silico results suggest new routes for improving computational RNA design methods and for extending these insights to assess "designability" of single RNA structures, as well as of switches for in vitro and in vivo applications.

Identification of possible siRNA molecules for TDP43 mutants causing amyotrophic lateral sclerosis: In silico design and molecular dynamics study

The DNA binding protein, TDP43 is a major protein involved in amyotrophic lateral sclerosis and other neurological disorders such as frontotemporal dementia, Alzheimer disease, etc. In the present study, we have designed possible siRNAs for the glycine rich region of tardbp mutants causing ALS disorder based on a systematic theoretical approach including (i) identification of respective codons for all mutants (reported at the protein level) based on both minimum free energy and probabilistic approaches, (ii) rational design of siRNA, (iii) secondary structure analysis for the target accessibility of siRNA, (iii) determination of the ability of siRNA to interact with mRNA and the formation/stability of duplex via molecular dynamics study for a period of 15ns and (iv) characterization of mRNA-siRNA duplex stability based on thermo-physical analysis. The stable GC-rich siRNA expressed strong binding affinity towards mRNA and forms stable duplex in A-form. The linear dependence between the thermo-physical parameters such as Tm, GC content and binding free energy revealed the ability of the identified siRNAs to interact with mRNA in comparable to that of the experimentally reported siRNAs. Hence, this present study proposes few siRNAs as the possible gene silencing agents in RNAi therapy based on the in silico approach.

Improved knockdown from artificial microRNAs in an enhanced miR-155 backbone: a designer's guide to potent multi-target RNAi

Artificial microRNA (amiRNA) sequences embedded in natural microRNA (miRNA) backbones have proven to be useful tools for RNA interference (RNAi). amiRNAs have reduced off-target and toxic effects compared to other RNAi-based methods such as short-hairpin RNAs (shRNA). amiRNAs are often less effective for knockdown, however, compared to their shRNA counterparts. We screened a large empirically-designed amiRNA set in the synthetic inhibitory BIC/miR-155 RNA (SIBR) scaffold and show common structural and sequence-specific features associated with effective amiRNAs. We then introduced exogenous motifs into the basal stem region which increase amiRNA biogenesis and knockdown potency. We call this modified backbone the enhanced SIBR (eSIBR) scaffold. Using chained amiRNAs for multi-gene knockdown, we show that concatenation of miRNAs targeting different genes is itself sufficient for increased knockdown efficacy. Further, we show that eSIBR outperforms wild-type SIBR (wtSIBR) when amiRNAs are chained. Finally, we use a lentiviral expression system in cultured neurons, where we again find that eSIBR amiRNAs are more potent for multi-target knockdown of endogenous genes. eSIBR will be a valuable tool for RNAi approaches, especially for studies where knockdown of multiple targets is desired.

Sequence Design for a Test Tube of Interacting Nucleic Acid Strands

We describe an algorithm for designing the equilibrium base-pairing properties of a test tube of interacting nucleic acid strands. A target test tube is specified as a set of desired "on-target" complexes, each with a target secondary structure and target concentration, and a set of undesired "off-target" complexes, each with vanishing target concentration. Sequence design is performed by optimizing the test tube ensemble defect, corresponding to the concentration of incorrectly paired nucleotides at equilibrium evaluated over the ensemble of the test tube. To reduce the computational cost of accepting or rejecting mutations to a random initial sequence, the structural ensemble of each on-target complex is hierarchically decomposed into a tree of conditional subensembles, yielding a forest of decomposition trees. Candidate sequences are evaluated efficiently at the leaf level of the decomposition forest by estimating the test tube ensemble defect from conditional physical properties calculated over the leaf subensembles. As optimized subsequences are merged toward the root level of the forest, any emergent defects are eliminated via ensemble redecomposition and sequence reoptimization. After successfully merging subsequences to the root level, the exact test tube ensemble defect is calculated for the first time, explicitly checking for the effect of the previously neglected off-target complexes. Any off-target complexes that form at appreciable concentration are hierarchically decomposed, added to the decomposition forest, and actively destabilized during subsequent forest reoptimization. For target test tubes representative of design challenges in the molecular programming and synthetic biology communities, our test tube design algorithm typically succeeds in achieving a normalized test tube ensemble defect ≤1% at a design cost within an order of magnitude of the cost of test tube analysis.

Efficient production of superior dumbbell-shaped DNA minimal vectors for small hairpin RNA expression

Genetic therapy holds great promise for the treatment of inherited or acquired genetic diseases; however, its breakthrough is hampered by the lack of suitable gene delivery systems. Dumbbell-shaped DNA minimal vectors represent an attractive, safe alternative to the commonly used viral vectors which are fraught with risk, but dumbbell generation appears to be costly and time-consuming. We developed a new PCR-based method for dumbbell production which comprises only two steps. First, PCR amplification of the therapeutic expression cassette using chemically modified primers to form a ready-to-ligate DNA structure; and second, a highly efficient intramolecular ligation reaction. Compared with conventional strategies, the new method produces dumbbell vectors more rapidly, with higher yields and purity, and at lower costs. In addition, such produced small hairpin RNA expressing dumbbells triggered superior target gene knockdown compared with conventionally produced dumbbells or plasmids. Our novel method is suitable for large-scale dumbbell production and can facilitate clinical applications of this vector system.

Oligonucleotide-based strategies to combat polyglutamine diseases

Considerable advances have been recently made in understanding the molecular aspects of pathogenesis and in developing therapeutic approaches for polyglutamine (polyQ) diseases. Studies on pathogenic mechanisms have extended our knowledge of mutant protein toxicity, confirmed the toxicity of mutant transcript and identified other toxic RNA and protein entities. One very promising therapeutic strategy is targeting the causative gene expression with oligonucleotide (ON) based tools. This straightforward approach aimed at halting the early steps in the cascade of pathogenic events has been widely tested for Huntington's disease and spinocerebellar ataxia type 3. In this review, we gather information on the use of antisense oligonucleotides and RNA interference triggers for the experimental treatment of polyQ diseases in cellular and animal models. We present studies testing non-allele-selective and allele-selective gene silencing strategies. The latter include targeting SNP variants associated with mutations or targeting the pathologically expanded CAG repeat directly. We compare gene silencing effectors of various types in a number of aspects, including their design, efficiency in cell culture experiments and pre-clinical testing. We discuss advantages, current limitations and perspectives of various ON-based strategies used to treat polyQ diseases.

In vivo therapeutic potential of Dicer-hunting siRNAs targeting infectious hepatitis C virus

The development of RNA interference (RNAi)-based therapy faces two major obstacles: selecting small interfering RNA (siRNA) sequences with strong activity, and identifying a carrier that allows efficient delivery to target organs. Additionally, conservative region at nucleotide level must be targeted for RNAi in applying to virus because hepatitis C virus (HCV) could escape from therapeutic pressure with genome mutations. In vitro preparation of Dicer-generated siRNAs targeting a conserved, highly ordered HCV 5′ untranslated region are capable of inducing strong RNAi activity. By dissecting the 5′-end of an RNAi-mediated cleavage site in the HCV genome, we identified potent siRNA sequences, which we designate as Dicer-hunting siRNAs (dh-siRNAs). Furthermore, formulation of the dh-siRNAs in an optimized multifunctional envelope-type nano device inhibited ongoing infectious HCV replication in human hepatocytes in vivo. Our efforts using both identification of optimal siRNA sequences and delivery to human hepatocytes suggest therapeutic potential of siRNA for a virus.

Effects of the sequence characteristics of miRNAs on multi-viral resistance mediated by single amiRNAs in transgenic tobacco

Artificial microRNA (amiRNA) has become the preferred viral defence that can be induced in plants. In this study, nine amiRNA target sites were selected that were based on the sequence characteristics of natural miRNAs in the cylindrical inclusion protein (CI), nuclear inclusion a protein (NIa), nuclear inclusion b protein (NIb), and coat protein (CP) genes of Potato virus Y (PVY(N)). These amiRNAs that exhibited high similarities to the sequences of PVY(N) and TEV-SD1 were considered. To study the effectiveness of gene silencing in amiRNA-mediated viral resistance, we constructed nine amiRNA plant expression vectors by replacing the functional sequences of miRNA319a precursors with our selected amiRNA sequences. These constructs were subsequently introduced to tobacco plants. A Northern blot assay verified that the nine amiRNA plant expression vectors could successfully express amiRNAs in plants. The analysis of viral resistance demonstrated that these transgenic tobacco plants could effectively inhibit PVY(N) and TEV-SD1 viral infections. The amiRNA that targeted the NIb and CP genes displayed a higher silencing efficiency than did the amiRNAs targeted CI and NIa genes. Northern blot analysis demonstrated that silencing was induced by the original amiRNAs and could be bilaterally extended by the siRNA pathway. That is, the amiRNA and the secondary siRNA mediated the degradation of viral RNA together. Genetic analysis demonstrated that the trait for viral resistance in transgenic plants can be consistently inherited via a single copy of the transgenic sequence. Considering the correlation between the sequence characteristics and the activity of amiRNA, we concluded that a few mismatched bases between the amiRNA and the target sequence could be allowed, particularly the mismatched bases in the 3' end of the amiRNA.

Bioinformatics of siRNA design

RNA interference mediated by small interfering RNAs is a powerful tool for investigation of gene functions and is increasingly used as a therapeutic agent. However, not all siRNAs are equally potent, and although simple rules for the selection of good siRNAs were proposed early on, siRNAs are still plagued with widely fluctuating efficiency. Recently, new design tools incorporating both the structural features of the targeted RNAs and the sequence features of the siRNAs substantially improved the efficacy of siRNAs. In this chapter we will present a review of sequence and structure-based algorithms behind them.

A universal TaqMan-based RT-PCR protocol for cost-efficient detection of small noncoding RNA

Several methods for the detection of RNA have been developed over time. For small RNA detection, a stem-loop reverse primer-based protocol relying on TaqMan RT-PCR has been described. This protocol requires an individual specific TaqMan probe for each target RNA and, hence, is highly cost-intensive for experiments with small sample sizes or large numbers of different samples. We describe a universal TaqMan-based probe protocol which can be used to detect any target sequence and demonstrate its applicability for the detection of endogenous as well as artificial eukaryotic and bacterial small RNAs. While the specific and the universal probe-based protocol showed the same sensitivity, the absolute sensitivity of detection was found to be more than 100-fold lower for both than previously reported. In subsequent experiments, we found previously unknown limitations intrinsic to the method affecting its feasibility in determination of mature template RISC incorporation as well as in multiplexing. Both protocols were equally specific in discriminating between correct and incorrect small RNA targets or between mature miRNA and its unprocessed RNA precursor, indicating the stem-loop RT-primer, but not the TaqMan probe, triggers target specificity. The presented universal TaqMan-based RT-PCR protocol represents a cost-efficient method for the detection of small RNAs.

Design of siRNA Therapeutics from the Molecular Scale

While protein-based therapeutics is well-established in the market, development of nucleic acid therapeutics has lagged. Short interfering RNAs (siRNAs) represent an exciting new direction for the pharmaceutical industry. These small, chemically synthesized RNAs can knock down the expression of target genes through the use of a native eukaryotic pathway called RNA interference (RNAi). Though siRNAs are routinely used in research studies of eukaryotic biological processes, transitioning the technology to the clinic has proven challenging. Early efforts to design an siRNA therapeutic have demonstrated the difficulties in generating a highly-active siRNA with good specificity and a delivery vehicle that can protect the siRNA as it is transported to a specific tissue. In this review article, we discuss design considerations for siRNA therapeutics, identifying criteria for choosing therapeutic targets, producing highly-active siRNA sequences, and designing an optimized delivery vehicle. Taken together, these design considerations provide logical guidelines for generating novel siRNA therapeutics.

Small interfering RNA (siRNA)-mediated knockdown of myostatin influences the expression of myogenic regulatory factors in caprine foetal myoblasts

Myostatin (MSTN) acts as a negative regulator of skeletal muscle development. Naturally occurring inactivating mutations in the coding region and knockout as well as knockdown of MSTN result in an increase in the muscle mass. However, the effect of MSTN knockdown on the expression of myogenic regulatory factors (MRFs) has not been studied in farm animals including goats. In the present study, using different synthetic siRNAs (n = 3), we demonstrated as high as 69 (p < 0.01) and 89% downregulation of MSTN mRNA and protein in the primary caprine foetal myoblast cells. Further, we also examined the effect of MSTN knockdown on the transcripts of MRFs including MyoD, Myf5 and MYOG. The expression of Myf5 remained unaffected (p = 0.60); however, MSTN downregulation caused a significant (p < 0.05) decrease and increase of MYOG and MyoD expression, respectively. Assessment of OAS1 expression confirmed the absence of any siRNA-elicited interferon response. Our results demonstrate that the downregulation of MSTN expression was accompanied by differential expressions of MRFs without any adverse interferon response. This study also suggests the importance of siRNA-mediated knockdown of MSTN as a potential alternative to increase muscle mass and meat production.

Self-duplexing CUG repeats selectively inhibit mutant huntingtin expression

Huntington’s disease (HD) is a neurodegenerative genetic disorder caused by the expansion of the CAG repeat in the translated sequence of the HTT gene. This expansion generates a mutant huntingtin protein that contains an abnormally elongated polyglutamine tract, which, together with mutant transcript, causes cellular dysfunction. Currently, there is no curative treatment available to patients suffering from HD; however, the selective inhibition of the mutant allele expression is a promising therapeutic option. In this study, we developed a new class of CAG repeat-targeting silencing reagents that consist of self-duplexing CUG repeats. Self-duplex formation was induced through one or several U-base substitutions. A number of self-duplexing guide-strand-only short interfering RNAs have been tested through transfection into cells derived from HD patients, showing distinct activity profiles. The best reagents were highly discriminatory between the normal and mutant HTT alleles (allele selectivity) and the HTT transcript and other transcripts containing shorter CAG repeats (gene selectivity). We also demonstrated that the self-duplexing CUG repeat short interfering RNAs use the RNA interference pathway to elicit silencing, and repeat-targeting reagents showed similar activity and selectivity when expressed from short hairpin RNA vectors to achieve more durable silencing effects.

Quantitative aspects of RNA silencing in metazoans

Small regulatory RNAs (microRNAs, siRNAs, and piRNAs) exhibit several unique features that clearly distinguish them from other known gene regulators. Their genomic organization, mode of action, and proposed biological functions raise specific questions. In this review, we focus on the quantitative aspect of small regulatory RNA biology. The original nature of these small RNAs accelerated the development of novel detection techniques and improved statistical methods and promoted new concepts that may unexpectedly generalize to other gene regulators. Quantification of natural phenomena is at the core of scientific practice, and the unique challenges raised by small regulatory RNAs have prompted many creative innovations by the scientific community.

Whole-genome thermodynamic analysis reduces siRNA off-target effects

Small interfering RNAs (siRNAs) are important tools for knocking down targeted genes, and have been widely applied to biological and biomedical research. To design siRNAs, two important aspects must be considered: the potency in knocking down target genes and the off-target effect on any nontarget genes. Although many studies have produced useful tools to design potent siRNAs, off-target prevention has mostly been delegated to sequence-level alignment tools such as BLAST. We hypothesize that whole-genome thermodynamic analysis can identify potential off-targets with higher precision and help us avoid siRNAs that may have strong off-target effects. To validate this hypothesis, two siRNA sets were designed to target three human genes IDH1, ITPR2 and TRIM28. They were selected from the output of two popular siRNA design tools, siDirect and siDesign. Both siRNA design tools have incorporated sequence-level screening to avoid off-targets, thus their output is believed to be optimal. However, one of the sets we tested has off-target genes predicted by Picky, a whole-genome thermodynamic analysis tool. Picky can identify off-target genes that may hybridize to a siRNA within a user-specified melting temperature range. Our experiments validated that some off-target genes predicted by Picky can indeed be inhibited by siRNAs. Similar experiments were performed using commercially available siRNAs and a few off-target genes were also found to be inhibited as predicted by Picky. In summary, we demonstrate that whole-genome thermodynamic analysis can identify off-target genes that are missed in sequence-level screening. Because Picky prediction is deterministic according to thermodynamics, if a siRNA candidate has no Picky predicted off-targets, it is unlikely to cause off-target effects. Therefore, we recommend including Picky as an additional screening step in siRNA design.

What parameters to consider and which software tools to use for target selection and molecular design of small interfering RNAs

The design of small gene silencing RNAs with a high probability of being efficient still has some elements of an art, especially when the lowest concentration of small molecules needs to be utilized. The design of highly target-specific small interfering RNAs or short hairpin RNAs is even a greater challenging task. Some logical schemes and software tools that can be used for simplifying both tasks are presented here. In addition, sequence motifs and sequence composition biases of small interfering RNAs that have to be avoided because of specificity concerns are also detailed.

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.

SiRNA sequence model: redesign algorithm based on available genome-wide libraries

The evolution of RNA interference (RNAi) and the development of technologies exploiting its biology have enabled scientists to rapidly examine the consequences of depleting a particular gene product in cells. Design tools have been developed based on experimental data to increase the knockdown efficiency of siRNAs. Not all siRNAs that are developed to a given target mRNA are equally effective. Currently available design algorithms take an accession, identify conserved regions among their transcript space, find accessible regions within the mRNA, design all possible siRNAs for these regions, filter them based on multi-scores thresholds, and then perform off-target filtration. These different criteria are used by commercial suppliers to produce siRNA genome-wide libraries for different organisms. In this article, we analyze existing siRNA design algorithms and evaluate weight of design parameters for libraries produced in the last decade. We proved that not all essential parameters are currently applied by siRNA vendors. Based on our evaluation results, we were able to suggest an siRNA sequence pattern. The findings in our study can be useful for commercial vendors improving the design of RNAi constructs, by addressing both the issue of potency and the issue of specificity.

Improved nucleic acid descriptors for siRNA efficacy prediction

Although considerable progress has been made recently in understanding how gene silencing is mediated by the RNAi pathway, the rational design of effective sequences is still a challenging task. In this article, we demonstrate that including three-dimensional descriptors improved the discrimination between active and inactive small interfering RNAs (siRNAs) in a statistical model. Five descriptor types were used: (i) nucleotide position along the siRNA sequence, (ii) nucleotide composition in terms of presence/absence of specific combinations of di- and trinucleotides, (iii) nucleotide interactions by means of a modified auto- and cross-covariance function, (iv) nucleotide thermodynamic stability derived by the nearest neighbor model representation and (v) nucleic acid structure flexibility. The duplex flexibility descriptors are derived from extended molecular dynamics simulations, which are able to describe the sequence-dependent elastic properties of RNA duplexes, even for non-standard oligonucleotides. The matrix of descriptors was analysed using three statistical packages in R (partial least squares, random forest, and support vector machine), and the most predictive model was implemented in a modeling tool we have made publicly available through SourceForge. Our implementation of new RNA descriptors coupled with appropriate statistical algorithms resulted in improved model performance for the selection of siRNA candidates when compared with publicly available siRNA prediction tools and previously published test sets. Additional validation studies based on in-house RNA interference projects confirmed the robustness of the scoring procedure in prospective studies.

Computational biology of RNA interactions

The biodiversity of the RNA world has been underestimated for decades. RNA molecules are key building blocks, sensors, and regulators of modern cells. The biological function of RNA molecules cannot be separated from their ability to bind to and interact with a wide space of chemical species, including small molecules, nucleic acids, and proteins. Computational chemists, physicists, and biologists have developed a rich tool set for modeling and predicting RNA interactions. These interactions are to some extent determined by the binding conformation of the RNA molecule. RNA binding conformations are approximated with often acceptable accuracy by sequence and secondary structure motifs. Secondary structure ensembles of a given RNA molecule can be efficiently computed in many relevant situations by employing a standard energy model for base pair interactions and dynamic programming techniques. The case of bi-molecular RNA-RNA interactions can be seen as an extension of this approach. However, unbiased transcriptome-wide scans for local RNA-RNA interactions are computationally challenging yet become efficient if the binding motif/mode is known and other external information can be used to confine the search space. Computational methods are less developed for proteins and small molecules, which bind to RNA with very high specificity. Binding descriptors of proteins are usually determined by in vitro high-throughput assays (e.g., microarrays or sequencing). Intriguingly, recent experimental advances, which are mostly based on light-induced cross-linking of binding partners, render in vivo binding patterns accessible yet require new computational methods for careful data interpretation. The grand challenge is to model the in vivo situation where a complex interplay of RNA binders competes for the same target RNA molecule. Evidently, bioinformaticians are just catching up with the impressive pace of these developments.

Optimized models for design of efficient miR30-based shRNAs

Small hairpin RNAs (shRNAs) became an important research tool in cell biology. Reliable design of these molecules is essential for the needs of large functional genomics projects. To optimize the design of efficient shRNAs, we performed comparative, thermodynamic, and correlation analyses of ~18,000 miR30-based shRNAs with known functional efficiencies, derived from the Sensor Assay project (Fellmann et al., 2011). We identified features of the shRNA guide strand that significantly correlate with the silencing efficiency and performed multiple regression analysis, using 4/5 of the data for training purposes and 1/5 for cross validation. A model that included the position-dependent nucleotide preferences was predictive in the cross-validation data subset (R = 0.39). However, a model, which in addition to the nucleotide preferences included thermodynamic shRNA features such as a thermodynamic duplex stability and position-dependent thermodynamic profile (dinucleotide free energy) was performing better (R = 0.53). Software "miR_Scan" was developed based upon the optimized models. Calculated mRNA target secondary structure stability showed correlation with shRNA silencing efficiency but failed to improve the model. Correlation analysis demonstrates that our algorithm for identification of efficient miR30-based shRNA molecules performs better than approaches that were developed for design of chemically synthesized siRNAs (R(max) = 0.36).

Myostatin gene silencing by RNA interference in chicken embryo fibroblast cells

Myostatin (MSTN), a member of transforming growth factor-β (TGF-β) superfamily, is a negative regulator of the skeletal muscle growth, and suppresses the proliferation and differentiation of myoblast cells. Dysfunction of MSTN gene either by natural mutation or genetic manipulation (knockout or knockdown) has been reported to interrupt its proper function and to increase the muscle mass in many mammalian species. RNA interference (RNAi) mediated by small interfering RNAs (siRNAs) or short hairpin RNAs (shRNAs) has become a powerful tool for gene knockdown studies. In the present study transient silencing of MSTN gene in chicken embryo fibroblast cells was evaluated using five different shRNA expression constructs. We report here up to 68% silencing of myostatin mRNA using these shRNA constructs in transiently transfected fibroblasts (p<0.05). This was, however, associated with induction of interferon responsive genes (OAS1, IFN-β) (3.7-64 folds; p<0.05). Further work on stable expression of antimyostatin shRNA with minimum interferon induction will be of immense value to increase the muscle mass in the transgenic animals.

Action and reaction: the biological response to siRNA and its delivery vehicles

RNA interference (RNAi)-based therapeutics have significant potential for the treatment of human disease. Safe and effective delivery of RNA to target tissues remains a major barrier to realizing its clinical potential. Several factors can affect the in vivo performance of short interfering RNA (siRNA) delivery formulations, including siRNA sequence, structure, chemical modification, and delivery formulation. This review provides an introduction to the principles underlying the pharmacokinetics and pharmacodynamics of systemically administered siRNA and its delivery formulations, including the factors that lead to its degradation, clearance, and tissue uptake, as well as its potential for immunogenicity, toxicity, and off-target effects within the body.

Improved siRNA/shRNA functionality by mismatched duplex

siRNA (small interfering RNA) and shRNA (small hairpin RNA) are powerful and commonly used tools in biomedical research. Currently, siRNAs are generally designed as two 21 nt strands of RNA that include a 19 nt completely complementary part and a 2 nt overhang. However, since the si/shRNAs use the endogenous miRNA machinery for gene silencing and the miRNAs are generally 22 nt in length and contain multiple internal mismatches, we tested if the functionality can be increased by designing the si/shRNAs to mimic a miRNA structure. We systematically investigated the effect of single or multiple mismatches introduced in the passenger strand at different positions on siRNA functionality. Mismatches at certain positions could significantly increase the functionality of siRNAs and also, in some cases decreased the unwanted passenger strand functionality. The same strategy could also be used to design shRNAs. Finally, we showed that both si and miRNA structured oligos (siRNA with or without mismatches in the passenger strand) can repress targets in all individual Ago containing cells, suggesting that the Ago proteins do not differentiate between si/miRNA-based structure for silencing activity.

MysiRNA-designer: a workflow for efficient siRNA design

The design of small interfering RNA (siRNA) is a multi factorial problem that has gained the attention of many researchers in the area of therapeutic and functional genomics. MysiRNA score was previously introduced that improves the correlation of siRNA activity prediction considering state of the art algorithms. In this paper, a new program, MysiRNA-Designer, is described which integrates several factors in an automated work-flow considering mRNA transcripts variations, siRNA and mRNA target accessibility, and both near-perfect and partial off-target matches. It also features the MysiRNA score, a highly ranked correlated siRNA efficacy prediction score for ranking the designed siRNAs, in addition to top scoring models Biopredsi, DISR, Thermocomposition21 and i-Score, and integrates them in a unique siRNA score-filtration technique. This multi-score filtration layer filters siRNA that passes the 90% thresholds calculated from experimental dataset features. MysiRNA-Designer takes an accession, finds conserved regions among its transcript space, finds accessible regions within the mRNA, designs all possible siRNAs for these regions, filters them based on multi-scores thresholds, and then performs SNP and off-target filtration. These strict selection criteria were tested against human genes in which at least one active siRNA was designed from 95.7% of total genes. In addition, when tested against an experimental dataset, MysiRNA-Designer was found capable of rejecting 98% of the false positive siRNAs, showing superiority over three state of the art siRNA design programs. MysiRNA is a freely accessible (Microsoft Windows based) desktop application that can be used to design siRNA with a high accuracy and specificity. We believe that MysiRNA-Designer has the potential to play an important role in this area.