Designing optimal siRNA based on target site accessibility

Computational analysis of sense-antisense chimeric transcripts reveals their potential regulatory features and the landscape of expression in human cells

Many human genes are transcribed from both strands and produce sense-antisense gene pairs. Sense-antisense (SAS) chimeric transcripts are produced upon the coalescing of exons/introns from both sense and antisense transcripts of the same gene. SAS chimera was first reported in prostate cancer cells. Subsequently, numerous SAS chimeras have been reported in the ChiTaRS-2.1 database. However, the landscape of their expression in human cells and functional aspects are still unknown. We found that longer palindromic sequences are a unique feature of SAS chimeras. Structural analysis indicates that a long hairpin-like structure formed by many consecutive Watson-Crick base pairs appears because of these long palindromic sequences, which possibly play a similar role as double-stranded RNA (dsRNA), interfering with gene expression. RNA-RNA interaction analysis suggested that SAS chimeras could significantly interact with their parental mRNAs, indicating their potential regulatory features. Here, 267 SAS chimeras were mapped in RNA-seq data from 16 healthy human tissues, revealing their expression in normal cells. Evolutionary analysis suggested the positive selection favoring sense-antisense fusions that significantly impacted the evolution of their function and structure. Overall, our study provides detailed insight into the expression landscape of SAS chimeras in human cells and identifies potential regulatory features.

The ViennaRNA web services

The ViennaRNA package is a widely used collection of programs for thermodynamic RNA secondary structure prediction. Over the years, many additional tools have been developed building on the core programs of the package to also address issues related to noncoding RNA detection, RNA folding kinetics, or efficient sequence design considering RNA-RNA hybridizations. The ViennaRNA web services provide easy and user-friendly web access to these tools. This chapter describes how to use this online platform to perform tasks such as prediction of minimum free energy structures, prediction of RNA-RNA hybrids, or noncoding RNA detection. The ViennaRNA web services can be used free of charge and can be accessed via http://rna.tbi.univie.ac.at.

Modeling the binding specificity of the RNA-binding protein GLD-1 suggests a function of coding region-located sites in translational repression

To understand the function of the hundreds of RNA-binding proteins (RBPs) that are encoded in animal genomes it is important to identify their target RNAs. Although it is generally accepted that the binding specificity of an RBP is well described in terms of the nucleotide sequence of its binding sites, other factors such as the structural accessibility of binding sites or their clustering, to enable binding of RBP multimers, are also believed to play a role. Here we focus on GLD-1, a translational regulator of Caenorhabditis elegans, whose binding specificity and targets have been studied with a variety of methods such as CLIP (cross-linking and immunoprecipitation), RIP-Chip (microarray measurement of RNAs associated with an immunoprecipitated protein), profiling of polysome-associated mRNAs and biophysical determination of binding affinities of GLD-1 for short nucleotide sequences. We show that a simple biophysical model explains the binding of GLD-1 to mRNA targets to a large extent, and that taking into account the accessibility of putative target sites significantly improves the prediction of GLD-1 binding, particularly due to a more accurate prediction of binding in transcript coding regions. Relating GLD-1 binding to translational repression and stabilization of its target transcripts we find that binding sites along the entire transcripts contribute to functional responses, and that CDS-located sites contribute most to translational repression. Finally, biophysical measurements of GLD-1 affinity for a small number of oligonucleotides appear to allow an accurate reconstruction of the sequence specificity of the protein. This approach can be applied to uncover the specificity and function of other RBPs.

Bifunctional short hairpin RNA (bi-shRNA): design and pathway to clinical application

The discovery of RNA interference (RNAi) engendered great excitement and raised expectations regarding its potential applications in biomedical research and clinical usage. Over the ensuing years, expanded understanding of RNAi and preliminary results from early clinical trials tempered enthusiasm with realistic appraisal resulting in cautious optimism and a better understanding of necessary research and clinical directions. As a result, data from more recent trials are beginning to show encouraging positive clinical outcomes. The capability of delivering a pharmacologically effective dose to the target site while avoiding adverse host reactions still remains a challenge although the delivery technology continues to improve. We have developed a novel vector-driven bifunctional short hairpin RNA (bi-shRNA) technology that harnesses both cleavage-dependent and cleavage-independent RISC loading pathways to enhance knockdown potency. Consequent advantages provided by the bi-shRNA include a lower effective systemic dose than comparator siRNA/shRNA to minimize the potential for off-target side effects, due to its ability to induce both a rapid (inhibition of protein translation) and delayed (mRNA cleavage and degradation) targeting effect depending on protein and mRNA kinetics, and a longer duration of effectiveness for clinical applications. Here, we provide an overview of key molecular methods for the design, construction, quality control, and application of bi-shRNA that we believe will be useful for others interested in utilizing this technology.

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.

Progress toward in vivo use of siRNAs-II

RNA interference (RNAi) has been extensively employed for in vivo research since its use was first demonstrated in mammalian cells 10 years ago. Design rules have improved, and it is now routinely possible to obtain reagents that suppress expression of any gene desired. At the same time, increased understanding of the molecular basis of unwanted side effects has led to the development of chemical modification strategies that mitigate these concerns. Delivery remains the single greatest hurdle to widespread adoption of in vivo RNAi methods. However, exciting advances have been made and new delivery systems under development may help to overcome these barriers. This review discusses advances in RNAi biochemistry and biology that impact in vivo use and provides an overview of select publications that demonstrate interesting applications of these principles. Emphasis is placed on work with synthetic, small interfering RNAs (siRNAs) published since the first installment of this review which appeared in 2006.

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.

A detailed investigation of accessibilities around target sites of siRNAs and miRNAs

MOTIVATION

The importance of RNA sequence analysis has been increasing since the discovery of various types of non-coding RNAs transcribed in animal cells. Conventional RNA sequence analyses have mainly focused on structured regions, which are stabilized by the stacking energies acting on adjacent base pairs. On the other hand, recent findings regarding the mechanisms of small interfering RNAs (siRNAs) and transcription regulation by microRNAs (miRNAs) indicate the importance of analyzing accessible regions where no base pairs exist. So far, relatively few studies have investigated the nature of such regions.

RESULTS

We have conducted a detailed investigation of accessibilities around the target sites of siRNAs and miRNAs. We have exhaustively calculated the correlations between the accessibilities around the target sites and the repression levels of the corresponding mRNAs. We have computed the accessibilities with an originally developed software package, called 'Raccess', which computes the accessibility of all the segments of a fixed length for a given RNA sequence when the maximal distance between base pairs is limited to a fixed size W. We show that the computed accessibilities are relatively insensitive to the choice of the maximal span W. We have found that the efficacy of siRNAs depends strongly on the accessibility of the very 3'-end of their binding sites, which might reflect a target site recognition mechanism in the RNA-induced silencing complex. We also show that the efficacy of miRNAs has a similar dependence on the accessibilities, but some miRNAs also show positive correlations between the efficacy and the accessibilities in broad regions downstream of their putative binding sites, which might imply that the downstream regions of the target sites are bound by other proteins that allow the miRNAs to implement their functions. We have also investigated the off-target effects of an siRNA as a potential RNAi therapeutic. We show that the off-target effects of the siRNA have similar correlations to the miRNA repression, indicating that they are caused by the same mechanism.

AVAILABILITY

The C++ source code of the Raccess software is available at http://www.ncrna.org/software/Raccess/ The microarray data on the measurements of the siRNA off-target effects are also available at the same site.

CONTACT

kiryu-h@k.u-tokyo.ac.jp