One Decade of Development and Evolution of MicroRNA Target Prediction Algorithms

Nearly two decades have passed since the publication of the first study reporting the discovery of microRNAs (miRNAs). The key role of miRNAs in post-transcriptional gene regulation led to the performance of an increasing number of studies focusing on origins, mechanisms of action and functionality of miRNAs. In order to associate each miRNA to a specific functionality it is essential to unveil the rules that govern miRNA action. Despite the fact that there has been significant improvement exposing structural characteristics of the miRNA-mRNA interaction, the entire physical mechanism is not yet fully understood. In this respect, the development of computational algorithms for miRNA target prediction becomes increasingly important. This manuscript summarizes the research done on miRNA target prediction. It describes the experimental data currently available and used in the field and presents three lines of computational approaches for target prediction. Finally, the authors put forward a number of considerations regarding current challenges and future direction

OligoWalk: an online siRNA design tool utilizing hybridization thermodynamics

Given an mRNA sequence as input, the OligoWalk web server generates a list of small interfering RNA (siRNA) candidate sequences, ranked by the probability of being efficient siRNA (silencing efficacy greater than 70%). To accomplish this, the server predicts the free energy changes of the hybridization of an siRNA to a target mRNA, considering both siRNA and mRNA self-structure. The free energy changes of the structures are rigorously calculated using a partition function calculation. By changing advanced options, the free energy changes can also be calculated using less rigorous lowest free energy structure or suboptimal structure prediction methods for the purpose of comparison. Considering the predicted free energy changes and local siRNA sequence features, the server selects efficient siRNA with high accuracy using a support vector machine. On average, the fraction of efficient siRNAs selected by the server that will be efficient at silencing is 78.6%. The OligoWalk web server is freely accessible through internet at http://rna.urmc.rochester.edu/servers/oligowalk

Hepatocellular Nuclear Factor 4 alpha (HNF-4 alpha) activation by saRNA rescues dyslipidemia and promotes favorable metabolic profile in a high fat diet (HFD) fed rat model.

67th Annual Meeting of the American-Association-for-the-Study-of-Liver-Diseases (AASLD), Boston, MA, NOV 11-15, 2016International audienceno abstrac

Inhibition of mutant huntingtin expression by RNA duplex targeting expanded CAG repeats

The specific silencing of the gene of interest is the major objective of RNA interference technology; therefore, unique sequences but not abundant sequence repeats are targeted by silencing reagents. Here, we describe the targeting of expanded CAG repeats that occur in transcripts derived from the mutant allele of the gene implicated in Huntington’s disease (HD) in the presence of the normal allele and other human mRNAs containing CAG and CUG repeat tracts. We show that a high degree of silencing selectivity may be achieved between the repeated sequences. We demonstrate preferential suppression of the mutant huntingtin allele and concomitant activation of the normal huntingtin allele in cell lines derived from HD patients that were transfected with short RNA duplexes composed of CAG and CUG repeats containing mutations at specific positions. These effects may lead to promising therapeutic modalities for HD, a condition for which no therapy presently exists

siRecords: a database of mammalian RNAi experiments and efficacies

RNAi-based gene-silencing techniques offer a fast and cost-effective way of knocking down genes’ functions in an easily regulated manner. Exciting progress has been made in recent years in the application of these techniques in basic biomedical research and therapeutic development. However, it remains a difficult task to design effective siRNA experiments with high efficacy and specificity. We present siRecords, an extensive database of mammalian RNAi experiments with consistent efficacy ratings. This database serves two purposes. First, it provides a large and diverse dataset of siRNA experiments. This dataset faithfully represents the general, diverse RNAi experimental practice, and allows more reliable siRNA design tools to be developed with the overfitting problem well curbed. Second, the database helps experimental RNAi researchers directly by providing them with the efficacy and other information about the siRNAs experiments designed and conducted previously against the genes of their interest. The current release of siRecords contains the records of 17 192 RNAi experiments targeting 5086 genes

An accurate and interpretable model for siRNA efficacy prediction

BACKGROUND: The use of exogenous small interfering RNAs (siRNAs) for gene silencing has quickly become a widespread molecular tool providing a powerful means for gene functional study and new drug target identification. Although considerable progress has been made recently in understanding how the RNAi pathway mediates gene silencing, the design of potent siRNAs remains challenging. RESULTS: We propose a simple linear model combining basic features of siRNA sequences for siRNA efficacy prediction. Trained and tested on a large dataset of siRNA sequences made recently available, it performs as well as more complex state-of-the-art models in terms of potency prediction accuracy, with the advantage of being directly interpretable. The analysis of this linear model allows us to detect and quantify the effect of nucleotide preferences at particular positions, including previously known and new observations. We also detect and quantify a strong propensity of potent siRNAs to contain short asymmetric motifs in their sequence, and show that, surprisingly, these motifs alone contain at least as much relevant information for potency prediction as the nucleotide preferences for particular positions. CONCLUSION: The model proposed for prediction of siRNA potency is as accurate as a state-of-the-art nonlinear model and is easily interpretable in terms of biological features. It is freely available on the web a

Construction of an Artificial MicroRNA Expression Vector for Simultaneous Inhibition of Multiple Genes in Mammalian Cells

Recently, artificial microRNA (amiRNA) has become a promising RNA interference (RNAi) technology. Here, we describe a flexible and reliable method for constructing both single- and multi-amiRNA expression vectors. Two universal primers, together with two specific primers carrying the encoding sequence of amiRNA were designed and utilized to synthesize the functional amiRNA cassette through a one-step PCR. With appropriate restriction sites, the synthesized amiRNA cassettes can be cloned into any site of different destination vectors. Using the method, we constructed both single- and multi-amiRNA expression vectors to target three reporter genes, which code firefly luciferase (Fluc), enhanced green fluorescent protein (EGFP) and β-galactosidase (LacZ), respectively. The expressions of three genes were all specifically inhibited by either the corresponding single- or the multi-amiRNA expression vector in 293T cells. And the RNAi efficiency of each amiRNA produced by both single- and multi-amiRNA expression vectors was comparable

Selection of hyperfunctional siRNAs with improved potency and specificity

One critical step in RNA interference (RNAi) experiments is to design small interfering RNAs (siRNAs) that can greatly reduce the expression of the target transcripts, but not of other unintended targets. Although various statistical and computational approaches have been attempted, this remains a challenge facing RNAi researchers. Here, we present a new experimentally validated method for siRNA design. By analyzing public siRNA data and focusing on hyperfunctional siRNAs, we identified a set of sequence features as potency selection criteria to build an siRNA design algorithm with support vector machines. Additional bioinformatics filters were also included in the algorithm to increase RNAi specificity by reducing potential sequence cross-hybridization or microRNA-like effects. Independent validation experiments were performed, which indicated that the newly designed siRNAs have significantly improved performance, and worked effectively even at low concentrations. Furthermore, our cell-based studies demonstrated that the siRNA off-target effects were significantly reduced when the siRNAs were delivered into cells at the 3 nM concentration compared to 30 nM. Thus, the capability of our new design program to select highly potent siRNAs also renders increased RNAi specificity because these siRNAs can be used at a much lower concentration. The siRNA design web server is available at http://www5.appliedbiosystems.com/tools/siDesign/

An efficient algorithm for systematic analysis of nucleotide strings suitable for siRNA design

<p>Abstract</p> <p>Background</p> <p>The "off-target" silencing effect hinders the development of siRNA-based therapeutic and research applications. Existing solutions for finding possible locations of siRNA seats within a large database of genes are either too slow, miss a portion of the targets, or are simply not designed to handle a very large number of queries. We propose a new approach that reduces the computational time as compared to existing techniques.</p> <p>Findings</p> <p>The proposed method employs tree-based storage in a form of a modified truncated suffix tree to sort all possible short string substrings within given set of strings (i.e. transcriptome). Using the new algorithm, we pre-computed a list of the best siRNA locations within each human gene ("siRNA seats"). siRNAs designed to reside within siRNA seats are less likely to hybridize off-target. These siRNA seats could be used as an input for the traditional "set-of-rules" type of siRNA designing software. The list of siRNA seats is available through a publicly available database located at <url>http://web.cos.gmu.edu/~gmanyam/siRNA_db/search.php</url></p> <p>Conclusions</p> <p>In attempt to perform top-down prediction of the human siRNA with minimized off-target hybridization, we developed an efficient algorithm that employs suffix tree based storage of the substrings. Applications of this approach are not limited to optimal siRNA design, but can also be useful for other tasks involving selection of the characteristic strings specific to individual genes. These strings could then be used as siRNA seats, as specific probes for gene expression studies by oligonucleotide-based microarrays, for the design of molecular beacon probes for Real-Time PCR and, generally, any type of PCR primers.</p