A high-efficiency gene silencing in plants using two-hit asymmetrical artificial MicroRNAs.

MicroRNAs (miRNAs) are small non-coding RNA molecules that play a crucial role in gene regulation. They are produced through an enzyme-guided process called dicing and have an asymmetrical structure with two nucleotide overhangs at the 3' ends. Artificial microRNAs (amiRNAs or amiRs) are designed to mimic the structure of miRNAs and can be used to silence specific genes of interest. Traditionally, amiRNAs are designed based on an endogenous miRNA precursor with certain mismatches at specific positions to increase their efficiency. In this study, the authors modified the highly expressed miR168a in Arabidopsis thaliana by replacing the single miR168 stem-loop/duplex with tandem asymmetrical amiRNA duplexes that follow the statistical rules of miRNA secondary structures. These tandem amiRNA duplexes, called "two-hit" amiRNAs, were shown to have a higher efficiency in silencing GFP and endogenous PDS reporter genes compared to traditional "one-hit" amiRNAs. The authors also demonstrated the effectiveness of "two-hit" amiRNAs in silencing genes involved in miRNA, tasiRNA, and hormone signalling pathways, individually or in families. Importantly, "two-hit" amiRNAs were also able to over-express endogenous miRNAs for their functions. The authors compare "two-hit" amiRNA technology with CRISPR/Cas9 and provide a web-based amiRNA designer for easy design and wide application in plants and even animals.

Design, Construction, and Validation of Artificial MicroRNA Vectors Using Agrobacterium-Mediated Transient Expression System.

Artificial microRNA (amiRNA) technology utilizes microRNA (miRNA) biogenesis pathway to produce artificially selected small RNAs using miRNA gene backbone. It provides a feasible strategy for inducing loss of gene function, and has been applied in functional genomics study, improvement of crop quality and plant virus disease resistance. A big challenge in amiRNA applications is the unpredictability of silencing efficacy of the designed amiRNAs and not all constructed amiRNA candidates would be expressed effectively in plant cells. We and others found that high efficiency and specificity in RNA silencing can be achieved by designing amiRNAs with perfect or almost perfect sequence complementarity to their targets. In addition, we recently demonstrated that Agrobacterium-mediated transient expression system can be used to validate amiRNA constructs, which provides a simple, rapid and effective method to select highly expressible amiRNA candidates for stable genetic transformation. Here, we describe the methods for design of amiRNA candidates with perfect or almost perfect base-pairing to the target gene or gene groups, incorporation of amiRNA candidates in miR168a gene backbone by one step inverse PCR amplification, construction of plant amiRNA expression vectors, and assay of transient expression of amiRNAs in Nicotiana benthamiana through agro-infiltration, small RNA extraction, and amiRNA Northern blot.

A parallel strategy for predicting the secondary structure of polycistronic microRNAs.

The biogenesis of a functional microRNA is largely dependent on the secondary structure of the microRNA precursor (pre-miRNA). Recently, it has been shown that microRNAs are present in the genome as the form of polycistronic transcriptional units in plants and animals. It will be important to design efficient computational methods to predict such structures for microRNA discovery and its applications in gene silencing. In this paper, we propose a parallel algorithm based on the master-slave architecture to predict the secondary structure from an input sequence. We conducted some experiments to verify the effectiveness of our parallel algorithm. The experimental results show that our algorithm is able to produce the optimal secondary structure of polycistronic microRNAs.

MicroRNAfold: pre-microRNA secondary structure prediction based on modified NCM model with thermodynamics-based scoring strategy.

An accurate prediction of the pre-microRNA secondary structure is important in miRNA informatics. Based on a recently proposed model, nucleotide cyclic motifs (NCM), to predict RNA secondary structure, we propose and implement a Modified NCM (MNCM) model with a physics-based scoring strategy to tackle the problem of pre-microRNA folding. Our microRNAfold is implemented using a global optimal algorithm based on the bottom-up local optimal solutions. Our experimental results show that microRNAfold outperforms the current leading prediction tools in terms of True Negative rate, False Negative rate, Specificity, and Matthews coefficient ratio.