Computational prediction of the localization of microRNAs within their pre-miRNA

Abstract

MicroRNAs (miRNAs) are short RNA species derived from hairpin-forming miRNA precursors (pre-miRNA) and acting as key posttranscriptional regulators. Most computational tools labeled as miRNA predictors are in fact pre-miRNA predictors and provide no information about the putative miRNA location within the pre-miRNA. Sequence and structural features that determine the location of the miRNA, and the extent to which these properties vary from species to species, are poorly understood. We have developed miRdup, a computational predictor for the identification of the most likely miRNA location within a given pre-miRNA or the validation of a candidate miRNA. MiRdup is based on a random forest classifier trained with experimentally validated miRNAs from miRbase, with features that characterize the miRNA–miRNA* duplex. Because we observed that miRNAs have sequence and structural properties that differ between species, mostly in terms of duplex stability, we trained various clade-specific miRdup models and obtained increased accuracy. MiRdup self-trains on the most recent version of miRbase and is easy to use. Combined with existing pre-miRNA predictors, it will be valuable for both de novo mapping of miRNAs and filtering of large sets of candidate miRNAs obtained from transcriptome sequencing projects. MiRdup is open source under the GPLv3 and available at http://www.cs.mcgill.ca/∼blanchem/mirdup/.

Bioinformatic identification and expression analysis of new microRNAs from wheat (Triticum aestivum L.)

“…The predicted structures were also validated on Wheat MicroRNA Portal (http://wheat.bioinfo. uqam.ca) (Agharbaoui et al 2015;Remita et al 2016) using mirDup (v1.2) (Leclercq et al 2013) with two datasets: all miRBase (B) r20 and Wheat (W) r20.…”

Long noncoding RNA ZFAS1 promotes tumorigenesis and metastasis in nasopharyngeal carcinoma by sponging miR‐892b to up‐regulate LPAR1 expression

“…19 Although the latest encouraging research has reported that up-regulated ZFAS1 acts as a promoter for the occurrence of NPC through the activation of the Wnt/β-catenin pathway, the role of ZFAS1 in NPC requires further investigation. [21][22][23] Multiple miRNAs including miR-1, miR-let-7 and miR-138 participate in the tumorigenesis, progression and metastasis of NPC through biological functions, such as inducing apoptosis and inhibiting proliferation. [21][22][23] Multiple miRNAs including miR-1, miR-let-7 and miR-138 participate in the tumorigenesis, progression and metastasis of NPC through biological functions, such as inducing apoptosis and inhibiting proliferation.…”

“…20 MiRNAs, a group of short noncoding RNAs, bind to target mRNAs by incomplete complementarity and then inhibit the translation or reduce the stability of target mRNAs. [21][22][23] Multiple miRNAs including miR-1, miR-let-7 and miR-138 participate in the tumorigenesis, progression and metastasis of NPC through biological functions, such as inducing apoptosis and inhibiting proliferation. Recently, miR-892b has been found to be associated with bladder cancer 24 and breast cancer.…”

Emerging techniques to decipher microRNAs (miRNAs) and their regulatory role in conferring abiotic stress tolerance of plants

“…The source codes of miRLocator are downloadable from the website (https:// github.com/cma2015/miRLocator). Leclercq et al (2013) reported the use of miRduplex (miRdup) (http://www.cs.mcgill.ca/*blanchem/mirdup/) as an efficient tool for the computational prediction of locating miRNAs within their pre-miRNAs. Ten-fold cross-validation of 5854 experimentally validated miRNAs across 19 plant species highlighted the fact that miRLocator is a better option in predicting mature miRNAs within plant pre-miRNAs than miRdup (Cui et al 2015a).…”