isomiR-SEA: an RNA-Seq analysis tool for miRNAs/isomiRs expression level profiling and miRNA-mRNA interaction sites evaluation

Abstract

BackgroundMassive parallel sequencing of transcriptomes, revealed the presence of many miRNAs and miRNAs variants named isomiRs with a potential role in several cellular processes through their interaction with a target mRNA. Many methods and tools have been recently devised to detect and quantify miRNAs from sequencing data. However, all of them are implemented on top of general purpose alignment methods, thus providing poorly accurate results and no information concerning isomiRs and conserved miRNA-mRNA interaction sites.ResultsTo overcome these limitations we present a novel algorithm named isomiR-SEA, that is able to provide users with very accurate miRNAs expression levels and both isomiRs and miRNA-mRNA interaction sites precise classifications. Tags are mapped on the known miRNAs sequences thanks to a specialized alignment algorithm developed on top of biological evidence concerning miRNAs structure. Specifically, isomiR-SEA checks for miRNA seed presence in the input tags and evaluates, during all the alignment phases, the positions of the encountered mismatches, thus allowing to distinguish among the different isomiRs and conserved miRNA-mRNA interaction sites.ConclusionsisomiR-SEA performances have been assessed on two public RNA-Seq datasets proving that the implemented algorithm is able to account for more reliable and accurate miRNAs expression levels with respect to those provided by two compared state of the art tools. Moreover, differently from the few methods currently available to perform isomiRs detection, the proposed algorithm implements the evaluation of isomiRs and conserved miRNA-mRNA interaction sites already in the first alignment phases, thus avoiding any additional filtering stages potentially responsible for the loss of useful information.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-016-0958-0) contains supplementary material, which is available to authorized users.

Unification of miRNA and isomiR research: the mirGFF3 format and the mirtop API

“…isomiR-SEA [37] implements a miRNA-specific alignment procedure for comparing each read of the sample to all the miRNA sequences from miRBase and MirGeneDB, collecting uniquely and multi-mapped sequences. The tool annotates the positions of the variations (mismatches and indels) enabling fine categorization of each aligned read that can be classified as canonical miRNA or one of the isomiRs described in Table 2.…”

“…Any isomiR sequence can be mapped to a UID and any UID can be converted back to the isomiR sequence it represents ( Figure 1B). Another characteristic of the mirGFF3 format which is specifically devised to maximize clarity, communication and standardization across the community is the 'Variant' attribute, which follows the isomiR description and miRNA-mRNA interaction sites adapted from isomiR-SEA format [37]. Briefly, modifications are based on comparing the sequence of a given isomiR to the reference miRNA in the chosen database.…”

Literature review of baseline information to support the risk assessment of RNAi‐based GM plants

“…http://cupidtool.sourceforge.net (Chiu et al, 2015) DIANALncBas e database of experimentally supported and in silico predicted miRNA Recognition Elements (MREs) on lncRNAs yes http://www.microrna.gr/LncBase (Paraskevop oulou et al, 2016) DIANAmicroT-ANN DIANA-microT-ANN combines multiple novel target site features through an artificial neural network (ANN) ECCA identification of shared miRNAs of different species NA ensemb le ensemble based on Borda count election on Pearson+IDA+Lasso methods (Le et al, 2015a) GenMiR ++ Generative model for miRNA regulation gespeR statistical model for deconvoluting off-target-confounded RNA interference screens http://icb.helmholtzmuenchen.de/mirlastic (Schmich et al, 2015) Hong20 16 NA IDA Pearson+IDA+Lasso (Le et al, 2015a) ImiRP target distruption by mutation https://github.com/imirp (Ryan et al, 2016) ImiRP https://github.com/imirp (Ryan et al, 2016) imiRTP (Ding et al, 2012b) isomiR-SEA miRNA expression levels http://eda.polito.it/isomir-sea (Urgese et al, 2016) isomiR-SEA http://eda.polito.it/isomir-sea/ (Urgese et al, 2016) Katanfo roush20 15 alignment information and gene expression profiles (Katanforous h and Mahdavi, 2015) Korfiati2 015 three distinct steps: a filtering step, a novel hybrid classification methodology and an advanced methodology to extract interpretable fuzzy rules from the final prediction model. The classification methodology (Korfiati et al, 2015) Predicted microRNA targets & target downregulation scores.…”

OPTIMIR, a novel algorithm for integrating available genome-wide genotype data into miRNA sequence alignment analysis

“…In this work, we propose a novel algorithm, OPTIMIR, for aligning miRNA sequences obtained from next generation sequencing and we applied it to plasma samples of 391 individuals from the MARTHA study. Borrowing some ideas from other alignment pipelines such as the addition of new sequences to the reference library corresponding to allelic versions of polymiRs (Baras et al, 2014;Russell et al, 2018) and a scoring strategy for handling cross-mapping reads (Urgese et al, 2016) or for discarding unlikely isomiRs (Bofill-De Ros et al, 2018), OPTIMIR has two features that make it unique. First, OPTIMIR is based on a scoring strategy that incorporate biological knowledge on miRNA editing to identify the most likely alignment in presence of cross-mapping reads.…”