miRador: a fast and precise tool for the prediction of plant miRNAs

Abstract

Plant microRNAs (miRNAs) are short, non-coding RNA molecules that restrict gene expression via post-transcriptional regulation and function in several essential pathways including development, growth, and stress responses. Accurately identifying miRNAs in populations of small RNA (sRNA) sequencing libraries is a computationally intensive process which has resulted in the misidentification of inaccurately annotated miRNA sequences. In recent years, criteria for miRNA annotation have been refined to reduce these misannotations. Here, we describe miRador, a novel miRNA identification tool that utilizes the most up-to-date, community-established criteria for accurate identification of miRNAs in plants. We combine target prediction and Parallel Analysis of RNA Ends (PARE) data to assess the precision of the miRNAs identified by miRador. We compare miRador to other commonly used miRNA prediction tools and we find that miRador is at least as precise as other prediction tools while being significantly faster than other tools.

The floral development of the allotetraploid Coffea arabica L. correlates with a small RNA dynamic reprogramming

“…The pipeline encompasses stages such as filtering for GC content between 20% and 65%, minimum free energy below −20 kcal/mol, and selecting mature sequences with over 85% identity to plant mature miRNA registered in the miRbase Release 22.1 (Kozomara et al., 2019). Subsequently, we augmented this collection of miRNAs with novel and conserved miRNAs predicted using miRador (Hammond et al., 2021) with the most up‐to‐date criteria to accurately identify plant miRNAs (Axtell & Meyers, 2018). Finally, we developed custom Python scripts to merge (collapse) miRNAs with identical (redundant) mature sequences predicted by both methodologies.…”

The RNAome landscape of tomato during arbuscular mycorrhizal symbiosis reveals an evolving RNA layer symbiotic regulatory network

“…miRNAs were identified using miRador ( https://github.com/rkweku/miRador ) with the options ‘gap = 6, match = 3, mismatch = -4, threshold = 40, maxRepLen = 300, organism = Sly’ ( Hammond et al., 2021 ). Candidate miRNAs were annotated as known or novel miRNAs by referencing the latest miRBase v22.1 ( Kozomara et al., 2019 ).…”

Genomics of small RNAs in the Brassicales

“…We used three tools: ShortStack, miR-PREFeR and miRador, to identify previously annotated and novel miRNAs in our samples (Johnson et al 2016;Lei and Sun 2014;Hammond et al 2021). Of the three, miRador proved to be most conservative, predicting fewer miRNAs, but also required no post-annotation filtering, as it implements the criteria for plant miRNA annotation set by .…”

“…We used three (3) different software packages to obtain a robust prediction of miRNAs across our Brassicales model genomes: ShortStack v3.8.5, miR-PREFeR v0.24 and miRador (Johnson et al 2016;Lei and Sun 2014;Hammond et al 2021).…”

“…We used ShortStack v3.8.5 to identify PHAS loci (Johnson et al 2016;Lei and Sun 2014;Hammond et al 2021). We ran ShortStack using the same parameters used for miRNA prediction, extending the sRNA size limit to a maximum of 24 nt.…”