PmiRDiscVali: an integrated pipeline for plant microRNA discovery and validation

MicroRNAs (miRNAs) constitute a well-known small RNA (sRNA) species with important regulatory roles. To date, several bioinformatics tools have been developed for large-scale prediction of miRNAs based on high-throughput sequencing data. However, some of these tools become invalid without reference...

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Bibliographic Details
Published in:BMC genomics 2019-02, Vol.20 (1), p.133-133, Article 133
Main Authors: Yu, Dongliang, Wan, Ying, Ito, Hidetaka, Ma, Xiaoxia, Xie, Tian, Wang, Tingzhang, Shao, Chaogang, Meng, Yijun
Format: Article
Language:English
Subjects:
Animals
Annotations
Bioinformatics
Candidates
Computational biology
Conservation
Degradation
Degradome sequencing (degradome-seq)
Gene expression
Gene sequencing
Genomes
Genomics
Graphic outputs
Identification
Intermediates
MicroRNA
MicroRNAs
miRNA
Next-generation sequencing
Pipelines
Plant genetics
Plant microRNA
Plant reliability
Processing
Researchers
Ribonucleic acid
RNA
RNA polymerase
Secondary structure
Software
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Summary:MicroRNAs (miRNAs) constitute a well-known small RNA (sRNA) species with important regulatory roles. To date, several bioinformatics tools have been developed for large-scale prediction of miRNAs based on high-throughput sequencing data. However, some of these tools become invalid without reference genomes, while some tools cannot supply user-friendly outputs. Besides, most of the current tools focus on the importance of secondary structures and sRNA expression patterns for miRNA prediction, while they do not pay attention to miRNA processing for reliability check. Here, we reported a pipeline PmiRDiscVali for plant miRNA discovery and partial validation. This pipeline integrated the popular tool miRDeep-P for plant miRNA prediction, making PmiRDiscVali compatible for both reference-based and de novo predictions. To check the prediction reliability, we adopted the concept that the miRNA processing intermediates could be tracked by degradome sequencing (degradome-seq) during the development of PmiRDiscVali. A case study was performed by using the public sequencing data of Dendrobium officinale, in order to show the clear and concise presentation of the prediction results. Summarily, the integrated pipeline PmiRDiscVali, featured with degradome-seq data-based validation and vivid result presentation, should be useful for large-scale identification of plant miRNA candidates.
ISSN:1471-2164
1471-2164
DOI:10.1186/s12864-019-5478-7