miRDeep-P: a computational tool for analyzing the microRNA transcriptome in plants

• Published in: Bioinformatics Vol. 27; no. 18; pp. 2614 - 2615
• Main Authors: Yang, Xiaozeng, Li, Lei
• Format: Journal Article
• Language: English
• Published: Oxford Oxford University Press 15.09.2011
• Subjects: Bioinformatics; Biological and medical sciences; Data Mining - methods; Fundamental and applied biological sciences. Psychology; Gene Expression; General aspects; Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects); MicroRNAs - genetics; Models, Genetic; Plants - genetics; Software; Transcriptome; Gene silencing; Plant; Vegetals; RNA interference; Micro RNA; Transcriptome
• ISSN: 1367-4803; 1367-4811; 1460-2059
• DOI: 10.1093/bioinformatics/btr430

Ultra-deep sampling of small RNA libraries by next-generation sequencing has provided rich information on the microRNA (miRNA) transcriptome of various plant species. However, few computational tools have been developed to effectively deconvolute the complex information. We sought to employ the signature distribution of small RNA reads along the miRNA precursor as a model in plants to profile expression of known miRNA genes and to identify novel ones. A freely available package, miRDeep-P, was developed by modifying miRDeep, which is based on a probabilistic model of miRNA biogenesis in animals, with a plant-specific scoring system and filtering criteria. We have tested miRDeep-P on eight small RNA libraries derived from three plants. Our results demonstrate miRDeep-P as an effective and easy-to-use tool for characterizing the miRNA transcriptome in plants. http://faculty.virginia.edu/lilab/miRDP/ CONTACT: ll4jn@virginia.edu Supplementary data are available at Bioinformatics online.