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

被引:186
作者
Yang, Xiaozeng [1 ]
Li, Lei [1 ]
机构
[1] Univ Virginia, Dept Biol, Charlottesville, VA 22904 USA
基金
美国国家科学基金会;
关键词
DEEP SEQUENCING DATA; EXPRESSION;
D O I
10.1093/bioinformatics/btr430
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Motivation: 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. Results: 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.
引用
收藏
页码:2614 / 2615
页数:2
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