A Bioinformatics Pipeline to Accurately and Efficiently Analyze the MicroRNA Transcriptomes in Plants
文献类型: 外文期刊
作者: Wang, Ying 1 ; Kuang, Zheng 1 ; Li, Lei 2 ; Yang, Xiaozeng 1 ;
作者机构: 1.Beijing Acad Agr & Forestry Sci, Beijing Agrobiotechnol Res Ctr, Beijing Key Lab Agr Genet Resources & Biotechnol, Beijing, Peoples R China
2.Peking Univ, Sch Adv Agr Sci, Peking Tsinghua Ctr Life Sci, State Key Lab Prot & Plant Gene Res, Beijing, Peoples R China
3.Peking Univ, Sch Life Sci, Beijing, Peoples R China
关键词: Genetics; Issue 155; microRNA (miRNA); plant; sRNA-seq; miRDeep-P2 (miRDP2); Next generation sequencing; plant miRNA criteria; miRDeep-P (miRDP)
期刊名称:JOVE-JOURNAL OF VISUALIZED EXPERIMENTS ( 影响因子:1.355; 五年影响因子:1.696 )
ISSN: 1940-087X
年卷期: 2020 年 155 期
页码:
收录情况: SCI
摘要: MicroRNAs (miRNAs) are 20- to 24-nucleotide (nt) endogenous small RNAs (sRNAs) extensively existing in plants and animals that play potent roles in regulating gene expression at the post-transcriptional level. Sequencing sRNA libraries by Next Generation Sequencing (NGS) methods has been widely employed to identify and analyze miRNA transcriptomes in the last decade, resulting in a rapid increase of miRNA discovery. However, two major challenges arise in plant miRNA annotation due to increasing depth of sequenced sRNA libraries as well as the size and complexity of plant genomes. First, many other types of sRNAs, in particular, short interfering RNAs (siRNAs) from sRNA libraries, are erroneously annotated as miRNAs by many computational tools. Second, it becomes an extremely time-consuming process for analyzing miRNA transcriptomes in plant species with large and complex genomes. To overcome these challenges, we recently upgraded miRDeep-P (a popular tool for miRNA transcriptome analyses) to miRDeep-P2 (miRDP2 for short) by employing a new filtering strategy, overhauling the scoring algorithm and incorporating newly updated plant miRNA annotation criteria. We tested miRDP2 against sequenced sRNA populations in five representative plants with increasing genomic complexity, including Arabidopsis, rice, tomato, maize and wheat. The results indicate that miRDP2 processed these tasks with very high efficiency. In addition, miRDP2 outperformed other prediction tools regarding sensitivity and accuracy. Taken together, our results demonstrate miRDP2 as a fast and accurate tool for analyzing plant miRNA transcriptomes, therefore a useful tool in helping the community better annotate miRNAs in plants.
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