Literature DB >> 25692236

Comprehensive analysis of human small RNA sequencing data provides insights into expression profiles and miRNA editing.

Jing Gong1, Yuliang Wu, Xiantong Zhang, Yifang Liao, Vusumuzi Leroy Sibanda, Wei Liu, An-Yuan Guo.   

Abstract

MicroRNAs (miRNAs) play key regulatory roles in various biological processes and diseases. A comprehensive analysis of large scale small RNA sequencing data (smRNA-seq) will be very helpful to explore tissue or disease specific miRNA markers and uncover miRNA variants. Here, we systematically analyzed 410 human smRNA-seq datasets, which samples are from 24 tissue/disease/cell lines. We tested the mapping strategies and found that it was necessary to make multiple-round mappings with different mismatch parameters. miRNA expression profiles revealed that on average ∼70% of known miRNAs were expressed at low level or not expressed (RPM < 1) in a sample and only ∼9% of known miRNAs were relatively highly expressed (RPM > 100). About 30% known miRNAs were not expressed in all of our used samples. The miRNA expression profiles were compiled into an online database (HMED, http://bioinfo.life.hust.edu.cn/smallRNA/). Dozens of tissue/disease specific miRNAs, disease/control dysregulated miRNAs and miRNAs with arm switching events were discovered. Further, we identified some highly confident editing sites including 24 A-to-I sites and 23 C-to-U sites. About half of them were widespread miRNA editing sites in different tissues. We characterized that the 2 types of editing sites have different features with regard to location, editing level and frequency. Our analyses for expression profiles, specific miRNA markers, arm switching, and editing sites, may provide valuable information for further studies of miRNA function and biomarker finding.

Entities:  

Keywords:  mapping strategy; miRNA editing; miRNA profiles; small RNA sequencing; tissue specific

Mesh:

Substances:

Year:  2014        PMID: 25692236      PMCID: PMC4615373          DOI: 10.1080/15476286.2014.996465

Source DB:  PubMed          Journal:  RNA Biol        ISSN: 1547-6286            Impact factor:   4.652


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