Evidence map›Paper›PMID 27229138›Full record

ArticleNucleic acids research2016

Accurate detection for a wide range of mutation and editing sites of microRNAs from small RNA high-throughput sequencing profiles.

Yun Zheng, Bo Ji, Renhua Song, Shengpeng Wang, Ting Li, Xiaotuo Zhang, Kun Chen, Tianqing Li, Jinyan Li

Open access · goldAbstract read
In one paragraph

Article in Nucleic acids research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 1 pooled it
3.8field-weighted citation impact, top 6% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

28 citing papers in PubMed, 1 synthesis or guideline pooled it, 48 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 3 institutions in 2 countries.

Yun ZhengFaculty of Life Science and Technology, Kunming University of Science and Technology Kunming, Yunnan 650500, China Faculty of Information Engineering and Automation, Kunming University of Science and Technology Kunming, Yunnan 650500, China zhengyun5488@gmail.com.
Bo JiFaculty of Life Science and Technology, Kunming University of Science and Technology Kunming, Yunnan 650500, China.
Renhua SongAdvanced Analytics Institute & Centre for Health Technologies, Faculty of Engineering & IT University of Technology Sydney, Australia.
Shengpeng WangFaculty of Life Science and Technology, Kunming University of Science and Technology Kunming, Yunnan 650500, China.
Ting LiFaculty of Life Science and Technology, Kunming University of Science and Technology Kunming, Yunnan 650500, China.
Xiaotuo ZhangFaculty of Information Engineering and Automation, Kunming University of Science and Technology Kunming, Yunnan 650500, China.
Kun ChenFaculty of Life Science and Technology, Kunming University of Science and Technology Kunming, Yunnan 650500, China.
Tianqing LiYunnan Key Lab of Primate Biomedicine Research; Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China.
Jinyan LiAdvanced Analytics Institute & Centre for Health Technologies, Faculty of Engineering & IT University of Technology Sydney, Australia jinyan.li@uts.edu.au.
Kunming University of Science and Technology · CNUniversity of Technology Sydney · AUYunnan Yingmao Biotechnology (China) · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Various types of mutation and editing (M/E) events in microRNAs (miRNAs) can change the stabilities of pre-miRNAs and/or complementarities between miRNAs and their targets. Small RNA (sRNA) high-throughput sequencing (HTS) profiles can contain many mutated and edited miRNAs. Systematic detection of miRNA mutation and editing sites from the huge volume of sRNA HTS profiles is computationally difficult, as high sensitivity and low false positive rate (FPR) are both required. We propose a novel method (named MiRME) for an accurate and fast detection of miRNA M/E sites using a progressive sequence alignment approach which refines sensitivity and improves FPR step-by-step. From 70 sRNA HTS profiles with over 1.3 billion reads, MiRME has detected thousands of statistically significant M/E sites, including 3'-editing sites, 57 A-to-I editing sites (of which 32 are novel), as well as some putative non-canonical editing sites. We demonstrated that a few non-canonical editing sites were not resulted from mutations in genome by integrating the analysis of genome HTS profiles of two human cell lines, suggesting the existence of new editing types to further diversify the functions of miRNAs. Compared with six existing studies or methods, MiRME has shown much superior performance for the identification and visualization of the M/E sites of miRNAs from the ever-increasing sRNA HTS profiles.

Indexed as

AlgorithmsCell LineGene DeletionGene LibraryGenome, HumanHigh-Throughput Nucleotide SequencingHumansMicroRNAsMutagenesis, InsertionalMutationPolymorphism, Single NucleotideRNA EditingMicroRNAs

Identifiers

PMID27229138
PMCPMC5001599
OpenAlexW2405344362

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.