Evidence map›Paper›PMID 25490151›Full record

ArticleJournal of visualized experiments : JoVE2014

Highly efficient ligation of small RNA molecules for microRNA quantitation by high-throughput sequencing.

Jerome E Lee, Rui Yi

Abstract readVideo-Audio Media
In one paragraph

Article in Journal of visualized experiments : JoVE, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. microRNA changes in liver tissue associated with fibrosis progression in patients with hepatitis C.Liver international : official journal of the International Association for the Study of the Liver · 2016
    Article
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

2 authors.

Jerome E LeeMolecular, Cellular, and Developmental Biology, University of Colorado, Boulder.
Rui YiMolecular, Cellular, and Developmental Biology, University of Colorado, Boulder; Linda Crnic Institute for Down Syndrome, University of Colorado, Denver; Rui.Yi@colorado.edu.

Funding

MicroRNA-mediated Regulation in Mammalian SkinR01AR059697 · NIAMS · UNIVERSITY OF COLORADO · PI YI, RUI · 2010 to 2020
$3.9M
NIAMS NIH HHS R01 AR059697NIAMS NIH HHS R01AR059697
6 · The paper itself

Abstract

MiRNA cloning and high-throughput sequencing, termed miR-Seq, stands alone as a transcriptome-wide approach to quantify miRNAs with single nucleotide resolution. This technique captures miRNAs by attaching 3' and 5' oligonucleotide adapters to miRNA molecules and allows de novo miRNA discovery. Coupling with powerful next-generation sequencing platforms, miR-Seq has been instrumental in the study of miRNA biology. However, significant biases introduced by oligonucleotide ligation steps have prevented miR-Seq from being employed as an accurate quantitation tool. Previous studies demonstrate that biases in current miR-Seq methods often lead to inaccurate miRNA quantification with errors up to 1,000-fold for some miRNAs. To resolve these biases imparted by RNA ligation, we have developed a small RNA ligation method that results in ligation efficiencies of over 95% for both 3' and 5' ligation steps. Benchmarking this improved library construction method using equimolar or differentially mixed synthetic miRNAs, consistently yields reads numbers with less than two-fold deviation from the expected value. Furthermore, this high-efficiency miR-Seq method permits accurate genome-wide miRNA profiling from in vivo total RNA samples.

Indexed as

Cloning, MolecularHigh-Throughput Nucleotide SequencingMicroRNAsRNASequence Analysis, RNATranscriptomeMicroRNAsRNA

Identifiers

PMID25490151
PMCPMC4354015

What OpenQuestion holds

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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.