Evidence map›Paper›PMID 24827614›Full record

ArticleRNA biology2014

MicroRNA binding sites in C. elegans 3' UTRs.

Chaochun Liu, William A Rennie, Bibekanand Mallick, Shaveta Kanoria, Dang Long, Adam Wolenc, C Steven Carmack, Ye Ding

Abstract read
In one paragraph

Article in RNA biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. STarMir Tools for Prediction of microRNA Binding Sites.Methods in molecular biology (Clifton, N.J.) · 2016
    Article
  5. Short interspersed DNA elements and miRNAs: a novel hidden gene regulation layer in zebrafish?Chromosome research : an international journal on the molecular, supramolecular and evolutionary aspects of chromosome biology · 2015
    Article
  6. Article
  7. 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

8 authors.

Chaochun LiuWadsworth Center; New York State Department of Health; Center for Medical Science; Albany, NY USA.
William A RennieWadsworth Center; New York State Department of Health; Center for Medical Science; Albany, NY USA.
Bibekanand MallickWadsworth Center; New York State Department of Health; Center for Medical Science; Albany, NY USA.
Shaveta KanoriaWadsworth Center; New York State Department of Health; Center for Medical Science; Albany, NY USA.
Dang LongWadsworth Center; New York State Department of Health; Center for Medical Science; Albany, NY USA.
Adam WolencWadsworth Center; New York State Department of Health; Center for Medical Science; Albany, NY USA.
C Steven CarmackWadsworth Center; New York State Department of Health; Center for Medical Science; Albany, NY USA.
Ye DingWadsworth Center; New York State Department of Health; Center for Medical Science; Albany, NY USA.

Funding

Novel Approaches to Mammalian MicroRNA Target PredictionR01GM099811 · NIGMS · WADSWORTH CENTER · PI DING, YE, LU, JUN · 2012 to 2015
$2.4M
NIGMS NIH HHS GM099811NIGMS NIH HHS R01 GM099811
6 · The paper itself

Abstract

MicroRNAs (miRNAs) are post-transcriptional regulators of gene expression. Since the discovery of lin-4, the founding member of the miRNA family, over 360 miRNAs have been identified for Caenorhabditis elegans (C. elegans). Prediction and validation of targets are essential for elucidation of regulatory functions of these miRNAs. For C. elegans, crosslinking immunoprecipitation (CLIP) has been successfully performed for the identification of target mRNA sequences bound by Argonaute protein ALG-1. In addition, reliable annotation of the 3' untranslated regions (3' UTRs) as well as developmental stage-specific expression profiles for both miRNAs and 3' UTR isoforms are available. By utilizing these data, we developed statistical models and bioinformatics tools for both transcriptome-scale and developmental stage-specific predictions of miRNA binding sites in C. elegans 3' UTRs. In performance evaluation via cross validation on the ALG-1 CLIP data, the models were found to offer major improvements over established algorithms for predicting both seed sites and seedless sites. In particular, our top-ranked predictions have a substantially higher true positive rate, suggesting a much higher likelihood of positive experimental validation. A gene ontology analysis of stage-specific predictions suggests that miRNAs are involved in dynamic regulation of biological functions during C. elegans development. In particular, miRNAs preferentially target genes related to development, cell cycle, trafficking, and cell signaling processes. A database for both transcriptome-scale and stage-specific predictions and software for implementing the prediction models are available through the Sfold web server at http://sfold.wadsworth.org.

Indexed as

3' Untranslated RegionsBinding SitesAnimalsBase PairingBase SequenceCaenorhabditis elegansComputational BiologyDatabases, Nucleic AcidGene Expression ProfilingGene Expression Regulation, DevelopmentalMaleMicroRNAsRNA, MessengerROC CurveSoftwareTranscriptome3' Untranslated RegionsMicroRNAsRNA, Messengerdevelopmental stageGO analysismicroRNApredictiontarget binding site

Identifiers

PMID24827614
PMCPMC4156501

What OpenQuestion holds

Textmetadata
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.