Evidence map›Paper›PMID 26089393›Full record

ArticleNucleic acids research2015

Transcriptome dynamics of the microRNA inhibition response.

Jiayu Wen, Eleonora Leucci, Roberto Vendramin, Sakari Kauppinen, Anders H Lund, Anders Krogh, Brian J Parker

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in Nucleic acids research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.2field-weighted citation impact, top 42% 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

5 citing papers in PubMed, 6 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors at 2 institutions in 2 countries.

Jiayu WenThe Bioinformatics Centre, Department of Biology, University of Copenhagen, Ole Maaloes Vej 5, 2200 Copenhagen N, Denmark Biotech Research and Innovation Centre (BRIC), University of Copenhagen, Ole Maaloes Vej 5, 2200 Copenhagen N, Denmark.
Eleonora LeucciBiotech Research and Innovation Centre (BRIC), University of Copenhagen, Ole Maaloes Vej 5, 2200 Copenhagen N, Denmark Laboratory for Molecular Cancer Biology, Center for the Biology of Disease, VIB, 3000 Leuven, Belgium; Laboratory for Molecular Cancer Biology, Center of Human Genetics, VIB, 3000 Leuven, Belgium.
Roberto VendraminLaboratory for Molecular Cancer Biology, Center for the Biology of Disease, VIB, 3000 Leuven, Belgium; Laboratory for Molecular Cancer Biology, Center of Human Genetics, VIB, 3000 Leuven, Belgium.
Sakari KauppinenDepartment of Haematology, Aalborg University Hospital, A.C. Meyers Vnge 15, 2450 Copenhagen SV, Denmark.
Anders H LundBiotech Research and Innovation Centre (BRIC), University of Copenhagen, Ole Maaloes Vej 5, 2200 Copenhagen N, Denmark anders.lund@bric.ku.dk.
Anders KroghThe Bioinformatics Centre, Department of Biology, University of Copenhagen, Ole Maaloes Vej 5, 2200 Copenhagen N, Denmark krogh@binf.ku.dk.
Brian J ParkerThe Bioinformatics Centre, Department of Biology, University of Copenhagen, Ole Maaloes Vej 5, 2200 Copenhagen N, Denmark Bioinformatics Institute, Agency for Science, Technology and Research (A*STAR), 30 Biopolis street, #07-01, Singapore 138671 bparker@binf.ku.dk.
Aalborg University Hospital · DKKU Leuven · BE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We report a high-resolution time series study of transcriptome dynamics following antimiR-mediated inhibition of miR-9 in a Hodgkin lymphoma cell-line-the first such dynamic study of the microRNA inhibition response-revealing both general and specific aspects of the physiological response. We show miR-9 inhibition inducing a multiphasic transcriptome response, with a direct target perturbation before 4 h, earlier than previously reported, amplified by a downstream peak at ∼32 h consistent with an indirect response due to secondary coherent regulation. Predictive modelling indicates a major role for miR-9 in post-transcriptional control of RNA processing and RNA binding protein regulation. Cluster analysis identifies multiple co-regulated gene regulatory modules. Functionally, we observe a shift over time from mRNA processing at early time points to translation at later time points. We validate the key observations with independent time series qPCR and we experimentally validate key predicted miR-9 targets. Methodologically, we developed sensitive functional data analytic predictive methods to analyse the weak response inherent in microRNA inhibition experiments. The methods of this study will be applicable to similar high-resolution time series transcriptome analyses and provides the context for more accurate experimental design and interpretation of future microRNA inhibition studies.

Indexed as

Gene Expression RegulationTranscriptomeCell Line, TumorCluster AnalysisGenomicsHumansMicroRNAsModels, GeneticRNA-Binding ProteinsRNA Processing, Post-TranscriptionalMicroRNAsRNA-Binding Proteins

Identifiers

PMID26089393
PMCPMC4513874
OpenAlexW1838268929

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.