Evidence map›Paper›PMID 27197243›Full record

ArticleGenome research2016

Improved definition of the mouse transcriptome via targeted RNA sequencing.

Giovanni Bussotti, Tommaso Leonardi, Michael B Clark, Tim R Mercer, Joanna Crawford, Lorenzo Malquori, Cedric Notredame, Marcel E Dinger, John S Mattick, Anton J Enright

Abstract read
In one paragraph

Article in Genome research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

  1. Evaluating the reliability of tools for mRNA annotation and IRES studies.bioRxiv : the preprint server for biology · 2026
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  17. Fingerprints of Modified RNA Bases from Deep Sequencing Profiles.Journal of the American Chemical Society · 2017
    Article
  18. Review
  19. Review
  20. Understanding the Role of lncRNAs in Nervous System Development.Advances in experimental medicine and biology · 2017
    Review
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

10 authors.

Giovanni BussottiEMBL, European Bioinformatics Institute, Cambridge, CB10 1SD, United Kingdom;ORCID 0000-0002-4078-7413
Tommaso LeonardiEMBL, European Bioinformatics Institute, Cambridge, CB10 1SD, United Kingdom;ORCID 0000-0002-4449-1863
Michael B ClarkGarvan Institute of Medical Research, Sydney, New South Wales 2010, Australia; MRC Functional Genomics Unit, Department of Physiology, Anatomy, and Genetics, University of Oxford, Oxford OX1 3PT, United Kingdom;
Tim R MercerGarvan Institute of Medical Research, Sydney, New South Wales 2010, Australia; St Vincent's Clinical School, UNSW Australia, Sydney, New South Wales 2052, Australia;
Joanna CrawfordInstitute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland 4072, Australia;
Lorenzo MalquoriInstitute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland 4072, Australia;
Cedric NotredameComparative Bioinformatics, Bioinformatics and Genomics Program, Centre for Genomic Regulation (CRG), 08003 Barcelona, Spain.
Marcel E DingerGarvan Institute of Medical Research, Sydney, New South Wales 2010, Australia; St Vincent's Clinical School, UNSW Australia, Sydney, New South Wales 2052, Australia;
John S MattickGarvan Institute of Medical Research, Sydney, New South Wales 2010, Australia; St Vincent's Clinical School, UNSW Australia, Sydney, New South Wales 2052, Australia;
Anton J EnrightEMBL, European Bioinformatics Institute, Cambridge, CB10 1SD, United Kingdom;ORCID 0000-0002-6090-3100

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Targeted RNA sequencing (CaptureSeq) uses oligonucleotide probes to capture RNAs for sequencing, providing enriched read coverage, accurate measurement of gene expression, and quantitative expression data. We applied CaptureSeq to refine transcript annotations in the current murine GRCm38 assembly. More than 23,000 regions corresponding to putative or annotated long noncoding RNAs (lncRNAs) and 154,281 known splicing junction sites were selected for targeted sequencing across five mouse tissues and three brain subregions. The results illustrate that the mouse transcriptome is considerably more complex than previously thought. We assemble more complete transcript isoforms than GENCODE, expand transcript boundaries, and connect interspersed islands of mapped reads. We describe a novel filtering pipeline that identifies previously unannotated but high-quality transcript isoforms. In this set, 911 GENCODE neighboring genes are condensed into 400 expanded gene models. Additionally, 594 GENCODE lncRNAs acquire an open reading frame (ORF) when their structure is extended with CaptureSeq. Finally, we validate our observations using current FANTOM and Mouse ENCODE resources.

Indexed as

TranscriptomeAnimalsGene Expression ProfilingHigh-Throughput Nucleotide SequencingMiceRNA, Long NoncodingRNA, Long Noncoding

Identifiers

PMID27197243
PMCPMC4864457

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.