Evidence map›Paper›PMID 28402429›Full record

ArticleNucleic acids research2017

A high quality Arabidopsis transcriptome for accurate transcript-level analysis of alternative splicing.

Runxuan Zhang, Cristiane P G Calixto, Yamile Marquez, Peter Venhuizen, Nikoleta A Tzioutziou, Wenbin Guo, Mark Spensley, Juan Carlos Entizne, Dominika Lewandowska, Sara Ten Have and 7 more

Open access · goldAbstract read
In one paragraph

Article in Nucleic acids research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 147 papers.

0numbers the graph read from it
0cells of the map it votes in
147citing papers in PubMed
12.8field-weighted citation impact, top 1% 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

147 citing papers in PubMed, 318 citations in OpenAlex.

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87 more citing papers are in PubMed but not listed here.

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

17 authors at 7 institutions in 6 countries.

Runxuan ZhangInformatics and Computational Sciences, The James Hutton Institute, Invergowrie, Dundee DD2 5DA, UK.
Cristiane P G CalixtoPlant Sciences Division, College of Life Sciences, University of Dundee, Invergowrie, Dundee DD2 5DA, UK.
Yamile MarquezMax F. Perutz Laboratories, Medical University of Vienna, Dr. Bohrgasse 9/3, 1030 Vienna, Austria.
Peter VenhuizenMax F. Perutz Laboratories, Medical University of Vienna, Dr. Bohrgasse 9/3, 1030 Vienna, Austria.
Nikoleta A TzioutziouPlant Sciences Division, College of Life Sciences, University of Dundee, Invergowrie, Dundee DD2 5DA, UK.
Wenbin GuoInformatics and Computational Sciences, The James Hutton Institute, Invergowrie, Dundee DD2 5DA, UK.
Mark SpensleyThe Donnelly Centre, University of Toronto, 160 College Street, Toronto, Ontario, Canada.
Juan Carlos EntiznePlant Sciences Division, College of Life Sciences, University of Dundee, Invergowrie, Dundee DD2 5DA, UK.
Dominika LewandowskaCell and Molecular Sciences, The James Hutton Institute, Invergowrie, Dundee DD2 5DA, UK.
Sara Ten HaveCentre for Gene Regulation and Expression, School of Life Sciences, University of Dundee, Dundee, UK.
Nicolas Frei Dit FreyInstitute of Plant Sciences Paris Saclay, INRA-CNRS-UEVE, Orsay 91405, France.
Heribert HirtInstitute of Plant Sciences Paris Saclay, INRA-CNRS-UEVE, Orsay 91405, France.
Allan B JamesInstitute of Molecular, Cell and Systems Biology, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow G12 8QQ, UK.
Hugh G NimmoInstitute of Molecular, Cell and Systems Biology, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow G12 8QQ, UK.
Andrea BartaMax F. Perutz Laboratories, Medical University of Vienna, Dr. Bohrgasse 9/3, 1030 Vienna, Austria.
Maria KalynaDepartment of Applied Genetics and Cell Biology, University of Natural Resources and Life Sciences - BOKU, Muthgasse 18, 1190 Vienna, Austria.
John W S BrownPlant Sciences Division, College of Life Sciences, University of Dundee, Invergowrie, Dundee DD2 5DA, UK.
James Hutton Institute · GBUniversity of Dundee · GBMax Perutz Labs · ATCentre National de la Recherche Scientifique · FRUniversity of Glasgow · GBBOKU University · ATUniversity of Toronto · CA

Funding

Austrian Science Fund FWF P 26333
6 · The paper itself

Abstract

Alternative splicing generates multiple transcript and protein isoforms from the same gene and thus is important in gene expression regulation. To date, RNA-sequencing (RNA-seq) is the standard method for quantifying changes in alternative splicing on a genome-wide scale. Understanding the current limitations of RNA-seq is crucial for reliable analysis and the lack of high quality, comprehensive transcriptomes for most species, including model organisms such as Arabidopsis, is a major constraint in accurate quantification of transcript isoforms. To address this, we designed a novel pipeline with stringent filters and assembled a comprehensive Reference Transcript Dataset for Arabidopsis (AtRTD2) containing 82,190 non-redundant transcripts from 34 212 genes. Extensive experimental validation showed that AtRTD2 and its modified version, AtRTD2-QUASI, for use in Quantification of Alternatively Spliced Isoforms, outperform other available transcriptomes in RNA-seq analysis. This strategy can be implemented in other species to build a pipeline for transcript-level expression and alternative splicing analyses.

Indexed as

Alternative SplicingGenes, InsectTranscriptomeArabidopsisGenetic VariationProteomicsReference ValuesReproducibility of ResultsRNA, UntranslatedSequence Analysis, RNATranscription, GeneticRNA, Untranslated

Identifiers

PMID28402429
PMCPMC5435985
OpenAlexW2605929552

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.