Evidence map›Paper›PMID 28038678›Full record

ArticleGenome biology2016

Human splicing diversity and the extent of unannotated splice junctions across human RNA-seq samples on the Sequence Read Archive.

Abhinav Nellore, Andrew E Jaffe, Jean-Philippe Fortin, José Alquicira-Hernández, Leonardo Collado-Torres, Siruo Wang, Robert A Phillips, Nishika Karbhari, Kasper D Hansen, Ben Langmead and 1 more

Open access · goldAbstract read
In one paragraph

Article in Genome biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 70 papers.

0numbers the graph read from it
0cells of the map it votes in
70citing papers in PubMed
9.1field-weighted citation impact, top 2% 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

70 citing papers in PubMed, 121 citations in OpenAlex.

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  16. SpliceProt 2.0: A Sequence Repository of Human, Mouse, and Rat Proteoforms.International journal of molecular sciences · 2024
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10 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors at 5 institutions in 2 countries.

Abhinav NelloreDepartment of Computer Science, Johns Hopkins University, Baltimore, MD, USA.
Andrew E JaffeDepartment of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Jean-Philippe FortinDepartment of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
José Alquicira-HernándezDepartment of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Leonardo Collado-TorresDepartment of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Siruo WangDepartment of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Robert A PhillipsDepartment of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Nishika KarbhariDepartment of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Kasper D HansenDepartment of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Ben LangmeadDepartment of Computer Science, Johns Hopkins University, Baltimore, MD, USA. langmea@cs.jhu.edu.
Jeffrey T LeekDepartment of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA. jtleek@gmail.com.
Johns Hopkins University · USLieber Institute for Brain Development · USSalisbury University · USThe University of Texas at Austin · USUniversidad Nacional Autónoma de México · MX

Funding

Hardening and Scaling Core Genomics SoftwareR01GM118568 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI LANGMEAD, BENJAMIN THOMAS · 2016 to 2020
$2.0M
Statistical models for biological and technical variation in RNA sequencingR01GM105705 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI LEEK, JEFFREY T. · 2013 to 2017
$1.5M
NIGMS NIH HHS R01 GM105705NIGMS NIH HHS R01 GM118568
6 · The paper itself

Abstract

backgroundGene annotations, such as those in GENCODE, are derived primarily from alignments of spliced cDNA sequences and protein sequences. The impact of RNA-seq data on annotation has been confined to major projects like ENCODE and Illumina Body Map 2.0.

resultsWe aligned 21,504 Illumina-sequenced human RNA-seq samples from the Sequence Read Archive (SRA) to the human genome and compared detected exon-exon junctions with junctions in several recent gene annotations. We found 56,861 junctions (18.6%) in at least 1000 samples that were not annotated, and their expression associated with tissue type. Junctions well expressed in individual samples tended to be annotated. Newer samples contributed few novel well-supported junctions, with the vast majority of detected junctions present in samples before 2013. We compiled junction data into a resource called intropolis available at http://intropolis.rail.bio . We used this resource to search for a recently validated isoform of the ALK gene and characterized the potential functional implications of unannotated junctions with publicly available TRAP-seq data.

conclusionsConsidering only the variation contained in annotation may suffice if an investigator is interested only in well-expressed transcript isoforms. However, genes that are not generally well expressed and nonetheless present in a small but significant number of samples in the SRA are likelier to be incompletely annotated. The rate at which evidence for novel junctions has been added to the SRA has tapered dramatically, even to the point of an asymptote. Now is perhaps an appropriate time to update incomplete annotations to include splicing present in the now-stable snapshot provided by the SRA.

Indexed as

Molecular Sequence AnnotationRNA Splice SitesAlternative SplicingComputational BiologyExonsGene Expression RegulationGenetic VariationHigh-Throughput Nucleotide SequencingHumansReproducibility of ResultsRNA SplicingSequence Analysis, RNARNA Splice SitesIntronRNA-seqSplicing

Identifiers

PMID28038678
PMCPMC5203714
OpenAlexW2566979164

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.