Evidence map›Paper›PMID 32865117›Full record

ArticleRNA biology2021

In silico identification of pseudo-exon activation events in personal genome and transcriptome data.

Narumi Sakaguchi, Mikita Suyama

Open access · hybridAbstract read
In one paragraph

Article in RNA biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
1.2field-weighted citation impact, top 22% 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

13 citing papers in PubMed, 18 citations in OpenAlex.

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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

2 authors at 1 institution in 1 country.

Narumi SakaguchiDivision of Bioinformatics, Medical Institute of Bioregulation, Kyushu University, Fukuoka, Japan.ORCID 0000-0002-4077-0099
Mikita SuyamaDivision of Bioinformatics, Medical Institute of Bioregulation, Kyushu University, Fukuoka, Japan.ORCID 0000-0001-9526-3193
Kyushu University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Causative mutations for human genetic disorders have mainly been identified in exonic regions that code for amino acid sequences. Recently, however, it has been reported that mutations in deep intronic regions can also cause certain human genetic disorders by creating novel splice sites, leading to pseudo-exon activation. To investigate how frequently pseudo-exon activation events occur in normal individuals, we conducted in silico identification of such events using personal genome data and corresponding high-quality transcriptome data. With rather stringent conditions, on average, 2.6 pseudo-exon activation events per individual were identified. More pseudo-exon activation events were found in 5' donor splice sites than in 3' acceptor splice sites. Although pseudo-exon activation events have sporadically been reported as causative mutations in genetic disorders, it is revealed in this study that such events can be observed in normal individuals at a certain frequency. We estimate that human genomes typically contain on average at least 10 pseudo-exon activation events. The actual number should be higher than this, because we used stringent criteria to identify pseudo-exon activation events. This suggests that it is worth considering the possibility of pseudo-exon activation when searching for causative mutations of genetic disorders if candidate mutations are not identified in coding regions or RNA splice sites.

Indexed as

Computational BiologyExonsGenomicsPseudogenesTranscriptional ActivationTranscriptomeDatabases, GeneticGene Expression ProfilingHumansMutationPolymorphism, Single NucleotideRegulatory Sequences, Nucleic AcidRNA Splice SitesRNA SplicingRNA Splice Sitesmutationpersonal genomePseudo-exon activationRNA-SeqRNA splicing

Identifiers

PMID32865117
PMCPMC7951959
OpenAlexW3082649417

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.