Evidence map›Paper›PMID 41278537›Full record

ReviewNAR genomics and bioinformatics2025

To be or not to be a protein coding mutation, that's the question!

Dylan De Groote, Daniele Pepe, Xander Janssens, Kim De Keersmaecker

Abstract readReview
In one paragraph

Review in NAR genomics and bioinformatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Dylan De GrooteLaboratory for Disease Mechanisms in Cancer, Department of Oncology, KU Leuven, Leuven 3000, Belgium.ORCID https://orcid.org/0009-0005-9864-9813
Daniele PepeLaboratory for Disease Mechanisms in Cancer, Department of Oncology, KU Leuven, Leuven 3000, Belgium.ORCID https://orcid.org/0000-0003-3354-2626
Xander JanssensLaboratory for Disease Mechanisms in Cancer, Department of Oncology, KU Leuven, Leuven 3000, Belgium.ORCID https://orcid.org/0000-0001-8064-5164
Kim De KeersmaeckerLaboratory for Disease Mechanisms in Cancer, Department of Oncology, KU Leuven, Leuven 3000, Belgium.ORCID https://orcid.org/0000-0002-7420-9531

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Accurate annotation of genetic variants-distinguishing whether they affect protein-coding or noncoding genomic regions-is crucial for evaluating their potential role in disease development. Prominent examples have been identified of variants that for many years had been considered to be coding missense or synonymous mutations targeting one gene, and that recently turned out to be noncoding variants, sometimes even modulating a shared regulatory region of multiple genes. These errors were caused by annotating to a canonical reference transcript, whereas an alternative transcript was in reality expressed in respect to which the mutations have a different annotation. Unfortunately, this practice of annotating genetic variants to a reference transcript, without verifying whether this transcript is expressed or whether the mutation causes a change of expressed transcript, is still widespread. However, the implementation of RNA sequencing and availability of these data in online portals allow to verify expressed transcripts in relevant tissues. Integration of DNA- and RNA-sequencing data, in which detected DNA mutations are annotated in respect to the transcripts that are expressed in the corresponding tissue or disease sample as detected by RNA sequencing, avoids misinterpretation of noncoding variants as coding and

Indexed as

MutationOpen Reading FramesHumansMolecular Sequence AnnotationSequence Analysis, RNA

Identifiers

PMID41278537
PMCPMC12634407

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.