Evidence map›Paper›PMID 40996716›Full record

ArticleDatabase : the journal of biological databases and curation2025

The state of the human coding gene catalogues.

Miguel Maquedano, Daniel Cerdán-Vélez, Michael L Tress

Abstract read
In one paragraph

Article in Database : the journal of biological databases and curation, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

3 authors.

Miguel MaquedanoBioinformatics Unit, Spanish National Cancer Research Centre (CNIO), Calle Melchor Fernandez Almagro, 3, 28029 Madrid, Spain.
Daniel Cerdán-VélezBioinformatics Unit, Spanish National Cancer Research Centre (CNIO), Calle Melchor Fernandez Almagro, 3, 28029 Madrid, Spain.
Michael L TressBioinformatics Unit, Spanish National Cancer Research Centre (CNIO), Calle Melchor Fernandez Almagro, 3, 28029 Madrid, Spain.ORCID 0000-0001-9046-6370

Funding

GENCODE Resource ProjectU41HG007234 · NHGRI · SANGER INSTITUTE · PI FLICEK, PAUL · 2013 to 2020
$20.3M
NHGRI NIH HHSNIH HHS U41 HG007234
6 · The paper itself

Abstract

In 2018, we analysed the three main repositories for the human proteome: Ensembl/GENCODE, RefSeq, and UniProtKB. At that time the three gene sets disagreed on the coding status of one of every eight annotated coding genes, and our results suggested that as many as 4234 of these genes might not be correctly classified. Here, we have repeated the analysis with updated versions of the three reference gene sets. Superficially, little appears to have changed. The three sets annotate 21 871 coding genes, slightly fewer than previously, and still disagree on the status of 2603 annotated genes, almost one in eight. However, we show that collaborations between the three reference gene sets have led to greater consensus. Reference catalogues have agreed on the coding status of another 249 genes since the last analysis while at least 700 genes have been reclassified. We still find that there are >2000 coding genes with at least one potential non-coding feature to indicate that they may not be coding genes. This includes a large majority of the 2603 genes for which annotators do not agree on coding status. In total, we believe that as many as 3000 genes may be misclassified as coding and could be annotated as non-coding genes, pseudogenes, or cancer antigens.

Indexed as

Databases, GeneticGenome, HumanMolecular Sequence AnnotationOpen Reading FramesProteomeHumansProteome

Identifiers

PMID40996716
PMCPMC12462614

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.