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Updated: Jan 6, 2026

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Published on: August 15, 2019
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The state of the human coding gene catalogues.
Miguel Maquedano1, Daniel Cerdán-Vélez1, Michael L Tress1
1Bioinformatics Unit, Spanish National Cancer Research Centre (CNIO), Calle Melchor Fernandez Almagro, 3, 28029 Madrid, Spain.
Database : the Journal of Biological Databases and Curation
|September 25, 2025
Summary
Analysis of human proteome repositories reveals persistent discrepancies in gene classification. Over 3000 protein-coding genes may be misclassified, highlighting the need for improved gene annotation accuracy.
Area of Science:
- Genomics
- Proteomics
- Bioinformatics
Background:
- Previous analysis in 2018 identified significant disagreement among major human proteome repositories (Ensembl/GENCODE, RefSeq, UniProtKB) regarding the coding status of annotated genes.
- The 2018 study suggested over 4000 genes might be incorrectly classified as coding.
Purpose of the Study:
- To re-evaluate the coding status of human genes using updated versions of the three main reference gene sets.
- To assess changes in gene set consensus and identify potentially misclassified coding genes.
Main Methods:
- Comparative analysis of gene annotations from Ensembl/GENCODE, RefSeq, and UniProtKB.
- Identification of discrepancies in coding status across the repositories.
- Evaluation of gene features that may indicate non-coding potential.
Main Results:
- The updated analysis still shows disagreement on the status of 2603 annotated genes (approximately 1 in 8).
- Collaborative efforts have increased consensus, with 249 additional genes now agreed upon as coding.
- Over 2000 genes exhibit features suggesting they may not be coding, with a majority of the 2603 disputed genes falling into this category.
Conclusions:
- Despite improvements, an estimated 3000 genes may be misclassified as coding and warrant re-annotation as non-coding genes, pseudogenes, or cancer antigens.
- Ongoing discrepancies underscore the dynamic nature of gene annotation and the need for continuous refinement of genomic databases.
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