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Updated: Apr 25, 2026
08:36
AirID-Based Proximity Labeling for Protein-Protein Interaction in Plants
Published on: September 16, 2022
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Misannotated domains in plant databases: lessons from 'PIPLC Y-box-containing' proteins
Lucas Amokrane1, Sébastien Aubourg2, Eric Ruelland1
1Unité Génie Enzymatique & Cellulaire, UMR CNRS 7025, Université de Technologie de Compiègne, Compiègne F-60203, France.
Trends in Plant Science
|April 23, 2026
Summary
Automated protein annotation can be misleading due to reliance on partial domain matches. A new context-aware framework integrating structure and evolution improves accuracy for reliable genomic interpretation.
Area of Science:
- Bioinformatics
- Computational Biology
- Genomics
Background:
- Automated protein annotation tools are widely used but often rely on incomplete domain matching.
- This approach risks inaccurate protein assignments by ignoring crucial structural and evolutionary context.
Purpose of the Study:
- To demonstrate how errors in automated protein annotation arise and propagate.
- To introduce a novel framework for context-aware protein annotation to enhance reliability.
Main Methods:
- Case study using phosphoinositide-dependent phospholipase C (PIPLC) Y-box-containing proteins.
- Integration of domain architecture, structural plausibility, and phylogenetic evidence for validation.
Main Results:
- Identified errors in domain-based annotation that obscure true biological functions.
- Showcased how these errors can lead to the formation of artificial protein classes.
- Demonstrated the propagation of annotation errors across biological databases.
Conclusions:
- Context-aware annotation is crucial for accurate genomic interpretation.
- The proposed framework provides actionable strategies for researchers and database curators.
- Improved annotation reliability is essential in the era of high-throughput genomics.
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