Misannotated domains in plant databases: lessons from 'PIPLC Y-box-containing' proteins

Automated protein annotation tools now scale rapidly, but many rely on partial matches to known protein domains and neglect structural or evolutionary context, risking misleading assignments. Using the annotation of 'phosphoinositide-dependent phospholipase C (PIPLC) Y-box-containing' proteins as a case study, we demonstrate how such errors arise, propagate across databases, and even contribute to the apparent emergence of artificial protein classes. Our analysis reveals that domain-based inference, without careful validation, can obscure true biological roles and distort genomic interpretations. To address this challenge, we propose a practical framework for context-aware annotation, integrating domain architecture, structural plausibility, and phylogenetic evidence. This approach offers researchers and database curators actionable strategies to improve annotation reliability in the era of high-throughput genomics.