ASSIGNING STANDARDIZED NOMENCLATURE TO CHICKEN G2E3 AND PHF7-LIKE GENES

Gene nomenclature-the standardized naming of genes based on evolutionary relationships and functional characteristics-is critical for accurate communication, database consistency, and comparative genomic studies. Despite advances in automated annotation, misclassification remains common in gene families with recent duplications or functional divergence. This issue is particularly evident in the chicken G2E3 and PHF7 gene families, where initial computational annotations labeled multiple gene loci as G2E3-like despite lacking key functional domains. The problem addressed in this study is the need for accurate, functionally informed classification of these genes to correct annotation errors and clarify their evolutionary history. These chicken G2E3-like genes were manually reviewed using a combination of domain architecture analysis and phylogenetic reconstruction, revealing that none of the genes previously labeled as G2E3-like contained the defining HECT domain required for E3 ligase activity. In contrast, both human and chicken G2E3 reference genes contain HECT domains. This led to the conclusion that the chicken genome does not possess multiple G2E3-like genes, but instead has undergone a lineage-specific expansion of PHF7-like genes. These expanded genes were systematically renamed based on their phylogenetic clustering, yielding a standardized nomenclature (e.g., PHF7A1, PHF7B1) that reflects evolutionary relationships and domain structure. My findings correct significant misannotations in the chicken genome and establish a replicable, evidence-based framework for gene classification that cannot be reliably achieved by computational tools alone. By clarifying the identity and evolutionary trajectory of PHF7 paralogs, this work enhances our understanding of gene family expansion in avian species and provides a reliable foundation for future studies on gene function, regulation, and reproductive biology in chickens. The standardized naming system also improves cross-species comparisons and facilitates accurate data interpretation in genomic databases and functional studies.