Gene Age Prediction is Robust to False Homology

Phylostratigraphy is a widely used computational approach for predicting gene age by analyzing protein sequence similarities across evolutionary lineages. In this study, we used the Homo sapiens proteome as a reference to analyze the effect of false homology in gene age prediction. We implemented a workflow using state-of-the-art algorithms for sequence similarity searches enhanced by dynamic setting of an E-value threshold. This threshold was calculated for every protein individually using results of similarity searches with reversed database, which identified proteins prone to false homology. We demonstrated that dynamically adjusted E-values effectively reduced false positive rates compared to fixed threshold. However, the results indicate that, while certain proteins are more prone to false homology, they constitute a small proportion of the dataset and, in general, current sequence search algorithms are robust against false homology and thus reliable for phylostratigraphy.