A Maximum Likelihood Method for Detecting Directional Evolution in Protein Sequences and Its Application to Influenza A Virus

We develop a model-based phylogenetic maximum likelihood test for evidence of preferential substitution toward a given residue at individual positions of a protein alignment-directional evolution of protein sequences (DEPS). DEPS can identify both the target residue and sites evolving toward it, help detect selective sweeps and frequency-dependent selection-scenarios that confound most existing tests for selection, and achieve good power and accuracy on simulated data. We applied DEPS to alignments representing different genomic regions of influenza A virus (IAV), sampled from avian hosts (H5N1 serotype) and human hosts (H3N2 serotype), and identified multiple directionally evolving sites in 5/8 genomic segments of H5N1 and H3N2 IAV. We propose a simple descriptive classification of directionally evolving sites into 5 groups based on the temporal distribution of residue frequencies and document known functional correlates, such as immune escape or host adaptation.