QMaker: Fast and Accurate Method to Estimate Empirical Models of Protein Evolution

Amino acid substitution models play a crucial role in phylogenetic analyses. Maximum likelihood (ML) methods have been proposed to estimate amino acid substitution models; however, they are typically complicated and slow. In this article, we propose QMaker, a new ML method to estimate a general time-reversible Q matrix from a large protein data set consisting of multiple sequence alignments. QMaker combines an efficient ML tree search algorithm, a model selection for handling themodel heterogeneity among alignments, and the consideration of rate mixturemodels among sites. We provide QMaker as a user-friendly function in the IQ-TREEsoftware package (http://www.iqtree.org) supporting the use of multiple CPU cores so that biologists can easily estimate amino acid substitution models from their own protein alignments. We used QMaker to estimate new empirical general amino acid substitution models from the current Pfam database as well as five clade-specific models for mammals, birds, insects, yeasts, and plants. Our results show that the new models considerably improve the fit between model and data and in some cases influence the inference of phylogenetic tree topologies.

Automated summary

Amino acid substitution models are crucial in phylogenetic analyses, and a new ML method called QMaker has been proposed to estimate a general time-reversible Q matrix from large protein data sets. QMaker combines an efficient ML tree search algorithm, model selection for handling model heterogeneity among alignments, and consideration of rate mixture models among sites.