Phylogenetic analyses
Phylogenetic trees were reconstructed using maximum likelihood (ML) implemented in IQ-TREE v. 1.5.5 (Nguyen, Schmidt, Von Haeseler, & Minh, 2015) under the general time-reversible (Tavaré, 1986), four class mixture model (GTR+FO*H4) on the unpartitioned matrix. This is a General Heterogeneous evolution On a Single Topology model (GHOST) that infers separate base frequencies per class and accounts for heterotachy or rate variation across sites and lineages (Crotty et al., 2020). Bootstrap support values (bs) were estimated via the ultrafast bootstrap algorithm with 1500 replicates (Minh, Nguyen, & Haeseler, 2013). Bayesian inference (BI) was assessed in ExaBayes v 1.5 (Aberer, Kobert, & Stamatakis, 2014) with the implemented GTRGAMMA model with four coupled Markov chain Monte Carlo (MCMC) runs, each with 10 million generations, and sampling every 500 generations. Convergence was checked based on the average standard deviation of split frequencies (ASDSF <0.2%). The first 25% of the trees were discarded as burn-in for each MCMC run prior to convergence. Topological robustness was assessed using posterior probabilities (pp). Trees were visualized in FigTree v. 1.4.4 (Rambaut, 2014) and edited in Adobe Illustrator CC 2018 (Fig. 1).