A Branch-Heterogeneous Model of Protein Evolution for Efficient Inference of Ancestral Sequences

Abstract

Most models of nucleotide or amino acid substitution used in phylogenetic studies assume that the evolutionary process has been homogeneous across lineages and that composition of nucleotides or amino acids has remained the same throughout the tree. These oversimplified assumptions are refuted by the observation that compositional variability characterizes extant biological sequences. Branch-heterogeneous models of protein evolution that account for compositional variability have been developed, but are not yet in common use because of the large number of parameters required, leading to high computational costs and potential overparameterization. Here, we present a new branch-nonhomogeneous and nonstationary model of protein evolution that captures more accurately the high complexity of sequence evolution. This model, henceforth called Correspondence and likelihood analysis (COaLA), makes use of a correspondence analysis to reduce the number of parameters to be optimized through maximum likelihood, focusing on most of the compositional variation observed in the data. The model was thoroughly tested on both simulated and biological data sets to show its high performance in terms of data fitting and CPU time. COaLA efficiently estimates ancestral amino acid frequencies and sequences, making it relevant for studies aiming at reconstructing and resurrecting ancestral amino acid sequences. Finally, we applied COaLA on a concatenate of universal amino acid sequences to confirm previous results obtained with a nonhomogeneous Bayesian model regarding the early pattern of adaptation to optimal growth temperature, supporting the mesophilic nature of the Last Universal Common Ancestor. [Ancestral sequence reconstruction; nonhomogeneous model; optimal growth temperature; phylogenomics; phylogeny.]

Integrative modeling of gene and genome evolution roots the archaeal tree of life

“…The LACA and the last common ancestors of each of the major archaeal clades (DPANN, Euryarchaeota+TACK/Lokiarchaeum, Euryarchaeota, and TACK+Lokiarchaeum) were all inferred to be thermophiles, and these inferences were robust to the inclusion of DPANN in the analysis (SI Appendix, Table S7); the median optimal growth temperature estimate for the LACA was 73.1°C in the full analysis, and 75.7°C in the analysis without DPANN. Interestingly, our model predicts mesophilic optimal growth temperatures for most modern DPANN genomes, consistent with the idea (84,85) that adaptation to mesophily from a thermophilic ancestor occurred independently in each of the major archaeal clades.…”

“…Previous work exploiting the correlation between sequence composition and optimal growth temperatures (OGTs) suggested that early Archaea were (hyper)thermophiles, with mesophily arising more recently in archaeal evolution (84,85). Given that some DPANN genomes have been obtained from mesophilic environments, we investigated the impact of a basal DPANN clade on estimates of ancestral temperature.…”

“…S18), allowing us to infer temperature optima for ancestral nodes in the tree. We sampled 100 ancestral sequences for each node at the base of the tree using the branch-heterogeneous CoaLA model (84), performing the analysis both with and without DPANN (Materials and Methods). The LACA and the last common ancestors of each of the major archaeal clades (DPANN, Euryarchaeota+TACK/Lokiarchaeum, Euryarchaeota, and TACK+Lokiarchaeum) were all inferred to be thermophiles, and these inferences were robust to the inclusion of DPANN in the analysis (SI Appendix, Table S7); the median optimal growth temperature estimate for the LACA was 73.1°C in the full analysis, and 75.7°C in the analysis without DPANN.…”

Evaluation of Ancestral Sequence Reconstruction Methods to Infer Nonstationary Patterns of Nucleotide Substitution

“…There has been much effort in developing nonstationary, nonhomogeneous, or nonreversible models of nucleotide or amino acid substitution for use in inference of phylogenetic relationships among distant species, in both the maximumlikelihood (Yang and Roberts 1995;Galtier and Gouy 1998;Dutheil and Boussau 2008;Jayaswal et al 2011;Groussin et al 2013;Gueguen et al 2013;Jayaswal et al 2014) and Bayesian (Foster 2004;Lartillot 2006, 2008) frameworks. Here our focus is on estimation of substitution rates and counting of substitutions to study the process of sequence evolution, with the phylogeny assumed known.…”

Probabilistic models of eukaryotic evolution: time for integration

“…Dimension reduction methods have been proposed more recently to limit the number of branch-specific parameters invoked by the model [49]. Alternatively, models considering partitions of branches into a small set of categories, each characterized by its vector of equilibrium frequencies, have been developed [50].…”