FastMG: a simple, fast, and accurate maximum likelihood procedure to estimate amino acid replacement rate matrices from large data sets

Data-specific substitution models improve protein-based phylogenetics

Calculating amino-acid substitution models that are specific for individual protein data sets is often difficult due to the computational burden of estimating large numbers of rate parameters. In this study, we tested the computational efficiency and accuracy of five methods used to estimate substitution models, namely Codeml, FastMG, IQ-TREE, P4 (maximum likelihood), and P4 (Bayesian inference). Data-specific substitution models were estimated from simulated alignments (with different lengths) that were generated from a known simulation model and simulation tree. Each of the resulting data-specific substitution models was used to calculate the maximum likelihood score of the simulation tree and simulated data that was used to calculate the model, and compared with the maximum likelihood scores of the known simulation model and simulation tree on the same simulated data. Additionally, the commonly-used empirical models, cpREV and WAG, were assessed similarly. Data-specific models performed better than the empirical models, which under-fitted the simulated alignments, had the highest difference to the simulation model maximum-likelihood score, clustered further from the simulation model in principal component analysis ordination, and inferred less accurate trees. Data-specific models and the simulation model shared statistically indistinguishable maximum-likelihood scores, indicating that the five methods were reasonably accurate at estimating substitution models by this measure. Nevertheless, tree statistics showed differences between optimal maximum likelihood trees. Unlike other model estimating methods, trees inferred using data-specific models generated with IQ-TREE and P4 (maximum likelihood) were not significantly different from the trees derived from the simulation model in each analysis, indicating that these two methods alone were the most accurate at estimating data-specific models. To show the benefits of using data-specific protein models several published data sets were reanalysed using IQ-TREE-estimated models. These newly estimated models were a better fit to the data than the empirical models that were used by the original authors, often inferred longer trees, and resulted in different tree topologies in more than half of the re-analysed data sets. The results of this study show that software availability and high computation burden are not limitations to generating better-fitting data-specific amino-acid substitution models for phylogenetic analyses.

CherryML: scalable maximum likelihood estimation of phylogenetic models

Phylogenetic models of molecular evolution are central to numerous biological applications spanning diverse timescales, from hundreds of millions of years involving orthologous proteins to just tens of days relating to single cells within an organism. A fundamental problem in these applications is estimating model parameters, for which maximum likelihood estimation is typically employed. Unfortunately, maximum likelihood estimation is a computationally expensive task, in some cases prohibitively so. To address this challenge, we here introduce CherryML, a broadly applicable method that achieves several orders of magnitude speedup by using a quantized composite likelihood over cherries in the trees. The massive speedup offered by our method should enable researchers to consider more complex and biologically realistic models than previously possible. Here we demonstrate CherryML's utility by applying it to estimate a general 400 × 400 rate matrix for residue-residue coevolution at contact sites in three-dimensional protein structures; we estimate that using current state-of-the-art methods such as the expectation-maximization algorithm for the same task would take >100,000 times longer.

Estimating amino acid substitution models for metazoan evolutionary studies

Amino acid substitution models represent the substitution rates among amino acids during the evolution of protein sequences. The models are a prerequisite for maximum likelihood or Bayesian methods to analyse the phylogenetic relationships among species based on their protein sequences. Estimating amino acid substitution models requires large protein datasets and intensive computation. In this paper, we presented the estimation of both time-reversible model (Q.met) and time non-reversible model (NQ.met) for multicellular animals (Metazoa). Analyses showed that the Q.met and NQ.met models were significantly better than existing models in analysing metazoan protein sequences. Moreover, the time non-reversible model NQ.met enables us to reconstruct the rooted phylogenetic tree for Metazoa. We recommend researchers to employ the Q.met and NQ.met models in analysing metazoan protein sequences.

Actinomyces marmotae sp. nov. and Actinomyces procaprae sp. nov. isolated from wild animals and reclassification of Actinomyces liubingyangii and Actinomyces tangfeifanii as Boudabousia liubingyangii comb. nov. and Boudabousia tangfeifanii comb. nov., respectively

Four Gram-stain-positive, catalase-negative, non-spore-forming, rod-shaped bacterial strains (zg-325^T, zg329, dk561^T and dk752) were isolated from the respiratory tract of marmot (Marmota himalayana) and the faeces of Tibetan gazelle (Procapra picticaudata) from the Qinghai-Tibet Plateau of PR China. The results of 16S rRNA gene sequence-based phylogenetic analyses indicated that strains zg-325^T and dk561^T represent members of the genus Actinomyces, most similar to Actinomyces denticolens DSM 20671^T and Actinomyces ruminicola B71^T, respectively. The DNA G+C contents of strains zg-325^T and dk561^T were 71.6 and 69.3 mol%, respectively. The digital DNA-DNA hybridization values of strains zg-325^T and dk561^T with their most closely related species were below the 70 % threshold for species demarcation. The four strains grew best at 35 °C in air containing 5 % CO₂ on brain heart infusion (BHI) agar with 5 % sheep blood. All four strains had C_18:1ω9c and C_16:0 as the major cellular fatty acids. MK-8 and MK-9 were the major menaquinones in zg-325^T while MK-10 was predominant in dk561^T. The major polar lipids included diphosphatidylglycerol and phosphatidylinositol. On the basis of several lines of evidence from phenotypic and phylogenetic analyses, zg-325^T and dk561^T represent novel species of the genus Actinomyces, for which the name Actinomyces marmotae sp. nov. and Actinomyces procaprae sp. nov. are proposed. The type strains are zg-325^T (=GDMCC 1.1724^T=JCM 34091^T) and dk561^T (=CGMCC 4.7566^T=JCM 33484^T). We also propose, on the basis of the phylogenetic results herein, the reclassification of Actinomyces liubingyangii and Actinomyces tangfeifanii as Boudabousia liubingyangii comb. nov. and Boudabousia tangfeifanii comb. nov., respectively.

MtOrt: an empirical mitochondrial amino acid substitution model for evolutionary studies of Orthoptera insects

BACKGROUND

Amino acid substitution models play an important role in inferring phylogenies from proteins. Although different amino acid substitution models have been proposed, only a few were estimated from mitochondrial protein sequences for specific taxa such as the mtArt model for Arthropoda. The increasing of mitochondrial genome data from broad Orthoptera taxa provides an opportunity to estimate the Orthoptera-specific mitochondrial amino acid empirical model.

RESULTS

We sequenced complete mitochondrial genomes of 54 Orthoptera species, and estimated an amino acid substitution model (named mtOrt) by maximum likelihood method based on the 283 complete mitochondrial genomes available currently. The results indicated that there are obvious differences between mtOrt and the existing models, and the new model can better fit the Orthoptera mitochondrial protein datasets. Moreover, topologies of trees constructed using mtOrt and existing models are frequently different. MtOrt does indeed have an impact on likelihood improvement as well as tree topologies. The comparisons between the topologies of trees constructed using mtOrt and existing models show that the new model outperforms the existing models in inferring phylogenies from Orthoptera mitochondrial protein data.

CONCLUSIONS

The new mitochondrial amino acid substitution model of Orthoptera shows obvious differences from the existing models, and outperforms the existing models in inferring phylogenies from Orthoptera mitochondrial protein sequences.

FLAVI: An Amino Acid Substitution Model for Flaviviruses

Amino acid substitution models represent substitution rates among amino acids during the evolution. The models play an important role in analyzing protein sequences, especially inferring phylogenies. The rapid evolution of flaviviruses is expanding the threat in public health. A number of models have been estimated for some viruses, however, they are unable to properly represent amino acid substitution patterns of flaviviruses. In this study, we collected protein sequences from the flavivirus genus to specifically estimate an amino acid substitution model, called FLAVI, for flaviviruses. Experiments showed that the collected dataset was sufficient to estimate a stable model. More importantly, the FLAVI model was remarkably better than other existing models in analyzing flavivirus protein sequences. We recommend researchers to use the FLAVI model when studying protein sequences of flaviviruses or closely related viruses.

mtProtEvol: the resource presenting molecular evolution analysis of proteins involved in the function of Vertebrate mitochondria

BACKGROUND

Heterotachy is the variation in the evolutionary rate of aligned sites in different parts of the phylogenetic tree. It occurs mainly due to epistatic interactions among the substitutions, which are highly complex and make it difficult to study protein evolution. The vast majority of computational evolutionary approaches for studying these epistatic interactions or their evolutionary consequences in proteins require high computational time. However, recently, it has been shown that the evolution of residue solvent accessibility (RSA) is tightly linked with changes in protein fitness and intra-protein epistatic interactions. This provides a computationally fast alternative, based on comparison of evolutionary rates of amino acid replacements with the rates of RSA evolutionary changes in order to recognize any shifts in epistatic interaction.

RESULTS

Based on RSA information, data randomization and phylogenetic approaches, we constructed a software pipeline, which can be used to analyze the evolutionary consequences of intra-protein epistatic interactions with relatively low computational time. We analyzed the evolution of 512 protein families tightly linked to mitochondrial function in Vertebrates and created "mtProtEvol", the web resource with data on protein evolution. In strict agreement with lifespan and metabolic rate data, we demonstrated that different functional categories of mitochondria-related proteins subjected to selection on accelerated and decelerated RSA rates in rodents and primates. For example, accelerated RSA evolution in rodents has been shown for Krebs cycle enzymes, respiratory chain and reactive oxygen species metabolism, while in primates these functions are stress-response, translation and mtDNA integrity. Decelerated RSA evolution in rodents has been demonstrated for translational machinery and oxidative stress response components.

CONCLUSIONS

mtProtEvol is an interactive resource focused on evolutionary analysis of epistatic interactions in protein families involved in Vertebrata mitochondria function and available at http://bioinfodbs.kantiana.ru/mtProtEvol /. This resource and the devised software pipeline may be useful tool for researchers in area of protein evolution.

Improved mitochondrial amino acid substitution models for metazoan evolutionary studies

BACKGROUND

Amino acid substitution models play an essential role in inferring phylogenies from mitochondrial protein data. However, only few empirical models have been estimated from restricted mitochondrial protein data of a hundred species. The existing models are unlikely to represent appropriately the amino acid substitutions from hundred thousands metazoan mitochondrial protein sequences.

RESULTS

We selected 125,935 mitochondrial protein sequences from 34,448 species in the metazoan kingdom to estimate new amino acid substitution models targeting metazoa, vertebrates and invertebrate groups. The new models help to find significantly better likelihood phylogenies in comparison with the existing models. We noted remarkable distances from phylogenies with the existing models to the maximum likelihood phylogenies that indicate a considerable number of incorrect bipartitions in phylogenies with the existing models. Finally, we used the new models and mitochondrial protein data to certify that Testudines, Aves, and Crocodylia form one separated clade within amniotes.

CONCLUSIONS

We introduced new mitochondrial amino acid substitution models for metazoan mitochondrial proteins. The new models outperform the existing models in inferring phylogenies from metazoan mitochondrial protein data. We strongly recommend researchers to use the new models in analysing metazoan mitochondrial protein data.