Biology subjects

Susko, E.

Publications and source records attributed to Susko, E..

12 recordsLinked to original sources

bioRxiv2026

PartitionFinder-mAIC: Phylogenetic Partitioning using Marginal Akaike Information Criterion

Partition models are widely used in phylogenomic analyses to account for heterogeneous evolutionary processes across different regions or loci of a sequence alignment. How alignment regions are grouped into partitions (the partitioning scheme) affects both the degree of over- or under-parameterization and the accuracy of downstream phylogenetic inferences. PartitionFinder is a widely adopted framework for selecting an optimal partitioning scheme. Using Akaike information criterion (AIC) and Bayesian information criterion (BIC), PartitionFinder merges partitions with similar evolutionary processes to avoid model overfitting. However, AIC and BIC are based on conditional likelihoods that treat partition assignments as fixed, whereas the recently introduced marginal AIC (mAIC) averages site likelihoods over the models of all partitions, providing a more appropriate criterion for inferring global parameters such as tree topology and branch lengths (Susko et al. 2026). Here, we implement mAIC for partition models in IQ-TREE 3 and integrate it into the PartitionFinder algorithms. Using a range of simulated and empirical DNA and protein datasets, we show that PartitionFinder-mAIC yields partitioning schemes with fewer partitions than those selected by AIC or BIC, and additionally improves phylogenetic inference at most key branches of the green plant evolution. The new PartitionFinder-mAIC is available in IQ-TREE version 3.1.4 with the command-line option -merit mAIC.

evolutionary biology↗

bioRxiv2026

GTRspmix: Capturing Heterogeneity of Exchangeabilities Across Sites to Improve Protein Phylogenetics

Site rate and profile mixture models capture the heterogeneity of the amino acid substitution process across sites. However, these models typically use a single matrix of amino acid exchangeabilities and ignore potential heterogeneities of these exchangeabilities across sites. Simply combining multiple exchangeability matrices with rate and profile mixtures leads to a combinatorial explosion of mixture components and a prohibitive increase in free parameters. Here, we introduce GTRspmix, a novel framework that incorporates multiple exchangeability matrices into profile and site rate mixture models while effectively managing model complexity. GTRspmix employs a clustering-based strategy that groups profiles and assigns a distinct exchangeability matrix to each profile cluster. Evaluations using both empirical and simulated datasets demonstrate that GTRspmix fits empirical data significantly better than conventional models, and that overparameterization does not present a problem for sufficiently large alignments. Based on these results, we estimated general-purpose empirical models (SXXpfamCYY series available in IQ-TREE3) from the Pfam database. These general-purpose models not only fit data much better, but they also influence branch length and tree topology estimates, effectively mitigating long-branch attraction artifacts. Because the total number of rate matrices remains manageable, the computational efficiency of the inference is identical to that of conventional profile mixture models (e.g., LG+C60+G4). GTRspmix provides a more realistic and flexible model of protein evolution, offering a robust foundation for the inference of reliable phylogenetic trees.

evolutionary biology↗

bioRxiv2026

A New Information Theoretic Approach Shows that Mixture Models Outperform Partitioned Models for Phylogenetic Analyses of Amino Acid Data

Partitioned and mixture models are widely employed in Maximum Likelihood phylogenetic analyses of large genomic datasets. Comparing the fit of the two types of models has been challenging, because standard information-theoretic approaches cannot be applied. Mixture models are increasingly popular for the analysis of amino acid datasets and can lead to different conclusions compared to partitioned models. This raises an important question - which type of model tends to perform better? Susko et al. (2026) recently introduced the marginal Akaike information criterion (mAIC), which allows mixture models and partitioned models to be directly compared for the first time. Here, we use the mAIC and a range of other approaches to compare the fit of mixture and partitioned models across a diverse set of empirical datasets. We show that mixture models are universally favoured on amino acid datasets. This has important implications for interpreting empirical analyses and suggests that continued development of mixture models is an important avenue for future research.

evolutionary biology↗

bioRxiv2025

Modeling site-and-branch-heterogeneity with GFmix

AO_SCPLOWBSTRACTC_SCPLOWPhylogenetic trees are often inferred from protein sequences sampled from diverse taxa across the tree of life. The compositions of these amino acid sequences may be heterogeneous across both sites and branches, particularly if deep phylogenetic divergences are the focus. Under some conditions, failure to model this compositional heterogeneity can lead to phylogenetic artefacts. However, the computational cost of phylogenetic inference with models accounting for compositional heterogeneity can be prohibitive. The originally proposed site-and-branch-heterogeneous GFmix model accounts for changing relative frequencies of G, A, R, and P (GARP) vs. F, Y, M, I, N, and K (FYMINK) amino acids resulting from extreme variation in G+C content among taxa. This GFmix model modifies a fitted site-heterogeneous profile mixture model in a branch-specific manner using parameters that reflect branch-specific amino acid compositions. This approach has been shown to improve likelihoods and reduce compositional artifacts. However, the original implementation of the model includes constraints which may sacrifice accuracy for computability and is limited to modeling variation in GARP/FYMINK composition. Here we investigate the properties of the original GFmix model in greater depth and present several improvements to the model. The improved GFmix models permit fewer constraints on branch-specific composition parameters, allow modeling of user-defined compositional heterogeneity, and provide for full maximum-likelihood optimization of parameters. We have also developed new methods for detecting compositional heterogeneity directly from sequence data. Analyses of simulated site-and-branch-heterogeneous data indicates that the improved GFmix models better estimate branch-specific compositions and branch lengths in heterogeneous trees. We applied the various versions of the GFmix model to a real dataset with known compositional heterogeneity artefacts. We find that the most complex GFmix model with full maximum likelihood parameter optimization consistently supports the correct tree over the artefactual tree with improved likelihoods. All versions of the GFmix model are available from https://www.mathstat.dal.ca/~tsusko/software.html.

evolutionary biology↗

bioRxiv2024

A robustly rooted tree of eukaryotes reveals their excavate ancestry.

The eukaryote Tree of Life (eToL) depicts the relationships among all eukaryotic organisms; its root represents the last eukaryotic common ancestor (LECA) from which all extant complex lifeforms are descended. Locating this root is crucial for reconstructing the features of LECA, both as the endpoint of eukaryogenesis and the start-point for the evolution of the myriad complex traits underpinning the diversification of living eukaryotes. However, the position of the root remains contentious due to pervasive phylogenetic artefacts stemming from inadequate evolutionary models, poor taxon sampling, and limited phylogenetic signal. Here, we estimate the root of the eToL with unprecedented resolution based on a new, much larger, dataset of mitochondrial proteins which includes all known eukaryotic supergroups. Our comprehensive analyses with state-of-the-art phylogenetic models reveal that the eukaryotic root lies between two multi-supergroup assemblages: Opimoda+ and Diphoda+. Compellingly, this position is consistently supported across different models and robustness analyses. Notably, groups containing typical excavates are placed on both sides of the root, suggesting the complex features of the excavate cell architecture trace back to LECA. This study is the most comprehensive phylogenetic investigation of the eukaryote root to date, shedding light on the ancestral cells from which extant eukaryotes arose and providing a crucial framework for investigating the origin and evolution of canonical eukaryotic features.

evolutionary biology↗

bioRxiv2024

GTRpmix: A linked general-time reversible model for profile mixture models

Profile mixture models capture distinct biochemical constraints on the amino acid substitution process at different sites in proteins. These models feature a mixture of time-reversible models with a common set of amino acid exchange rates (a matrix of exchangeabilities) and distinct sets of equilibrium amino acid frequencies known as profiles. Combining the exchangeability matrix with each profile generates the matrix of instantaneous rates of amino acid exchange for that profile. Currently, empirically estimated exchangeability matrices (e.g., the LG or WAG matrices) are widely used for phylogenetic inference under profile mixture models. However, such matrices were originally estimated using site homogeneous models with a single set of equilibrium amino acid frequencies; therefore unlikely to be optimal for site heterogeneous profile mixture models. Here we describe the GTRpmix model, implemented in IQ-TREE2, that allows maximum likelihood estimation of a common set of exchangeabilities for all site classes under any profile mixture model. We show that exchangeability matrices estimated in the presence of a site-heterogeneous profile mixture model differ markedly from the widely used LG matrix and dramatically improve model fit and topological estimation accuracy for empirical test cases. Because the GTRpmix model is computationally expensive, we provide two exchangeability matrices estimated from large concatenated phylogenomic supermatrices under the C60 profile mixture model that can be used as fixed matrices for phylogenetic analyses. One of these, called Eukaryotic Linked Mixture (ELM), is designed for phylogenetic analysis of proteins encoded by nuclear genomes of eukaryotes, and the other, Eukaryotic and Archeal Linked mixture (EAL), for reconstructing relationships between eukaryotes and Archaea. These matrices when combined with profile mixture models fit data much better and have improved topology estimation relative to the empirical LG matrix combined with the same underlying mixture models. Version v2.3.1 of IQ-TREE2 implementing these models is available at www.iqtree.org.

molecular biology↗

bioRxiv2023

Several independent adaptations of archaea to hypersaline environments

Several archaeal lineages thrive in high, saturating salt concentrations. These extremely halophilic archaea, including Halobacteria, Nanohaloarchaeota, Methanonatronarchaeia, and Haloplasmatales, must maintain osmotic equilibrium with their environment. For this, they use a salt-in strategy, which involves pumping molar concentrations of potassium into the cells, which, in turn, has led to extensive proteome-wide modifications to prevent protein aggregation. However, the evolutionary history underlying these adaptations remains poorly understood. In particular, the number of times that these dramatic proteome-sweeping changes occurred is unclear due to the conflicting phylogenetic positions found for several of these lineages. Here, we present a resolved phylogeny of extremely halophilic archaea obtained using improved taxon sampling and state-of-the-art phylogenetic approaches designed to cope with the strong compositional biases of their proteomes. We describe two new uncultured lineages, Afararchaeaceae and Asboarchaeaceae, which break the long branches at the base of Haloarchaea and Nanohaloarchaeota, respectively. Our extensive phylogenomic analyses show that at least four independent adaptations to extreme halophily occurred during archaeal evolution. Finally, gene-tree/species-tree reconciliation suggests that gene duplication and horizontal gene transfer played an important role in this process, for example, by spreading key genes (such as those encoding potassium transporters) across the various extremely halophilic lineages.

evolutionary biology↗

bioRxiv2022

Are profile mixture models over-parameterized?

Biochemical constraints on the admissible amino acids at specific sites in proteins leads to heterogeneity of the amino acid substitution process over sites in alignments. It is well known that phylogenetic models of protein sequence evolution that do not account for site heterogeneity are prone to long-branch attraction (LBA) artifacts. Profile mixture models were developed to model heterogeneity of preferred amino acids at sites via a finite distribution of site classes each with a distinct set of equilibrium amino acid frequencies. However, it is unknown whether the large number of parameters in such models associated with the many amino acid frequency classes can adversely affect tree topology estimates because of over-parameterization. Here we demonstrate theoretically that for long sequences, over-parameterization does not create problems for estimation with profile mixture models. Under mild conditions, tree, amino acid frequencies and other model parameters converge to true values as sequence length increases, even when there are large numbers of components in the frequency profile distributions. Because large sample theory does not necessarily imply good behavior for shorter alignments we explore performance of these models with short alignments simulated with tree topologies that are prone to LBA artifacts. We find that over-parameterization is not a problem for complex profile mixture models even when there are many amino acid frequency classes. In fact, simple models with few site classes behave poorly. Interestingly, we also found that misspecification of the amino acid frequency classes does not lead to increased LBA artifacts as long as the estimated cumulative distribution function of the amino acid frequencies at sites adequately approximates the true one. In contrast, misspecification of the amino acid exchangeability rates can severely negatively affect parameter estimation. Finally, we explore the effects of including in the profile mixture model an additional F-class representing the overall frequencies of amino acids in the data set. Surprisingly, the F-class does not help parameter estimation significantly, and can decrease the probability of correct tree estimation, depending on the scenario, even though it tends to improve likelihood scores.

evolutionary biology↗

bioRxiv2021

Conditions under which distributions of edge length ratios on phylogenetic trees can be used to order evolutionary events

Two recent high profile studies have attempted to use edge (branch) length ratios from large sets of phylogenetic trees to determine the relative ages of genes of different origins in the evolution of eukaryotic cells. This approach can be straightforwardly justified if substitution rates are constant over the tree for a given protein. However, such strict molecular clock assumptions are not expected to hold on the billion-year timescale. Here we propose an alternative set of conditions under which comparisons of edge length distributions from multiple sets of phylogenies of proteins with different origins can be validly used to discern the order of their origins. We also point out scenarios where these conditions are not expected to hold and caution is warranted.

evolutionary biology↗

bioRxiv2020

MLS3: A New Type of Multilevel Selection

In most multispecies multilevel selection (MLS) models, offspring communities are generated by random assembly of individuals in numbers reflecting sizes of parental communities releasing them (MLS1), or by differential community dispersal based on a community-level trait such as size (MLS2). In both, offspring communities colonize vacant spaces: different communities never compete for the same space. Here we propose a third MLS type (MLS3) where multispecies communities disperse (migrate) into already-occupied spaces, larger communities more frequently. Conspecific variants compete, often opposing selection for community size against fitness within species. This makes the outcome of MLS3 less apparent than MLS1 and MLS2 where such tension is absent. Our simulations show that, if community size depends strongly on reduction in the fitness of individual community members, such a reduction (comprising a sort of "inter-species altruism") will evolve. The framework we present represents a step toward conceptualizing community coalescence in the context of metacommunities.

evolutionary biology↗

bioRxiv2020

The ups and downs of amino acid co-evolution: evolutionary Stokes and anti-Stokes shifts

The most fundamental form of epistasis occurs between residues within a protein. Epistatic interactions can have significant consequences for evolutionary dynamics. For example, a substitution to a deleterious amino acid may be compensated for by replacements at other sites which increase its propensity (a function of its average fitness) over time - this is the evolutionary Stokes shift. We discovered that an opposite trend -the decrease in amino acid propensity with time-can also occur via the same epistatic dynamics. We define this novel and pervasive phenomenon as the evolutionary anti-Stokes shift. Our extensive simulations of three natural proteins show that evolutionary Stokes and anti-Stokes shifts occur with similar frequencies and magnitudes across the protein. This high-lights that decreasing amino acid propensities, on their own, are not conclusive evidence of adaptive responses to a changing environment. We find that stabilizing substitutions are often permissive (i.e., expand potential evolutionary paths) whereas destabilizing substitutions are restrictive. We show how these dynamics explain the variations in amino acid propensities associated with both evolutionary shifts in propensities.

evolutionary biology↗

bioRxiv2018

An updated phylogeny of the Alphaproteobacteria reveals that the Rickettsiales and Holosporales have independent origins

The Alphaproteobacteria is an extraordinarily diverse and ancient group of bacteria. Previous attempts to infer its deep phylogeny have been plagued with methodological artefacts. To overcome this, we analyzed a dataset of 200 single-copy and conserved genes and employed diverse strategies to reduce compositional artefacts. Such strategies include using novel dataset-specific profile mixture models and recoding schemes, and removing sites, genes and taxa that are compositionally biased. We show that the Rickettsiales and Holosporales (both groups of intracellular parasites of eukaryotes) are not sisters to each other, but instead, the Holosporales has a derived position within the Rhodospirillales. Furthermore, we find that the Rhodospirillales might be paraphyletic and that the Geminicoccaceae could be sister to all ancestrally free-living alphaproteobacteria. Our robust phylogeny will serve as a framework for future studies that aim to place mitochondria, and novel environmental diversity, within the Alphaproteobacteria.

evolutionary biology↗