Microbial life has dominated Earth’s history but left a sparse fossil record, greatly hindering our understanding of evolution in deep time. However, bacterial metabolism has left signatures in the geochemical record, most conspicuously the Great Oxidation Event (GOE). We combine machine learning and phylogenetic reconciliation to infer ancestral bacterial transitions to aerobic lifestyles, linking them to the GOE to calibrate the bacterial time tree. Extant bacterial phyla trace their diversity to the Archaean and Proterozoic, and bacterial families prior to the Phanerozoic. We infer that most bacterial phyla were ancestrally anaerobic and adopted aerobic lifestyles after the GOE. However, in the cyanobacterial ancestor, aerobic metabolism likely predated the GOE, which may have facilitated the evolution of oxygenic photosynthesis.
In recent years, phylogenetic reconciliation has emerged as a promising approach for studying microbial ecology and evolution. The core idea is to model how gene trees evolve along a species tree and to explain differences between them via evolutionary events including gene duplications, transfers, and losses. Here, we describe how phylogenetic reconciliation provides a natural framework for studying genome evolution and highlight recent applications including ancestral gene content inference, the rooting of species trees, and the insights into metabolic evolution and ecological transitions they yield. Reconciliation analyses have elucidated the evolution of diverse microbial lineages, from Chlamydiae to Asgard archaea, shedding light on ecological adaptation, host-microbe interactions, and symbiotic relationships. However, there are many opportunities for broader application of the approach in microbiology. Continuing improvements to make reconciliation models more realistic and scalable, and integration of ecological metadata such as habitat, pH, temperature, and oxygen use offer enormous potential for understanding the rich tapestry of microbial life.
ALE and GeneRax are tools for probabilistic gene tree-species tree reconciliation. Based on a common underlying statistical model of how gene trees evolve along species trees, these methods rely on gene vs. species tree discordance to infer gene duplication, transfer, and loss events, map gene family origins, and root species trees. Published analyses have used these methods to root species trees of Archaea, Bacteria, and several eukaryotic groups, as well as to infer ancestral gene repertoires. However, it was recently suggested that reconciliation-based estimates of duplication and transfer events using the ALE/GeneRax model were unreliable, with potential implications for species tree rooting. Here, we assess these criticisms and find that the methods are accurate when applied to simulated data and in generally good agreement with alternative methodological approaches on empirical data. In particular, ALE recovers variation in gene duplication and transfer frequencies across lineages that is consistent with the known biology of studied clades. In plants and opisthokonts, ALE recovers the consensus species tree root; in Bacteria-where there is less certainty about the root position-ALE agrees with alternative approaches on the most likely root region. Overall, ALE and related approaches are promising tools for studying genome evolution.
The timing of early cellular evolution, from the divergence of Archaea and Bacteria to the origin of eukaryotes, is poorly constrained. The ATP synthase complex is thought to have originated prior to the Last Universal Common Ancestor (LUCA) and analyses of ATP synthase genes, together with ribosomes, have played a key role in inferring and rooting the tree of life. We reconstruct the evolutionary history of ATP synthases using an expanded taxon sampling set and develop a phylogenetic cross-bracing approach, constraining equivalent speciation nodes to be contemporaneous, based on the phylogenetic imprint of endosymbioses and ancient gene duplications. This approach results in a highly resolved, dated species tree and establishes an absolute timeline for ATP synthase evolution. Our analyses show that the divergence of ATP synthase into F- and A/V-type lineages was a very early event in cellular evolution dating back to more than 4 Ga, potentially predating the diversification of Archaea and Bacteria. Our cross-braced, dated tree of life also provides insight into more recent evolutionary transitions including eukaryogenesis, showing that the eukaryotic nuclear and mitochondrial lineages diverged from their closest archaeal (2.67-2.19 Ga) and bacterial (2.58-2.12 Ga) relatives at approximately the same time, with a slightly longer nuclear stem-lineage.
Most of life’s diversity and history is microbial but it has left a meagre fossil record, greatly hindering understanding of evolution in deep time. However, the co-evolution of life and the Earth system has left signatures of bacterial metabolism in the geochemical record, most conspicuously the Great Oxidation Event (GOE) ∼2.33 billion years ago (Ga, (Poulton et al. 2021)), in which oxygenic photosynthesis and tectonism (Eguchi, Seales, and Dasgupta 2019) transformed Earth’s biosphere from dominantly anaerobic to aerobic. Here, we combine machine learning and phylogenetic reconciliation to infer ancestral transitions to aerobic lifestyles during bacterial evolution. Linking these transitions to the GOE provides new constraints to infer the timetree of Bacteria. We find that extant bacterial phyla are truly ancient, having radiated in the Archaean and the Proterozoic: the oldest include Bacillota (Firmicutes), which radiated 3.1-3.7 Ga, Cyanobacteria (3.3-3.5 Ga) and Patescibacteria (3-3.5 Ga). We show that most bacterial phyla were ancestrally anaerobic and that most transitions to an aerobic lifestyle post-dated the GOE. Our analyses trace oxygen production and consumption back to Cyanobacteria. From that starting point, horizontal transfer seeded aerobic lifestyles across bacterial diversity over hundreds of millions of years. Our analyses demonstrate that the diversification of aerobes proceeded in two waves corresponding to the GOE and to a second sustained rise in atmospheric O 2 at the dawn of the Palezoic (Krause et al. 2022).
Species tree-aware phylogenetic methods model how gene trees are generated along the species tree by a series of evolutionary events, including the duplication, transfer and loss of genes. Over the past ten years these methods have emerged as a powerful tool for inferring and rooting gene and species trees, inferring ancestral gene repertoires, and studying the processes of gene and genome evolution. However, these methods are complex and can be more difficult to use than traditional phylogenetic approaches. Method development is rapid, and it can be difficult to decide between approaches and interpret results. Here, we review ALE and GeneRax, two popular packages for reconciling gene and species trees, explaining how they work, how results can be interpreted, and providing a tutorial for practical analysis. It was recently suggested that reconciliation-based estimates of duplication and transfer frequencies are unreliable. We evaluate this criticism and find that, provided parameters are estimated from the data rather than being fixed based on prior assumptions, reconciliation-based inferences are in good agreement with the literature, recovering variation in gene duplication and transfer frequencies across lineages consistent with the known biology of studied clades. For example, published datasets support the view that transfers greatly outnumber duplications in most prokaryotic lineages. We conclude by discussing some limitations of current models and prospects for future progress. Significance statement Evolutionary trees provide a framework for understanding the history of life and organising biodiversity. In this review, we discuss some recent progress on statistical methods that allow us to combine information from many different genes within the framework of an overarching phylogenetic species tree. We review the advantages and uses of these methods and discuss case studies where they have been used to resolve deep branches within the tree of life. We conclude with the limitations of current methods and suggest how they might be overcome in the future.
Interpreting phylogenetic trees requires a root, which provides the direction of evolution and polarizes ancestor-descendant relationships. But inferring the root using genetic data is difficult, particularly in cases where the closest available outgroup is only distantly related, which are common for microbes. In this chapter, we present a workflow for estimating rooted species trees and the evolutionary history of the gene families that evolve within them using probabilistic gene tree-species tree reconciliation. We illustrate the pipeline using a small dataset of prokaryotic genomes, for which the example scripts can be run using modest computer resources. We describe the rooting method used in this work in the context or other rooting strategies and discuss some of the limitations and opportunities presented by probabilistic gene tree-species tree reconciliation methods.
Many organisms are able to incorporate exogenous DNA into their genomes. This process, called lateral gene transfer (LGT), has the potential to benefit the recipient organism by providing useful coding sequences, such as antibiotic resistance genes or enzymes which expand the organism's metabolic niche. For evolutionary biologists, LGTs have often been considered a nuisance because they complicate the reconstruction of the underlying species tree that many analyses aim to recover. However, LGT events between distinct organisms harbor information on the relative divergence time of the donor and recipient lineages. As a result transfers provide a novel and as yet mostly unexplored source of information to determine the order of divergence of clades, with the potential for absolute dating if linked to the fossil record.
A rooted bacterial tree is necessary to understand early evolution, but the position of the root is contested. Here, we model the evolution of 11,272 gene families to identify the root, extent of horizontal gene transfer (HGT), and the nature of the last bacterial common ancestor (LBCA). Our analyses root the tree between the major clades Terrabacteria and Gracilicutes and suggest that LBCA was a free-living flagellated, rod-shaped double-membraned organism. Contrary to recent proposals, our analyses reject a basal placement of the Candidate Phyla Radiation, which instead branches sister to Chloroflexota within Terrabacteria. While most gene families (92%) have evidence of HGT, overall, two-thirds of gene transmissions have been vertical, suggesting that a rooted tree provides a meaningful frame of reference for interpreting bacterial evolution.
The accrual of genomic data from both cultured and uncultured microorganisms provides new opportunities to develop systematic taxonomies based on evolutionary relationships. Previously, we established a bacterial taxonomy through the Genome Taxonomy Database. Here, we propose a standardized archaeal taxonomy that is derived from a 122-concatenated-protein phylogeny that resolves polyphyletic groups and normalizes ranks based on relative evolutionary divergence. The resulting archaeal taxonomy, which forms part of the Genome Taxonomy Database, is stable for a range of phylogenetic variables including marker gene selection, inference methods, corrections for rate heterogeneity and compositional bias, tree rooting scenarios and expansion of the genome database. Rank normalization is shown to robustly correct for substitution rates varying up to 30-fold using simulated datasets. Taxonomic curation follows the rules of the International Code of Nomenclature of Prokaryotes while taking into account proposals to formally recognize the rank of phylum and to use genome sequences as type material. This taxonomy is based on 2,392 archaeal genomes, 93.3% of which required one or more changes to their existing taxonomy, mainly owing to incomplete classification. We identify 16 archaeal phyla and reclassify 3 major monophyletic units from the former Euryarchaeota and one phylum that unites the Thaumarchaeota–Aigarchaeota–Crenarchaeota–Korarchaeota (TACK) superphylum into a single phylum. Resolving widespread incomplete and uneven archaeal classifications is achieved by a rank-normalized genome-based taxonomy.
An increasing wealth of genomic data from cultured and uncultured microorganisms provides the opportunity to develop a systematic taxonomy based on evolutionary relationships. Here we propose a standardized archaeal taxonomy, as part of the Genome Taxonomy Database (GTDB), derived from a 122 concatenated protein phylogeny that resolves polyphyletic groups and normalizes ranks based on relative evolutionary divergence (RED). The resulting archaeal taxonomy is stable under a range of phylogenetic variables, including marker genes, inference methods, corrections for rate heterogeneity and compositional bias, tree rooting scenarios, and expansion of the genome database. Rank normalization was shown to robustly correct for substitution rates varying up to 30-fold using simulated datasets. Taxonomic curation follows the rules of the International Code of Nomenclature of Prokaryotes (ICNP) while taking into account proposals to formally recognise the rank of phylum and to use genome sequences as type material. The taxonomy is based on 2,392 quality screened archaeal genomes, the great majority of which (93.3%) required one or more changes to their existing taxonomy, mostly as a result of incomplete classification. In total, 16 archaeal phyla are described, including reclassification of three major monophyletic units from the former Euryarchaeota and one phylum resulting from uniting the TACK superphylum into a single phylum. The taxonomy is publicly available at the GTDB website (https://gtdb.ecogenomic.org).
The reconstruction of the chromosomal organization of ancient genomes has many applications in comparative and evolutionary genomics. Here we propose a novel, methodological, use for these predicted ancestral syntenies, directly focused on phylogenomics. It is a way to assess the accuracy of gene trees and species trees. We use a method that reconstructs, from gene trees and extant gene orders, ancestral adjacencies, i.e. the immediate neighborhood between pairs of genes, independently for each pair. This independence allows to split the computations into many independent problems that can each be solved exactly using efficient algorithms, but might result in sets of ancestral adjacencies that are incompatible with the expected linear or circular structure of chromosomes. We show here that this drawback can actually be turned into a useful 1 This work benefited from the support of ComputeCanada.
Abstract Summary Here we present Zombi, a tool to simulate the evolution of species, genomes and sequences in silico, that considers for the first time the evolution of genomes in extinct lineages. It also incorporates various features that have not to date been combined in a single simulator, such as the possibility of generating species trees with a pre-defined variation of speciation and extinction rates through time, simulating explicitly intergenic sequences of variable length and outputting gene tree—species tree reconciliations. Availability and implementation Source code and manual are freely available in https://github.com/AADavin/ZOMBI/. Supplementary information Supplementary data are available at Bioinformatics online.
Motivation:A reconciliation is an annotation of the nodes of a gene tree with evolutionary events-for example, speciation, gene duplication, transfer, loss, etc.-along with a mapping onto a species tree. Many algorithms and software produce or use reconciliations but often using different reconciliation formats, regarding the type of events considered or whether the species tree is dated or not. This complicates the comparison and communication between different programs.Results:Here, we gather a consortium of software developers in gene tree species tree reconciliation to propose and endorse a format that aims to promote an integrative-albeit flexible-specification of phylogenetic reconciliations. This format, named recPhyloXML, is accompanied by several tools such as a reconciled tree visualizer and conversion utilities.Availability and implementation:http://phylariane.univ-lyon1.fr/recphyloxml/.
Biodiversity has always been predominantly microbial, and the scarcity of fossils from bacteria, archaea and microbial eukaryotes has prevented a comprehensive dating of the tree of life. Here, we show that patterns of lateral gene transfer deduced from an analysis of modern genomes encode a novel and abundant source of information about the temporal coexistence of lineages throughout the history of life. We use state-of-the-art species tree-aware phylogenetic methods to reconstruct the history of thousands of gene families and demonstrate that dates implied by gene transfers are consistent with estimates from relaxed molecular clocks in Bacteria, Archaea and Eukarya. We present the order of speciations according to lateral gene transfer data calibrated to geological time for three datasets comprising 40 genomes for Cyanobacteria, 60 genomes for Archaea and 60 genomes for Fungi. An inspection of discrepancies between transfers and clocks and a comparison with mammalian fossils show that gene transfer in microbes is potentially as informative for dating the tree of life as the geological record in macroorganisms.
Biodiversity has always been predominantly microbial and the scarcity of fossils from bacteria, archaea and microbial eukaryotes has prevented a comprehensive dating of the tree of life. Here we show that patterns of lateral gene transfer deduced from the analysis of modern genomes encode a novel and abundant source of information about the temporal coexistence of lineages throughout the history of life. We use new phylogenetic methods to reconstruct the history of thousands of gene families and demonstrate that dates implied by gene transfers are consistent with estimates from relaxed molecular clocks in Bacteria, Archaea and Eukaryotes. An inspection of discrepancies between transfers and clocks and a comparison with mammal fossils show that gene transfer in microbes is potentially as informative for dating the tree of life as the geological record in macroorganisms.
Lateral gene transfers between ancient species contain information about the relative timing of species diversification. Specifically, the ancestors of a donor species must have existed before the descendants of the recipient species. Hence, the detection of a transfer event can be translated into a time constraint between nodes of a phylogeny if the donor and recipient can be identified. When a set of transfers is detected by interpreting the phylogenetic discordance between gene trees and a species tree, the set of all deduced time constraints can be used to rank the species tree, i.e. order totally its internal nodes. Unfortunately lateral gene transfer detection is challenging and current methods produce a significant proportion of false positives. As a result, often, no ranking of the species tree is compatible with the full set of time constraints deduced from predicted transfers. Here we propose a method, implemented in a software called MaxTiC (Maximum Time Consistency), which takes as input a species tree and a series of (possibly inconsistent) time constraints between its internal nodes, weighted by confidence scores. MaxTiC outputs a ranked species tree compatible with a subset of constraints with maximum cumulated confidence score. We extensively test the method on simulated datasets, under a wide range of conditions that we compare to measures on biological datasets. In most conditions the obtained ranked tree is very close to the real one, confirming the potential of dating the history of life with transfers by maximizing time consistency. MaxTiC is freely available, distributed along with a documentation and several examples: https://github.com/ssolo/ALE/tree/master/maxtic .
To reconstruct the timing of the diversification of life on Earth, biologists combine fossil evidence with inferences drawn from the comparison of genome sequences. These inferences are based on the molecular clock or on a softer version of it, the relaxed molecular clock. This approach consists of estimating the divergence between sequences and then, assuming that mutations occur clockwise , trying to determine the age of the ancestral sequence. This method can be refined by using diverse models that relax the hypothesis of constant pace of evolution and consider that sequences can evolve at different speeds. Some models assume that these rates of evolution are independent along the different branches of the tree relating the different sequences of DNA; some others consider that the rates are correlated among related branches, so the rate of a given branch is inherited to some extent from the parental one. Which is of these methods perform best is still heavily debated. In spite of the sophistication of the different models, calculating these rates is not a trivial problem and the best estimates of divergence time have usually very wide confidence intervals. To overcome this problem scientists can use fossils, that can be independently dated using methods such as stratigraphy or radiometry. Fossils are useful because they provide external information that can be used to constrain the positions of the nodes in a species tree, improving the accuracy of the estimates of the molecular clock. Combining relaxed molecular clock estimates and fossil is in active field of research in phylogenetics [1]. However, fossils are extremely scarce in the geological record. For about 80 % of the history of life, all organisms were unicellular, which means that finding fossils becomes an almost impossible task. Bones and hard shells are easy to be preserved but they just became frequent after the Cambrian explosion, when all the major animal clades appear at sudden. Before that Earth was dominated by bacteria and to a minor extent, small eukaryotes. These organisms are extremely small organisms with no hard parts that can fossilize easily. On top of that, for the few existent fossils we have there is very little certainty about the clades to which they belong, since morphological features cannot be used to place them in a phylogenetic tree. This means that if we are interested in studying what happened in the distant past, we have very little help coming from fossils and we must rely almost exclusively in the information conveyed by the DNA. As we previously stated, this is a hard problem since the estimates of the molecular clock can vary widely. We need accurate calculations if we want to know for example when did Eukaryotes diversify or when did cyanobacteria appear on Earth. To overcome these problems, we propose a new method of dating, based on the DNA sequence complementary to the molecular clock. Lateral gene transfer (LGT) is a common and almost universal phenomenon in nature, where different species (sometimes even species belonging to different domains) exchange genes. This can be detected using differences between species trees and gene trees. We do this using ALE, a method to reconcile species trees and gene trees that allows.
Although the role of lateral gene transfer is well recognized in the evolution of bacteria, it is generally assumed that it has had less influence among eukaryotes. To explore this hypothesis, we compare the dynamics of genome evolution in two groups of organisms: cyanobacteria and fungi. Ancestral genomes are inferred in both clades using two types of methods: first, Count, a gene tree unaware method that models gene duplications, gains and losses to explain the observed numbers of genes present in a genome; second, ALE, a more recent gene tree-aware method that reconciles gene trees with a species tree using a model of gene duplication, loss and transfer. We compare their merits and their ability to quantify the role of transfers, and assess the impact of taxonomic sampling on their inferences. We present what we believe is compelling evidence that gene transfer plays a significant role in the evolution of fungi.