Persistent, Private, and Mobile Genes: A Model for Gene Dynamics in Evolving Pangenomes

The pangenome of a species is the set of all genes carried by at least one member of the species. In bacteria, pangenomes can be much larger than the set of genes carried by a single organism. Many questions remain unanswered regarding the evolutionary forces shaping the patterns of the presence/absence of genes in pangenomes of a given species. We introduce a new model for bacterial pangenome evolution along a species phylogeny that explicitly describes the timing of appearance of each gene in the species and accounts for three generic types of gene evolutionary dynamics: persistent genes that are present in the ancestral genome, private genes that are specific to a given clade, and mobile genes that are imported once into the gene pool and then undergo frequent horizontal gene transfers. We call this model the Persistent-Private-Mobile (PPM) model. We develop an algorithm fitting the PPM model and apply it to a dataset of 902 Salmonella enterica genomes. We show that the best fitting model is able to reproduce the global pattern of some multivariate statistics like the gene frequency spectrum and the parsimony vs. frequency plot. Moreover, the gene classification induced by the PPM model allows us to study the position of accessory genes on the chromosome depending on their category, as well as the gene functions that are most present in each category. This work paves the way for a mechanistic understanding of pangenome evolution, and the PPM model developed here could be used for dynamics-aware gene classification.

Genomic epidemiology of Staphylococcus aureus from the Iberian Peninsula highlights the expansion of livestock associated-CC398 towards wildlife

Staphylococcus aureus is a versatile pathobiont, exhibiting a broad host range, including humans, other mammals, and avian species. Host specificity determinants, virulence, and antimicrobial resistance genes are often shared by strains circulating at the animal-human interface. While transmission dynamics studies have shown strain exchange between humans and livestock, knowledge of the source, genetic diversification, and transmission drivers of S. aureus in wildlife lag behind. In this work, we explore a wide array of S. aureus genomes from different sources in the Iberian Peninsula to understand population structure, gene content and niche adaptation at the human-livestock-wildlife nexus. Through Bayesian inference, we address the hypothesis that S. aureus strains in wildlife originate from humanized landscapes, either from contact with humans or through interactions with livestock. Phylogenetic reconstruction applied to whole genome sequence data was completed with a dataset of 450 isolates featuring multiple clones from the 1990-2022 period and a subset of CC398 strains representing the 2008-2022 period. Phylodynamic signatures of S. aureus from the Iberian Peninsula suggest widespread circulation of most clones among humans before jumping to other hosts. The number of transitions of CC398 strains within each host category (human, livestock, wildlife) was high (88.26 %), while the posterior probability of transitions from livestock to wildlife was remarkably high (0.99). Microbial genome-wide association analysis did not evidence genome rearrangements nor biomarkers suggesting S. aureus niche adaptation to wildlife, thus supporting recent spill overs. Altogether, our findings indicate that S. aureus isolates collected in the past years from wildlife most likely represent multiple introduction events from livestock. The clonal origin of CC398 and its potential to disseminate and evolve through different animal host species are highlighted, calling for management practices at the livestock-wildlife axis to improve biosecurity and thus restrict S. aureus transmission and niche expansion along gradients of human influence.

Unravelling the complex interplay between antibiotic consumption and adaptive changes in methicillin-resistant Staphylococcus aureus

OBJECTIVES

This study aims to elucidate the genomic dynamics driving the emergence of antimicrobial resistance (AMR), with a specific focus on the interplay between AMR and antimicrobial usage.

METHODS

We conducted a comprehensive analysis using a ST239 methicillin-resistant Staphylococcus aureus (MRSA) dataset over a continuous 12-year period from a single hospital. Genomic analyses were performed tracking the changes in MRSA populations, particularly the emergence of reduced vancomycin susceptibility, and assessing the impact of glycopeptide use on these emergence events.

RESULTS

Our findings reveal a significant correlation between hospital glycopeptide usage and the selection of MRSA strains with reduced vancomycin susceptibility. Genomic analyses provided insights into the molecular mechanisms driving resistance emergence, including the slowing of the molecular clock rate in response to heightened antimicrobial consumption.

CONCLUSIONS

In conclusion, this study the highlights the complex dynamics between AMR and antimicrobial use at the hospital level. The observed correlation between antimicrobial consumption and the development of less susceptible MRSA strains underscores the importance of antimicrobial stewardship programmes and the establishment of optimal consumption thresholds for mitigating AMR effectively.

Quantification and modeling of turnover dynamics of de novo transcripts in Drosophila melanogaster

Most of the transcribed eukaryotic genomes are composed of non-coding transcripts. Among these transcripts, some are newly transcribed when compared to outgroups and are referred to as de novo transcripts. De novo transcripts have been shown to play a major role in genomic innovations. However, little is known about the rates at which de novo transcripts are gained and lost in individuals of the same species. Here, we address this gap and estimate the de novo transcript turnover rate with an evolutionary model. We use DNA long reads and RNA short reads from seven geographically remote samples of inbred individuals of Drosophila melanogaster to detect de novo transcripts that are gained on a short evolutionary time scale. Overall, each sampled individual contains around 2500 unspliced de novo transcripts, with most of them being sample specific. We estimate that around 0.15 transcripts are gained per year, and that each gained transcript is lost at a rate around 5× 10-5 per year. This high turnover of transcripts suggests frequent exploration of new genomic sequences within species. These rate estimates are essential to comprehend the process and timescale of de novo gene birth.

Rapid expansion of Neisseria gonorrhoeae ST7827 clone in Australia, with variable ceftriaxone phenotype unexplained by genotype

BACKGROUND

Neisseria gonorrhoeae is identified as a priority pathogen due to its capacity to rapidly develop antimicrobial resistance (AMR). Following the easing of SARS-CoV-2 pandemic travel restrictions across international borders in the state of New South Wales (NSW), Australia, a surge of gonococcal isolates with raised ceftriaxone MIC values were detected.

METHODS

All N. gonorrhoeae isolates (n = 150) with increased ceftriaxone MIC values in NSW between 1 January 2021 and July 2022 from males and females from all sites were sequenced.

RESULTS

A new emergence and rapid expansion of an N. gonorrhoeae ST7827 clone was documented within NSW, Australia and provides further evidence of the ability of N. gonorrhoeae to undergo sufficient genomic changes and re-emerge as a geographically restricted subclone. Mapping AMR determinants to MIC results did not reveal any genomic pattern that correlated with MIC values.

CONCLUSIONS

The rapid dissemination and establishment of this clone at the population level is a new and concerning demonstration of the agility of this pathogen, and underscores concerns about similar incursions and establishment of MDR clones. Moreover, it is notable that in this context the AMR genotype-phenotype correlates remain unclear, which requires further investigation to enable better understanding of genomic aspects of AMR in N. gonorrhoeae.

A multidrug-resistant Salmonella enterica Typhimurium DT104 complex lineage circulating among humans and cattle in the USA lost the ability to produce pertussis-like toxin ArtAB

Salmonella enterica subsp. enterica serotype Typhimurium definitive type 104 (DT104) can infect both humans and animals and is often multidrug-resistant (MDR). Previous studies have indicated that, unlike most S . Typhimurium, the overwhelming majority of DT104 strains produce pertussis-like toxin ArtAB via prophage-encoded genes artAB . However, DT104 that lack artAB have been described on occasion. Here, we identify an MDR DT104 complex lineage circulating among humans and cattle in the USA, which lacks artAB (i.e. the ‘U.S. artAB -negative major clade’; n =42 genomes). Unlike most other bovine- and human-associated DT104 complex strains from the USA (n =230 total genomes), which harbour artAB on prophage Gifsy-1 (n =177), members of the U.S. artAB -negative major clade lack Gifsy-1, as well as anti-inflammatory effector gogB . The U.S. artAB -negative major clade encompasses human- and cattle-associated strains isolated from ≥11 USA states over a 20-year period. The clade was predicted to have lost artAB , Gifsy-1 and gogB circa 1985–1987 (95 % highest posterior density interval 1979.0–1992.1). When compared to DT104 genomes from other regions of the world (n =752 total genomes), several additional, sporadic artAB , Gifsy-1 and/or gogB loss events among clades encompassing five or fewer genomes were observed. Using phenotypic assays that simulate conditions encountered during human and/or bovine digestion, members of the U.S. artAB -negative major clade did not differ from closely related Gifsy-1/artAB /gogB -harbouring U.S. DT104 complex strains (ANOVA raw P >0.05); thus, future research is needed to elucidate the roles that artAB , gogB and Gifsy-1 play in DT104 virulence in humans and animals.

Robust analysis of prokaryotic pangenome gene gain and loss rates with Panstripe

Horizontal gene transfer (HGT) plays a critical role in the evolution and diversification of many microbial species. The resulting dynamics of gene gain and loss can have important implications for the development of antibiotic resistance and the design of vaccine and drug interventions. Methods for the analysis of gene presence/absence patterns typically do not account for errors introduced in the automated annotation and clustering of gene sequences. In particular, methods adapted from ecological studies, including the pangenome gene accumulation curve, can be misleading as they may reflect the underlying diversity in the temporal sampling of genomes rather than a difference in the dynamics of HGT. Here, we introduce Panstripe, a method based on generalized linear regression that is robust to population structure, sampling bias, and errors in the predicted presence/absence of genes. We show using simulations that Panstripe can effectively identify differences in the rate and number of genes involved in HGT events, and illustrate its capability by analyzing several diverse bacterial genome data sets representing major human pathogens.

Evolution of the connectivity and indispensability of a transferable gene: the simplicity hypothesis

BACKGROUND

The number of interactions between a transferable gene or its protein product and genes or gene products native to its microbial host is referred to as connectivity. Such interactions impact the tendency of the gene to be retained by evolution following horizontal gene transfer (HGT) into a microbial population. The complexity hypothesis posits that the protein product of a transferable gene with lower connectivity is more likely to function in a way that is beneficial to a new microbial host compared to the protein product of a transferable gene with higher connectivity. A gene with lower connectivity is consequently more likely to be fixed in any microbial population it enters by HGT. The more recently proposed simplicity hypothesis posits that the connectivity of a transferable gene might increase over time within any single microbial population due to gene-host coevolution, but that differential rates of colonization of microbial populations by HGT in accordance with differences in connectivity might act to counter this and even reduce connectivity over time, comprising an evolutionary trade-off.

RESULTS

We present a theoretical model that can be used to predict the conditions under which gene-host coevolution might increase or decrease the connectivity of a transferable gene over time. We show that the opportunity to enter new microbial populations by HGT can cause the connectivity of a transferable gene to evolve toward lower values, particularly in an environment that is unstable with respect to the function of the gene's protein product. We also show that a lack of such opportunity in a stable environment can cause the connectivity of a transferable gene to evolve toward higher values.

CONCLUSION

Our theoretical model suggests that the connectivity of a transferable gene can change over time toward higher values corresponding to a more sessile state of lower transferability or lower values corresponding to a more itinerant state of higher transferability, depending on the ecological milieu in which the gene exists. We note, however, that a better understanding of gene-host coevolutionary dynamics in natural microbial systems is required before any further conclusions about the veracity of the simplicity hypothesis can be drawn.

Strains Associated with Two 2020 Welder Anthrax Cases in the United States Belong to Separate Lineages within Bacillus cereus sensu lato

Anthrax-causing members of Bacillus cereus sensu lato (s.l.) pose a serious threat to public health. While most anthrax-causing strains resemble B. anthracis phenotypically, rare cases of anthrax-like illness caused by strains resembling “B. cereus” have been reported. Here, whole-genome sequencing was used to characterize three B. cereus s.l. isolates associated with two 2020 welder anthrax cases in the United States, which resembled “B. cereus” phenotypically. Comparison of the three genomes sequenced here to all publicly available, high-quality B. cereus s.l. genomes (n = 2890 total genomes) demonstrated that genomes associated with each case effectively belonged to separate species at the conventional 95% average nucleotide identity prokaryotic species threshold. Two PubMLST sequence type 78 (ST78) genomes affiliated with a case in Louisiana were most closely related to B. tropicus and possessed genes encoding the Bps exopolysaccharide capsule, as well as hemolysin BL (Hbl) and cytotoxin K (CytK). Comparatively, a ST108 genome associated with a case in Texas was most closely related to B. anthracis; however, like other anthrax-causing strains most closely related to B. anthracis, this genome did not possess Bps-, Hbl-, or CytK-encoding genes. Overall, results presented here provide insights into the evolution of anthrax-causing B. cereus s.l.

Current Methods for Recombination Detection in Bacteria

The role of genetic exchanges, i.e., homologous recombination (HR) and horizontal gene transfer (HGT), in bacteria cannot be overestimated for it is a pivotal mechanism leading to their evolution and adaptation, thus, tracking the signs of recombination and HGT events is importance both for fundamental and applied science. To date, dozens of bioinformatics tools for revealing recombination signals are available, however, their pros and cons as well as the spectra of solvable tasks have not yet been systematically reviewed. Moreover, there are two major groups of software. One aims to infer evidence of HR, while the other only deals with horizontal gene transfer (HGT). However, despite seemingly different goals, all the methods use similar algorithmic approaches, and the processes are interconnected in terms of genomic evolution influencing each other. In this review, we propose a classification of novel instruments for both HR and HGT detection based on the genomic consequences of recombination. In this context, we summarize available methodologies paying particular attention to the type of traceable events for which a certain program has been designed.

Mirage: estimation of ancestral gene-copy numbers by considering different evolutionary patterns among gene families

Motivation

Reconstruction of gene copy number evolution is an essential approach for understanding how complex biological systems have been organized. Although various models have been proposed for gene copy number evolution, existing evolutionary models have not appropriately addressed the fact that different gene families can have very different gene gain/loss rates.

Results

In this study, we developed Mirage (MIxtuRe model for Ancestral Genome Estimation), which allows different gene families to have flexible gene gain/loss rates. Mirage can use three models for formulating heterogeneous evolution among gene families: the discretized Γ model, probability distribution-free model and pattern mixture (PM) model. Simulation analysis showed that Mirage can accurately estimate heterogeneous gene gain/loss rates and reconstruct gene-content evolutionary history. Application to empirical datasets demonstrated that the PM model fits genome data from various taxonomic groups better than the other heterogeneous models. Using Mirage, we revealed that metabolic function-related gene families displayed frequent gene gains and losses in all taxa investigated.

Availability and implementation

The source code of Mirage is freely available at https://github.com/fukunagatsu/Mirage.

Supplementary information

Supplementary data are available at Bioinformatics Advances online.

Should Networks Supplant Tree Building?

Recent studies suggested that network methods should supplant tree building as the basis of genealogical analysis. This proposition is based upon two arguments. First is the observation that bacterial and archaeal lineages experience processes oppositional to bifurcation and hence the representation of the evolutionary process in a tree like structure is illogical. Second is the argument tree building approaches are circular-you ask for a tree and you get one, which pins a verificationist label on tree building that, if correct, should be the end of phylogenetic analysis as we currently know it. In this review, we examine these questions and suggest that rumors of the death of the bacterial tree of life are exaggerated at best.

Batch-Learning Self-Organizing Map Identifies Horizontal Gene Transfer Candidates and Their Origins in Entire Genomes

Horizontal gene transfer (HGT) has been widely suggested to play a critical role in the environmental adaptation of microbes; however, the number and origin of the genes in microbial genomes obtained through HGT remain unknown as the frequency of detected HGT events is generally underestimated, particularly in the absence of information on donor sequences. As an alternative to phylogeny-based methods that rely on sequence alignments, we have developed an alignment-free clustering method on the basis of an unsupervised neural network “Batch-Learning Self-Organizing Map (BLSOM)” in which sequence fragments are clustered based solely on oligonucleotide similarity without taxonomical information, to detect HGT candidates and their origin in entire genomes. By mapping the microbial genomic sequences on large-scale BLSOMs constructed with nearly all prokaryotic genomes, HGT candidates can be identified, and their origin assigned comprehensively, even for microbial genomes that exhibit high novelty. By focusing on two types of Alphaproteobacteria, specifically psychrotolerant Sphingomonas strains from an Antarctic lake, we detected HGT candidates using BLSOM and found higher proportions of HGT candidates from organisms belonging to Betaproteobacteria in the genomes of these two Antarctic strains compared with those of continental strains. Further, an origin difference was noted in the HGT candidates found in the two Antarctic strains. Although their origins were highly diversified, gene functions related to the cell wall or membrane biogenesis were shared among the HGT candidates. Moreover, analyses of amino acid frequency suggested that housekeeping genes and some HGT candidates of the Antarctic strains exhibited different characteristics to other continental strains. Lys, Ser, Thr, and Val were the amino acids found to be increased in the Antarctic strains, whereas Ala, Arg, Glu, and Leu were decreased. Our findings strongly suggest a low-temperature adaptation process for microbes that may have arisen convergently as an independent evolutionary strategy in each Antarctic strain. Hence, BLSOM analysis could serve as a powerful tool in not only detecting HGT candidates and their origins in entire genomes, but also in providing novel perspectives into the environmental adaptations of microbes.

Producing polished prokaryotic pangenomes with the Panaroo pipeline

Population-level comparisons of prokaryotic genomes must take into account the substantial differences in gene content resulting from horizontal gene transfer, gene duplication and gene loss. However, the automated annotation of prokaryotic genomes is imperfect, and errors due to fragmented assemblies, contamination, diverse gene families and mis-assemblies accumulate over the population, leading to profound consequences when analysing the set of all genes found in a species. Here, we introduce Panaroo, a graph-based pangenome clustering tool that is able to account for many of the sources of error introduced during the annotation of prokaryotic genome assemblies. Panaroo is available at https://github.com/gtonkinhill/panaroo .

A quantitative risk assessment method for synthetic biology products in the environment

The need to prevent possible adverse environmental health impacts resulting from synthetic biology (SynBio) products is widely acknowledged in both the SynBio risk literature and the global regulatory community. To-date, however, discussions of potential risks of SynBio products have been largely speculative, and the limited attempts to characterize the risks of SynBio products have been non-uniform and entirely qualitative. As the SynBio discipline continues to accelerate and bring forth novel, highly-engineered life forms, a standardized risk assessment framework will become critical for ensuring that the environmental risks of these products are characterized in a consistent, reliable, and objective manner that incorporates all SynBio-unique risk factors. In their current forms, established risk assessment frameworks - including those that address traditional genetically modified organisms - fall short of the features required of this standard framework. To address this gap, we propose the Quantitative Risk Assessment Method for Synthetic Biology Products (QRA-SynBio) - an incremental build on established risk assessment methodologies that supplements traditional paradigms with the SynBio risk factors that are currently absent, and necessitates quantitative analysis for more transparent and objective risk characterizations. We demonstrate through a hypothetical case study that the proposed framework facilitates defensible quantification of the environmental risks of SynBio products in both foreseeable and hypothetical use scenarios. Additionally, we show how the quantitative nature of the proposed method can promote increased experimental investigation into the true likelihood of hazard and exposure parameters and highlight the most sensitive parameters where uncertainty should be reduced, ultimately leading to more targeted SynBio risk research and yielding more precise characterizations of risk.

Impacts of florfenicol on the microbiota landscape and resistome as revealed by metagenomic analysis

BACKGROUND

Drug-resistant fish pathogens can cause significant economic loss to fish farmers. Since 2012, florfenicol has become an approved drug for treating both septicemia and columnaris diseases in freshwater fish. Due to the limited drug options available for aquaculture, the impact of the therapeutical florfenicol treatment on the microbiota landscape as well as the resistome present in the aquaculture farm environment needs to be evaluated.

RESULTS

Time-series metagenomic analyses were conducted to the aquatic microbiota present in the tank-based catfish production systems, in which catfish received standard therapeutic 10-day florfenicol treatment following the federal veterinary regulations. Results showed that the florfenicol treatment shifted the structure of the microbiota and reduced the biodiversity of it by acting as a strong stressor. Planctomycetes, Chloroflexi, and 13 other phyla were susceptible to the florfenicol treatment and their abundance was inhibited by the treatment. In contrast, the abundance of several bacteria belonging to the Proteobacteria, Bacteroidetes, Actinobacteria, and Verrucomicrobia phyla increased. These bacteria with increased abundance either harbor florfenicol-resistant genes (FRGs) or had beneficial mutations. The florfenicol treatment promoted the proliferation of florfenicol-resistant genes. The copy number of phenicol-specific resistance genes as well as multiple classes of antibiotic-resistant genes (ARGs) exhibited strong correlations across different genetic exchange communities (p < 0.05), indicating the horizontal transfer of florfenicol-resistant genes among these bacterial species or genera. Florfenicol treatment also induced mutation-driven resistance. Significant changes in single-nucleotide polymorphism (SNP) allele frequencies were observed in membrane transporters, genes involved in recombination, and in genes with primary functions of a resistance phenotype.

CONCLUSIONS

The therapeutical level of florfenicol treatment significantly altered the microbiome and resistome present in catfish tanks. Both intra-population and inter-population horizontal ARG transfer was observed, with the intra-population transfer being more common. The oxazolidinone/phenicol-resistant gene optrA was the most prevalent transferred ARG. In addition to horizontal gene transfer, bacteria could also acquire florfenicol resistance by regulating the innate efflux systems via mutations. The observations made by this study are of great importance for guiding the strategic use of florfenicol, thus preventing the formation, persistence, and spreading of florfenicol-resistant bacteria and resistance genes in aquaculture.

panX: pan-genome analysis and exploration

Horizontal transfer, gene loss, and duplication result in dynamic bacterial genomes shaped by a complex mixture of different modes of evolution. Closely related strains can differ in the presence or absence of many genes, and the total number of distinct genes found in a set of related isolates—the pan-genome—is often many times larger than the genome of individual isolates. We have developed a pipeline that efficiently identifies orthologous gene clusters in the pan-genome. This pipeline is coupled to a powerful yet easy-to-use web-based visualization for interactive exploration of the pan-genome. The visualization consists of connected components that allow rapid filtering and searching of genes and inspection of their evolutionary history. For each gene cluster, panX displays an alignment, a phylogenetic tree, maps mutations within that cluster to the branches of the tree and infers gain and loss of genes on the core-genome phylogeny. PanX is available at pangenome.de. Custom pan-genomes can be visualized either using a web server or by serving panX locally as a browser-based application.

The Role of Homology and Orthology in the Phylogenomic Analysis of Metazoan Gene Content

Resolving the relationships of animals (Metazoa) is crucial to our understanding of the origin of key traits such as muscles, guts, and nerves. However, a broadly accepted metazoan consensus phylogeny has yet to emerge. In part, this is because the genomes of deeply diverging and fast-evolving lineages may undergo significant gene turnover, reducing the number of orthologs shared with related phyla. This can limit the usefulness of traditional phylogenetic methods that rely on alignments of orthologous sequences. Phylogenetic analysis of gene content has the potential to circumvent this orthology requirement, with binary presence/absence of homologous gene families representing a source of phylogenetically informative characters. Applying binary substitution models to the gene content of 26 complete animal genomes, we demonstrate that patterns of gene conservation differ markedly depending on whether gene families are defined by orthology or homology, that is, whether paralogs are excluded or included. We conclude that the placement of some deeply diverging lineages may exceed the limit of resolution afforded by the current methods based on comparisons of orthologous protein sequences, and novel approaches are required to fully capture the evolutionary signal from genes within genomes.

What is an archaeon and are the Archaea really unique?

The recognition of the group Archaea as a major branch of the tree of life (ToL) prompted a new view of the evolution of biodiversity. The genomic representation of archaeal biodiversity has since significantly increased. In addition, advances in phylogenetic modeling of multi-locus datasets have resolved many recalcitrant branches of the ToL. Despite the technical advances and an expanded taxonomic representation, two important aspects of the origins and evolution of the Archaea remain controversial, even as we celebrate the 40th anniversary of the monumental discovery. These issues concern (i) the uniqueness (monophyly) of the Archaea, and (ii) the evolutionary relationships of the Archaea to the Bacteria and the Eukarya; both of these are relevant to the deep structure of the ToL. To explore the causes for this persistent ambiguity, I examine multiple datasets and different phylogenetic approaches that support contradicting conclusions. I find that the uncertainty is primarily due to a scarcity of information in standard datasets-universal core-genes datasets-to reliably resolve the conflicts. These conflicts can be resolved efficiently by comparing patterns of variation in the distribution of functional genomic signatures, which are less diffused unlike patterns of primary sequence variation. Relatively lower heterogeneity in distribution patterns minimizes uncertainties and supports statistically robust phylogenetic inferences, especially of the earliest divergences of life. This case study further highlights the limitations of primary sequence data in resolving difficult phylogenetic problems, and raises questions about evolutionary inferences drawn from the analyses of sequence alignments of a small set of core genes. In particular, the findings of this study corroborate the growing consensus that reversible substitution mutations may not be optimal phylogenetic markers for resolving early divergences in the ToL, nor for determining the polarity of evolutionary transitions across the ToL.

Akaryotes and Eukaryotes are independent descendants of a universal common ancestor

We reconstructed a global tree of life (ToL) with non-reversible and non-stationary models of genome evolution that root trees intrinsically. We implemented Bayesian model selection tests and compared the statistical support for four conflicting ToL hypotheses. We show that reconstructions obtained with a Bayesian implementation (Klopfstein et al., 2015) are consistent with reconstructions obtained with an empirical Sankoff parsimony (ESP) implementation (Harish et al., 2013). Both are based on the genome contents of coding sequences for protein domains (superfamilies) from hundreds of genomes. Thus, we conclude that the independent descent of Eukaryotes and Akaryotes (archaea and bacteria) from the universal common ancestor (UCA) is the most probable as well as the most parsimonious hypothesis for the evolutionary origins of extant genomes. Reconstructions of ancestral proteomes by both Bayesian and ESP methods suggest that at least 70% of unique domain-superfamilies known in extant species were present in the UCA. In addition, identification of a vast majority (96%) of the mitochondrial superfamilies in the UCA proteome precludes a symbiotic hypothesis for the origin of eukaryotes. Accordingly, neither the archaeal origin of eukaryotes nor the bacterial origin of mitochondria is supported by the data. The proteomic complexity of the UCA suggests that the evolution of cellular phenotypes in the two primordial lineages, Akaryotes and Eukaryotes, was driven largely by duplication of common superfamilies as well as by loss of unique superfamilies. Finally, innovation of novel superfamilies has played a surprisingly small role in the evolution of Akaryotes and only a marginal role in the evolution of Eukaryotes.