Biology subjects

Wolf, Y. I.

Publications and source records attributed to Wolf, Y. I..

At least 55 records · Page 3Linked to original sources

bioRxiv2021

Epistasis at the SARS-CoV-2 RBD Interface and the Propitiously Boring Implications for Vaccine Escape

At the time of this writing, December 2021, potential emergence of vaccine escape variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a grave global concern. The interface between the receptor-binding domain (RBD) of SARS-CoV-2 spike (S) protein and the host receptor (ACE2) overlap with the binding site of principal neutralizing antibodies (NAb), limiting the repertoire of viable mutations. Nonetheless, variants with multiple mutations in the RBD have rose to dominance. Non-additive, epistatic relationships among RBD mutations are apparent, and assessing the impact of such epistasis on the mutational landscape is crucial. Epistasis can substantially increase the risk of vaccine escape and cannot be completely characterized through the study of the wild type (WT) alone. We employed protein structure modeling using Rosetta to compare the effects of all single mutants at the RBD-NAb and RBD-ACE2 interfaces for the WT, Delta, Gamma, and Omicron variants. Overall, epistasis at the RBD interface appears to be limited and the effects of most multiple mutations are additive. Epistasis at the Delta variant interface weakly stabilizes NAb interaction relative to ACE2 interaction, whereas in the Gamma variant, epistasis more substantially destabilizes NAb interaction. Although a small, systematic trend towards NAb destabilization not observed for Delta or Gamma was detected for Omicron, and despite bearing significantly more RBD mutations, the epistatic landscape of the Omicron variant closely resembles that of Gamma. These results suggest that, although Omicron poses new risks not observed with Delta, structural constraints on the RBD hamper continued evolution towards more complete vaccine escape. The modest ensemble of mutations relative to the WT that are currently known to reduce vaccine efficacy is likely to comprise the majority of all possible escape mutations for future variants, predicting continued efficacy of the existing vaccines. SignificanceEmergence of vaccine escape variants of SARS-CoV-2 is arguably the most pressing problem during the COVID-19 pandemic as vaccines are distributed worldwide. We employed a computational approach to assess the risk of antibody escape resulting from mutations in the receptor-binding domain of the spike protein of the wild type SARS-CoV-2 virus as well as the Delta, Gamma, and Omicron variants. At the time of writing, December, 2021, Omicron is poised to replace Delta as the dominant variant worldwide. The efficacy of the existing vaccines against Omicron could be substantially reduced relative to the WT and the potential for vaccine escape is of grave concern. Our results suggest that although Omicron poses new evolutionary risks not observed for the Delta variant, structural constraints on the RBD make continued evolution towards more complete vaccine escape unlikely. The modest set of escape-enhancing mutations already identified for the wild type likely include the majority of all possible mutations with this effect.

microbiology↗

bioRxiv2021

A Ratio-Dependent Model of Replicator-Genetic Parasite Coevolution Demonstrates Instability of the Parasite-Free State

Nearly all organisms on earth are hosts to diverse genetic parasites including viruses and various types of mobile genetic elements. The emergence and persistence of genetic parasites was hypothesized to be an intrinsic feature of biological evolution. Here we examine this proposition by analysis of a ratio-dependent Lotka-Volterra type model of replicator(host)-parasite coevolution where the evolutionary outcome depends on the ratio of the host and parasite numbers. In a large, unbounded domain of the space of the model parameters, which include the replicator carrying capacity, the damage inflicted by the parasite, the replicative advantage of the parasites, and its mortality rate, the parasite-free equilibrium takes the form of a saddle and accordingly is unstable. Therefore, the evolutionary outcome is either the stable coexistence of the replicator and the parasite or extinction of both. Thus, the results of ratio-dependent model analysis are compatible with the hypothesis that genetic parasites are inherent to life.

evolutionary biology↗

bioRxiv2021

Non-essential ribosomal proteins in bacteria and archaea identified using COGs

Ribosomal proteins (RPs) are highly conserved across the bacterial and archaeal domains. Although many RPs are essential for survival, genome analysis demonstrates the absence of some RP genes in many bacterial and archaeal genomes. Furthermore, global transposon mutagenesis and/or targeted deletion showed that elimination of some RP genes had only a moderate effect on the bacterial growth rate. Here, we systematically analyze the evolutionary conservation of RPs in prokaryotes by compiling the list of the ribosomal genes that are missing from the one or more genomes in the recently updated version of the Clusters of Orthologous Genes (COG) database. Some of these absences occurred because the respective genes carried frameshifts, presumably, resulting from sequencing errors, while others were overlooked and not translated during genome annotation. Apart from these annotation errors, we identified multiple genuine losses of RP genes in a variety of bacteria and archaea. Some of these losses are clade-specific, whereas others occur in symbionts and parasites with dramatically reduced genomes. The lists of computationally and experimentally defined non-essential ribosomal genes show a substantial overlap, revealing a common trend in prokaryote ribosome evolution that could be linked to the architecture and assembly of the ribosomes. Thus, RPs that are located at the surface of the ribosome and/or are incorporated at a late stage of ribosome assembly are more likely to be non-essential and to be lost during microbial evolution, particularly, in the course of genome compaction. IMPORTANCEIn many prokaryote genomes, one or more ribosomal protein (RP) genes are missing. Analysis of 1,309 prokaryote genomes included in the COG database shows that only about half of the RPs are universally conserved in bacteria and archaea. In contrast, up to 21 other RPs are missing in some genomes, primarily, tiny (<1 Mb) genomes of host-associated bacteria and archaea. Ten universal and nine archaea-specific ribosomal proteins show clear patterns of lineage-specific gene loss. Most of the RPs that are frequently lost from bacterial genomes are located on the ribosome periphery and are non-essential in Escherichia coli and Bacillus subtilis. These results reveal general trends and common constraints in the architecture and evolution of ribosomes in prokaryotes.

genomics↗

bioRxiv2020

Expanding diversity of Asgard archaea and the elusive ancestry of eukaryotes

Comparative analysis of 162 (nearly) complete genomes of Asgard archaea, including 75 not reported previously, substantially expands the phylogenetic and metabolic diversity of the Asgard superphylum, with six additional phyla proposed. Phylogenetic analysis does not strongly support origin of eukaryotes from within Asgard, leaning instead towards a three-domain topology, with eukaryotes branching outside archaea. Comprehensive protein domain analysis in the 162 Asgard genomes results in a major expansion of the set of eukaryote signature proteins (ESPs). The Asgard ESPs show variable phyletic distributions and domain architectures, suggestive of dynamic evolution via horizontal gene transfer (HGT), gene loss, gene duplication and domain shuffling. The results appear best compatible with the origin of the conserved core of eukaryote genes from an unknown ancestral lineage deep within or outside the extant archaeal diversity. Such hypothetical ancestors would accumulate components of the mobile archaeal eukaryome via extensive HGT, eventually, giving rise to eukaryote-like cells.

genomics↗

bioRxiv2020

Ongoing Adaptive Evolution and Globalization of Sars-Cov-2

Understanding the trends in SARS-CoV-2 evolution is paramount to control the COVID- 19 pandemic. We analyzed more than 300,000 high quality genome sequences of SARS-CoV-2 variants available as of January 2021. The results show that the ongoing evolution of SARS-CoV-2 during the pandemic is characterized primarily by purifying selection, but a small set of sites appear to evolve under positive selection. The receptor-binding domain of the spike protein and the nuclear localization signal (NLS) associated region of the nucleocapsid protein are enriched with positively selected amino acid replacements. These replacements form a strongly connected network of apparent epistatic interactions and are signatures of major partitions in the SARS-CoV-2 phylogeny. Virus diversity within each geographic region has been steadily growing for the entirety of the pandemic, but analysis of the phylogenetic distances between pairs of regions reveals four distinct periods based on global partitioning of the tree and the emergence of key mutations. The initial period of rapid diversification into region- specific phylogenies that ended in February 2020 was followed by a major extinction event and global homogenization concomitant with the spread of D614G in the spike protein, ending in March 2020. The NLS associated variants across multiple partitions rose to global prominence in March-July, during a period of stasis in terms of inter- regional diversity. Finally, beginning July 2020, multiple mutations, some of which have since been demonstrated to enable antibody evasion, began to emerge associated with ongoing regional diversification, which might be indicative of speciation. SignificanceUnderstanding the ongoing evolution of SARS-CoV-2 is essential to control and ultimately end the pandemic. We analyzed more than 300,000 SARS-CoV-2 genomes available as of January 2021 and demonstrate adaptive evolution of the virus that affects, primarily, multiple sites in the spike and nucleocapsid protein. Selection appears to act on combinations of mutations in these and other SARS-CoV-2 genes. Evolution of the virus is accompanied by ongoing adaptive diversification within and between geographic regions. This diversification could substantially prolong the pandemic and the vaccination campaign, in which variant-specific vaccines are likely to be required.

microbiology↗

bioRxiv2020

Phylogenetic evidence of headful packaging strategy in gene transfer agents

Gene transfer agents (GTAs) are virus-like particles encoded and produced by many bacteria and archaea. Unlike viruses, GTAs package fragments of the host genome instead of the genes that encode the components of the GTA itself. As a result of this non-specific DNA packaging, GTAs can transfer genes within bacterial and archaeal communities. GTAs clearly evolved from viruses and are thought to have been maintained in prokaryotic genomes due to the advantages associated with their DNA transfer capacity. The most-studied GTA is produced by the alphaproteobacterium Rhodobacter capsulatus (RcGTA), which packages random portions of the host genome at a lower DNA density than usually observed in tailed bacterial viruses. How the DNA packaging properties of RcGTA evolved from those of the ancestral virus remains unknown. To address this question, we reconstructed the evolutionary history of the large subunit of the terminase (TerL), a highly conserved enzyme used by viruses and GTAs to package DNA. We found that RcGTA-like TerLs grouped within viruses that employ the headful packaging strategy. Because distinct mechanisms of viral DNA packaging correspond to differences in the TerL amino acid sequence, our finding suggests that RcGTA evolved from a headful packaging virus. Headful packaging is the least sequence-specific mode of DNA packaging, which would facilitate the switch from packaging of the viral genome to packaging random pieces of the host genome during GTA evolution.

evolutionary biology↗

bioRxiv2020

Modified base-binding EVE and DCD Domains Implicated in the Origins of Programmed Cell Death and the piRNA Pathway

BackgroundDNA and RNA of most cellular life forms and many viruses contain an expansive repertoire of modified bases. The modified bases play diverse biological roles that include both regulation of transcription and translation, and protection against restriction endonucleases and antibiotics. Modified bases are often recognized by dedicated protein domains. However, the elaborate networks of interactions and processes mediated by modified bases are far from being completely understood. ResultsWe present a comprehensive census and classification of EVE domains that belong to the PUA/ASCH domain superfamily and bind various modified bases in DNA and RNA. Prokaryotes encode two classes of EVE domain proteins, slow-evolving and fast-evolving. The slow-evolving EVE domains in -proteobacteria are embedded in a conserved operonic context that implies involvement in coupling between translation and respiration, in particular, cytochrome c biogenesis, potentially, via binding 5-methylcytosine in tRNAs. In {beta} and {gamma}-proteobacteria, the conserved associations implicate the EVE domains in the coordination of cell division, biofilm formation, and global transcriptional regulation by non-coding 6S small RNAs, which are potentially modified and bound by the EVE domains. Down-regulation of the EVE-encoding operons might cause dormancy or programmed cell death (PCD). In eukaryotes, the EVE-domain-containing THYN1-like proteins appear to inhibit PCD and regulate the cell cycle, likely, via binding 5-methylcytosine and its derivatives in DNA and/or RNA. Thus, the link between PCD and cytochrome c that appears to be universal in eukaryotes might have been inherited from the -proteobacterial, proto-mitochondrial endosymbiont and, unexpectedly, could involve modified base recognition by EVE domains. In numerous prokaryotic genomes, fast-evolving EVE domains are embedded in defense contexts, including toxin-antitoxin modules and Type IV restriction systems, all of which can also induce PCD. These EVE domains likely recognize modified bases in invading DNA molecules and target them for restriction. We additionally identified EVE-like prokaryotic Development and Cell Death (DCD) domains that are also implicated in defense functions including PCD. This function was inherited by eukaryotes but, in animals, the DCD proteins apparently were displaced by the extended Tudor family, whose partnership with Piwi-related Argonautes became the centerpiece of the piRNA system. ConclusionsRecognition of modified bases in DNA and RNA by EVE-like domains appears to be an important, but until now, under-appreciated, common denominator in a variety of processes including PCD, cell cycle control, antivirus immunity, stress response and germline development in animals.

genomics↗

bioRxiv2020

Punctuated equilibrium as the default mode of evolution of large populations on fitness landscapes dominated by saddle points in the weak-mutation limit

Punctuated equilibrium is a mode of evolution in which phenetic change occurs in rapid bursts that are separated by much longer intervals of stasis during which mutations accumulate but no major phenotypic change occurs. Punctuated equilibrium has been originally proposed within the framework of paleobiology, to explain the lack of transitional forms that is typical of the fossil record. Theoretically, punctuated equilibrium has been linked to self-organized criticality (SOC), a model in which the size of avalanches in an evolving system is power-law distributed, resulting in increasing rarity of major events. We show here that, under the weak-mutation limit, a large population would spend most of the time in stasis in the vicinity of saddle points in the fitness landscape. The periods of stasis are punctuated by fast transitions, in lnNe time (Ne, effective population size), when a new beneficial mutation is fixed in the evolving population, which moves to a different saddle, or on much rarer occasions, from a saddle to a local peak. Thus, punctuated equilibrium is the default mode of evolution under a simple model that does not involve SOC or other special conditions. SignificanceThe gradual character of evolution is a key feature of the Darwinian worldview. However, macroevolutionary events are often thought to occur in a non-gradualist manner, in a regime known as punctuated equilibrium, whereby extended periods of evolutionary stasis are punctuated by rapid transitions between states. Here we analyze a mathematical model of population evolution on fitness landscapes and show that, for a large population in the weak-mutation limit, the process of adaptive evolution consists of extended periods of stasis, which the population spends around saddle points on the landscape, interrupted by rapid transitions to new saddle points when a beneficial mutation is fixed. Thus, punctuated equilibrium appears to be the default regime of biological evolution.

evolutionary biology↗

bioRxiv2020

Unique genomic features of crAss-like phages, the dominant component of the human gut virome

CrAssphage is the most abundant virus identified in the human gut virome and the founding member of a large group of bacteriophages that infect bacteria of the phylum Bacteroidetes and have been discovered by metagenomics of both animal-associated and environmental habitats. By analysis of circular contigs from human gut microbiomes, we identified nearly 600 genomes of crAss-like phages. Phylogenetic analysis of conserved genes demonstrates the monophyly of crAss-like phages, which can be expected to become a new order of viruses, and of 5 distinct branches, likely, families within that order. Two of these putative families have not been identified previously. The phages in one of these groups have large genomes (145-192 kilobases) and contain an unprecedented high density of self-splicing introns and inteins. Many crAss-like phages encode suppressor tRNAs that enable readthrough of UGA or UAG stop-codons, mostly, in late phage genes, which could represent a distinct anti-defense strategy. Another putative anti-defense mechanism that might target an unknown defense system in Bacteroidetes inhibiting phage DNA replication involves multiple switches of the phage DNA polymerase type between A and B families. Thus, comparative genomic analysis of the expanded assemblage of crAss-like phages reveals several unusual features of genome architecture and expression as well as phage biology that were not apparent from the previous crAssphage analyses.

microbiology↗

bioRxiv2020

Prediction of the virus incubation period for COVID-19 and future outbreaks

A crucial factor in mitigating respiratory viral outbreaks is early determination of the duration of the incubation period and, accordingly, the required quarantine time for potentially exposed individuals. Here, we explore different genomic features of RNA viruses that correlate with the incubation times and provide a predictive model that accurately estimates the upper limit incubation time for diverse viruses including SARS-CoV-2, and thus, could help control future outbreaks.

microbiology↗

bioRxiv2020

Selection for reducing energy cost of protein production drives the GC content and amino acid composition bias in gene transfer agents

Gene transfer agents (GTAs) are virus-like elements integrated into bacterial genomes, particularly, those of Alphaproteobacteria. The GTAs can be induced under nutritional stress, incorporate random fragments of bacterial DNA into mini-phage particles, lyse the host cells and infect neighboring bacteria, thus enhancing horizontal gene transfer. We show that the GTA genes evolve under pronounced positive selection for the reduction of the energy cost of protein production as shown by comparison of the amino acid compositions with both homologous viral genes and host genes. The energy saving in GTA genes is comparable to or even more pronounced than that in the genes encoding the most abundant, essential bacterial proteins. In cases when viruses acquire genes from GTAs, the bias in amino acid composition disappears in the course of evolution, showing that reduction of the energy cost of protein is an important factor of evolution of GTAs but not bacterial viruses. These findings strongly suggest that GTAs are bacterial adaptations rather than selfish, virus-like elements. Because GTA production kills the host cell and does not propagate the GTA genome, it appears likely that the GTAs are retained in the course of evolution via kin or group selection. Therefore, we hypothesize that GTA facilitate the survival of bacterial populations under energy-limiting conditions through the spread of metabolic and transport capabilities via horizontal gene transfer and increase of nutrient availability resulting from the altruistic suicide of GTA-producing cells. ImportanceKin and group selection remain controversial topics in evolutionary biology. We argue that these types of selection are likely to operate in bacterial populations by showing that bacterial Gene Transfer Agents (GTAs), but not related viruses, evolve under positive selection for the reduction of the energy cost of a GTA particle production. We hypothesize that GTAs are dedicated devices for the survival of bacteria under the conditions of nutrient limitation. The benefits conferred by GTAs under nutritional stress appear to include horizontal dissemination of genes that could provide bacteria with enhanced capabilities for nutrient utilization and the increase of nutrient availability through the lysis of GTA-producing bacteria.

evolutionary biology↗

bioRxiv2020

Horizontal gene transfer barrier shapes the evolution of prokaryotic pangenomes

The genomes of bacteria and archaea evolve by extensive loss and gain of genes which, for any group of related prokaryotic genomes, result in the formation of a pangenome with the universal, asymmetrical U-shaped distribution of gene commonality. To elucidate the evolutionary factors that define the specific shape of this distribution, we investigate the fit of simple models of genome evolution to the empirically observed gene commonality distributions and genomes intersections for 33 groups of closely related bacterial genomes. The combined analysis of genome intersections and gene commonality shows that at least one of the two simplifying assumptions that are usually adopted for modeling the evolution of the U-shaped distribution, those of infinitely many genes and constant genome size, is invalid. The violation of both these assumptions stems from the horizontal gene transfer barrier, i.e. the cost of accommodation of foreign genes by prokaryotes.

evolutionary biology↗

bioRxiv2020

Genomic determinants of pathogenicity in SARS-CoV-2 and other human coronaviruses

SARS-CoV-2 poses an immediate, major threat to public health across the globe. Here we report an in-depth molecular analysis to reconstruct the evolutionary origins of the enhanced pathogenicity of SARS-CoV-2 and other coronaviruses that are severe human pathogens. Using integrated comparative genomics and machine learning techniques, we identify key genomic features that differentiate SARS-CoV-2 and the viruses behind the two previous deadly coronavirus outbreaks, SARS-CoV and MERS-CoV, from less pathogenic coronaviruses. These features include enhancement of the nuclear localization signals in the nucleocapsid protein and distinct inserts in the spike glycoprotein that appear to be associated with high case fatality rate of these coronaviruses as well as the host switch from animals to humans. The identified features could be crucial elements of coronavirus pathogenicity and possible targets for diagnostics, prognostication and interventions.

microbiology↗

bioRxiv2020

Seeker: Alignment-free identification of bacteriophage genomes by deep learning

Advances in metagenomics enable massive discovery of diverse, distinct microbes and viruses. Bacteriophages, the most abundant biological entity on Earth, evolve rapidly, and therefore, detection of unknown bacteriophages in sequence datasets is a challenge. The existing methods rely on sequence similarity to known bacteriophage sequences, impeding the identification and characterization of distinct bacteriophage families. We present Seeker, a deep-learning tool for reference-free identification of phage sequences. Seeker allows rapid detection of phages in sequence datasets and clean differentiation of phage sequences from bacterial ones, even for phages with little sequence similarity to established phage families. We comprehensively validate Seekers ability to identify unknown phages and employ Seeker to detect unknown phages, some of which are highly divergent from known phage families. We provide a web portal (seeker.pythonanywhere.com) and a user-friendly python package (https://github.com/gussow/seeker) allowing researchers to easily apply Seeker in metagenomic studies, for the detection of diverse unknown bacteriophages.

microbiology↗

bioRxiv2020

Histidine-Triad Hydrolases Provide Resistance to Peptide-Nucleotide Antibiotics

The Escherichia coli microcin C (McC) and related compounds are potent Trojan-horse peptide-nucleotide antibiotics. The peptide part facilitates transport into sensitive cells. Inside the cell, the peptide part is degraded by non-specific peptidases releasing an aspartamide-adenylate containing a phosphoramide bond. This non-hydrolyzable compound inhibits aspartyl-tRNA synthetase. In addition to the efficient export of McC outside of the producing cells, special mechanisms evolved to avoid self-toxicity caused by the degradation of the peptide part inside the producers. Here, we report that histidine triad (HIT) hydrolases encoded in biosynthetic clusters of some McC homologs or by stand-alone genes confer resistance to McC-like compounds by hydrolyzing the phosphoramide bond in toxic aspartamide-adenosine, rendering them inactive. IMPORTANCEUncovering the mechanisms of resistance is a required step for countering the looming antibiotic resistance crisis. In this communication, we show how universally conserved histidine triad hydrolases provide resistance to microcin C - a potent inhibitor of bacterial protein synthesis.

biochemistry↗

bioRxiv2020

Vast diversity of anti-CRISPR proteins predicted with a machine-learning approach

Bacteria and archaea evolve under constant pressure from numerous, diverse viruses and thus have evolved multiple defense systems. The CRISPR-Cas are adaptive immunity systems that have been harnessed for the development of the new generation of genome editing and engineering tools. In the incessant host-parasite arms race, viruses evolved multiple anti-defense mechanisms including numerous, diverse anti-CRISPR proteins (Acrs) that can inhibit CRISPR-Cas and therefore have enormous potential for application as modulators of genome editing tools. Most Acrs are small, highly variable proteins which makes their prediction a formidable task. We developed a machine learning approach for comprehensive Acr prediction. The model showed high predictive power when tested against an unseen test set that included several families of recently discovered Acrs and was employed to predict 2,500 novel candidate Acr families. An examination of the top candidates confirms that they possess typical Acr features. One of the top candidates was independently tested and found to possess anti-CRISPR activity (AcrIIA12). We provide a web resource (http://acrcatalog.pythonanywhere.com/) to access the predicted Acrs sequences and annotation. The results of this analysis expand the repertoire of predicted Acrs almost by two orders of magnitude and provide a rich resource for experimental Acr discovery.

microbiology↗

bioRxiv2019

In silico learning of tumor evolution through mutational time series

Cancer arises through the accumulation of somatic mutations over time. Understanding the sequence of mutation occurrence during cancer progression can assist early and accurate diagnosis and improve clinical decision-making. Here we employ Long Short-Term Memory networks (LSTMs), a class of recurrent neural network, to learn the evolution of a tumor through an ordered sequence of mutations. We demonstrate the capacity of LSTMs to learn complex dynamics of the mutational time series governing tumor progression, allowing accurate prediction of the mutational burden and the occurrence of mutations in the sequence. Using the probabilities learned by the LSTM, we simulate mutational data and show that the simulation results are statistically indistinguishable from the empirical data. We identify passenger mutations that are significantly associated with established cancer drivers in the sequence and demonstrate that the genes carrying these mutations are substantially enriched in interactions with the corresponding driver genes. Breaking the network into modules consisting of driver genes and their interactors, we show that these interactions are associated with poor patient prognosis, thus likely conferring growth advantage for tumor progression. Thus, application of LSTM provides for prediction of numerous additional conditional drivers and to reveal hitherto unknown aspects of cancer evolution.\n\nSignificanceCancer is caused by the effects of somatic mutations known as drivers. Although a number of major cancer drivers have been identified, it is suspected that many more comparatively rare and conditional drivers exist, and the interactions between different cancer-associated mutations that might be relevant for tumor progression are not well understood. We applied an advanced neural network approach to learn the sequence of mutations and the mutational burden in colon and lung cancers, and to identify mutations that are associated with individual drivers. A significant ordering of driver mutations is demonstrated, and numerous, previously undetected conditional drivers are identified. These findings broaden the existing understanding of the mechanisms of tumor progression and have implications for therapeutic strategies.

bioinformatics↗

bioRxiv2019

Homologous recombination substantially delays sequence but not gene content divergence of prokaryotic populations

Evolution of bacterial and archaeal genomes is a highly dynamic process that involves extensive gain and loss of genes. Therefore, phylogenetic trees of prokaryotes can be constructed both by the traditional sequence-based methods (gene trees) and by comparison of gene compositions (genome trees). Comparing the branch lengths in gene and genome trees with identical topologies for 34 clusters of closely related bacterial and archaeal genomes, we found that the terminal branches of gene trees were systematically compressed compared to those of genome trees. Thus, sequence evolution seems to be significantly delayed with respect to genome evolution by gene gain and loss. The extent of this delay widely differs among bacterial and archaeal lineages. We develop and explore mathematical models demonstrating that the delay of sequence divergence can be explained by sequence homogenization that is caused by homologous recombination. Once evolving genomes become isolated by barriers that impede homologous recombination, gene and genome evolution processes settle into parallel trajectories, and genomes diverge, resulting in speciation. This model of prokaryotic genome evolution gives a mechanistic explanation of our previous finding that archaeal genomes contain a class of genes that turn over rapidly, before significant sequence divergence occurs, and provides a framework for correcting phylogenetic trees, to make them consistent with the dynamics of gene turnover.

evolutionary biology↗