Accurate inference of orthologous genes is a pre-requisite for most comparative genomics studies, and is also important for functional annotation of new genomes. Identification of orthologous gene sets typically involves phylogenetic tree analysis, heuristic algorithms based on sequence conservation, synteny analysis, or some combination of these approaches. The most direct tree-based methods typically rely on the comparison of an individual gene tree with a species tree. Once the two trees are accurately constructed, orthologs are straightforwardly identified by the definition of orthology as those homologs that are related by speciation, rather than gene duplication, at their most recent point of origin. Although ideal for the purpose of orthology identification in principle, phylogenetic trees are computationally expensive to construct for large numbers of genes and genomes, and they often contain errors, especially at large evolutionary distances. Moreover, in many organisms, in particular prokaryotes and viruses, evolution does not appear to have followed a simple ‘tree-like’ mode, which makes conventional tree reconciliation inapplicable. Other, heuristic methods identify probable orthologs as the closest homologous pairs or groups of genes in a set of organisms. These approaches are faster and easier to automate than tree-based methods, with efficient implementations provided by graph-theoretical algorithms enabling comparisons of thousands of genomes. Comparisons of these two approaches show that, despite conceptual differences, they produce similar sets of orthologs, especially at short evolutionary distances. Synteny also can aid in identification of orthologs. Often, tree-based, sequence similarity- and synteny-based approaches can be combined into flexible hybrid methods.
homolog; ortholog; paralog; xenolog; orthologous groups; tree reconciliation; comparative genomics
A stochastic, agent-based mathematical model of the coevolution of the archaeal and bacterial adaptive immunity system, CRISPR-Cas, and lytic viruses shows that CRISPR-Cas immunity can stabilize the virus-host coexistence rather than leading to the extinction of the virus. In the model, CRISPR-Cas immunity does not specifically promote viral diversity, presumably because the selection pressure on each single proto-spacer is too weak. However, the overall virus diversity in the presence of CRISPR-Cas grows due to the increase of the host and, accordingly, the virus population size. Above a threshold value of total viral diversity, which is proportional to the viral mutation rate and population size, the CRISPR-Cas system becomes ineffective and is lost due to the associated fitness cost. Our previous modeling study has suggested that the ubiquity of CRISPR-Cas in hyperthermophiles, which contrasts its comparative low prevalence in mesophiles, is due to lower rates of mutation fixation in thermal habitats. The present findings offer a complementary, simpler perspective on this contrast through the larger population sizes of mesophiles compared to hyperthermophiles, because of which CRISPR-Cas can become ineffective in mesophiles. The efficacy of CRISPR-Cas sharply increases with the number of proto-spacers per viral genome, potentially explaining the low information content of the proto-spacer-associated motif (PAM) that is required for spacer acquisition by CRISPR-Cas because a higher specificity would restrict the number of spacers available to CRISPR-Cas, thus hampering immunity. The very existence of the PAM might reflect the tradeoff between the requirement of diverse spacers for efficient immunity and avoidance of autoimmunity.
Bacteria and archaea face continual onslaughts of rapidly diversifying viruses and plasmids. Many prokaryotes maintain adaptive immune systems known as clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated genes (Cas). CRISPR-Cas systems are genomic sensors that serially acquire viral and plasmid DNA fragments (spacers) that are utilized to target and cleave matching viral and plasmid DNA in subsequent genomic invasions, offering critical immunological memory. Only 50% of sequenced bacteria possess CRISPR-Cas immunity, in contrast to over 90% of sequenced archaea. To probe why half of bacteria lack CRISPR-Cas immunity, we combined comparative genomics and mathematical modeling. Analysis of hundreds of diverse prokaryotic genomes shows that CRISPR-Cas systems are substantially more prevalent in thermophiles than in mesophiles. With sequenced bacteria disproportionately mesophilic and sequenced archaea mostly thermophilic, the presence of CRISPR-Cas appears to depend more on environmental temperature than on bacterial-archaeal taxonomy. Mutation rates are typically severalfold higher in mesophilic prokaryotes than in thermophilic prokaryotes. To quantitatively test whether accelerated viral mutation leads microbes to lose CRISPR-Cas systems, we developed a stochastic model of virus-CRISPR coevolution. The model competes CRISPR-Cas-positive (CRISPR-Cas+) prokaryotes against CRISPR-Cas-negative (CRISPR-Cas−) prokaryotes, continually weighing the antiviral benefits conferred by CRISPR-Cas immunity against its fitness costs. Tracking this cost-benefit analysis across parameter space reveals viral mutation rate thresholds beyond which CRISPR-Cas cannot provide sufficient immunity and is purged from host populations. These results offer a simple, testable viral diversity hypothesis to explain why mesophilic bacteria disproportionately lack CRISPR-Cas immunity. More generally, fundamental limits on the adaptability of biological sensors (Lamarckian evolution) are predicted.
A remarkable recent discovery in microbiology is that bacteria and archaea possess systems conferring immunological memory and adaptive immunity. Clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated genes (CRISPR-Cas) are genomic sensors that allow prokaryotes to acquire DNA fragments from invading viruses and plasmids. Providing immunological memory, these stored fragments destroy matching DNA in future viral and plasmid invasions. CRISPR-Cas systems also provide adaptive immunity, keeping up with mutating viruses and plasmids by continually acquiring new DNA fragments. Surprisingly, less than 50% of mesophilic bacteria, in contrast to almost 90% of thermophilic bacteria and Archaea, maintain CRISPR-Cas immunity. Using mathematical modeling, we probe this dichotomy, showing how increased viral mutation rates can explain the reduced prevalence of CRISPR-Cas systems in mesophiles. Rapidly mutating viruses outrun CRISPR-Cas immune systems, likely decreasing their prevalence in bacterial populations. Thus, viral adaptability may select against, rather than for, immune adaptability in prokaryotes.
The widespread exchange of genes among prokaryotes, known as horizontal gene transfer (HGT), is often considered to “uproot” the Tree of Life (TOL). Indeed, it is by now fully clear that genes in general possess different evolutionary histories. However, the possibility remains that the TOL concept can be reformulated and remain valid as a statistical central trend in the phylogenetic “Forest of Life” (FOL). This article describes a computational pipeline developed to chart the FOL by comparative analysis of thousands of phylogenetic trees. This analysis reveals a distinct, consistent phylogenetic signal that is particularly strong among the Nearly Universal Trees (NUTs), which correspond to genes represented in all or most of the analyzed organisms. Despite the substantial amount of apparent HGT seen even among the NUTs, these gene transfers appear to be distributed randomly and do not obscure the central tree-like trend.
The recently discovered CRISPR-Cas adaptive immune system is present in almost all archaea and many bacteria. It consists of cassettes of CRISPR repeats that incorporate spacers homologous to fragments of viral or plasmid genomes that are employed as guide RNAs in the immune response, along with numerous CRISPR-associated (cas) genes that encode proteins possessing diverse, only partially characterized activities required for the action of the system. Here, we investigate the evolution of the cas genes and show that they evolve under purifying selection that is typically much weaker than the median strength of purifying selection affecting genes in the respective genomes. The exceptions are the cas1 and cas2 genes that typically evolve at levels of purifying selection close to the genomic median. Thus, although these genes are implicated in the acquisition of spacers from alien genomes, they do not appear to be directly involved in an arms race between bacterial and archaeal hosts and infectious agents. These genes might possess functions distinct from and additional to their role in the CRISPR-Cas-mediated immune response. Taken together with evidence of the frequent horizontal transfer of cas genes reported previously and with the wide-spread microscale recombination within these genes detected in this work, these findings reveal the highly dynamic evolution of cas genes. This conclusion is in line with the involvement of CRISPR-Cas in antiviral immunity that is likely to entail a coevolutionary arms race with rapidly evolving viruses. However, we failed to detect evidence of strong positive selection in any of the cas genes.
When Charles Darwin formulated the central principles of evolutionary biology in the Origin of Species in 1859 and the architects of the Modern Synthesis integrated these principles with population genetics almost a century later, the principal if not the sole objects of evolutionary biology were multicellular eukaryotes, primarily animals and plants. Before the advent of efficient gene sequencing, all attempts to extend evolutionary studies to bacteria have been futile. Sequencing of the rRNA genes in thousands of microbes allowed the construction of the three- domain “ribosomal Tree of Life” that was widely thought to have resolved the evolutionary relationships between the cellular life forms. However, subsequent massive sequencing of numerous, complete microbial genomes revealed novel evolutionary phenomena, the most fundamental of these being: (1) pervasive horizontal gene transfer (HGT), in large part mediated by viruses and plasmids, that shapes the genomes of archaea and bacteria and call for a radical revision (if not abandonment) of the Tree of Life concept, (2) Lamarckian-type inheritance that appears to be critical for antivirus defense and other forms of adaptation in prokaryotes, and (3) evolution of evolvability, i.e., dedicated mechanisms for evolution such as vehicles for HGT and stress-induced mutagenesis systems. In the non-cellular part of the microbial world, phylogenomics and metagenomics of viruses and related selfish genetic elements revealed enormous genetic and molecular diversity and extremely high abundance of viruses that come across as the dominant biological entities on earth. Furthermore, the perennial arms race between viruses and their hosts is one of the defining factors of evolution. Thus, microbial phylogenomics adds new dimensions to the fundamental picture of evolution even as the principle of descent with modification discovered by Darwin and the laws of population genetics remain at the core of evolutionary biology.
Darwin; modern synthesis; comparative genomics; tree of life; horizontal gene transfer
Evolutionary binary characters are features of species or genes, indicating the absence (value zero) or presence (value one) of some property. Examples include eukaryotic gene architecture (the presence or absence of an intron in a particular locus), gene content, and morphological characters. In many studies, the acquisition of such binary characters is assumed to represent a rare evolutionary event, and consequently, their evolution is analyzed using various flavors of parsimony. However, when gain and loss of the character are not rare enough, a probabilistic analysis becomes essential. Here, we present a comprehensive probabilistic model to describe the evolution of binary characters on a bifurcating phylogenetic tree. A fast software tool, EREM, is provided, using maximum likelihood to estimate the parameters of the model and to reconstruct ancestral states (presence and absence in internal nodes) and events (gain and loss events along branches).
With the continuously accelerating genome sequencing from diverse groups of archaea and bacteria, accurate identification of gene orthology and availability of readily expandable clusters of orthologous genes are essential for the functional annotation of new genomes. We report an update of the collection of archaeal Clusters of Orthologous Genes (arCOGs) to cover, on average, 91% of the protein-coding genes in 168 archaeal genomes. The new arCOGs were constructed using refined algorithms for orthology identification combined with extensive manual curation, including incorporation of the results of several completed and ongoing research projects in archaeal genomics. A new level of classification is introduced, superclusters that unit two or more arCOGs and more completely reflect gene family evolution than individual, disconnected arCOGs. Assessment of the current archaeal genome annotation in public databases indicates that consistent use of arCOGs can significantly improve the annotation quality. In addition to their utility for genome annotation, arCOGs also are a platform for phylogenomic analysis. We explore this aspect of arCOGs by performing a phylogenomic study of the Thermococci that are traditionally viewed as the basal branch of the Euryarchaeota. The results of phylogenomic analysis that involved both comparison of multiple phylogenetic trees and a search for putative derived shared characters by using phyletic patterns extracted from the arCOGs reveal a likely evolutionary relationship between the Thermococci, Methanococci, and Methanobacteria. The arCOGs are expected to be instrumental for a comprehensive phylogenomic study of the archaea.
arCOGs; genome annotation; phylogenomics; Thermococci; methanogens
When selection is strong and mutations are rare, evolution can be thought of as an uphill trajectory in a rugged fitness landscape. In this context the fitness landscape is a directed acyclic graph in which nodes are genotypes and edges lead from lower to higher fitness genotypes that differ by a single mutation. Because the space of genotypes is vastly multi-dimensional, classification of fitness landscapes is challenging. Many proposed summary characteristics of fitness landscapes attempt to quantify biologically relevant and intuitive notions such as roughness or peak accessibility in alternative ways. Here we explore, in different types of landscapes, the behavior of the recently introduced mean path divergence which quantifies the degree of similarity among evolutionary trajectories with the same endpoints. We find that monotonic trajectories in empirical and model fitness landscapes are significantly more constrained, with low median path divergence, than those in purely additive landscapes. By contrast, transcription factor sequence specificity (aptamer binding affinity) landscapes are markedly smoother and allow substantial variability in monotonic paths that can be greater than that in fully additive landscapes. We propose that the smoothness of the specificity landscapes is a consequence of the simple dependence of the transcription factor binding affinity on the aptamer sequence in contrast to the complex sequence-fitness mapping in folding landscapes.
Microbial genome sequencing projects produce numerous sequences of deduced proteins, only a small fraction of which have been or will ever be studied experimentally. This leaves sequence analysis as the only feasible way to annotate these proteins and assign to them tentative functions. The Clusters of Orthologous Groups of proteins (COGs) database (http://www.ncbi.nlm.nih.gov/COG/), first created in 1997, has been a popular tool for functional annotation. Its success was largely based on (i) its reliance on complete microbial genomes, which allowed reliable assignment of orthologs and paralogs for most genes; (ii) orthology-based approach, which used the function(s) of the characterized member(s) of the protein family (COG) to assign function(s) to the entire set of carefully identified orthologs and describe the range of potential functions when there were more than one; and (iii) careful manual curation of the annotation of the COGs, aimed at detailed prediction of the biological function(s) for each COG while avoiding annotation errors and overprediction. Here we present an update of the COGs, the first since 2003, and a comprehensive revision of the COG annotations and expansion of the genome coverage to include representative complete genomes from all bacterial and archaeal lineages down to the genus level. This re-analysis of the COGs shows that the original COG assignments had an error rate below 0.5% and allows an assessment of the progress in functional genomics in the past 12 years. During this time, functions of many previously uncharacterized COGs have been elucidated and tentative functional assignments of many COGs have been validated, either by targeted experiments or through the use of high-throughput methods. A particularly important development is the assignment of functions to several widespread, conserved proteins many of which turned out to participate in translation, in particular rRNA maturation and tRNA modification. The new version of the COGs is expected to become an important tool for microbial genomics.
Microbial genomes encompass a sizable fraction of poorly characterized, narrowly spread fast-evolving genes. Using sensitive methods for sequences comparison and protein structure prediction, we performed a detailed comparative analysis of clusters of such genes, which we denote “dark matter islands”, in archaeal genomes. The dark matter islands comprise up to 20 % of archaeal genomes and show remarkable heterogeneity and diversity. Nevertheless, three classes of entities are common in these genomic loci: (a) integrated viral genomes and other mobile elements; (b) defense systems, and (c) secretory and other membrane-associated systems. The dark matter islands in the genome of thermophiles and mesophiles show similar general trends of gene content, but thermophiles are substantially enriched in predicted membrane proteins whereas mesophiles have a greater proportion of recognizable mobile elements. Based on this analysis, we predict the existence of several novel groups of viruses and mobile elements, previously unnoticed variants of CRISPR-Cas immune systems, and new secretory systems that might be involved in stress response, intermicrobial conflicts and biogenesis of novel, uncharacterized membrane structures.
Electronic supplementary material
The online version of this article (doi:10.1007/s00792-014-0672-7) contains supplementary material, which is available to authorized users.
Archaeal genomes; ORFans; Genomic islands; Integration; Viruses; Defense
Gene evolution is traditionally considered within the framework of the molecular clock (MC) model whereby each gene is characterized by an approximately constant rate of evolution. Recent comparative analysis of numerous phylogenies of prokaryotic genes has shown that a different model of evolution, denoted the Universal PaceMaker (UPM), which postulates conservation of relative, rather than absolute evolutionary rates, yields a better fit to the phylogenetic data. Here, we show that the UPM model is a better fit than the MC for genome wide sets of phylogenetic trees from six species of Drosophila and nine species of yeast, with extremely high statistical significance. Unlike the prokaryotic phylogenies that include distant organisms and multiple horizontal gene transfers, these are simple data sets that cover groups of closely related organisms and consist of gene trees with the same topology as the species tree. The results indicate that both lineage-specific and gene-specific rates are important in genome evolution but the lineage-specific contribution is greater. Similar to the MC, the gene evolution rates under the UPM are strongly overdispersed, approximately 2-fold compared with the expectation from sampling error alone. However, we show that neither Drosophila nor yeast genes form distinct clusters in the tree space. Thus, the gene-specific deviations from the UPM, although substantial, are uncorrelated and most likely depend on selective factors that are largely unique to individual genes. Thus, the UPM appears to be a key feature of genome evolution across the history of cellular life.
molecular clock; genome evolution; phylogenetic trees; relative evolution rates
Genome-wide comparison of phylogenetic trees is becoming an increasingly common approach in evolutionary genomics, and a variety of approaches for such comparison have been developed. In this article we present several methods for comparative analysis of large numbers of phylogenetic trees. To compare phylogenetic trees taking into account the bootstrap support for each internal branch, the Boot-Split Distance (BSD) method is introduced as an extension of the previously developed Split Distance (SD) method for tree comparison. The BSD method implements the straightforward idea that comparison of phylogenetic trees can be made more robust by treating tree splits differentially depending on the bootstrap support. Approaches are also introduced for detecting tree-like and net-like evolutionary trends in the phylogenetic Forest of Life (FOL), i.e., the entirety of the phylogenetic trees for conserved genes of prokaryotes. The principal method employed for this purpose includes mapping quartets of species onto trees to calculate the support of each quartet topology and so to quantify the tree and net contributions to the distances between species. We describe the applications methods used to analyze the FOL and the results obtained with these methods. These results support the concept of the Tree of Life (TOL) as a central evolutionary trend in the FOL as opposed to the traditional view of the TOL as a ‘species tree’.
Forest of life; tree of life; phylogenomic methods; tree comparison; map of quartets
The shape of the distribution of evolutionary distances between orthologous genes in pairs of closely related genomes is universal throughout the entire range of cellular life forms. The near invariance of this distribution across billions of years of evolution can be accounted for by the Universal Pace Maker (UPM) model of genome evolution that yields a significantly better fit to the phylogenetic data than the Molecular Clock (MC) model. Unlike the MC, the UPM model does not assume constant gene-specific evolutionary rates but rather postulates that, in each evolving lineage, the evolutionary rates of all genes change (approximately) in unison although the pacemakers of different lineages are not necessarily synchronized. Here, we dissect the nearly constant evolutionary rate distribution by comparing the genome-wide relative rates of evolution of individual genes in pairs or triplets of closely related genomes from diverse bacterial and archaeal taxa. We show that, although the gene-specific relative rate is an important feature of genome evolution that explains more than half of the variance of the evolutionary distances, the ranges of relative rate variability are extremely broad even for universal genes. Because of this high variance, the gene-specific rate is a poor predictor of the conservation rank for any gene in any particular lineage.
evolutionary rate; universal genes; molecular clock; universal pacemaker of genome evolution
Our knowledge of prokaryotic defense systems has vastly expanded as the result of comparative genomic analysis, followed by experimental validation. This expansion is both quantitative, including the discovery of diverse new examples of known types of defense systems, such as restriction-modification or toxin-antitoxin systems, and qualitative, including the discovery of fundamentally new defense mechanisms, such as the CRISPR-Cas immunity system. Large-scale statistical analysis reveals that the distribution of different defense systems in bacterial and archaeal taxa is non-uniform, with four groups of organisms distinguishable with respect to the overall abundance and the balance between specific types of defense systems. The genes encoding defense system components in bacterial and archaea typically cluster in defense islands. In addition to genes encoding known defense systems, these islands contain numerous uncharacterized genes, which are candidates for new types of defense systems. The tight association of the genes encoding immunity systems and dormancy- or cell death-inducing defense systems in prokaryotic genomes suggests that these two major types of defense are functionally coupled, providing for effective protection at the population level.
We compare the sets of experimentally validated long intergenic non-coding (linc)RNAs from human and mouse and apply a maximum likelihood approach to estimate the total number of lincRNA genes as well as the size of the conserved part of the lincRNome. Under the assumption that the sets of experimentally validated lincRNAs are random samples of the lincRNomes of the corresponding species, we estimate the total lincRNome size at approximately 40,000 to 50,000 species, at least twice the number of protein-coding genes. We further estimate that the fraction of the human and mouse euchromatic genomes encoding lincRNAs is more than twofold greater than the fraction of protein-coding sequences. Although the sequences of most lincRNAs are much less strongly conserved than protein sequences, the extent of orthology between the lincRNomes is unexpectedly high, with 60 to 70% of the lincRNA genes shared between human and mouse. The orthologous mammalian lincRNAs can be predicted to perform equivalent functions; accordingly, it appears likely that thousands of evolutionarily conserved functional roles of lincRNAs remain to be characterized.
Genome analysis of humans and other mammals reveals a surprisingly small number of protein-coding genes, only slightly over 20,000 (although the diversity of actual proteins is substantially augmented by alternative transcription and alternative splicing). Recent analysis of the mammalian genomes and transcriptomes, in particular, using the RNAseq technology, shows that, in addition to protein-coding genes, mammalian genomes encode many long non-coding RNAs. For some of these transcripts, various regulatory functions have been demonstrated, but on the whole the repertoire of long non-coding RNAs remains poorly characterized. We compared the identified long intergenic non-coding (linc)RNAs from human and mouse, and employed a specially developed statistical technique to estimate the size and evolutionary conservation of the human and mouse lincRNomes. The estimates show that there are at least twice as many human and mouse lincRNAs than there are protein-coding genes. Moreover, about two third of the lincRNA genes appear to be conserved between human and mouse, implying thousands of conserved but still uncharacterized functions.
Evolution of prokaryotes involves extensive loss and gain of genes, which lead to substantial differences in the gene repertoires even among closely related organisms. Through a wide range of phylogenetic depths, gene frequency distributions in prokaryotic pangenomes bear a characteristic, asymmetrical U-shape, with a core of (nearly) universal genes, a “shell” of moderately common genes, and a “cloud” of rare genes. We employ mathematical modeling to investigate evolutionary processes that might underlie this universal pattern. Gene frequency distributions for almost 400 groups of 10 bacterial or archaeal species each over a broad range of evolutionary distances were fit to steady-state, infinite allele models based on the distribution of gene replacement rates and the phylogenetic tree relating the species in each group. The fits of the theoretical frequency distributions to the empirical ones yield model parameters and estimates of the goodness of fit. Using the Akaike Information Criterion, we show that the neutral model of genome evolution, with the same replacement rate for all genes, can be confidently rejected. Of the three tested models with purifying selection, the one in which the distribution of replacement rates is derived from a stochastic population model with additive per-gene fitness yields the best fits to the data. The selection strength estimated from the fits declines with evolutionary divergence while staying well outside the neutral regime. These findings indicate that, unlike some other universal distributions of genomic variables, for example, the distribution of paralogous gene family membership, the gene frequency distribution is substantially affected by selection.
gene frequency distribution; steady genome model; goodness of fit; evolution mechanisms
We describe the draft genome of the microcrustacean Daphnia pulex, which is only 200 Mb and contains at least 30,907 genes. The high gene count is a consequence of an elevated rate of gene duplication resulting in tandem gene clusters. More than 1/3 of Daphnia’s genes have no detectable homologs in any other available proteome, and the most amplified gene families are specific to the Daphnia lineage. The co-expansion of gene families interacting within metabolic pathways suggests that the maintenance of duplicated genes is not random, and the analysis of gene expression under different environmental conditions reveals that numerous paralogs acquire divergent expression patterns soon after duplication. Daphnia-specific genes – including many additional loci within sequenced regions that are otherwise devoid of annotations – are the most responsive genes to ecological challenges.
A fundamental observation of comparative genomics is that the distribution of evolution rates across the complete sets of orthologous genes in pairs of related genomes remains virtually unchanged throughout the evolution of life, from bacteria to mammals. The most straightforward explanation for the conservation of this distribution appears to be that the relative evolution rates of all genes remain nearly constant, or in other words, that evolutionary rates of different genes are strongly correlated within each evolving genome. This correlation could be explained by a model that we denoted Universal PaceMaker (UPM) of genome evolution. The UPM model posits that the rate of evolution changes synchronously across genome-wide sets of genes in all evolving lineages. Alternatively, however, the correlation between the evolutionary rates of genes could be a simple consequence of molecular clock (MC). We sought to differentiate between the MC and UPM models by fitting thousands of phylogenetic trees for bacterial and archaeal genes to supertrees that reflect the dominant trend of vertical descent in the evolution of archaea and bacteria and that were constrained according to the two models. The goodness of fit for the UPM model was better than the fit for the MC model, with overwhelming statistical significance, although similarly to the MC, the UPM is strongly overdispersed. Thus, the results of this analysis reveal a universal, genome-wide pacemaker of evolution that could have been in operation throughout the history of life.
A central concept of evolution is Molecular Clock according to which each gene evolves at a characteristic, near constant rate. Numerous studies support the Molecular Clock hypothesis in principle but also show that the clock is indeed very approximate. Genome-wide comparative analysis of phylogenetic trees described here reveals a distinct, more general feature of genome evolution that we called Universal Pacemaker. Under this model, when the rate of evolution changes, the change occurs synchronously in many if not all genes in the evolving genome. In other words, the relative rates of gene evolution remain constant across long evolutionary spans: if a gene is slow relative to the rest of the genes in the given lineage, it is always slow, and if it evolves fast, it is always fast. We show here that the Universal Pacemaker model fits the available data much better than the traditional Molecular Clock model. These findings are compatible with the previously observed accelerations and decelerations of evolution in individual lineages but we show that synchronous, genome-wide change of evolutionary rates is a global feature of genome evolution that appears to pervade the entire history of life.
Orthologous relationships between genes are routinely inferred from bidirectional best hits (BBH) in pairwise genome comparisons. However, to our knowledge, it has never been quantitatively demonstrated that orthologs form BBH. To test this “BBH-orthology conjecture,” we take advantage of the operon organization of bacterial and archaeal genomes and assume that, when two genes in compared genomes are flanked by two BBH show statistically significant sequence similarity to one another, these genes are bona fide orthologs. Under this assumption, we tested whether middle genes in “syntenic orthologous gene triplets” form BBH. We found that this was the case in more than 95% of the syntenic gene triplets in all genome comparisons. A detailed examination of the exceptions to this pattern, including maximum likelihood phylogenetic tree analysis, showed that some of these deviations involved artifacts of genome annotation, whereas very small fractions represented random assignment of the best hit to one of closely related in-paralogs, paralogous displacement in situ, or even less frequent genuine violations of the BBH–orthology conjecture caused by acceleration of evolution in one of the orthologs. We conclude that, at least in prokaryotes, genes for which independent evidence of orthology is available typically form BBH and, conversely, BBH can serve as a strong indication of gene orthology.
orthology; bidirectional best hit; genome comparison; synteny
There are no known RNA viruses that infect Archaea. Filling this gap in our knowledge of viruses will enhance our understanding of the relationships between RNA viruses from the three domains of cellular life and, in particular, could shed light on the origin of the enormous diversity of RNA viruses infecting eukaryotes. We describe here the identification of novel RNA viral genome segments from high-temperature acidic hot springs in Yellowstone National Park in the United States. These hot springs harbor low-complexity cellular communities dominated by several species of hyperthermophilic Archaea. A viral metagenomics approach was taken to assemble segments of these RNA virus genomes from viral populations isolated directly from hot spring samples. Analysis of these RNA metagenomes demonstrated unique gene content that is not generally related to known RNA viruses of Bacteria and Eukarya. However, genes for RNA-dependent RNA polymerase (RdRp), a hallmark of positive-strand RNA viruses, were identified in two contigs. One of these contigs is approximately 5,600 nucleotides in length and encodes a polyprotein that also contains a region homologous to the capsid protein of nodaviruses, tetraviruses, and birnaviruses. Phylogenetic analyses of the RdRps encoded in these contigs indicate that the putative archaeal viruses form a unique group that is distinct from the RdRps of RNA viruses of Eukarya and Bacteria. Collectively, our findings suggest the existence of novel positive-strand RNA viruses that probably replicate in hyperthermophilic archaeal hosts and are highly divergent from RNA viruses that infect eukaryotes and even more distant from known bacterial RNA viruses. These positive-strand RNA viruses might be direct ancestors of RNA viruses of eukaryotes.
Spliceosomal introns are one of the principal distinctive features of eukaryotes. Nevertheless, different large-scale studies disagree about even the most basic features of their evolution. In order to come up with a more reliable reconstruction of intron evolution, we developed a model that is far more comprehensive than previous ones. This model is rich in parameters, and estimating them accurately is infeasible by straightforward likelihood maximization. Thus, we have developed an expectation-maximization algorithm that allows for efficient maximization. Here, we outline the model and describe the expectation-maximization algorithm in detail. Since the method works with intron presence–absence maps, it is expected to be instrumental for the analysis of the evolution of other binary characters as well.
Maximum likelihood; expectation-maximization; intron evolution; ancestral reconstruction; eukaryotic gene structure
Archaeal and bacterial ribosomes contain more than 50 proteins, including 34 that are universally conserved in the three domains of cellular life (bacteria, archaea, and eukaryotes). Despite the high sequence conservation, annotation of ribosomal (r-) protein genes is often difficult because of their short lengths and biased sequence composition. We developed an automated computational pipeline for identification of r-protein genes and applied it to 995 completely sequenced bacterial and 87 archaeal genomes available in the RefSeq database. The pipeline employs curated seed alignments of r-proteins to run position-specific scoring matrix (PSSM)-based BLAST searches against six-frame genome translations, mitigating possible gene annotation errors. As a result of this analysis, we performed a census of prokaryotic r-protein complements, enumerated missing and paralogous r-proteins, and analyzed the distributions of ribosomal protein genes among chromosomal partitions. Phyletic patterns of bacterial and archaeal r-protein genes were mapped to phylogenetic trees reconstructed from concatenated alignments of r-proteins to reveal the history of likely multiple independent gains and losses. These alignments, available for download, can be used as search profiles to improve genome annotation of r-proteins and for further comparative genomics studies.
Multiple constraints variously affect different parts of the genomes of diverse life forms. The selective pressures that shape the evolution of viral, archaeal, bacterial and eukaryotic genomes differ markedly, even among relatively closely related animal and bacterial lineages; by contrast, constraints affecting protein evolution seem to be more universal. The constraints that shape the evolution of genomes and phenomes are complemented by the plasticity and robustness of genome architecture, expression and regulation. Taken together, these findings are starting to reveal complex networks of evolutionary processes that must be integrated to attain a new synthesis of evolutionary biology.