Estimating Pangenomes with Roary.

A description of the genetic makeup of a species based on a single genome is often insufficient because it ignores the variability in gene repertoire among multiple strains. The estimation of the pangenome of a species is a solution to this issue as it provides an overview of genes that are shared by all strains and genes that are present in only some of the genomes. These different sets of genes can then be analyzed functionally to explore correlations with unique phenotypes and adaptations. This protocol presents the usage of Roary, a Linux-native pangenome application. Roary is a straightforward software that provides 1) an overview about core and accessory genes for those interested in general trends and, also, 2) detailed information on gene presence/absence in each genome for in-depth analyses. Results are provided both in text and graphic format.

Choice of species affects phylogenetic stability of deep nodes: an empirical example in Terrabacteria.

MOTIVATION: The promise of higher phylogenetic stability through increased dataset sizes within tree of life (TOL) reconstructions has not been fulfilled. Among the many possible causes are changes in species composition (taxon sampling) that could influence phylogenetic accuracy of the methods by altering the relative weight of the evolutionary histories of each individual species. This effect would be stronger in clades that are represented by few lineages, which is common in many prokaryote phyla. Indeed, phyla with fewer taxa showed the most discordance among recent TOL studies. We implemented an approach to systematically test how the identity of taxa among a larger dataset and the number of taxa included affected the accuracy of phylogenetic reconstruction. RESULTS: Utilizing an empirical dataset within Terrabacteria we found that even within scenarios consisting of the same number of taxa, the species used strongly affected phylogenetic stability. Furthermore, we found that trees with fewer species were more dissimilar to the tree produced from the full dataset. These results hold even when the tree is composed by many phyla and only one of them is being altered. Thus, the effect of taxon sampling in one group does not seem to be buffered by the presence of many other clades, making this issue relevant even to very large datasets. Our results suggest that a systematic evaluation of phylogenetic stability through taxon resampling is advisable even for very large datasets. AVAILABILITY AND IMPLEMENTATION: https://github.com/BlabOaklandU/PATS.git. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The Timetree of Prokaryotes: New Insights into Their Evolution and Speciation.

The increasing size of timetrees in recent years has led to a focus on diversification analyses to better understand patterns of macroevolution. Thus far, nearly all studies have been conducted with eukaryotes primarily because phylogenies have been more difficult to reconstruct and calibrate to geologic time in prokaryotes. Here, we have estimated a timetree of 11,784 'species' of prokaryotes and explored their pattern of diversification. We used data from the small subunit ribosomal RNA along with an evolutionary framework from previous multi-gene studies to produce three alternative timetrees. For each timetree we surprisingly found a constant net diversification rate derived from an exponential increase of lineages and showing no evidence of saturation (rate decline), the same pattern found previously in eukaryotes. The implication is that prokaryote diversification as a whole is the result of the random splitting of lineages and is neither limited by existing diversity (filled niches) nor responsive in any major way to environmental changes.

Profiles of low complexity regions in Apicomplexa.

BACKGROUND: Low complexity regions (LCRs) are a ubiquitous feature in genomes and yet their evolutionary history and functional roles are unclear. Previous studies have shown contrasting evidence in favor of both neutral and selective mechanisms of evolution for different sets of LCRs suggesting that modes of identification of these regions may play a role in our ability to discern their evolutionary history. To further investigate this issue, we used a multiple threshold approach to identify species-specific profiles of proteome complexity and, by comparing properties of these sets, determine the influence that starting parameters have on evolutionary inferences. RESULTS: We find that, although qualitatively similar, quantitatively each species has a unique LCR profile which represents the frequency of these regions within each genome. Inferences based on these profiles are more accurate in comparative analyses of genome complexity as they allow to determine the relative complexity of multiple genomes as well as the type of repetitiveness that is most common in each. Based on the multiple threshold LCR sets obtained, we identified predominant evolutionary mechanisms at different complexity levels, which show neutral mechanisms acting on highly repetitive LCRs (e.g., homopolymers) and selective forces becoming more important as heterogeneity of the LCRs increases. CONCLUSIONS: Our results show how inferences based on LCRs are influenced by the parameters used to identify these regions. Sets of LCRs are heterogeneous aggregates of regions that include homo- and heteropolymers and, as such, evolve according to different mechanisms. LCR profiles provide a new way to investigate genome complexity across species and to determine the driving mechanism of their evolution.

A Protocol for Diagnosing the Effect of Calibration Priors on Posterior Time Estimates: A Case Study for the Cambrian Explosion of Animal Phyla.

We present a procedure to test the effect of calibration priors on estimated times, which applies a recently developed calibration-free approach (RelTime) method that produces relative divergence times for all nodes in the tree. We illustrate this protocol by applying it to a timetree of metazoan diversification (Erwin DH, Laflamme M, Tweedt SM, Sperling EA, Pisani D, Peterson KJ. 2011. The Cambrian conundrum: early divergence and later ecological success in the early history of animals. Science 334:1091-1097.), which placed the divergence of animal phyla close to the time of the Cambrian explosion inferred from the fossil record. These analyses revealed that the two maximum-only calibration priors in the pre-Cambrian are the primary determinants of the young divergence times among animal phyla in this study. In fact, these two maximum-only calibrations produce divergence times that severely violate minimum boundaries of almost all of the other 22 calibration constraints. The use of these 22 calibrations produces dates for metazoan divergences that are hundreds of millions of years earlier in the Proterozoic. Our results encourage the use of calibration-free approaches to identify most influential calibration constraints and to evaluate their impact in order to achieve biologically robust interpretations.

Discovery and expression analysis of alternative splicing events conserved among plant SR proteins.

The high frequency of alternative splicing among the serine/arginine-rich (SR) family of proteins in plants has been linked to important roles in gene regulation during development and in response to environmental stress. In this article, we have searched and manually annotated all the SR proteins in the genomes of maize and sorghum. The experimental validation of gene structure by reverse transcription-polymerase chain reaction (RT-PCR) analysis revealed, with few exceptions, that SR genes produced multiple isoforms of transcripts by alternative splicing. Despite sharing high structural similarity and conserved positions of the introns, the profile of alternative splicing diverged significantly between maize and sorghum for the vast majority of SR genes. These include many transcript isoforms discovered by RT-PCR and not represented in extant expressed sequence tag (EST) collection. However, we report the occurrence of various maize and sorghum SR mRNA isoforms that display evolutionary conservation of splicing events with their homologous SR genes in Arabidopsis and moss. Our data also indicate an important role of both 5' and 3' untranslated regions in the regulation of SR gene expression. These observations have potentially important implications for the processes of evolution and adaptation of plants to land.

Statistics and truth in phylogenomics.

Phylogenomics refers to the inference of historical relationships among species using genome-scale sequence data and to the use of phylogenetic analysis to infer protein function in multigene families. With rapidly decreasing sequencing costs, phylogenomics is becoming synonymous with evolutionary analysis of genome-scale and taxonomically densely sampled data sets. In phylogenetic inference applications, this translates into very large data sets that yield evolutionary and functional inferences with extremely small variances and high statistical confidence (P value). However, reports of highly significant P values are increasing even for contrasting phylogenetic hypotheses depending on the evolutionary model and inference method used, making it difficult to establish true relationships. We argue that the assessment of the robustness of results to biological factors, that may systematically mislead (bias) the outcomes of statistical estimation, will be a key to avoiding incorrect phylogenomic inferences. In fact, there is a need for increased emphasis on the magnitude of differences (effect sizes) in addition to the P values of the statistical test of the null hypothesis. On the other hand, the amount of sequence data available will likely always remain inadequate for some phylogenomic applications, for example, those involving episodic positive selection at individual codon positions and in specific lineages. Again, a focus on effect size and biological relevance, rather than the P value, may be warranted. Here, we present a theoretical overview and discuss practical aspects of the interplay between effect sizes, bias, and P values as it relates to the statistical inference of evolutionary truth in phylogenomics.

Identification of genomic loci regulating platelet plasminogen activator inhibitor-1 in mice.

BACKGROUND: Plasminogen activator inhibitor-1 (PAI-1, Serpine1) is an important circulating fibrinolysis inhibitor. PAI-1 exists in 2 pools, packaged within platelet α-granules and freely circulating in plasma. Elevated plasma PAI-1 levels are associated with cardiovascular disease. However, little is known about the regulation of platelet PAI-1 (pPAI-1). OBJECTIVES: We investigated the genetic control of pPAI-1 levels in mice and humans. METHODS: We measured pPAI-1 antigen levels via enzyme-linked immunosorbent assay in platelets isolated from 10 inbred mouse strains, including LEWES/EiJ (LEWES) and C57BL/6J (B6). LEWES and B6 were crossed to produce the F1 generation, B6LEWESF1. B6LEWESF1 mice were intercrossed to produce B6LEWESF2 mice. These mice were subjected to genome-wide genetic marker genotyping followed by quantitative trait locus analysis to identify pPAI-1 regulatory loci. RESULTS: We identified differences in pPAI-1 between several laboratory strains, with LEWES having pPAI-1 levels more than 10-fold higher than those in B6. Quantitative trait locus analysis of B6LEWESF2 offspring identified a major pPAI-1 regulatory locus on chromosome 5 from 136.1 to 137.6 Mb (logarithm of the odds score, 16.2). Significant pPAI-1 modifier loci on chromosomes 6 and 13 were also identified. CONCLUSION: Identification of pPAI-1 genomic regulatory elements provides insights into platelet/megakaryocyte-specific and cell type-specific gene expression. This information can be used to design more precise therapeutic targets for diseases where PAI-1 plays a role.

Fast and slow implementations of relaxed-clock methods show similar patterns of accuracy in estimating divergence times.

Phylogenetic analyses are using increasingly larger data sets for estimating divergence times. With this increase in data sizes, the computation time required is becoming a bottleneck in evolutionary investigations. Our recent study of two relaxed-clock programs (BEAST and MultiDivTime [MDT]) showed their usefulness in time estimation; however, they place a significant computational time burden on biologists even for moderately small data sets. Here, we report speed and accuracy of another relaxed-clock program (MCMCTree, MC2T). We find it to be much faster than both MDT and BEAST while producing comparable time estimates. These results will encourage the analysis of larger data sets as well as the evaluation of the robustness of estimated times to changes in the model of evolutionary rates and clock calibrations.

Evolution of modern birds revealed by mitogenomics: timing the radiation and origin of major orders.

Mitochondrial (mt) genes and genomes are among the major sources of data for evolutionary studies in birds. This places mitogenomic studies in birds at the core of intense debates in avian evolutionary biology. Indeed, complete mt genomes are actively been used to unveil the phylogenetic relationships among major orders, whereas single genes (e.g., cytochrome c oxidase I [COX1]) are considered standard for species identification and defining species boundaries (DNA barcoding). In this investigation, we study the time of origin and evolutionary relationships among Neoaves orders using complete mt genomes. First, we were able to solve polytomies previously observed at the deep nodes of the Neoaves phylogeny by analyzing 80 mt genomes, including 17 new sequences reported in this investigation. As an example, we found evidence indicating that columbiforms and charadriforms are sister groups. Overall, our analyses indicate that by improving the taxonomic sampling, complete mt genomes can solve the evolutionary relationships among major bird groups. Second, we used our phylogenetic hypotheses to estimate the time of origin of major avian orders as a way to test if their diversification took place prior to the Cretaceous/Tertiary (K/T) boundary. Such timetrees were estimated using several molecular dating approaches and conservative calibration points. Whereas we found time estimates slightly younger than those reported by others, most of the major orders originated prior to the K/T boundary. Finally, we used our timetrees to estimate the rate of evolution of each mt gene. We found great variation on the mutation rates among mt genes and within different bird groups. COX1 was the gene with less variation among Neoaves orders and the one with the least amount of rate heterogeneity across lineages. Such findings support the choice of COX 1 among mt genes as target for developing DNA barcoding approaches in birds.

Molecular evidence for an Asian origin of monitor lizards followed by Tertiary dispersals to Africa and Australasia.

Monitor lizards are emblematic reptiles that are widely distributed in the Old World. Although relatively well studied in vertebrate research, their biogeographic history is still controversial. We constructed a molecular dataset for 54 anguimorph species, including representatives of all families with detailed sampling of the Varanidae (38 species). Our results are consistent with an Asian origin of the Varanidae followed by a dispersal to Africa 41 (49-33) Ma, possibly via an Iranian route. Another major event was the dispersal of monitors to Australia in the Late Eocene-Oligocene 32 (39-26) Ma. This divergence estimate adds to the suggestion that Australia was colonized by several squamate lineages prior to the collision of the Australian plate with the Asian plate starting 25 Ma.

Genomics of Adaptation and Speciation.

The availability of genome data provides a unique window into speciation mechanisms with virtually infinite amounts of information, providing a pathway for a better understanding of major evolutionary questions [...].

Back to the Future: Reintegrating Biology to Understand How Past Eco-evolutionary Change Can Predict Future Outcomes.

During the last few decades, biologists have made remarkable progress in understanding the fundamental processes that shape life. But despite the unprecedented level of knowledge now available, large gaps still remain in our understanding of the complex interplay of eco-evolutionary mechanisms across scales of life. Rapidly changing environments on Earth provide a pressing need to understand the potential implications of eco-evolutionary dynamics, which can be achieved by improving existing eco-evolutionary models and fostering convergence among the sub-fields of biology. We propose a new, data-driven approach that harnesses our knowledge of the functioning of biological systems to expand current conceptual frameworks and develop corresponding models that can more accurately represent and predict future eco-evolutionary outcomes. We suggest a roadmap toward achieving this goal. This long-term vision will move biology in a direction that can wield these predictive models for scientific applications that benefit humanity and increase the resilience of natural biological systems. We identify short, medium, and long-term key objectives to connect our current state of knowledge to this long-term vision, iteratively progressing across three stages: (1) utilizing knowledge of biological systems to better inform eco-evolutionary models, (2) generating models with more accurate predictions, and (3) applying predictive models to benefit the biosphere. Within each stage, we outline avenues of investigation and scientific applications related to the timescales over which evolution occurs, the parameter space of eco-evolutionary processes, and the dynamic interactions between these mechanisms. The ability to accurately model, monitor, and anticipate eco-evolutionary changes would be transformational to humanity's interaction with the global environment, providing novel tools to benefit human health, protect the natural world, and manage our planet's biosphere.

Genetic analysis of human RNA binding motif protein 48 (RBM48) reveals an essential role in U12-type intron splicing.

U12-type or minor introns are found in most multicellular eukaryotes and constitute ∼0.5% of all introns in species with a minor spliceosome. Although the biological significance for the evolutionary conservation of U12-type introns is debated, mutations disrupting U12 splicing cause developmental defects in both plants and animals. In human hematopoietic stem cells, U12 splicing defects disrupt proper differentiation of myeloid lineages and are associated with myelodysplastic syndrome, predisposing individuals to acute myeloid leukemia. Mutants in the maize ortholog of RNA binding motif protein 48 (RBM48) have aberrant U12-type intron splicing. Human RBM48 was recently purified biochemically as part of the minor spliceosome and shown to recognize the 5' end of the U6atac snRNA. In this report, we use CRISPR/Cas9-mediated ablation of RBM48 in human K-562 cells to show the genetic function of RBM48. RNA-seq analysis comparing wild-type and mutant K-562 genotypes found that 48% of minor intron-containing genes have significant U12-type intron retention in RBM48 mutants. Comparing these results to maize rbm48 mutants defined a subset of minor intron-containing genes disrupted in both species. Mutations in the majority of these orthologous minor intron-containing genes have been reported to cause developmental defects in both plants and animals. Our results provide genetic evidence that the primary defect of human RBM48 mutants is aberrant U12-type intron splicing, while a comparison of human and maize RNA-seq data identifies candidate genes likely to mediate mutant phenotypes of U12-type splicing defects.

Timing the origin of human malarias: the lemur puzzle.

BACKGROUND: Timing the origin of human malarias has been a focus of great interest. Previous studies on the mitochondrial genome concluded that Plasmodium in primates, including those parasitic to humans, radiated relatively recently during a process where host switches were common. Those investigations, however, assumed constant rate of evolution and tightly bound (fixed) calibration points based on host fossils or host distribution. We investigate the effect of such assumptions using different molecular dating methods. We include parasites from Lemuroidea since their distribution provides an external validation to time estimates allowing us to disregard scenarios that cannot explain their introduction in Madagascar. RESULTS: We reject the assumption that the Plasmodium mitochondrial genome, as a unit or each gene separately, evolves at a constant rate. Our analyses show that Lemuroidea parasites are a monophyletic group that shares a common ancestor with all Catarrhini malarias except those related to P. falciparum. However, we found no evidence that this group of parasites branched with their hosts early in the evolution of primates. We applied relaxed clock methods and different calibrations points to explore the origin of primate malarias including those found in African apes. We showed that previous studies likely underestimated the origin of malarial parasites in primates. CONCLUSIONS: The use of fossils from the host as absolute calibration and the assumption of a strict clock likely underestimate time when performing molecular dating analyses on malarial parasites. Indeed, by exploring different calibration points, we found that the time for the radiation of primate parasites may have taken place in the Eocene, a time consistent with the radiation of African anthropoids. The radiation of the four human parasite lineages was part of such events. The time frame estimated in this investigation, together with our phylogenetic analyses, made plausible a scenario where gorillas and humans acquired malaria from a Pan lineage.

Performance of relaxed-clock methods in estimating evolutionary divergence times and their credibility intervals.

The rapid expansion of sequence data and the development of statistical approaches that embrace varying evolutionary rates among lineages have encouraged many more investigators to use DNA and protein data to time species divergences. Here, we report results from a systematic evaluation, by means of computer simulation, of the performance of two frequently used relaxed-clock methods for estimating these times and their credibility intervals (CrIs). These relaxed-clock methods allow rates to vary in a phylogeny randomly over lineages (e.g., BEAST software) and in autocorrelated fashion (e.g., MultiDivTime software). We applied these methods for analyzing sequence data sets simulated using naturally derived parameters (evolutionary rates, sequence lengths, and base substitution patterns) and assuming that clock calibrations are known without error. We find that the estimated times are, on average, close to the true times as long as the assumed model of lineage rate changes matches the actual model. The 95% CrIs also contain the true time for >or=95% of the simulated data sets. However, the use of incorrect lineage rate model reduces this frequency to 83%, indicating that the relaxed-clock methods are not robust to the violation of underlying lineage rate model. Because these rate models are rarely known a priori and are difficult to detect empirically, we suggest building composite CrIs using CrIs produced from MultiDivTime and BEAST analysis. These composite CrIs are found to contain the true time for >or=97% data sets. Our analyses also verify the usefulness of the common practice of interpreting the congruence of times inferred from different methods as a reflection of the accuracy of time estimates. Overall, our results show that simple strategies can be used to enhance our ability to estimate times and their CrIs when using the relaxed-clock methods.

A major clade of prokaryotes with ancient adaptations to life on land.

Evolutionary trees of prokaryotes usually define the known classes and phyla but less often agree on the relationships among those groups. This has been attributed to the effects of horizontal gene transfer, biases in sequence change, and large evolutionary distances. Furthermore, higher level clades of prokaryote phyla rarely are supported by information from ecology and cell biology. Nonetheless, common patterns are beginning to emerge as larger numbers of species are analyzed with sophisticated methods. Here, we show how combined evidence from phylogenetic, cytological, and environmental data support the existence of an evolutionary group that appears to have had a common ancestor on land early in Earth's history and includes two-thirds of known prokaryote species. Members of this terrestrial clade (Terrabacteria), which includes Cyanobacteria, the gram-positive phyla (Actinobacteria and Firmicutes), and two phyla with cell walls that differ structurally from typical gram-positive and gram-negative phyla (Chloroflexi and Deinococcus-Thermus), possess important adaptations such as resistance to environmental hazards (e.g., desiccation, ultraviolet radiation, and high salinity) and oxygenic photosynthesis. Moreover, the unique properties of the cell wall in gram-positive taxa, which likely evolved in response to terrestrial conditions, have contributed toward pathogenicity in many species. These results now leave open the possibility that terrestrial adaptations may have played a larger role in prokaryote evolution than currently understood.

RelTime Relaxes the Strict Molecular Clock throughout the Phylogeny.

The RelTime method estimates divergence times when evolutionary rates vary among lineages. Theoretical analyses show that RelTime relaxes the strict molecular clock throughout a molecular phylogeny, and it performs well in the analyses of empirical and computer simulated data sets in which evolutionary rates are variable. Lozano-Fernandez et al. (2017) found that the application of RelTime to one metazoan data set (Erwin et al. 2011) produced equal rates for several ancient lineages, which led them to speculate that RelTime imposes a strict molecular clock for deep animal divergences. RelTime does not impose a strict molecular clock. The pattern observed by Lozano-Fernandez et al. (2017) was a result of the use of an option to assign the same rate to lineages in RelTime when the rates are not statistically significantly different. The median rate difference was 5% for many deep metazoan lineages for the Erwin et al. (2011) data set, so the rate equality was not rejected. In fact, RelTime analyses with and without the option to test rate differences produced very similar time estimates. We also found that the Bayesian time estimates vary widely depending on the root priors assigned, and that the use of less restrictive priors produces Bayesian divergence times that are concordant with those from RelTime for the Erwin et al. (2011) data set. Therefore, it is prudent to discuss Bayesian estimates obtained under a range of priors in any discourse about molecular dating, including method comparisons.

A genomic timescale of prokaryote evolution: insights into the origin of methanogenesis, phototrophy, and the colonization of land.

BACKGROUND: The timescale of prokaryote evolution has been difficult to reconstruct because of a limited fossil record and complexities associated with molecular clocks and deep divergences. However, the relatively large number of genome sequences currently available has provided a better opportunity to control for potential biases such as horizontal gene transfer and rate differences among lineages. We assembled a data set of sequences from 32 proteins (approximately 7600 amino acids) common to 72 species and estimated phylogenetic relationships and divergence times with a local clock method. RESULTS: Our phylogenetic results support most of the currently recognized higher-level groupings of prokaryotes. Of particular interest is a well-supported group of three major lineages of eubacteria (Actinobacteria, Deinococcus, and Cyanobacteria) that we call Terrabacteria and associate with an early colonization of land. Divergence time estimates for the major groups of eubacteria are between 2.5-3.2 billion years ago (Ga) while those for archaebacteria are mostly between 3.1-4.1 Ga. The time estimates suggest a Hadean origin of life (prior to 4.1 Ga), an early origin of methanogenesis (3.8-4.1 Ga), an origin of anaerobic methanotrophy after 3.1 Ga, an origin of phototrophy prior to 3.2 Ga, an early colonization of land 2.8-3.1 Ga, and an origin of aerobic methanotrophy 2.5-2.8 Ga. CONCLUSIONS: Our early time estimates for methanogenesis support the consideration of methane, in addition to carbon dioxide, as a greenhouse gas responsible for the early warming of the Earths' surface. Our divergence times for the origin of anaerobic methanotrophy are compatible with highly depleted carbon isotopic values found in rocks dated 2.8-2.6 Ga. An early origin of phototrophy is consistent with the earliest bacterial mats and structures identified as stromatolites, but a 2.6 Ga origin of cyanobacteria suggests that those Archean structures, if biologically produced, were made by anoxygenic photosynthesizers. The resistance to desiccation of Terrabacteria and their elaboration of photoprotective compounds suggests that the common ancestor of this group inhabited land. If true, then oxygenic photosynthesis may owe its origin to terrestrial adaptations.