Incongruence in the phylogenomics era

Genome-scale data and the development of novel statistical phylogenetic approaches have greatly aided the reconstruction of a broad sketch of the tree of life and resolved many of its branches. However, incongruence - the inference of conflicting evolutionary histories - remains pervasive in phylogenomic data, hampering our ability to reconstruct and interpret the tree of life. Biological factors, such as incomplete lineage sorting, horizontal gene transfer, hybridization, introgression, recombination and convergent molecular evolution, can lead to gene phylogenies that differ from the species tree. In addition, analytical factors, including stochastic, systematic and treatment errors, can drive incongruence. Here, we review these factors, discuss methodological advances to identify and handle incongruence, and highlight avenues for future research.

Genome sequencing and resequencing identified three horizontal gene transfers and uncovered the genetic mechanism on the intraspecies adaptive evolution of Gastrodia elata Blume

Horizontal gene transfer is a rare and useful genetic mechanism in higher plants. Gastrodia elata Blume (GE) (Orchidaceae), well known as traditional medicinal material in East Asia, adopts a heterotrophic lifestyle, thus being considered to be more prone to horizontal gene transfer (HGT). GE is a "polytypic species" that currently comprised of five recognized forms according to the plant morphology. G. elata Blume forma elata (GEE) and G. elata Bl.f.glauca (GEG) are two common forms that naturally grow in different habitats with difference in altitude and latitude. G. elata Bl.f.viridis (GEV) often occurs sporadically in cultivated populations of GEE and GEG. However, the genetic relationships and genetic mechanism underpinned the divergent ecological adaptations of GEE and GEG have not been revealed. Here, we assembled a chromosome-level draft genome of GEE with 1.04 Gb. Among predicted 17,895 protein coding genes, we identified three HGTs. Meanwhile, we resequenced 10 GEE accessions, nine GEG accessions, and 10 GEV accessions, and identified two independent genetic lineages: GEG_pedigree (GEG individuals and GEV individuals collected from GEG populations) and GEE_pedigree (GEE individuals and GEV individuals collected from GEE populations), which strongly support the taxonomic status of GEE and GEG as subspecies, not as different forms. In highly differentiated genomic regions of GEE_pedigree and GEG_pedigree, three chalcone synthase-encoding genes and one Phox/Bem1p (PB1) domain of encoding Auxin (AUX)/Indoleacetic acid (IAA) were identified in selection sweeping genome regions, which suggested that differentiation between GEE_pedigree and GEG_pedigree was promoted by the selection of genes related to photoresponse and growth and development. Overall, this new genome would be helpful for breeding and utilization of GE and the new findings would deepen the understanding about ecological adaptation and evolution of GE.

Old genes in new places: A taxon-rich analysis of interdomain lateral gene transfer events

Vertical inheritance is foundational to Darwinian evolution, but fails to explain major innovations such as the rapid spread of antibiotic resistance among bacteria and the origin of photosynthesis in eukaryotes. While lateral gene transfer (LGT) is recognized as an evolutionary force in prokaryotes, the role of LGT in eukaryotic evolution is less clear. With the exception of the transfer of genes from organelles to the nucleus, a process termed endosymbiotic gene transfer (EGT), the extent of interdomain transfer from prokaryotes to eukaryotes is highly debated. A common critique of studies of interdomain LGT is the reliance on the topology of single-gene trees that attempt to estimate more than one billion years of evolution. We take a more conservative approach by identifying cases in which a single clade of eukaryotes is found in an otherwise prokaryotic gene tree (i.e. exclusive presence). Starting with a taxon-rich dataset of over 13,600 gene families and passing data through several rounds of curation, we identify and categorize the function of 306 interdomain LGT events into diverse eukaryotes, including 189 putative EGTs, 52 LGTs into Opisthokonta (i.e. animals, fungi and their microbial relatives), and 42 LGTs nearly exclusive to anaerobic eukaryotes. To assess differential gene loss as an explanation for exclusive presence, we compare branch lengths within each LGT tree to a set of vertically-inherited genes subsampled to mimic gene loss (i.e. with the same taxonomic sampling) and consistently find shorter relative distance between eukaryotes and prokaryotes in LGT trees, a pattern inconsistent with gene loss. Our methods provide a framework for future studies of interdomain LGT and move the field closer to an understanding of how best to model the evolutionary history of eukaryotes.

Conflict over the eukaryote root resides in strong outliers, mosaics and missing data sensitivity of site-specific (CAT) mixture models

Phylogenetic reconstruction using concatenated loci ("phylogenomics" or "supermatrix phylogeny") is a powerful tool for solving evolutionary splits that are poorly resolved in single gene/protein trees (SGTs). However, recent phylogenomic attempts to resolve the eukaryote root have yielded conflicting results, along with claims of various artefacts hidden in the data. We have investigated these conflicts using two new methods for assessing phylogenetic conflict. ConJak uses whole marker (gene or protein) jackknifing to assess deviation from a central mean for each individual sequence, while ConWin uses a sliding window to screen for incongruent protein fragments (mosaics). Both methods allow selective masking of individual sequences or sequence fragments in order to minimize missing data, an important consideration for resolving deep splits with limited data. Analyses focused on a set of 76 eukaryotic proteins of bacterial-ancestry previously used in various combinations to assess the branching order among the three major divisions of eukaryotes: Amorphea (mainly animals, fungi and Amoebozoa), Diaphoretickes (most other well-known eukaryotes and nearly all algae) and Excavata, represented here by Discoba (Jakobida, Heterolobosea, and Euglenozoa). ConJak analyses found strong outliers to be concentrated in under-sampled lineages, while ConWin analyses of Discoba, the most under-sampled of the major lineages, detected potentially incongruent fragments scattered throughout. Phylogenetic analyses of the full data using an LG-gamma model support a Discoba sister scenario (neozoan-excavate root), which rises to 99-100% bootstrap support with data masked according to either protocol. However, analyses with two site-specific (CAT) mixture models yielded widely inconsistent results and a striking sensitivity to missing data. The neozoan-excavate root places Amorphea and Diaphoretickes as more closely related to each other than either is to Discoba, a fundamental relationship that should remain unaffected by additional taxa.

The Evolutionary Origins of Extreme Halophilic Archaeal Lineages

Interest and controversy surrounding the evolutionary origins of extremely halophilic Archaea has increased in recent years, due to the discovery and characterization of the Nanohaloarchaea and the Methanonatronarchaeia. Initial attempts in explaining the evolutionary placement of the two new lineages in relation to the classical Halobacteria (also referred to as Haloarchaea) resulted in hypotheses that imply the new groups share a common ancestor with the Haloarchaea. However, more recent analyses have led to a shift: the Nanohaloarchaea have been largely accepted as being a member of the DPANN superphylum, outside of the euryarchaeota; whereas the Methanonatronarchaeia have been placed near the base of the Methanotecta (composed of the class II methanogens, the Halobacteriales, and Archaeoglobales). These opposing hypotheses have far-reaching implications on the concepts of convergent evolution (distantly related groups evolve similar strategies for survival), genome reduction, and gene transfer. In this work, we attempt to resolve these conflicts with phylogenetic and phylogenomic data. We provide a robust taxonomic sampling of Archaeal genomes that spans the Asgardarchaea, TACK Group, euryarchaeota, and the DPANN superphylum. In addition, we assembled draft genomes from seven new representatives of the Nanohaloarchaea from distinct geographic locations. Phylogenies derived from these data imply that the highly conserved ATP synthase catalytic/noncatalytic subunits of Nanohaloarchaea share a sisterhood relationship with the Haloarchaea. We also employ a novel gene family distance clustering strategy which shows this sisterhood relationship is not likely the result of a recent gene transfer. In addition, we present and evaluate data that argue for and against the monophyly of the DPANN superphylum, in particular, the inclusion of the Nanohaloarchaea in DPANN.

Dissecting incongruence between concatenation- and quartet-based approaches in phylogenomic data

Topological conflict or incongruence is widespread in phylogenomic data. Concatenation- and coalescent-based approaches often result in incongruent topologies, but the causes of this conflict can be difficult to characterize. We examined incongruence stemming from conflict between likelihood-based signal (quantified by the difference in gene-wise log likelihood score or ΔGLS) and quartet-based topological signal (quantified by the difference in gene-wise quartet score or ΔGQS) for every gene in three phylogenomic studies in animals, fungi, and plants, which were chosen because their concatenation-based IQ-TREE (T1) and quartet-based ASTRAL (T2) phylogenies are known to produce eight conflicting internal branches (bipartitions). By comparing the types of phylogenetic signal for all genes in these three data matrices, we found that 30% - 36% of genes in each data matrix are inconsistent, that is, each of these genes has higher log likelihood score for T1 versus T2 (i.e., ΔGLS >0) whereas its T1 topology has lower quartet score than its T2 topology (i.e., ΔGQS <0) or vice versa. Comparison of inconsistent and consistent genes using a variety of metrics (e.g., evolutionary rate, gene tree topology, distribution of branch lengths, hidden paralogy, and gene tree discordance) showed that inconsistent genes are more likely to recover neither T1 nor T2 and have higher levels of gene tree discordance than consistent genes. Simulation analyses demonstrate that removal of inconsistent genes from datasets with low levels of incomplete lineage sorting (ILS) and low and medium levels of gene tree estimation error (GTEE) reduced incongruence and increased accuracy. In contrast, removal of inconsistent genes from datasets with medium and high ILS levels and high GTEE levels eliminated or extensively reduced incongruence, but the resulting congruent species phylogenies were not always topologically identical to the true species trees.

Reconstructing the Phylogeny of Corynebacteriales while Accounting for Horizontal Gene Transfer

Horizontal gene transfer is a common mechanism in Bacteria that has contributed to the genomic content of existing organisms. Traditional methods for estimating bacterial phylogeny, however, assume only vertical inheritance in the evolution of homologous genes, which may result in errors in the estimated phylogenies. We present a new method for estimating bacterial phylogeny that accounts for the presence of genes acquired by horizontal gene transfer between genomes. The method identifies and corrects putative transferred genes in gene families, before applying a gene tree-based summary method to estimate bacterial species trees. The method was applied to estimate the phylogeny of the order Corynebacteriales, which is the largest clade in the phylum Actinobacteria. We report a collection of 14 phylogenetic trees on 360 Corynebacteriales genomes. All estimated trees display each genus as a monophyletic clade. The trees also display several relationships proposed by past studies, as well as new relevant relationships between and within the main genera of Corynebacteriales: Corynebacterium, Mycobacterium, Nocardia, Rhodococcus, and Gordonia. An implementation of the method in Python is available on GitHub at https://github.com/UdeS-CoBIUS/EXECT (last accessed April 2, 2020).

Multilocus sequence analysis revealed a high genotypic diversity of Aeromonas hydrophila infecting fish in Uganda

A multilocus sequence analysis (MLSA) was carried out to delineate Aeromonas hydrophila from fish in Uganda. Five housekeeping genes including recA, gyrB, metG, gltA and pps; and the 16S rRNA gene were amplified and sequenced from a total of nine A. hydrophila isolates. The obtained sequences were edited, and consensus sequences generated for each gene locus. The housekeeping gene sequences were concatenated and phylogenetic analysis performed in MEGA version 7.0.2. Pairwise distances ranged from 0.000 to 0.118, highest within the gltA gene locus and lowest within the 16S rRNA gene. The average evolutionary diversity within isolates from the same source ranged between 0.002 and 0.037, and it was 0.033 between the different sources. Similar tree topologies were obtained from the different gene loci with recA, metG and gyrB being more consistent in discriminating isolates according to sources while the 16S rRNA gene had the lowest resolution. The concatenated tree had the highest discriminatory power. This study revealed that A. hydrophila strains infecting fish in Uganda are of diverse genotypes suggesting different sources of infection in a given outbreak. Efforts to minimize spread of the bacteria across sources should be emphasized to control infections of mixed genotypes.

Reconstructing evolutionary trees in parallel for massive sequences

BACKGROUND

Building the evolutionary trees for massive unaligned DNA sequences is challenging and crucial. However, reconstructing evolutionary tree for ultra-large sequences is hard. Massive multiple sequence alignment is also challenging and time/space consuming. Hadoop and Spark are developed recently, which bring spring light for the classical computational biology problems. In this paper, we tried to solve the multiple sequence alignment and evolutionary reconstruction in parallel.

RESULTS

HPTree, which is developed in this paper, can deal with big DNA sequence files quickly. It works well on the >1GB files, and gets better performance than other evolutionary reconstruction tools. Users could use HPTree for reonstructing evolutioanry trees on the computer clusters or cloud platform (eg. Amazon Cloud). HPTree could help on population evolution research and metagenomics analysis.

CONCLUSIONS

In this paper, we employ the Hadoop and Spark platform and design an evolutionary tree reconstruction software tool for unaligned massive DNA sequences. Clustering and multiple sequence alignment are done in parallel. Neighbour-joining model was employed for the evolutionary tree building. We opened our software together with source codes via http://lab.malab.cn/soft/HPtree/ .

Phylogenomic Reconstruction of the Oomycete Phylogeny Derived from 37 Genomes

The oomycetes are a class of eukaryotes and include ecologically significant animal and plant pathogens. Single-gene and multigene phylogenetic studies of individual oomycete genera and of members of the larger classes have resulted in conflicting conclusions concerning interspecies relationships among these species, particularly for the Phytophthora genus. The onset of next-generation sequencing techniques now means that a wealth of oomycete genomic data is available. For the first time, we have used genome-scale phylogenetic methods to resolve oomycete phylogenetic relationships. We used supertree methods to generate single-gene and multigene species phylogenies. Overall, our supertree analyses utilized phylogenetic data from 8,355 oomycete gene families. We have also complemented our analyses with superalignment phylogenies derived from 131 single-copy ubiquitous gene families. Our results show that a genome-scale approach to oomycete phylogeny resolves oomycete classes and clades. Our analysis represents an important first step in large-scale phylogenomic analysis of the oomycetes.

The oomycetes are a class of microscopic, filamentous eukaryotes within the Stramenopiles-Alveolata-Rhizaria (SAR) supergroup which includes ecologically significant animal and plant pathogens, most infamously the causative agent of potato blight Phytophthora infestans. Single-gene and concatenated phylogenetic studies both of individual oomycete genera and of members of the larger class have resulted in conflicting conclusions concerning species phylogenies within the oomycetes, particularly for the large Phytophthora genus. Genome-scale phylogenetic studies have successfully resolved many eukaryotic relationships by using supertree methods, which combine large numbers of potentially disparate trees to determine evolutionary relationships that cannot be inferred from individual phylogenies alone. With a sufficient amount of genomic data now available, we have undertaken the first whole-genome phylogenetic analysis of the oomycetes using data from 37 oomycete species and 6 SAR species. In our analysis, we used established supertree methods to generate phylogenies from 8,355 homologous oomycete and SAR gene families and have complemented those analyses with both phylogenomic network and concatenated supermatrix analyses. Our results show that a genome-scale approach to oomycete phylogeny resolves oomycete classes and individual clades within the problematic Phytophthora genus. Support for the resolution of the inferred relationships between individual Phytophthora clades varies depending on the methodology used. Our analysis represents an important first step in large-scale phylogenomic analysis of the oomycetes.

IMPORTANCE The oomycetes are a class of eukaryotes and include ecologically significant animal and plant pathogens. Single-gene and multigene phylogenetic studies of individual oomycete genera and of members of the larger classes have resulted in conflicting conclusions concerning interspecies relationships among these species, particularly for the Phytophthora genus. The onset of next-generation sequencing techniques now means that a wealth of oomycete genomic data is available. For the first time, we have used genome-scale phylogenetic methods to resolve oomycete phylogenetic relationships. We used supertree methods to generate single-gene and multigene species phylogenies. Overall, our supertree analyses utilized phylogenetic data from 8,355 oomycete gene families. We have also complemented our analyses with superalignment phylogenies derived from 131 single-copy ubiquitous gene families. Our results show that a genome-scale approach to oomycete phylogeny resolves oomycete classes and clades. Our analysis represents an important first step in large-scale phylogenomic analysis of the oomycetes.

Genomic composition and dynamics among Methanomicrobiales predict adaptation to contrasting environments

Members of the order Methanomicrobiales are abundant, and sometimes dominant, hydrogenotrophic (H₂-CO₂ utilizing) methanoarchaea in a broad range of anoxic habitats. Despite their key roles in greenhouse gas emissions and waste conversion to methane, little is known about the physiological and genomic bases for their widespread distribution and abundance. In this study, we compared the genomes of nine diverse Methanomicrobiales strains, examined their pangenomes, reconstructed gene flow and identified genes putatively mediating their success across different habitats. Most strains slowly increased gene content whereas one, Methanocorpusculum labreanum, evidenced genome downsizing. Peat-dwelling Methanomicrobiales showed adaptations centered on improved transport of scarce inorganic nutrients and likely use H⁺ rather than Na⁺ transmembrane chemiosmotic gradients during energy conservation. In contrast, other Methanomicrobiales show the potential to concurrently use Na⁺ and H⁺ chemiosmotic gradients. Analyses also revealed that the Methanomicrobiales lack a canonical electron bifurcation system (MvhABGD) known to produce low potential electrons in other orders of hydrogenotrophic methanogens. Additional putative differences in anabolic metabolism suggest that the dynamics of interspecies electron transfer from Methanomicrobiales syntrophic partners can also differ considerably. Altogether, these findings suggest profound differences in electron trafficking in the Methanomicrobiales compared with other hydrogenotrophs, and warrant further functional evaluations.

Metabolic network motifs can provide novel insights into evolution: The evolutionary origin of Eukaryotic organelles as a case study

Phylogenetic trees are typically constructed using genetic and genomic data, and provide robust evolutionary relationships of species from the genomic point of view. We present an application of network motif mining and analysis of metabolic pathways that when used in combination with phylogenetic trees can provide a more complete picture of evolution. By using distributions of three-node motifs as a proxy for metabolic similarity, we analyze the ancestral origin of Eukaryotic organelles from the metabolic point of view to illustrate the application of our motif mining and analysis network approach. Our analysis suggests that the hypothesis of an early proto-Eukaryote could be valid. It also suggests that a δ- or ϵ-Proteobacteria may have been the endosymbiotic partner that gave rise to modern mitochondria. Our evolutionary analysis needs to be extended by building metabolic network reconstructions of species from the phylum Crenarchaeota, which is considered to be a possible archaeal ancestor of the eukaryotic cell. In this paper, we also propose a methodology for constructing phylogenetic trees that incorporates metabolic network signatures to identify regions of genomically-estimated phylogenies that may be spurious. We find that results generated from our approach are consistent with a parallel phylogenetic analysis using the method of feature frequency profiles.

Bioinformatic genome comparisons for taxonomic and phylogenetic assignments using Aeromonas as a test case

Prokaryotic taxonomy is the underpinning of microbiology, as it provides a framework for the proper identification and naming of organisms. The “gold standard” of bacterial species delineation is the overall genome similarity determined by DNA-DNA hybridization (DDH), a technically rigorous yet sometimes variable method that may produce inconsistent results. Improvements in next-generation sequencing have resulted in an upsurge of bacterial genome sequences and bioinformatic tools that compare genomic data, such as average nucleotide identity (ANI), correlation of tetranucleotide frequencies, and the genome-to-genome distance calculator, or in silico DDH (isDDH). Here, we evaluate ANI and isDDH in combination with phylogenetic studies using Aeromonas, a taxonomically challenging genus with many described species and several strains that were reassigned to different species as a test case. We generated improved, high-quality draft genome sequences for 33 Aeromonas strains and combined them with 23 publicly available genomes. ANI and isDDH distances were determined and compared to phylogenies from multilocus sequence analysis of housekeeping genes, ribosomal proteins, and expanded core genes. The expanded core phylogenetic analysis suggested relationships between distant Aeromonas clades that were inconsistent with studies using fewer genes. ANI values of ≥96% and isDDH values of ≥70% consistently grouped genomes originating from strains of the same species together. Our study confirmed known misidentifications, validated the recent revisions in the nomenclature, and revealed that a number of genomes deposited in GenBank are misnamed. In addition, two strains were identified that may represent novel Aeromonas species.

Improvements in DNA sequencing technologies have resulted in the ability to generate large numbers of high-quality draft genomes and led to a dramatic increase in the number of publically available genomes. This has allowed researchers to characterize microorganisms using genome data. Advantages of genome sequence-based classification include data and computing programs that can be readily shared, facilitating the standardization of taxonomic methodology and resolving conflicting identifications by providing greater uniformity in an overall analysis. Using Aeromonas as a test case, we compared and validated different approaches. Based on our analyses, we recommend cutoff values for distance measures for identifying species. Accurate species classification is critical not only to obviate the perpetuation of errors in public databases but also to ensure the validity of inferences made on the relationships among species within a genus and proper identification in clinical and veterinary diagnostic laboratories.

Extensive genomic variation within clonal bacterial groups resulted from homologous recombination

Due to divergence, genetic variation is generally believed to be high among distantly related strains, low among closely related ones and little or none within the same classified clonal groups. Several recent genome-wide studies, however, revealed that significant genetic variation resides in a considerable number of genes among strains with identical MLST (Multilocus sequence typing) types and much of the variation was introduced by homologous recombination. Recognizing and understanding genomic variation within clonal bacterial groups could shed new light on the evolutionary path of infectious agents and the emergence of particularly pathogenic or virulent variants. This commentary presents our recent contributions to this line of work.

Supertrees Based on the Subtree Prune-and-Regraft Distance

Supertree methods reconcile a set of phylogenetic trees into a single structure that is often interpreted as a branching history of species. A key challenge is combining conflicting evolutionary histories that are due to artifacts of phylogenetic reconstruction and phenomena such as lateral gene transfer (LGT). Many supertree approaches use optimality criteria that do not reflect underlying processes, have known biases, and may be unduly influenced by LGT. We present the first method to construct supertrees by using the subtree prune-and-regraft (SPR) distance as an optimality criterion. Although calculating the rooted SPR distance between a pair of trees is NP-hard, our new maximum agreement forest-based methods can reconcile trees with hundreds of taxa and>50 transfers in fractions of a second, which enables repeated calculations during the course of an iterative search. Our approach can accommodate trees in which uncertain relationships have been collapsed to multifurcating nodes. Using a series of benchmark datasets simulated under plausible rates of LGT, we show that SPR supertrees are more similar to correct species histories than supertrees based on parsimony or Robinson-Foulds distance criteria. We successfully constructed an SPR supertree from a phylogenomic dataset of 40,631 gene trees that covered 244 genomes representing several major bacterial phyla. Our SPR-based approach also allowed direct inference of highways of gene transfer between bacterial classes and genera. A Small number of these highways connect genera in different phyla and can highlight specific genes implicated in long-distance LGT. [Lateral gene transfer; matrix representation with parsimony; phylogenomics; prokaryotic phylogeny; Robinson-Foulds; subtree prune-and-regraft; supertrees.].

tRNA signatures reveal a polyphyletic origin of SAR11 strains among alphaproteobacteria

Molecular phylogenetics and phylogenomics are subject to noise from horizontal gene transfer (HGT) and bias from convergence in macromolecular compositions. Extensive variation in size, structure and base composition of alphaproteobacterial genomes has complicated their phylogenomics, sparking controversy over the origins and closest relatives of the SAR11 strains. SAR11 are highly abundant, cosmopolitan aquatic Alphaproteobacteria with streamlined, A+T-biased genomes. A dominant view holds that SAR11 are monophyletic and related to both Rickettsiales and the ancestor of mitochondria. Other studies dispute this, finding evidence of a polyphyletic origin of SAR11 with most strains distantly related to Rickettsiales. Although careful evolutionary modeling can reduce bias and noise in phylogenomic inference, entirely different approaches may be useful to extract robust phylogenetic signals from genomes. Here we develop simple phyloclassifiers from bioinformatically derived tRNA Class-Informative Features (CIFs), features predicted to target tRNAs for specific interactions within the tRNA interaction network. Our tRNA CIF-based model robustly and accurately classifies alphaproteobacterial genomes into one of seven undisputed monophyletic orders or families, despite great variability in tRNA gene complement sizes and base compositions. Our model robustly rejects monophyly of SAR11, classifying all but one strain as Rhizobiales with strong statistical support. Yet remarkably, conventional phylogenetic analysis of tRNAs classifies all SAR11 strains identically as Rickettsiales. We attribute this discrepancy to convergence of SAR11 and Rickettsiales tRNA base compositions. Thus, tRNA CIFs appear more robust to compositional convergence than tRNA sequences generally. Our results suggest that tRNA-CIF-based phyloclassification is robust to HGT of components of the tRNA interaction network, such as aminoacyl-tRNA synthetases. We explain why tRNAs are especially advantageous for prediction of traits governing macromolecular interactions from genomic data, and why such traits may be advantageous in the search for robust signals to address difficult problems in classification and phylogeny.

If gene products work well in the networks of foreign cells, their genes may transfer horizontally between unrelated genomes. What factors dictate the ability to integrate into foreign networks? Different RNAs and proteins must interact specifically in order to function well as a system. For example, tRNA functions are determined by the interactions they have with other macromolecules. We have developed ways to predict, from genomic data alone, how tRNAs distinguish themselves to their specific interaction partners. Here, as proof of concept, we built a robust computational model from these bioinformatic predictions in seven lineages of Alphaproteobacteria. We validated our model by classifying hundreds of diverse alphaproteobacterial taxa and tested it on eight strains of SAR11, a phylogenetically controversial group that is highly abundant in the world's oceans. We found that different strains of SAR11 are more distantly related, both to each other and to mitochondria, than widely believed. We explain conflicting results about SAR11 as an artifact of bias created by the variability in base contents of alphaproteobacterial genomes. While this bias affects tRNAs too, our classifier appears unexpectedly robust to it. More broadly, our results suggest that traits governing macromolecular interactions may be more faithfully vertically inherited than the macromolecules themselves.

Evolution of multicellularity coincided with increased diversification of cyanobacteria and the Great Oxidation Event

Cyanobacteria are among the most diverse prokaryotic phyla, with morphotypes ranging from unicellular to multicellular filamentous forms, including those able to terminally (i.e., irreversibly) differentiate in form and function. It has been suggested that cyanobacteria raised oxygen levels in the atmosphere around 2.45-2.32 billion y ago during the Great Oxidation Event (GOE), hence dramatically changing life on the planet. However, little is known about the temporal evolution of cyanobacterial lineages, and possible interplay between the origin of multicellularity, diversification of cyanobacteria, and the rise of atmospheric oxygen. We estimated divergence times of extant cyanobacterial lineages under Bayesian relaxed clocks for a dataset of 16S rRNA sequences representing the entire known diversity of this phylum. We tested whether the evolution of multicellularity overlaps with the GOE, and whether multicellularity is associated with significant shifts in diversification rates in cyanobacteria. Our results indicate an origin of cyanobacteria before the rise of atmospheric oxygen. The evolution of multicellular forms coincides with the onset of the GOE and an increase in diversification rates. These results suggest that multicellularity could have played a key role in triggering cyanobacterial evolution around the GOE.

Homologous recombination drives both sequence diversity and gene content variation in Neisseria meningitidis

The study of genetic and phenotypic variation is fundamental for understanding the dynamics of bacterial genome evolution and untangling the evolution and epidemiology of bacterial pathogens. Neisseria meningitidis (Nm) is among the most intriguing bacterial pathogens in genomic studies due to its dynamic population structure and complex forms of pathogenicity. Extensive genomic variation within identical clonal complexes (CCs) in Nm has been recently reported and suggested to be the result of homologous recombination, but the extent to which recombination contributes to genomic variation within identical CCs has remained unclear. In this study, we sequenced two Nm strains of identical serogroup (C) and multi-locus sequence type (ST60), and conducted a systematic analysis with an additional 34 Nm genomes. Our results revealed that all gene content variation between the two ST60 genomes was introduced by homologous recombination at the conserved flanking genes, and 94.25% or more of sequence divergence was caused by homologous recombination. Recombination was found in genes associated with virulence factors, antigenic outer membrane proteins, and vaccine targets, suggesting an important role of homologous recombination in rapidly altering the pathogenicity and antigenicity of Nm. Recombination was also evident in genes of the restriction and modification systems, which may undermine barriers to DNA exchange. In conclusion, homologous recombination can drive both gene content variation and sequence divergence in Nm. These findings shed new light on the understanding of the rapid pathoadaptive evolution of Nm and other recombinogenic bacterial pathogens.