Modeling protein evolution with several amino acid replacement matrices depending on site rates

QMix: An Efficient Program to Automatically Estimate Multi-Matrix Mixture Models for Amino Acid Substitution Process

The single-matrix amino acid (AA) substitution models are widely used in phylogenetic analyses; however, they are unable to properly model the heterogeneity of AA substitution rates among sites. The multi-matrix mixture models can handle the site rate heterogeneity and outperform the single-matrix models. Estimating multi-matrix mixture models is a complex process and no computer program is available for this task. In this study, we implemented a computer program of the so-called QMix based on the algorithm of LG4X and LG4M with several enhancements to automatically estimate multi-matrix mixture models from large datasets. QMix employs QMaker algorithm instead of XRATE algorithm to accurately and rapidly estimate the parameters of models. It is able to estimate mixture models with different number of matrices and supports multi-threading computing to efficiently estimate models from thousands of genes. We re-estimate mixture models LG4X and LG4M from 1471 HSSP alignments. The re-estimated models (HP4X and HP4M) are slightly better than LG4X and LG4M in building maximum likelihood trees from HSSP and TreeBASE datasets. QMix program required about 10 hours on a computer with 18 cores to estimate a mixture model with four matrices from 200 HSSP alignments. It is easy to use and freely available for researchers.

MAST: Phylogenetic Inference with Mixtures Across Sites and Trees

Hundreds or thousands of loci are now routinely used in modern phylogenomic studies. Concatenation approaches to tree inference assume that there is a single topology for the entire dataset, but different loci may have different evolutionary histories due to incomplete lineage sorting (ILS), introgression, and/or horizontal gene transfer; even single loci may not be treelike due to recombination. To overcome this shortcoming, we introduce an implementation of a multi-tree mixture model that we call mixtures across sites and trees (MAST). This model extends a prior implementation by Boussau et al. (2009) by allowing users to estimate the weight of each of a set of pre-specified bifurcating trees in a single alignment. The MAST model allows each tree to have its own weight, topology, branch lengths, substitution model, nucleotide or amino acid frequencies, and model of rate heterogeneity across sites. We implemented the MAST model in a maximum-likelihood framework in the popular phylogenetic software, IQ-TREE. Simulations show that we can accurately recover the true model parameters, including branch lengths and tree weights for a given set of tree topologies, under a wide range of biologically realistic scenarios. We also show that we can use standard statistical inference approaches to reject a single-tree model when data are simulated under multiple trees (and vice versa). We applied the MAST model to multiple primate datasets and found that it can recover the signal of ILS in the Great Apes, as well as the asymmetry in minor trees caused by introgression among several macaque species. When applied to a dataset of 4 Platyrrhine species for which standard concatenated maximum likelihood (ML) and gene tree approaches disagree, we observe that MAST gives the highest weight (i.e., the largest proportion of sites) to the tree also supported by gene tree approaches. These results suggest that the MAST model is able to analyze a concatenated alignment using ML while avoiding some of the biases that come with assuming there is only a single tree. We discuss how the MAST model can be extended in the future.

The effectiveness of selection in a species affects the direction of amino acid frequency evolution

Nearly neutral theory predicts that species with higher effective population size (N e ) are better able to purge slightly deleterious mutations. We compare evolution in high-N e vs. low-N e vertebrates to reveal which amino acid frequencies are subject to subtle selective preferences. We take three complementary approaches, two measuring flux and one measuring outcomes. First, we fit non-stationary substitution models of amino acid flux using maximum likelihood, comparing the high-N e clade of rodents and lagomorphs to its low-N e sister clade of primates and colugos. Second, we compare evolutionary outcomes across a wider range of vertebrates, via correlations between amino acid frequencies and N e . Third, we dissect the details of flux in human, chimpanzee, mouse, and rat, as scored by parsimony - this also enables comparison to a historical paper. All three methods agree on which amino acids are preferred under more effective selection. Preferred amino acids tend to be smaller, less costly to synthesize, and to promote intrinsic structural disorder. Parsimony-induced bias in the historical study produces an apparent reduction in structural disorder, perhaps driven by slightly deleterious substitutions. Within highly exchangeable pairs of amino acids, arginine is strongly preferred over lysine, and valine over isoleucine, consistent with more effective selection preferring a marginally larger free energy of folding. These two preferences match differences between thermophiles and mesophilic relatives. These results reveal the biophysical consequences of mutation-selection-drift balance, and demonstrate the utility of nearly neutral theory for understanding protein evolution.

Is Over-parameterization a Problem for Profile Mixture Models?

Biochemical constraints on the admissible amino acids at specific sites in proteins lead to heterogeneity of the amino acid substitution process over sites in alignments. It is well known that phylogenetic models of protein sequence evolution that do not account for site heterogeneity are prone to long-branch attraction (LBA) artifacts. Profile mixture models were developed to model heterogeneity of preferred amino acids at sites via a finite distribution of site classes each with a distinct set of equilibrium amino acid frequencies. However, it is unknown whether the large number of parameters in such models associated with the many amino acid frequency vectors can adversely affect tree topology estimates because of over-parameterization. Here, we demonstrate theoretically that for long sequences, over-parameterization does not create problems for estimation with profile mixture models. Under mild conditions, tree, amino acid frequencies, and other model parameters converge to true values as sequence length increases, even when there are large numbers of components in the frequency profile distributions. Because large sample theory does not necessarily imply good behavior for shorter alignments we explore the performance of these models with short alignments simulated with tree topologies that are prone to LBA artifacts. We find that over-parameterization is not a problem for complex profile mixture models even when there are many amino acid frequency vectors. In fact, simple models with few site classes behave poorly. Interestingly, we also found that misspecification of the amino acid frequency vectors does not lead to increased LBA artifacts as long as the estimated cumulative distribution function of the amino acid frequencies at sites adequately approximates the true one. In contrast, misspecification of the amino acid exchangeability rates can severely negatively affect parameter estimation. Finally, we explore the effects of including in the profile mixture model an additional "F-class" representing the overall frequencies of amino acids in the data set. Surprisingly, the F-class does not help parameter estimation significantly and can decrease the probability of correct tree estimation, depending on the scenario, even though it tends to improve likelihood scores.

Accurate Detection of Convergent Mutations in Large Protein Alignments With ConDor

Evolutionary convergences are observed at all levels, from phenotype to DNA and protein sequences, and changes at these different levels tend to be correlated. Notably, convergent mutations can lead to convergent changes in phenotype, such as changes in metabolism, drug resistance, and other adaptations to changing environments. We propose a two-component approach to detect mutations subject to convergent evolution in protein alignments. The "Emergence" component selects mutations that emerge more often than expected, while the "Correlation" component selects mutations that correlate with the convergent phenotype under study. With regard to Emergence, a phylogeny deduced from the alignment is provided by the user and is used to simulate the evolution of each alignment position. These simulations allow us to estimate the expected number of mutations in a neutral model, which is compared to the observed number of mutations in the data studied. In Correlation, a comparative phylogenetic approach, is used to measure whether the presence of each of the observed mutations is correlated with the convergent phenotype. Each component can be used on its own, for example Emergence when no phenotype is available. Our method is implemented in a standalone workflow and a webserver, called ConDor. We evaluate the properties of ConDor using simulated data, and we apply it to three real datasets: sedge PEPC proteins, HIV reverse transcriptase, and fish rhodopsin. The results show that the two components of ConDor complement each other, with an overall accuracy that compares favorably to other available tools, especially on large datasets.

Phylogenomics resolves the higher-level phylogeny of herbivorous eriophyoid mites (Acariformes: Eriophyoidea)

BACKGROUND

Eriophyoid mites (Eriophyoidea) are among the largest groups in the Acariformes; they are strictly phytophagous. The higher-level phylogeny of eriophyoid mites, however, remains unresolved due to the limited number of available morphological characters-some of them are homoplastic. Nevertheless, the eriophyoid mites sequenced to date showed highly variable mitochondrial (mt) gene orders, which could potentially be useful for resolving the higher-level phylogenetic relationships.

RESULTS

Here, we sequenced and compared the complete mt genomes of 153 eriophyoid mite species, which showed 54 patterns of rearranged mt gene orders relative to that of the hypothetical ancestor of arthropods. The shared derived mt gene clusters support the monophyly of eriophyoid mites (Eriophyoidea) as a whole and the monophylies of six clades within Eriophyoidea. These monophyletic groups and their relationships were largely supported in the phylogenetic trees inferred from mt genome sequences as well. Our molecular dating results showed that Eriophyoidea originated in the Triassic and diversified in the Cretaceous, coinciding with the diversification of angiosperms.

CONCLUSIONS

This study reveals multiple molecular synapomorphies (i.e. shared derived mt gene clusters) at different levels (i.e. family, subfamily or tribe level) from the complete mt genomes of 153 eriophyoid mite species. We demonstrated the use of derived mt gene clusters in unveiling the higher-level phylogeny of eriophyoid mites, and underlines the origin of these mites and their co-diversification with angiosperms.

Phylogenomics of endemic Australian Ulopinae (Hemiptera: Cicadomorpha: Cicadellidae)

Ulopinae is a distinctive subfamily of leafhoppers that is widely distributed across the Afrotropical, Palearctic, Indomalayan and Australasian regions. The ulopine fauna of Australia is entirely endemic and includes two tribes of striking appearance, the Ulopini and Cephalelini. Knowledge of these groups is fragmentary and in many instances, no information is available beyond original descriptions. We assess the monophyly, phylogenetic placement and species-level diversity of the Ulopini genus Austrolopa . Phylogenetic analyses based on sequence data from target nuclear loci (18S , 28S , H2A and H3 ) and mitochondrial genomes (15 genes) for 23 membracoid taxa yielded congruent topologies. Our results provide strong evidence for the monophyly of Ulopinae and a clade consisting of Ulopini + Cephalelini. However, a non-monophyletic Cephalelini arises from within a polyphyletic Ulopini. Austrolopa was strongly recovered as monophyletic in all analyses, a result also supported by morphological features. The genus currently includes six species, three of which are described based on morphological and molecular data: Austrolopa botanica , sp. nov. , Austrolopa rotunda , sp. nov. and Austrolopa sublima , sp. nov. A lectotype designation is provided for Austrolopa kingensis Evans, 1937, sp. reval. Our findings illustrate that the Australian Ulopinae is far more diverse than currently circumscribed and several species of Austrolopa are yet to be recognised. ZooBank: urn:lsid:zoobank.org:pub:1480285B-8F61-4659-A929-2B1EF3168868.

Meteora sporadica, a protist with incredible cell architecture, is related to Hemimastigophora

"Kingdom-level" branches are being added to the tree of eukaryotes at a rate approaching one per year, with no signs of slowing down.1,2,3,4 Some are completely new discoveries, whereas others are morphologically unusual protists that were previously described but lacked molecular data. For example, Hemimastigophora are predatory protists with two rows of flagella that were known since the 19th century but proved to represent a new deep-branching eukaryote lineage when phylogenomic analyses were conducted.2Meteora sporadica5 is a protist with a unique morphology; cells glide over substrates along a long axis of anterior and posterior projections while a pair of lateral "arms" swing back and forth, a motility system without any obvious parallels. Originally, Meteora was described by light microscopy only, from a short-term enrichment of deep-sea sediment. A small subunit ribosomal RNA (SSU rRNA) sequence was reported recently, but the phylogenetic placement of Meteora remained unresolved.6 Here, we investigated two cultivated Meteora sporadica isolates in detail. Transmission electron microscopy showed that both the anterior-posterior projections and the arms are supported by microtubules originating from a cluster of subnuclear microtubule organizing centers (MTOCs). Neither have a flagellar axoneme-like structure. Sequencing the mitochondrial genome showed this to be among the most gene-rich known, outside jakobids. Remarkably, phylogenomic analyses of 254 nuclear protein-coding genes robustly support a close relationship with Hemimastigophora. Our study suggests that Meteora and Hemimastigophora together represent a morphologically diverse "supergroup" and thus are important for resolving the tree of eukaryote life and early eukaryote evolution.

Ant backbone phylogeny resolved by modelling compositional heterogeneity among sites in genomic data

Ants are the most ubiquitous and ecologically dominant arthropods on Earth, and understanding their phylogeny is crucial for deciphering their character evolution, species diversification, and biogeography. Although recent genomic data have shown promise in clarifying intrafamilial relationships across the tree of ants, inconsistencies between molecular datasets have also emerged. Here I re-examine the most comprehensive published Sanger-sequencing and genome-scale datasets of ants using model comparison methods that model among-site compositional heterogeneity to understand the sources of conflict in phylogenetic studies. My results under the best-fitting model, selected on the basis of Bayesian cross-validation and posterior predictive model checking, identify contentious nodes in ant phylogeny whose resolution is modelling-dependent. I show that the Bayesian infinite mixture CAT model outperforms empirical finite mixture models (C20, C40 and C60) and that, under the best-fitting CAT-GTR + G4 model, the enigmatic Martialis heureka is sister to all ants except Leptanillinae, rejecting the more popular hypothesis supported under worse-fitting models, that place it as sister to Leptanillinae. These analyses resolve a lasting controversy in ant phylogeny and highlight the significance of model comparison and adequate modelling of among-site compositional heterogeneity in reconstructing the deep phylogeny of insects.

A Guide to Phylogenomic Inference

Phylogenomics aims at reconstructing the evolutionary histories of organisms taking into account whole genomes or large fractions of genomes. Phylogenomics has significant applications in fields such as evolutionary biology, systematics, comparative genomics, and conservation genetics, providing valuable insights into the origins and relationships of species and contributing to our understanding of biological diversity and evolution. This chapter surveys phylogenetic concepts and methods aimed at both gene tree and species tree reconstruction while also addressing common pitfalls, providing references to relevant computer programs. A practical phylogenomic analysis example including bacterial genomes is presented at the end of the chapter.

Phylogenomics reveals an almost perfect polytomy among the almost ungulates (Paenungulata)

Phylogenetic studies have resolved most relationships among Eutherian Orders. However, the branching order of elephants (Proboscidea), hyraxes (Hyracoidea), and sea cows (Sirenia) (i.e., the Paenungulata) has remained uncertain since at least 1758, when Linnaeus grouped elephants and manatees into a single Order (Bruta) to the exclusion of hyraxes. Subsequent morphological, molecular, and large-scale phylogenomic datasets have reached conflicting conclusions on the branching order within Paenungulates. We use a phylogenomic dataset of alignments from 13,388 protein-coding genes across 261 Eutherian mammals to infer phylogenetic relationships within Paenungulates. We find that gene trees almost equally support the three alternative resolutions of Paenungulate relationships and that despite strong support for a Proboscidea+Hyracoidea split in the multispecies coalescent (MSC) tree, there is significant evidence for gene tree uncertainty, incomplete lineage sorting, and introgression among Proboscidea, Hyracoidea, and Sirenia. Indeed, only 8-10% of genes have statistically significant phylogenetic signal to reject the hypothesis of a Paenungulate polytomy. These data indicate little support for any resolution for the branching order Proboscidea, Hyracoidea, and Sirenia within Paenungulata and suggest that Paenungulata may be as close to a real, or at least unresolvable, polytomy as possible.

A sequence-based evolutionary distance method for Phylogenetic analysis of highly divergent proteins

Because of the limited effectiveness of prevailing phylogenetic methods when applied to highly divergent protein sequences, the phylogenetic analysis problem remains challenging. Here, we propose a sequence-based evolutionary distance algorithm termed sequence distance (SD), which innovatively incorporates site-to-site correlation within protein sequences into the distance estimation. In protein superfamilies, SD can effectively distinguish evolutionary relationships both within and between protein families, producing phylogenetic trees that closely align with those based on structural information, even with sequence identity less than 20%. SD is highly correlated with the similarity of the protein structure, and can calculate evolutionary distances for thousands of protein pairs within seconds using a single CPU, which is significantly faster than most protein structure prediction methods that demand high computational resources and long run times. The development of SD will significantly advance phylogenetics, providing researchers with a more accurate and reliable tool for exploring evolutionary relationships.

DNA Sequences Are as Useful as Protein Sequences for Inferring Deep Phylogenies

Inference of deep phylogenies has almost exclusively used protein rather than DNA sequences based on the perception that protein sequences are less prone to homoplasy and saturation or to issues of compositional heterogeneity than DNA sequences. Here, we analyze a model of codon evolution under an idealized genetic code and demonstrate that those perceptions may be misconceptions. We conduct a simulation study to assess the utility of protein versus DNA sequences for inferring deep phylogenies, with protein-coding data generated under models of heterogeneous substitution processes across sites in the sequence and among lineages on the tree, and then analyzed using nucleotide, amino acid, and codon models. Analysis of DNA sequences under nucleotide-substitution models (possibly with the third codon positions excluded) recovered the correct tree at least as often as analysis of the corresponding protein sequences under modern amino acid models. We also applied the different data-analysis strategies to an empirical dataset to infer the metazoan phylogeny. Our results from both simulated and real data suggest that DNA sequences may be as useful as proteins for inferring deep phylogenies and should not be excluded from such analyses. Analysis of DNA data under nucleotide models has a major computational advantage over protein-data analysis, potentially making it feasible to use advanced models that account for among-site and among-lineage heterogeneity in the nucleotide-substitution process in inference of deep phylogenies.

Evolutionary conservation of Trichomonas-mycoplasma symbiosis across the host species barrier

Introduction

The protozoan parasite Trichomonas vaginalis is the most common cellular sexually transmitted disease in humans, and the closely related species Trichomonas gallinae is an avian parasite of ecological and economic importance. Phylogenetic evidence suggests T. vaginalis arose during bird to human transmission of a T. gallinae-like ancestor. Trichomonas vaginalis shares a strong clinical association with the independent sexually transmitted pathogen Metamycoplasma (formerly Mycoplasma) hominis, and the uncultured bacterium "Candidatus Malacoplasma (formerly Mycoplasma) girerdii," with the latter association being an order of magnitude stronger. Both bacterial species have been shown to profoundly influence T. vaginalis growth, energy production and virulence-associated mechanisms.

Methods

Evidence for a novel Malacoplasma sp. was discovered by in vivo Illumina metatranscriptomics sequencing of the T. gallinae-infected pigeon mouth. We leveraged published 16S rDNA profiling data from digestive tract of 12 healthy and 24 T. gallinae-infected pigeons to investigate association between the novel Malacoplasma sp. and T. gallinae. We utilised Illumina metagenomics sequencing targeted to pigeon oral and crop samples infected with the novel Malacoplasma sp. to generate its full-length genome sequence. Sequence similarity network analysis was used to compare annotated proteins from the novel Malacoplasma sp. with a range of other related species.

Results

Here we present evidence for a novel Malacoplasma species, related to "Ca. M. girerdii," that is strongly associated with T. gallinae in the upper digestive tract of domestic pigeons. Analysis of the genome sequence revealed gene features apparently specific to a Trichomonas-symbiotic Malacoplasma lineage.

Discussion

These data support a model of long-term association between Trichomonas and Malacoplasma spp. that has been conserved across diversification of the Trichomonas lineage and the host species barrier from birds to human.

Phylogenomics of weevils revisited: data curation and modelling compositional heterogeneity

Weevils represent one of the most prolific radiations of beetles and the most diverse group of herbivores on land. The phylogeny of weevils (Curculionoidea) has received extensive attention, and a largely satisfactory framework for their interfamilial relationships has been established. However, a recent phylogenomic study of Curculionoidea based on anchored hybrid enrichment (AHE) data yielded an abnormal placement for the family Belidae (strongly supported as sister to Nemonychidae + Anthribidae). Here we reanalyse the genome-scale AHE data for Curculionoidea using various models of molecular evolution and data filtering methods to mitigate anticipated systematic errors and reduce compositional heterogeneity. When analysed with the infinite mixture model CAT-GTR or using appropriately filtered datasets, Belidae are always recovered as sister to the clade (Attelabidae, (Caridae, (Brentidae, Curculionidae))), which is congruent with studies based on morphology and other sources of molecular data. Although the relationships of the 'higher Curculionidae' remain challenging to resolve, we provide a consistent and robust backbone phylogeny of weevils. Our extensive analyses emphasize the significance of data curation and modelling across-site compositional heterogeneity in phylogenomic studies.

Data-specific substitution models improve protein-based phylogenetics

Calculating amino-acid substitution models that are specific for individual protein data sets is often difficult due to the computational burden of estimating large numbers of rate parameters. In this study, we tested the computational efficiency and accuracy of five methods used to estimate substitution models, namely Codeml, FastMG, IQ-TREE, P4 (maximum likelihood), and P4 (Bayesian inference). Data-specific substitution models were estimated from simulated alignments (with different lengths) that were generated from a known simulation model and simulation tree. Each of the resulting data-specific substitution models was used to calculate the maximum likelihood score of the simulation tree and simulated data that was used to calculate the model, and compared with the maximum likelihood scores of the known simulation model and simulation tree on the same simulated data. Additionally, the commonly-used empirical models, cpREV and WAG, were assessed similarly. Data-specific models performed better than the empirical models, which under-fitted the simulated alignments, had the highest difference to the simulation model maximum-likelihood score, clustered further from the simulation model in principal component analysis ordination, and inferred less accurate trees. Data-specific models and the simulation model shared statistically indistinguishable maximum-likelihood scores, indicating that the five methods were reasonably accurate at estimating substitution models by this measure. Nevertheless, tree statistics showed differences between optimal maximum likelihood trees. Unlike other model estimating methods, trees inferred using data-specific models generated with IQ-TREE and P4 (maximum likelihood) were not significantly different from the trees derived from the simulation model in each analysis, indicating that these two methods alone were the most accurate at estimating data-specific models. To show the benefits of using data-specific protein models several published data sets were reanalysed using IQ-TREE-estimated models. These newly estimated models were a better fit to the data than the empirical models that were used by the original authors, often inferred longer trees, and resulted in different tree topologies in more than half of the re-analysed data sets. The results of this study show that software availability and high computation burden are not limitations to generating better-fitting data-specific amino-acid substitution models for phylogenetic analyses.

An excavate root for the eukaryote tree of life

Much of the higher-order phylogeny of eukaryotes is well resolved, but the root remains elusive. We assembled a dataset of 183 eukaryotic proteins of archaeal ancestry to test this root. The resulting phylogeny identifies four lineages of eukaryotes currently classified as "Excavata" branching separately at the base of the tree. Thus, Parabasalia appear as the first major branch of eukaryotes followed sequentially by Fornicata, Preaxostyla, and Discoba. All four excavate branch points receive full statistical support from analyses with commonly used evolutionary models, a protein structure partition model that we introduce here, and various controls for deep phylogeny artifacts. The absence of aerobic mitochondria in Parabasalia, Fornicata, and Preaxostyla suggests that modern eukaryotes arose under anoxic conditions, probably much earlier than expected, and without the benefit of mitochondrial respiration.

Precipitation is the main axis of tropical plant phylogenetic turnover across space and time

Early natural historians-Comte de Buffon, von Humboldt, and De Candolle-established environment and geography as two principal axes determining the distribution of groups of organisms, laying the foundations for biogeography over the subsequent 200 years, yet the relative importance of these two axes remains unresolved. Leveraging phylogenomic and global species distribution data for Mimosoid legumes, a pantropical plant clade of c. 3500 species, we show that the water availability gradient from deserts to rain forests dictates turnover of lineages within continents across the tropics. We demonstrate that 95% of speciation occurs within a precipitation niche, showing profound phylogenetic niche conservatism, and that lineage turnover boundaries coincide with isohyets of precipitation. We reveal similar patterns on different continents, implying that evolution and dispersal follow universal processes.

Genomic diversity and biosynthetic capabilities of sponge-associated chlamydiae

Sponge microbiomes contribute to host health, nutrition, and defense through the production of secondary metabolites. Chlamydiae, a phylum of obligate intracellular bacteria ranging from animal pathogens to endosymbionts of microbial eukaryotes, are frequently found associated with sponges. However, sponge-associated chlamydial diversity has not yet been investigated at the genomic level and host interactions thus far remain unexplored. Here, we sequenced the microbiomes of three sponge species and found high, though variable, Chlamydiae relative abundances of up to 18.7% of bacteria. Using genome-resolved metagenomics 18 high-quality sponge-associated chlamydial genomes were reconstructed, covering four chlamydial families. Among these, Candidatus Sororchlamydiaceae shares a common ancestor with Chlamydiaceae animal pathogens, suggesting long-term co-evolution with animals. Based on gene content, sponge-associated chlamydiae resemble members from the same family more than sponge-associated chlamydiae of other families, and have greater metabolic versatility than known chlamydial animal pathogens. Sponge-associated chlamydiae are also enriched in genes for degrading diverse compounds found in sponges. Unexpectedly, we identified widespread genetic potential for secondary metabolite biosynthesis across Chlamydiae, which may represent an unexplored source of novel natural products. This finding suggests that Chlamydiae members may partake in defensive symbioses and that secondary metabolites play a wider role in mediating intracellular interactions. Furthermore, sponge-associated chlamydiae relatives were found in other marine invertebrates, pointing towards wider impacts of the Chlamydiae phylum on marine ecosystems.

Discovery of two novel Torque Teno viruses in Callithrix penicillata provides insights on Anelloviridae diversification dynamics

The development of high-throughput sequencing (HTS) technologies and metagenomics protocols deeply impacted the discovery of viral diversity. Moreover, the characterization of novel viruses in the Neotropical primates (NP) is central for the comprehension of viral evolution dynamics in those hosts, due to their evolutionary proximity to Old World primates, including humans. In the present work, novel anelloviruses were detected and characterized through HTS protocols in the NP Callithrix penicillata, the common black-tufted marmoset. De novo assembly of generated sequences was carried out, and a total of 15 contigs were identified with complete Anelloviridae ORF1 gene, two of them including a flanking GC-rich region, confirming the presence of two whole novel genomes of ~3 kb. The identified viruses were monophyletic within the Epsilontorquevirus genus, a lineage harboring previously reported anelloviruses infecting hosts from the Cebidae family. The genetic divergence found in the new viruses characterized two novel species, named Epsilontorquevirus callithrichensis I and II. The phylogenetic pattern inferred for the Epsilontorquevirus genus was consistent with the topology of their host species tree, echoing a virus-host diversification model observed in other viral groups. This study expands the host span of Anelloviridae and provides insights into their diversification dynamics, highlighting the importance of sampling animal viral genomes to obtain a clearer depiction of their long-term evolutionary processes.

Neogastropod (Mollusca, Gastropoda) phylogeny: A step forward with mitogenomes

The Neogastropoda (Mollusca, Gastropoda) encompass more than 15,000 described species of marine predators, including several model organisms in toxinology, embryology and physiology. However, their phylogenetic relationships remain mostly unresolved and their classification unstable. We took advantage of the many mitogenomes published in GenBank to produce a new molecular phylogeny of the neogastropods. We completed the taxon sampling by using an in-house bioinformatic pipeline to retrieve mitochondrial genes from 13 transcriptomes, corresponding to five families not represented in GenBank, for a final dataset of 113 taxa. Because mitogenomic data are prone to reconstruction artefacts, eight different evolutionary models were applied to reconstruct phylogenetic trees with IQTREE, RAxML and MrBayes. If the over-parametrization of some models produced trees with aberrant internal long branches, the global topology of the trees remained stable over models and softwares, and several relationships were revealed or found supported here for the first time. However, even if our dataset encompasses 60% of the valid families of neogastropods, some key taxa are missing and should be added in the future before proposing a revision of the classification of the neogastropods. Our study also demonstrates that even complex models struggle to satisfactorily handle the evolutionary history of mitogenomes, still leading to long-branch attractions in phylogenetic trees. Other approaches, such as reduced-genome strategies, must be envisaged to fully resolve the neogastropod phylogeny.

Microbial communities of Auka hydrothermal sediments shed light on vent biogeography and the evolutionary history of thermophily

Hydrothermal vents have been key to our understanding of the limits of life, and the metabolic and phylogenetic diversity of thermophilic organisms. Here we used environmental metagenomics combined with analysis of physicochemical data and 16S rRNA gene amplicons to characterize the sediment-hosted microorganisms at the recently discovered Auka vents in the Gulf of California. We recovered 325 metagenome assembled genomes (MAGs) representing 54 phyla, over 30% of those currently known, showing the microbial community in Auka hydrothermal sediments is highly diverse. 16S rRNA gene amplicon screening of 224 sediment samples across the vent field indicates that the MAGs retrieved from a single site are representative of the microbial community in the vent field sediments. Metabolic reconstruction of a vent-specific, deeply branching clade within the Desulfobacterota suggests these organisms metabolize sulfur using novel octaheme cytochrome-c proteins related to hydroxylamine oxidoreductase. Community-wide comparison between Auka MAGs and MAGs from Guaymas Basin revealed a remarkable 20% species-level overlap, suggestive of long-distance species transfer over 400 km and subsequent sediment colonization. Optimal growth temperature prediction on the Auka MAGs, and thousands of reference genomes, shows that thermophily is a trait that has evolved frequently. Taken together, our Auka vent field results offer new perspectives on our understanding of hydrothermal vent microbiology.

Leishmania guyanensis M4147 as a new LRV1-bearing model parasite: Phosphatidate phosphatase 2-like protein controls cell cycle progression and intracellular lipid content

Leishmaniasis is a parasitic vector-borne disease caused by the protistan flagellates of the genus Leishmania. Leishmania (Viannia) guyanensis is one of the most common causative agents of the American tegumentary leishmaniasis. It has previously been shown that L. guyanensis strains that carry the endosymbiotic Leishmania RNA virus 1 (LRV1) cause more severe form of the disease in a mouse model than those that do not. The presence of the virus was implicated into the parasite's replication and spreading. In this respect, studying the molecular mechanisms of cellular control of viral infection is of great medical importance. Here, we report ~30.5 Mb high-quality genome assembly of the LRV1-positive L. guyanensis M4147. This strain was turned into a model by establishing the CRISPR-Cas9 system and ablating the gene encoding phosphatidate phosphatase 2-like (PAP2L) protein. The orthologue of this gene is conspicuously absent from the genome of an unusual member of the family Trypanosomatidae, Vickermania ingenoplastis, a species with mostly bi-flagellated cells. Our analysis of the PAP2L-null L. guyanensis showed an increase in the number of cells strikingly resembling the bi-flagellated V. ingenoplastis, likely as a result of the disruption of the cell cycle, significant accumulation of phosphatidic acid, and increased virulence compared to the wild type cells.

PHACT: Phylogeny-aware computing of tolerance for missense mutations

Evolutionary conservation is a fundamental resource for predicting the substitutability of amino acids and loss of function in proteins. The use of multiple sequence alignment alone-without considering the evolutionary relationships among sequences-results in the redundant counting of evolutionarily related alteration events as if they were independent. Here we propose a new method, PHACT that predicts the pathogenicity of missense mutations directly from the phylogenetic tree of proteins. PHACT travels through the nodes of the phylogenetic tree and evaluates the deleteriousness of a substitution based on the probability differences of ancestral amino acids between neighboring nodes in the tree. Moreover, PHACT assigns weights to each node in the tree based on their distance to the query organism. For each potential amino acid substitution, the algorithm generates a score that is used to calculate the effect of substitution on protein function. To analyze the predictive performance of PHACT, we performed various experiments over the subsets of two datasets that include 3023 proteins and 61662 variants in total. The experiments demonstrated that our method outperformed the widely used pathogenicity prediction tools (i.e., SIFT and PolyPhen-2) and achieved better predictive performance than did other conventional statistical approaches presented in dbNSFP. The PHACT source code is available at https://github.com/CompGenomeLab/PHACT.

Gene sharing among plasmids and chromosomes reveals barriers for antibiotic resistance gene transfer

The emergence of antibiotic resistant bacteria is a major threat to modern medicine. Rapid adaptation to antibiotics is often mediated by the acquisition of plasmids carrying antibiotic resistance (ABR) genes. Nonetheless, the determinants of plasmid-mediated ABR gene transfer remain debated. Here, we show that the propensity of ABR gene transfer via plasmids is higher for accessory chromosomal ABR genes in comparison with core chromosomal ABR genes, regardless of the resistance mechanism. Analysing the pattern of ABR gene occurrence in the genomes of 2635 Enterobacteriaceae isolates, we find that 33% of the 416 ABR genes are shared between chromosomes and plasmids. Phylogenetic reconstruction of ABR genes occurring on both plasmids and chromosomes supports their evolution by lateral gene transfer. Furthermore, accessory ABR genes (encoded in less than 10% of the chromosomes) occur more abundantly in plasmids in comparison with core ABR genes (encoded in greater than or equal to 90% of the chromosomes). The pattern of ABR gene occurrence in plasmids and chromosomes is similar to that in the total Escherichia genome. Our results thus indicate that the previously recognized barriers for gene acquisition by lateral gene transfer apply also to ABR genes. We propose that the functional complexity of the underlying ABR mechanism is an important determinant of ABR gene transferability. This article is part of the theme issue 'The secret lives of microbial mobile genetic elements'.

Expanding the Menu: Are Polyphagy and Gene Family Expansions Linked across Lepidoptera?

Evolutionary expansions and contractions of gene families are often correlated with key innovations and/or ecological characteristics. In butterflies and moths (Lepidoptera), expansions of gene families involved in detoxification of plant specialized metabolites are hypothesized to facilitate a polyphagous feeding style. However, analyses supporting this hypothesis are mostly based on a limited number of lepidopteran species. We applied a phylogenomics approach, using 37 lepidopteran genomes, to analyze if gene family evolution (gene gain and loss) is associated with the evolution of polyphagy. Specifically, we compared gene counts and evolutionary gene gain and loss rates of gene families involved in adaptations with plant feeding. We correlated gene evolution to host plant family range (phylogenetic diversity) and specialized metabolite content of plant families (functional metabolite diversity). We found a higher rate for gene loss than gene gain in Lepidoptera, a potential consequence of genomic rearrangements and deletions after (potentially small-scale) duplication events. Gene family expansions and contractions varied across lepidopteran families, and were associated to host plant use and specialization levels. Within the family Noctuidae, a higher expansion rate for gene families involved in detoxification can be related to the large number of polyphagous species. However, gene family expansions are observed in both polyphagous and monophagous lepidopteran species and thus seem to be species-specific in the taxa sampled. Nevertheless, a significant positive correlation of gene counts of the carboxyl- and choline esterase and glutathione-S-transferase detoxification gene families with the level of polyphagy was identified across Lepidoptera.

Testing Phylogenetic Stability with Variable Taxon Sampling

Over the past three decades, computational capabilities have grown at such a rapid rate that they have given rise to many computationally heavy science fields such as phylogenomics. As increasingly more genomes are sequenced in the three domains of life, larger and more species-complete phylogenetic tree reconstructions are leading to a better understanding of the tree of life and the evolutionary histories in deep times. However, these large datasets pose unique challenges from a modeling and computational perspective: accurately describing the evolutionary process of thousands of species is still beyond the capability of current models, while the computational burden limits our ability to test multiple hypotheses. Thus, it is common practice to reduce the size of a dataset by selecting species to represent a clade (taxon sampling). Unfortunately, this process is subjective, and comparisons of large tree of life studies show that choice and number of species used in a dataset can alter the topology obtained. Thus, taxon sampling is, in itself, a process that needs to be fully investigated to determine its effect on phylogenetic stability. Here, we present the theory and practical application of an automated pipeline that can be easily implemented to explore the effect of taxon sampling on phylogenetic reconstructions. The application of this approach was recently discussed in a study of Terrabacteria and shows its power in investigating the accuracy of deep nodes of a phylogeny.

Evolutionary history and divergence times of Odonata (dragonflies and damselflies) revealed through transcriptomics

Dragonflies and damselflies are among the earliest flying insects with extant representatives. However, unraveling details of their long evolutionary history, such as egg laying (oviposition) strategies, is impeded by unresolved phylogenetic relationships, particularly in damselflies. Here we present a transcriptome-based phylogenetic reconstruction of Odonata, analyzing 2,980 protein-coding genes in 105 species representing nearly all the order's families. All damselfly and most dragonfly families are recovered as monophyletic. Our data suggest a sister relationship between dragonfly families of Gomphidae and Petaluridae. According to our divergence time estimates, both crown-Zygoptera and -Anisoptera arose during the late Triassic. Egg-laying with a reduced ovipositor apparently evolved in dragonflies during the late Jurassic/early Cretaceous. Lastly, we also test the impact of fossil choice and placement, particularly, of the extinct fossil species, †Triassolestodes asiaticus, and †Proterogomphus renateae on divergence time estimates. We find placement of †Proterogomphus renateae to be much more impactful than †Triassolestodes asiaticus.

Phylogeny of gracillariid leaf-mining moths: evolution of larval behaviour inferred from phylogenomic and Sanger data

Gracillariidae is the most taxonomically diverse cosmopolitan leaf-mining moth family, consisting of nearly 2000 named species in 105 described genera, classified into eight extant subfamilies. The majority of gracillariid species are internal plant feeders as larvae, creating mines and galls in plant tissue. Despite their diversity and ecological adaptations, their phylogenetic relationships, especially among subfamilies, remain uncertain. Genomic data (83 taxa, 589 loci) were integrated with Sanger data (130 taxa, 22 loci), to reconstruct a phylogeny of Gracillariidae. Based on analyses of both datasets combined and analyzed separately, monophyly of Gracillariidae and all its subfamilies, monophyly of the clade "LAMPO" (subfamilies: Lithocolletinae, Acrocercopinae, Marmarinae, Phyllocnistinae, and Oecophyllembiinae) and relationships of its subclade "AMO" (subfamilies: Acrocercopinae, Marmarinae, and Oecophyllembiinae) were strongly supported. A sister-group relationship of Ornixolinae to the remainder of the family, and a monophyletic leaf roller lineage (Callicercops Vári + Parornichinae) + Gracillariinae, as sister to the "LAMPO" clade were supported by the most likely tree. Dating analyses indicate a mid-Cretaceous (105.3 Ma) origin of the family, followed by a rapid diversification into the nine subfamilies predating the Cretaceous-Palaeogene extinction. We hypothesize that advanced larval behaviours, such as making keeled or tentiform blotch mines, rolling leaves and galling, allowed gracillariids to better avoid larval parasitoids allowing them to further diversify. Finally, we stabilize the classification by formally re-establishing the subfamily ranks of Marmarinae stat.rev., Oecophyllembiinae stat.rev. and Parornichinae stat.rev., and erect a new subfamily, Callicercopinae Li, Ohshima and Kawahara to accommodate the enigmatic genus Callicercops.

Lower statistical support with larger datasets: insights from the Ochrophyta radiation

It is commonly assumed that increasing the number of characters has the potential to resolve evolutionary radiations. Here, we studied photosynthetic stramenopiles (Ochrophyta) using alignments of heterogeneous origin mitochondrion, plastid, and nucleus. Surprisingly while statistical support for the relationships between the six major Ochrophyta lineages increases when comparing the mitochondrion (6,762 sites) and plastid (21,692 sites) trees, it decreases in the nuclear (209,105 sites) tree. Statistical support is not simply related to the data set size but also to the quantity of phylogenetic signal available at each position and our ability to extract it. Here, we show that this ability for current phylogenetic methods is limited, because conflicting results were obtained when varying taxon sampling. Even though the use of a better fitting model improved signal extraction and reduced the observed conflicts, the plastid data set provided higher statistical support for the ochrophyte radiation than the larger nucleus data set. We propose that the higher support observed in the plastid tree is due to an acceleration of the evolutionary rate in one short deep internal branch, implying that more phylogenetic signal per position is available to resolve the Ochrophyta radiation in the plastid than in the nuclear data set. Our work therefore suggests that, in order to resolve radiations, beyond the obvious use of data sets with more positions, we need to continue developing models of sequence evolution that better extract the phylogenetic signal and design methods to search for genes/characters that contain more signal specifically for short internal branches.

Novelties in Fuscosporellaceae (Fuscosporellales): Two New Parafuscosporella from Thailand Revealed by Morphology and Phylogenetic Analyses

Asexual morphs of freshwater fungi have been mostly reported from tropical and subtropical regions. From our ongoing investigation of the diversity and taxonomy of freshwater microfungi in Thailand, a country with rich natural resources and diverse ecosystems, Parafuscosporella ellipsoconidiogena sp. nov. and P. obovata sp. nov., collected from decaying submerged twigs at Phalad Waterfall in a conserved forest in Chiang Mai Zoo, Chiang Mai Province, northern Thailand, are proposed. DNA phylogenies based on a combination of ITS and LSU datasets support the placement of these species in Parafuscosporella (Fuscosporellaceae, Fuscosporellales, Sordariomycetes), and these two novel species differ from known species in terms of morphology. Detailed descriptions, illustrations and a key to Parafuscosporella species are provided, as well as comparisons with other accepted Parafuscosporella species.

Genome and transcriptome analysis of the beet armyworm Spodoptera exigua reveals targets for pest control

The genus Spodoptera (Lepidoptera: Noctuidae) includes some of the most infamous insect pests of cultivated plants including Spodoptera frugiperda, Spodoptera litura, and Spodoptera exigua. To effectively develop targeted pest control strategies for diverse Spodoptera species, genomic resources are highly desired. To this aim, we provide the genome assembly and developmental transcriptome comprising all major life stages of S. exigua, the beet armyworm. Spodoptera exigua is a polyphagous herbivore that can feed on > 130 host plants, including several economically important crops. The 419 Mb beet armyworm genome was sequenced from a female S. exigua pupa. Using a hybrid genome sequencing approach (Nanopore long-read data and Illumina short read), a high-quality genome assembly was achieved (N50 = 1.1 Mb). An official gene set (18,477 transcripts) was generated by automatic annotation and by using transcriptomic RNA-seq datasets of 18 S. exigua samples as supporting evidence. In-depth analyses of developmental stage-specific expression combined with gene tree analyses of identified homologous genes across Lepidoptera genomes revealed four potential genes of interest (three of them Spodoptera-specific) upregulated during first- and third-instar larval stages for targeted pest-outbreak management. The beet armyworm genome sequence and developmental transcriptome covering all major developmental stages provide critical insights into the biology of this devastating polyphagous insect pest species worldwide. In addition, comparative genomic analyses across Lepidoptera significantly advance our knowledge to further control other invasive Spodoptera species and reveals potential lineage-specific target genes for pest control strategies.

Phylogenomics reveals accelerated late Cretaceous diversification of bee flies (Diptera: Bombyliidae)

Bombyliidae is a very species-rich and widespread family of parasitoid flies with more than 250 genera classified into 17 extant subfamilies. However, little is known about their evolutionary history or how their present-day diversity was shaped. Transcriptomes of 15 species and anchored hybrid enrichment (AHE) sequence captures of 86 species, representing 94 bee fly species and 14 subfamilies, were used to reconstruct the phylogeny of Bombyliidae. We integrated data from transcriptomes across each of the main lineages in our AHE tree to build a data set with more genes (550 loci versus 216 loci) and higher support levels. Our overall results show strong congruence with the current classification of the family, with 11 out of 14 included subfamilies recovered as monophyletic. Heterotropinae and Mythicomyiinae are successive sister groups to the remainder of the family. We examined the evolution of key morphological characters through our phylogenetic hypotheses and show that neither the "sand chamber subfamilies" nor the "Tomophthalmae" are monophyletic in our phylogenomic analyses. Based on our results, we reinstate two tribes at the subfamily level (Phthiriinae stat. rev. and Ecliminae stat. rev.) and we include the genus Sericosoma Macquart (previously incertae sedis) in the subfamily Oniromyiinae, bringing the total number of bee fly subfamilies to 19. Our dating analyses indicate a Jurassic origin of the family (165-194 Ma), with the sand chamber evolving early in bee fly evolution, in the late Jurassic or mid-Cretaceous (100-165 Ma). We hypothesize that the angiosperm radiation and the hothouse climate established during the late Cretaceous accelerated the diversification of bee flies, by providing an expanded range of resources for the parasitoid larvae and nectarivorous adults.

Disentangling the aging gene expression network of termite queens

Background

Most insects are relatively short-lived, with a maximum lifespan of a few weeks, like the aging model organism, the fruit-fly Drosophila melanogaster. By contrast, the queens of many social insects (termites, ants and some bees) can live from a few years to decades. This makes social insects promising models in aging research providing insights into how a long reproductive life can be achieved. Yet, aging studies on social insect reproductives are hampered by a lack of quantitative data on age-dependent survival and time series analyses that cover the whole lifespan of such long-lived individuals. We studied aging in queens of the drywood termite Cryptotermes secundus by determining survival probabilities over a period of 15 years and performed transcriptome analyses for queens of known age that covered their whole lifespan.

Results

The maximum lifespan of C. secundus queens was 13 years, with a median maximum longevity of 11.0 years. Time course and co-expression network analyses of gene expression patterns over time indicated a non-gradual aging pattern. It was characterized by networks of genes that became differentially expressed only late in life, namely after ten years, which associates well with the median maximum lifespan for queens. These old-age gene networks reflect processes of physiological upheaval. We detected strong signs of stress, decline, defense and repair at the transcriptional level of epigenetic control as well as at the post-transcriptional level with changes in transposable element activity and the proteostasis network. The latter depicts an upregulation of protein degradation, together with protein synthesis and protein folding, processes which are often down-regulated in old animals. The simultaneous upregulation of protein synthesis and autophagy is indicative of a stress-response mediated by the transcription factor cnc, a homolog of human nrf genes.

Conclusions

Our results show non-linear senescence with a rather sudden physiological upheaval at old-age. Most importantly, they point to a re-wiring in the proteostasis network and stress as part of the aging process of social insect queens, shortly before queens die.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07649-4.

Scalable Empirical Mixture Models That Account for Across-Site Compositional Heterogeneity

Biochemical demands constrain the range of amino acids acceptable at specific sites resulting in across-site compositional heterogeneity of the amino acid replacement process. Phylogenetic models that disregard this heterogeneity are prone to systematic errors, which can lead to severe long-branch attraction artifacts. State-of-the-art models accounting for across-site compositional heterogeneity include the CAT model, which is computationally expensive, and empirical distribution mixture models estimated via maximum likelihood (C10–C60 models). Here, we present a new, scalable method EDCluster for finding empirical distribution mixture models involving a simple cluster analysis. The cluster analysis utilizes specific coordinate transformations which allow the detection of specialized amino acid distributions either from curated databases or from the alignment at hand. We apply EDCluster to the HOGENOM and HSSP databases in order to provide universal distribution mixture (UDM) models comprising up to 4,096 components. Detailed analyses of the UDM models demonstrate the removal of various long-branch attraction artifacts and improved performance compared with the C10–C60 models. Ready-to-use implementations of the UDM models are provided for three established software packages (IQ-TREE, Phylobayes, and RevBayes).

Biosynthesis of Long-Chain Polyunsaturated Fatty Acids in Marine Gammarids: Molecular Cloning and Functional Characterisation of Three Fatty Acyl Elongases

Long-chain (C20-24) polyunsaturated fatty acids (LC-PUFAs) are essential nutrients that are mostly produced in marine ecosystems. Previous studies suggested that gammarids have some capacity to endogenously produce LC-PUFAs. This study aimed to investigate the repertoire and functions of elongation of very long-chain fatty acid (Elovl) proteins in gammarids. Our results show that gammarids have, at least, three distinct elovl genes with putative roles in LC-PUFA biosynthesis. Phylogenetics allowed us to classify two elongases as Elovl4 and Elovl6, as they were bona fide orthologues of vertebrate Elovl4 and Elovl6. Moreover, a third elongase was named as "Elovl1/7-like" since it grouped closely to the Elovl1 and Elovl7 found in vertebrates. Molecular analysis of the deduced protein sequences indicated that the gammarid Elovl4 and Elovl1/7-like were indeed polyunsaturated fatty acid (PUFA) elongases, whereas Elovl6 had molecular features typically found in non-PUFA elongases. This was partly confirmed in the functional assays performed on the marine gammarid Echinogammarus marinus Elovl, which showed that both Elovl4 and Elovl1/7-like elongated PUFA substrates ranging from C18 to C22. E. marinus Elovl6 was only able to elongate C18 PUFA substrates, suggesting that this enzyme does not play major roles in the LC-PUFA biosynthesis of gammarids.

Relative Model Fit Does Not Predict Topological Accuracy in Single-Gene Protein Phylogenetics

It is regarded as best practice in phylogenetic reconstruction to perform relative model selection to determine an appropriate evolutionary model for the data. This procedure ranks a set of candidate models according to their goodness of fit to the data, commonly using an information theoretic criterion. Users then specify the best-ranking model for inference. Although it is often assumed that better-fitting models translate to increase accuracy, recent studies have shown that the specific model employed may not substantially affect inferences. We examine whether there is a systematic relationship between relative model fit and topological inference accuracy in protein phylogenetics, using simulations and real sequences. Simulations employed site-heterogeneous mechanistic codon models that are distinct from protein-level phylogenetic inference models, allowing us to investigate how protein models performs when they are misspecified to the data, as will be the case for any real sequence analysis. We broadly find that phylogenies inferred across models with vastly different fits to the data produce highly consistent topologies. We additionally find that all models infer similar proportions of false-positive splits, raising the possibility that all available models of protein evolution are similarly misspecified. Moreover, we find that the parameter-rich GTR (general time reversible) model, whose amino acid exchangeabilities are free parameters, performs similarly to models with fixed exchangeabilities, although the inference precision associated with GTR models was not examined. We conclude that, although relative model selection may not hinder phylogenetic analysis on protein data, it may not offer specific predictable improvements and is not a reliable proxy for accuracy.

IQ-TREE 2: New Models and Efficient Methods for Phylogenetic Inference in the Genomic Era

IQ-TREE (http://www.iqtree.org, last accessed February 6, 2020) is a user-friendly and widely used software package for phylogenetic inference using maximum likelihood. Since the release of version 1 in 2014, we have continuously expanded IQ-TREE to integrate a plethora of new models of sequence evolution and efficient computational approaches of phylogenetic inference to deal with genomic data. Here, we describe notable features of IQ-TREE version 2 and highlight the key advantages over other software.

Evidence for sponges as sister to all other animals from partitioned phylogenomics with mixture models and recoding

Resolving the relationships between the major lineages in the animal tree of life is necessary to understand the origin and evolution of key animal traits. Sponges, characterized by their simple body plan, were traditionally considered the sister group of all other animal lineages, implying a gradual increase in animal complexity from unicellularity to complex multicellularity. However, the availability of genomic data has sparked tremendous controversy as some phylogenomic studies support comb jellies taking this position, requiring secondary loss or independent origins of complex traits. Here we show that incorporating site-heterogeneous mixture models and recoding into partitioned phylogenomics alleviates systematic errors that hamper commonly-applied phylogenetic models. Testing on real datasets, we show a great improvement in model-fit that attenuates branching artefacts induced by systematic error. We reanalyse key datasets and show that partitioned phylogenomics does not support comb jellies as sister to other animals at either the supermatrix or partition-specific level.

QMaker: Fast and accurate method to estimate empirical models of protein evolution

Amino acid substitution models play a crucial role in phylogenetic analyses. Maximum likelihood (ML) methods have been proposed to estimate amino acid substitution models; however, they are typically complicated and slow. In this article, we propose QMaker, a new ML method to estimate a general time-reversible \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$Q$\end{document} matrix from a large protein data set consisting of multiple sequence alignments. QMaker combines an efficient ML tree search algorithm, a model selection for handling the model heterogeneity among alignments, and the consideration of rate mixture models among sites. We provide QMaker as a user-friendly function in the IQ-TREE software package (http://www.iqtree.org) supporting the use of multiple CPU cores so that biologists can easily estimate amino acid substitution models from their own protein alignments. We used QMaker to estimate new empirical general amino acid substitution models from the current Pfam database as well as five clade-specific models for mammals, birds, insects, yeasts, and plants. Our results show that the new models considerably improve the fit between model and data and in some cases influence the inference of phylogenetic tree topologies.[Amino acid replacement matrices; amino acid substitution models; maximum likelihood estimation; phylogenetic inferences.]

Beyond Drosophila: resolving the rapid radiation of schizophoran flies with phylotranscriptomics

BACKGROUND

The most species-rich radiation of animal life in the 66 million years following the Cretaceous extinction event is that of schizophoran flies: a third of fly diversity including Drosophila fruit fly model organisms, house flies, forensic blow flies, agricultural pest flies, and many other well and poorly known true flies. Rapid diversification has hindered previous attempts to elucidate the phylogenetic relationships among major schizophoran clades. A robust phylogenetic hypothesis for the major lineages containing these 55,000 described species would be critical to understand the processes that contributed to the diversity of these flies. We use protein encoding sequence data from transcriptomes, including 3145 genes from 70 species, representing all superfamilies, to improve the resolution of this previously intractable phylogenetic challenge.

RESULTS

Our results support a paraphyletic acalyptrate grade including a monophyletic Calyptratae and the monophyly of half of the acalyptrate superfamilies. The primary branching framework of Schizophora is well supported for the first time, revealing the primarily parasitic Pipunculidae and Sciomyzoidea stat. rev. as successive sister groups to the remaining Schizophora. Ephydroidea, Drosophila's superfamily, is the sister group of Calyptratae. Sphaeroceroidea has modest support as the sister to all non-sciomyzoid Schizophora. We define two novel lineages corroborated by morphological traits, the 'Modified Oviscapt Clade' containing Tephritoidea, Nerioidea, and other families, and the 'Cleft Pedicel Clade' containing Calyptratae, Ephydroidea, and other families. Support values remain low among a challenging subset of lineages, including Diopsidae. The placement of these families remained uncertain in both concatenated maximum likelihood and multispecies coalescent approaches. Rogue taxon removal was effective in increasing support values compared with strategies that maximise gene coverage or minimise missing data.

CONCLUSIONS

Dividing most acalyptrate fly groups into four major lineages is supported consistently across analyses. Understanding the fundamental branching patterns of schizophoran flies provides a foundation for future comparative research on the genetics, ecology, and biocontrol.

Comparative transcriptomics of ice-crawlers demonstrates cold specialization constrains niche evolution in a relict lineage

Key changes in ecological niche space are often critical to understanding how lineages diversify during adaptive radiations. However, the converse, or understanding why some lineages are depauperate and relictual, is more challenging, as many factors may constrain niche evolution. In the case of the insect order Grylloblattodea, highly conserved thermal breadth is assumed to be closely tied to their relictual status, but has not been formerly tested. Here, we investigate whether evolutionary constraints in the physiological tolerance of temperature can help explain relictualism in this lineage. Using a comparative transcriptomics approach, we investigate gene expression following acute heat and cold stress across members of Grylloblattodea and their sister group, Mantophasmatodea. We additionally examine patterns of protein evolution, to identify candidate genes of positive selection. We demonstrate that cold specialization in Grylloblattodea has been accompanied by the loss of the inducible heat shock response under both acute heat and cold stress. Additionally, there is widespread evidence of selection on protein-coding genes consistent with evolutionary constraints due to cold specialization. This includes positive selection on genes involved in trehalose transport, metabolic function, mitochondrial function, oxygen reduction, oxidative stress, and protein synthesis. These patterns of molecular adaptation suggest that Grylloblattodea have undergone evolutionary trade-offs to survive in cold habitats and should be considered highly vulnerable to climate change. Finally, our transcriptomic data provide a robust backbone phylogeny for generic relationships within Grylloblattodea and Mantophasmatodea. Major phylogenetic splits in each group relate to arid conditions driving biogeographical patterns, with support for a sister-group relationship between North American Grylloblatta and Altai-Sayan Grylloblattella, and a range disjunction in Namibia splitting major clades within Mantophasmatodea.

Chemoreceptor Diversity in Apoid Wasps and Its Reduction during the Evolution of the Pollen-Collecting Lifestyle of Bees (Hymenoptera: Apoidea)

Chemoreceptors help insects to interact with their environment, to detect and assess food sources and oviposition sites, and to aid in intra- and interspecific communication. In Hymenoptera, species of eusocial lineages possess large chemoreceptor gene repertoires compared with solitary species, possibly because of their additional need to recognize nest-mates and caste. However, a critical piece of information missing so far has been the size of chemoreceptor gene repertoires of solitary apoid wasps. Apoid wasps are a paraphyletic group of almost exclusively solitary Hymenoptera phylogenetically positioned between ant and bee, both of which include eusocial species. We report the chemosensory-related gene repertoire sizes of three apoid wasps: Ampulex compressa, Cerceris arenaria, and Psenulus fuscipennis. We annotated genes encoding odorant (ORs), gustatory, and ionotropic receptors and chemosensory soluble proteins and odorant-binding proteins in transcriptomes of chemosensory tissues of the above three species and in early draft genomes of two species, A. compressa and C. arenaria. Our analyses revealed that apoid wasps possess larger OR repertoires than any bee lineage, that the last common ancestor of Apoidea possessed a considerably larger OR repertoire (∼160) than previously estimated (73), and that the expansion of OR genes in eusocial bees was less extensive than previously assumed. Intriguingly, the evolution of pollen-collecting behavior in the stem lineage of bees was associated with a notable loss of OR gene diversity. Thus, our results support the view that herbivorous Hymenoptera tend to possess smaller OR repertoires than carnivorous, parasitoid, or kleptoparasitic species.

Four myriapod relatives - but who are sisters? No end to debates on relationships among the four major myriapod subgroups

Background

Phylogenetic relationships among the myriapod subgroups Chilopoda, Diplopoda, Symphyla and Pauropoda are still not robustly resolved. The first phylogenomic study covering all subgroups resolved phylogenetic relationships congruently to morphological evidence but is in conflict with most previously published phylogenetic trees based on diverse molecular data. Outgroup choice and long-branch attraction effects were stated as possible explanations for these incongruencies. In this study, we addressed these issues by extending the myriapod and outgroup taxon sampling using transcriptome data.

Results

We generated new transcriptome data of 42 panarthropod species, including all four myriapod subgroups and additional outgroup taxa. Our taxon sampling was complemented by published transcriptome and genome data resulting in a supermatrix covering 59 species. We compiled two data sets, the first with a full coverage of genes per species (292 single-copy protein-coding genes), the second with a less stringent coverage (988 genes). We inferred phylogenetic relationships among myriapods using different data types, tree inference, and quartet computation approaches. Our results unambiguously support monophyletic Mandibulata and Myriapoda. Our analyses clearly showed that there is strong signal for a single unrooted topology, but a sensitivity of the position of the internal root on the choice of outgroups. However, we observe strong evidence for a clade Pauropoda+Symphyla, as well as for a clade Chilopoda+Diplopoda.

Conclusions

Our best quartet topology is incongruent with current morphological phylogenies which were supported in another phylogenomic study. AU tests and quartet mapping reject the quartet topology congruent to trees inferred with morphological characters. Moreover, quartet mapping shows that confounding signal present in the data set is sufficient to explain the weak signal for the quartet topology derived from morphological characters. Although outgroup choice affects results, our study could narrow possible trees to derivatives of a single quartet topology. For highly disputed relationships, we propose to apply a series of tests (AU and quartet mapping), since results of such tests allow to narrow down possible relationships and to rule out confounding signal.

Timing the origin of eukaryotic cellular complexity with ancient duplications

Eukaryogenesis is one of the most enigmatic evolutionary transitions, during which simple prokaryotic cells gave rise to complex eukaryotic cells. While evolutionary intermediates are lacking, gene duplications provide information on the order of events by which eukaryotes originated. Here we use a phylogenomics approach to reconstruct successive steps during eukaryogenesis. We found that gene duplications roughly doubled the proto-eukaryotic gene repertoire, with families inherited from the Asgard archaea-related host being duplicated most. By relatively timing events using phylogenetic distances we inferred that duplications in cytoskeletal and membrane trafficking families were among the earliest events, whereas most other families expanded predominantly after mitochondrial endosymbiosis. Altogether, we infer that the host that engulfed the proto-mitochondrion had some eukaryote-like complexity, which drastically increased upon mitochondrial acquisition. This scenario bridges the signs of complexity observed in Asgard archaeal genomes to the proposed role of mitochondria in triggering eukaryogenesis.

mPartition: A Model-Based Method for Partitioning Alignments

Maximum likelihood (ML) analysis of nucleotide or amino-acid alignments is widely used to infer evolutionary relationships among species. Computing the likelihood of a phylogenetic tree from such alignments is a complicated task because the evolutionary processes typically vary across sites. A number of studies have shown that partitioning alignments into sub-alignments of sites, where each sub-alignment is analyzed using a different model of evolution (e.g., GTR + I + G), is a sensible strategy. Current partitioning methods group sites into subsets based on the inferred rates of evolution at the sites. However, these do not provide sufficient information to adequately reflect the substitution processes of characters at the sites. Moreover, the site rate-based methods group all invariant sites into one subset, potentially resulting in wrong phylogenetic trees. In this study, we propose a partitioning method, called mPartition, that combines not only the evolutionary rates but also substitution models at sites to partition alignments. Analyses of different partitioning methods on both real and simulated datasets showed that mPartition was better than the other partitioning methods tested. Notably, mPartition overcame the pitfall of grouping all invariant sites into one subset. Using mPartition may lead to increased accuracy of ML-based phylogenetic inference, especially for multiple loci or whole genome datasets.

OBAMA: OBAMA for Bayesian amino-acid model averaging

Background

Bayesian analyses offer many benefits for phylogenetic, and have been popular for analysis of amino acid alignments. It is necessary to specify a substitution and site model for such analyses, and often an ad hoc, or likelihood based method is employed for choosing these models that are typically of no interest to the analysis overall.

Methods

We present a method called OBAMA that averages over substitution models and site models, thus letting the data inform model choices and taking model uncertainty into account. It uses trans-dimensional Markov Chain Monte Carlo (MCMC) proposals to switch between various empirical substitution models for amino acids such as Dayhoff, WAG, and JTT. Furthermore, it switches base frequencies from these substitution models or use base frequencies estimated based on the alignment. Finally, it switches between using gamma rate heterogeneity or not, and between using a proportion of invariable sites or not.

Results

We show that the model performs well in a simulation study. By using appropriate priors, we demonstrate both proportion of invariable sites and the shape parameter for gamma rate heterogeneity can be estimated. The OBAMA method allows taking in account model uncertainty, thus reducing bias in phylogenetic estimates. The method is implemented in the OBAMA package in BEAST 2, which is open source licensed under LGPL and allows joint tree inference under a wide range of models.

Methane, arsenic, selenium and the origins of the DMSO reductase family

Mononuclear molybdoenzymes of the dimethyl sulfoxide reductase (DMSOR) family catalyze a number of reactions essential to the carbon, nitrogen, sulfur, arsenic, and selenium biogeochemical cycles. These enzymes are also ancient, with many lineages likely predating the divergence of the last universal common ancestor into the Bacteria and Archaea domains. We have constructed rooted phylogenies for over 1,550 representatives of the DMSOR family using maximum likelihood methods to investigate the evolution of the arsenic biogeochemical cycle. The phylogenetic analysis provides compelling evidence that formylmethanofuran dehydrogenase B subunits, which catalyze the reduction of CO₂ to formate during hydrogenotrophic methanogenesis, constitutes the most ancient lineage. Our analysis also provides robust support for selenocysteine as the ancestral ligand for the Mo/W atom. Finally, we demonstrate that anaerobic arsenite oxidase and respiratory arsenate reductase catalytic subunits represent a more ancient lineage of DMSORs compared to aerobic arsenite oxidase catalytic subunits, which evolved from the assimilatory nitrate reductase lineage. This provides substantial support for an active arsenic biogeochemical cycle on the anoxic Archean Earth. Our work emphasizes that the use of chalcophilic elements as substrates as well as the Mo/W ligand in DMSORs has indelibly shaped the diversification of these enzymes through deep time.