Statistics and truth in phylogenomics

Testing the utility of alternative metrics of branch support to address the ancient evolutionary radiation of tunas, stromateoids, and allies (Teleostei: Pelagiaria)

The use of high-throughput sequencing technologies to produce genome-scale datasets was expected to settle some long-standing controversies across the Tree of Life, particularly in areas where short branches occur at deep timescales. Instead, these datasets have often yielded many well-supported but conflicting topologies, and highly variable gene-tree distributions. A variety of branch-support metrics beyond the nonparametric bootstrap are now available to assess how robust a phylogenetic hypothesis may be, as well as new methods to quantify gene-tree discordance. We applied multiple branch support metrics to an ancient group of marine fishes (Teleostei: Pelagiaria) whose interfamilial relationships have proven difficult to resolve due to a rapid accumulation of lineages very early in its history. We analyzed hundreds of loci including published UCE data and newly generated exonic data along with their flanking regions to represent all 16 extant families for more than 150 out of 284 valid species in the group. Branch support was lower for interfamilial relationships (except the SH-like aLRT and aBayes methods) regardless of the type of marker used. Several nodes that were highly supported with bootstrap had very low site and gene-tree concordance, revealing underlying conflict. Despite this conflict, we were able to identify four consistent interfamilial clades, each comprised of two or three families. Combining exons with their flanking regions also produced increased branch lengths in the deep branches of the pelagiarian tree. Our results demonstrate the limitations of employing current metrics of branch support and species-tree estimation when assessing the confidence of ancient evolutionary radiations and emphasize the necessity to embrace alternative measurements to explore phylogenetic uncertainty and discordance in phylogenomic datasets.

Indels in SARS-CoV-2 occur at template-switching hotspots

The evolutionary dynamics of SARS-CoV-2 have been carefully monitored since the COVID-19 pandemic began in December 2019. However, analysis has focused primarily on single nucleotide polymorphisms and largely ignored the role of insertions and deletions (indels) as well as recombination in SARS-CoV-2 evolution. Using sequences from the GISAID database, we catalogue over 100 insertions and deletions in the SARS-CoV-2 consensus sequences. We hypothesize that these indels are artifacts of recombination events between SARS-CoV-2 replicates whereby RNA-dependent RNA polymerase (RdRp) re-associates with a homologous template at a different loci ("imperfect homologous recombination"). We provide several independent pieces of evidence that suggest this. (1) The indels from the GISAID consensus sequences are clustered at specific regions of the genome. (2) These regions are also enriched for 5' and 3' breakpoints in the transcription regulatory site (TRS) independent transcriptome, presumably sites of RNA-dependent RNA polymerase (RdRp) template-switching. (3) Within raw reads, these indel hotspots have cases of both high intra-host heterogeneity and intra-host homogeneity, suggesting that these indels are both consequences of de novo recombination events within a host and artifacts of previous recombination. We briefly analyze the indels in the context of RNA secondary structure, noting that indels preferentially occur in "arms" and loop structures of the predicted folded RNA, suggesting that secondary structure may be a mechanism for TRS-independent template-switching in SARS-CoV-2 or other coronaviruses. These insights into the relationship between structural variation and recombination in SARS-CoV-2 can improve our reconstructions of the SARS-CoV-2 evolutionary history as well as our understanding of the process of RdRp template-switching in RNA viruses.

High-quality carnivoran genomes from roadkill samples enable comparative species delineation in aardwolf and bat-eared fox

In a context of ongoing biodiversity erosion, obtaining genomic resources from wildlife is essential for conservation. The thousands of yearly mammalian roadkill provide a useful source material for genomic surveys. To illustrate the potential of this underexploited resource, we used roadkill samples to study the genomic diversity of the bat-eared fox (Otocyon megalotis) and the aardwolf (Proteles cristatus), both having subspecies with similar disjunct distributions in Eastern and Southern Africa. First, we obtained reference genomes with high contiguity and gene completeness by combining Nanopore long reads and Illumina short reads. Then, we showed that the two subspecies of aardwolf might warrant species status (P. cristatus and P. septentrionalis) by comparing their genome-wide genetic differentiation to pairs of well-defined species across Carnivora with a new Genetic Differentiation index (GDI) based on only a few resequenced individuals. Finally, we obtained a genome-scale Carnivora phylogeny including the new aardwolf species.

Analysis of selection in protein-coding sequences accounting for common biases

The evolution of protein-coding genes is usually driven by selective processes, which favor some evolutionary trajectories over others, optimizing the subsequent protein stability and activity. The analysis of selection in this type of genetic data is broadly performed with the metric nonsynonymous/synonymous substitution rate ratio (dN/dS). However, most of the well-established methodologies to estimate this metric make crucial assumptions, such as lack of recombination or invariable codon frequencies along genes, which can bias the estimation. Here, we review the most relevant biases in the dN/dS estimation and provide a detailed guide to estimate this metric using state-of-the-art procedures that account for such biases, along with illustrative practical examples and recommendations. We also discuss the traditional interpretation of the estimated dN/dS emphasizing the importance of considering complementary biological information such as the role of the observed substitutions on the stability and function of proteins. This review is oriented to help evolutionary biologists that aim to accurately estimate selection in protein-coding sequences.

Target-capture phylogenomics provide insights on gene and species tree discordances in Old World treefrogs (Anura: Rhacophoridae)

Genome-scale data have greatly facilitated the resolution of recalcitrant nodes that Sanger-based datasets have been unable to resolve. However, phylogenomic studies continue to use traditional methods such as bootstrapping to estimate branch support; and high bootstrap values are still interpreted as providing strong support for the correct topology. Furthermore, relatively little attention has been given to assessing discordances between gene and species trees, and the underlying processes that produce phylogenetic conflict. We generated novel genomic datasets to characterize and determine the causes of discordance in Old World treefrogs (Family: Rhacophoridae)-a group that is fraught with conflicting and poorly supported topologies among major clades. Additionally, a suite of data filtering strategies and analytical methods were applied to assess their impact on phylogenetic inference. We showed that incomplete lineage sorting was detected at all nodes that exhibited high levels of discordance. Those nodes were also associated with extremely short internal branches. We also clearly demonstrate that bootstrap values do not reflect uncertainty or confidence for the correct topology and, hence, should not be used as a measure of branch support in phylogenomic datasets. Overall, we showed that phylogenetic discordances in Old World treefrogs resulted from incomplete lineage sorting and that species tree inference can be improved using a multi-faceted, total-evidence approach, which uses the most amount of data and considers results from different analytical methods and datasets.

Comprehensive phylogeny of Myrmecocystus honey ants highlights cryptic diversity and infers evolution during aridification of the American Southwest

The New World ant genus Myrmecocystus Wesmael, 1838 (Formicidae: Formicinae: Lasiini) is endemic to arid and semi-arid habitats of the western United States and Mexico. Several intriguing life history traits have been described for the genus, the best-known of which are replete workers, that store liquified food in their largely expanded crops and are colloquially referred to as "honeypots". Despite their interesting biology and ecological importance for arid ecosystems, the evolutionary history of Myrmecocystus ants is largely unknown and the current taxonomy presents an unsatisfactory systematic framework. We use ultraconserved elements to infer the evolutionary history of Myrmecocystus ants and provide a comprehensive, dated phylogenetic framework that clarifies the molecular systematics within the genus with high statistical support, reveals cryptic diversity, and reconstructs ancestral foraging activity. Using maximum likelihood, Bayesian and species tree approaches on a data set of 134 ingroup specimens (including samples from natural history collections and type material), we recover largely identical topologies that leave the position of only few clades uncertain and cover the intra- and interspecific variation of 28 of the 29 described and six undescribed species. In addition to traditional support values, such as bootstrap and posterior probability, we quantify genealogical concordance to estimate the effects of conflicting evolutionary histories on phylogenetic inference. Our analyses reveal that the current taxonomic classification of the genus is inconsistent with the molecular phylogenetic inference, and we identify cryptic diversity in seven species. Divergence dating suggests that the split between Myrmecocystus and its sister taxon Lasius occurred in the early Miocene. Crown group Myrmecocystus started diversifying about 14.08 Ma ago when the gradual aridification of the southwestern United States and northern Mexico led to formation of the American deserts and to adaptive radiations of many desert taxa.

Genetic diversity of the cardiopulmonary canid nematode Angiostrongylus vasorum within and between rural and urban fox populations

Angiostrongylus vasorum is an emerging parasitic cardiopulmonary nematode of dogs, foxes, and other canids. In dogs, the infection causes respiratory and bleeding disorders along with other clinical signs collectively known as canine angiostrongylosis, while foxes represent an important wildlife reservoir. Despite the spread of A. vasorum across various countries in Europe and the Americas, little is known about the genetic diversity of A. vasorum populations at a local level in a highly endemic area. Thus, in the present study, we investigated the genetic diversity of 323 adult A. vasorum nematodes from 64 foxes living in the canton of Zurich, Switzerland. Among those, 279 worms isolated from 20 foxes were analyzed separately to investigate the genetic diversity of multiple worms within individual foxes. Part of the mitochondrial cytochrome c oxidase subunit I (mtCOI) gene was amplified and sequenced. Overall, 16 mitochondrial haplotypes were identified. The analysis of multiple worms per host revealed 12 haplotypes, with up to 5 different haplotypes in single individuals. Higher haplotype diversity (n = 10) of nematodes from foxes of urban areas than in rural areas (n = 7) was observed, with 5 shared haplotypes. Comparing our data with published GenBank sequences, five haplotypes were found to be unique within the Zurich nematode population. Interestingly, A. vasorum nematodes obtained from foxes in London and Zurich shared the same dominating haplotype. Further studies are needed to clarify if this haplotype has a different pathogenicity that may contribute to its dominance. Our findings show the importance of foxes as a reservoir for genetic parasite recombination and indicate that high fox population densities in urban areas with small and overlapping home ranges allow multiple infection events that lead to high genetic variability of A. vasorum.

Functional, Morphological, and Evolutionary Characterization of Hearing in Subterranean, Eusocial African Mole-Rats

Naked mole-rats are highly vocal, eusocial, subterranean rodents with, counterintuitively, poor hearing. The causes underlying their altered hearing are unknown. Moreover, whether altered hearing is degenerate or adaptive to their unique lifestyles is controversial. We used various methods to identify the factors contributing to altered hearing in naked and the related Damaraland mole-rats and to examine whether these alterations result from relaxed or adaptive selection. Remarkably, we found that cochlear amplification was absent from both species despite normal prestin function in outer hair cells isolated from naked mole-rats. Instead, loss of cochlear amplification appears to result from abnormal hair bundle morphologies observed in both species. By exploiting a well-curated deafness phenotype-genotype database, we identified amino acid substitutions consistent with abnormal hair bundle morphology and reduced hearing sensitivity. Amino acid substitutions were found in unique groups of six hair bundle link proteins. Molecular evolutionary analyses revealed shifts in selection pressure at both the gene and the codon level for five of these six hair bundle link proteins. Substitutions in three of these proteins are associated exclusively with altered hearing. Altogether, our findings identify the likely mechanism of altered hearing in African mole-rats, making them the only identified mammals naturally lacking cochlear amplification. Moreover, our findings suggest that altered hearing in African mole-rats is adaptive, perhaps tailoring hearing to eusocial and subterranean lifestyles. Finally, our work reveals multiple, unique evolutionary trajectories in African mole-rat hearing and establishes species members as naturally occurring disease models to investigate human hearing loss.

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.

Larger, unfiltered datasets are more effective at resolving phylogenetic conflict: Introns, exons, and UCEs resolve ambiguities in Golden-backed frogs (Anura: Ranidae; genus Hylarana)

Using FrogCap, a recently-developed sequence-capture protocol, we obtained >12,000 highly informative exons, introns, and ultraconserved elements (UCEs), which we used to illustrate variation in evolutionary histories of these classes of markers, and to resolve long-standing systematic problems in Southeast Asian Golden-backed frogs of the genus-complex Hylarana. We also performed a comprehensive suite of analyses to assess the relative performance of different genetic markers, data filtering strategies, tree inference methods, and different measures of branch support. To reduce gene tree estimation error, we filtered the data using different thresholds of taxon completeness (missing data) and parsimony informative sites (PIS). We then estimated species trees using concatenated datasets and Maximum Likelihood (IQ-TREE) in addition to summary (ASTRAL-III), distance-based (ASTRID), and site-based (SVDQuartets) multispecies coalescent methods. Topological congruence and branch support were examined using traditional bootstrap, local posterior probabilities, gene concordance factors, quartet frequencies, and quartet scores. Our results did not yield a single concordant topology. Instead, introns, exons, and UCEs clearly possessed different phylogenetic signals, resulting in conflicting, yet strongly-supported phylogenetic estimates. However, a combined analysis comprising the most informative introns, exons, and UCEs converged on a similar topology across all analyses, with the exception of SVDQuartets. Bootstrap values were consistently high despite high levels of incongruence and high proportions of gene trees supporting conflicting topologies. Although low bootstrap values did indicate low heuristic support, high bootstrap support did not necessarily reflect congruence or support for the correct topology. This study reiterates findings of some previous studies, which demonstrated that traditional bootstrap values can produce positively misleading measures of support in large phylogenomic datasets. We also showed a remarkably strong positive relationship between branch length and topological congruence across all datasets, implying that very short internodes remain a challenge to resolve, even with orders of magnitude more data than ever before. Overall, our results demonstrate that more data from unfiltered or combined datasets produced superior results. Although data filtering reduced gene tree incongruence, decreased amounts of data also biased phylogenetic estimation. A point of diminishing returns was evident, at which higher congruence (from more stringent filtering) at the expense of amount of data led to topological error as assessed by comparison to more complete datasets across different genomic markers. Additionally, we showed that applying a parameter-rich model to a partitioned analysis of concatenated data produces better results compared to unpartitioned, or even partitioned analysis using model selection. Despite some lingering uncertainties, a combined analysis of our genomic data and sequences supplemented from GenBank (on the basis of a few gene regions) revealed highly supported novel systematic arrangements. Based on these new findings, we transfer Amnirana nicobariensis into the genus Indosylvirana; and I. milleti and Hylarana celebensis to the genus Papurana. We also provisionally place H. attigua in the genus Papurana pending verification from positively identified (voucher substantiated) samples.

Disentangling Sources of Gene Tree Discordance in Phylogenomic Data Sets: Testing Ancient Hybridizations in Amaranthaceae s.l

Gene tree discordance in large genomic data sets can be caused by evolutionary processes such as incomplete lineage sorting and hybridization, as well as model violation, and errors in data processing, orthology inference, and gene tree estimation. Species tree methods that identify and accommodate all sources of conflict are not available, but a combination of multiple approaches can help tease apart alternative sources of conflict. Here, using a phylotranscriptomic analysis in combination with reference genomes, we test a hypothesis of ancient hybridization events within the plant family Amaranthaceae s.l. that was previously supported by morphological, ecological, and Sanger-based molecular data. The data set included seven genomes and 88 transcriptomes, 17 generated for this study. We examined gene-tree discordance using coalescent-based species trees and network inference, gene tree discordance analyses, site pattern tests of introgression, topology tests, synteny analyses, and simulations. We found that a combination of processes might have generated the high levels of gene tree discordance in the backbone of Amaranthaceae s.l. Furthermore, we found evidence that three consecutive short internal branches produce anomalous trees contributing to the discordance. Overall, our results suggest that Amaranthaceae s.l. might be a product of an ancient and rapid lineage diversification, and remains, and probably will remain, unresolved. This work highlights the potential problems of identifiability associated with the sources of gene tree discordance including, in particular, phylogenetic network methods. Our results also demonstrate the importance of thoroughly testing for multiple sources of conflict in phylogenomic analyses, especially in the context of ancient, rapid radiations. We provide several recommendations for exploring conflicting signals in such situations. [Amaranthaceae; gene tree discordance; hybridization; incomplete lineage sorting; phylogenomics; species network; species tree; transcriptomics.]

An integrative phylogenomic approach to elucidate the evolutionary history and divergence times of Neuropterida (Insecta: Holometabola)

BACKGROUND

The latest advancements in DNA sequencing technologies have facilitated the resolution of the phylogeny of insects, yet parts of the tree of Holometabola remain unresolved. The phylogeny of Neuropterida has been extensively studied, but no strong consensus exists concerning the phylogenetic relationships within the order Neuroptera. Here, we assembled a novel transcriptomic dataset to address previously unresolved issues in the phylogeny of Neuropterida and to infer divergence times within the group. We tested the robustness of our phylogenetic estimates by comparing summary coalescent and concatenation-based phylogenetic approaches and by employing different quartet-based measures of phylogenomic incongruence, combined with data permutations.

RESULTS

Our results suggest that the order Raphidioptera is sister to Neuroptera + Megaloptera. Coniopterygidae is inferred as sister to all remaining neuropteran families suggesting that larval cryptonephry could be a ground plan feature of Neuroptera. A clade that includes Nevrorthidae, Osmylidae, and Sisyridae (i.e. Osmyloidea) is inferred as sister to all other Neuroptera except Coniopterygidae, and Dilaridae is placed as sister to all remaining neuropteran families. Ithonidae is inferred as the sister group of monophyletic Myrmeleontiformia. The phylogenetic affinities of Chrysopidae and Hemerobiidae were dependent on the data type analyzed, and quartet-based analyses showed only weak support for the placement of Hemerobiidae as sister to Ithonidae + Myrmeleontiformia. Our molecular dating analyses suggest that most families of Neuropterida started to diversify in the Jurassic and our ancestral character state reconstructions suggest a primarily terrestrial environment of the larvae of Neuropterida and Neuroptera.

CONCLUSION

Our extensive phylogenomic analyses consolidate several key aspects in the backbone phylogeny of Neuropterida, such as the basal placement of Coniopterygidae within Neuroptera and the monophyly of Osmyloidea. Furthermore, they provide new insights into the timing of diversification of Neuropterida. Despite the vast amount of analyzed molecular data, we found that certain nodes in the tree of Neuroptera are not robustly resolved. Therefore, we emphasize the importance of integrating the results of morphological analyses with those of sequence-based phylogenomics. We also suggest that comparative analyses of genomic meta-characters should be incorporated into future phylogenomic studies of Neuropterida.

A new phylogenetic protocol: dealing with model misspecification and confirmation bias in molecular phylogenetics

Molecular phylogenetics plays a key role in comparative genomics and has increasingly significant impacts on science, industry, government, public health and society. In this paper, we posit that the current phylogenetic protocol is missing two critical steps, and that their absence allows model misspecification and confirmation bias to unduly influence phylogenetic estimates. Based on the potential offered by well-established but under-used procedures, such as assessment of phylogenetic assumptions and tests of goodness of fit, we introduce a new phylogenetic protocol that will reduce confirmation bias and increase the accuracy of phylogenetic estimates.

Investigating the utility of traditional and genomic multi-locus datasets to resolve relationships in Lipaugus and Tijuca (Cotingidae)

Rapid diversification limits our ability to resolve evolutionary relationships and examine diversification history, as in the case of the Neotropical cotingas. Here we present an analysis with complete taxon sampling for the cotinga genera Lipaugus and Tijuca, which include some of the most range-restricted (e.g., T. condita) and also the most widespread and familiar (e.g., L. vociferans) forest birds in the Neotropics. We used two datasets: (1) Sanger sequencing data sampled from eight loci in 34 individuals across all described taxa and (2) sequence capture data linked to 1,079 ultraconserved elements and conserved exons sampled from one or two individuals per species. Phylogenies estimated from the Sanger sequencing data failed to resolve three nodes, but the sequence capture data produced a well-supported tree. Lipaugus and Tijuca formed a single, highly supported clade, but Tijuca species were not sister and were embedded within Lipaugus. A dated phylogeny confirmed Lipaugus and Tijuca diversified rapidly in the Miocene. Our study provides a detailed evolutionary hypothesis for Lipaugus and Tijuca and demonstrates that increasing genomic sampling can prove instrumental in resolving the evolutionary history of recent radiations.

Streamlining universal single-copy orthologue and ultraconserved element design: A case study in Collembola

Genomic data sets are increasingly central to ecological and evolutionary biology, but far fewer resources are available for invertebrates. Powerful new computational tools and the rapidly decreasing cost of Illumina sequencing are beginning to change this, enabling rapid genome assembly and reference marker extraction. We have developed and tested a practical workflow for developing genomic resources in nonmodel groups with real-world data on Collembola (springtails), one of the most dominant soil animals on Earth. We designed universal molecular marker sets, single-copy orthologues (BUSCOs) and ultraconserved elements (UCEs), using three existing and 11 newly generated genomes. Both marker types were tested in silico via marker capture success and phylogenetic performance. The new genomes were assembled with Illumina short reads and 9,585-14,743 protein-coding genes were predicted with ab initio and protein homology evidence. We identified 1,997 benchmarking universal single-copy orthologues (BUSCOs) across 14 genomes and created and assessed a custom BUSCO data set for extracting single-copy genes. We also developed a new UCE probe set containing 46,087 baits targeting 1,885 loci. We successfully captured 1,437-1,865 BUSCOs and 975-1,186 UCEs across 14 genomes. Phylogenomic reconstructions using these markers proved robust, giving new insight on deep-time collembolan relationships. Our study demonstrates the feasibility of generating thousands of universal markers from highly efficient whole-genome sequencing, providing a valuable resource for genome-scale investigations in evolutionary biology and ecology.

Metagenomics methods for the study of plant-associated microbial communities: A review

Plant microbiota have different effects on the plant which can be beneficial or pathogenic. In this study, we concentrated on beneficial microbes associated with plants using endophytic microbes as a case study. Detailed knowledge of the microbial diversity, abundance, composition, functional genes patterns, and metabolic pathways at genome level could assist in understanding the contributions of microbial community towards plant growth and health. Recently, the study of microbial community has improved greatly with the discovery of next-generation sequencing and bioinformatics technologies. Analysis of next generation sequencing data and a proper computational method plays a key role in examining microbial metagenome. This review presents the general metagenomics and computational methods used in processing plant associated metagenomes with concentration on endophytes. This includes 1) introduction of plant-associated microbiota and the factors driving their diversity. 2) plant metagenome focusing on DNA extraction, verification and quality control. 3) metagenomics methods used in community analysis of endophytes focusing on maize plant and, 4) computational methods used in the study of endophytic microbiomes. Limitations and future prospects of metagenomics and computational methods for the analysis of plant-associated metagenome (endophytic metagenome) were also discussed with the aim of fostering its development. We conclude that there is need to adopt advanced genomic features such as k-mers of random size, which do not depend on annotation and can represent other sequence alternatives.

Phylogenetic Clustering by Linear Integer Programming (PhyCLIP)

Subspecies nomenclature systems of pathogens are increasingly based on sequence data. The use of phylogenetics to identify and differentiate between clusters of genetically similar pathogens is particularly prevalent in virology from the nomenclature of human papillomaviruses to highly pathogenic avian influenza (HPAI) H5Nx viruses. These nomenclature systems rely on absolute genetic distance thresholds to define the maximum genetic divergence tolerated between viruses designated as closely related. However, the phylogenetic clustering methods used in these nomenclature systems are limited by the arbitrariness of setting intra and intercluster diversity thresholds. The lack of a consensus ground truth to define well-delineated, meaningful phylogenetic subpopulations amplifies the difficulties in identifying an informative distance threshold. Consequently, phylogenetic clustering often becomes an exploratory, ad hoc exercise. Phylogenetic Clustering by Linear Integer Programming (PhyCLIP) was developed to provide a statistically principled phylogenetic clustering framework that negates the need for an arbitrarily defined distance threshold. Using the pairwise patristic distance distributions of an input phylogeny, PhyCLIP parameterizes the intra and intercluster divergence limits as statistical bounds in an integer linear programming model which is subsequently optimized to cluster as many sequences as possible. When applied to the hemagglutinin phylogeny of HPAI H5Nx viruses, PhyCLIP was not only able to recapitulate the current WHO/OIE/FAO H5 nomenclature system but also further delineated informative higher resolution clusters that capture geographically distinct subpopulations of viruses. PhyCLIP is pathogen-agnostic and can be generalized to a wide variety of research questions concerning the identification of biologically informative clusters in pathogen phylogenies. PhyCLIP is freely available at http://github.com/alvinxhan/PhyCLIP, last accessed March 15, 2019.

High-throughput sequencing (HTS) for the analysis of viral populations

The development of High-Throughput Sequencing (HTS) technologies is having a major impact on the genomic analysis of viral populations. Current HTS platforms can capture nucleic acid variation across millions of genes for both selected amplicons and full viral genomes. HTS has already facilitated the discovery of new viruses, hinted new taxonomic classifications and provided a deeper and broader understanding of their diversity, population and genetic structure. Hence, HTS has already replaced standard Sanger sequencing in basic and applied research fields, but the next step is its implementation as a routine technology for the analysis of viruses in clinical settings. The most likely application of this implementation will be the analysis of viral genomics, because the huge population sizes, high mutation rates and very fast replacement of viral populations have demonstrated the limited information obtained with Sanger technology. In this review, we describe new technologies and provide guidelines for the high-throughput sequencing and genetic and evolutionary analyses of viral populations and metaviromes, including software applications. With the development of new HTS technologies, new and refurbished molecular and bioinformatic tools are also constantly being developed to process and integrate HTS data. These allow assembling viral genomes and inferring viral population diversity and dynamics. Finally, we also present several applications of these approaches to the analysis of viral clinical samples including transmission clusters and outbreak characterization.

Model Choice, Missing Data, and Taxon Sampling Impact Phylogenomic Inference of Deep Basidiomycota Relationships

Resolving deep divergences in the tree of life is challenging even for analyses of genome-scale phylogenetic data sets. Relationships between Basidiomycota subphyla, the rusts and allies (Pucciniomycotina), smuts and allies (Ustilaginomycotina), and mushroom-forming fungi and allies (Agaricomycotina) were found particularly recalcitrant both to traditional multigene and genome-scale phylogenetics. Here, we address basal Basidiomycota relationships using concatenated and gene tree-based analyses of various phylogenomic data sets to examine the contribution of several potential sources of bias. We evaluate the contribution of biological causes (hard polytomy, incomplete lineage sorting) versus unmodeled evolutionary processes and factors that exacerbate their effects (e.g., fast-evolving sites and long-branch taxa) to inferences of basal Basidiomycota relationships. Bayesian Markov Chain Monte Carlo and likelihood mapping analyses reject the hard polytomy with confidence. In concatenated analyses, fast-evolving sites and oversimplified models of amino acid substitution favored the grouping of smuts with mushroom-forming fungi, often leading to maximal bootstrap support in both concatenation and coalescent analyses. On the contrary, the most conserved data subsets grouped rusts and allies with mushroom-forming fungi, although this relationship proved labile, sensitive to model choice, to different data subsets and to missing data. Excluding putative long-branch taxa, genes with high proportions of missing data and/or with strong signal failed to reveal a consistent trend toward one or the other topology, suggesting that additional sources of conflict are at play. While concatenated analyses yielded strong but conflicting support, individual gene trees mostly provided poor support for any resolution of rusts, smuts, and mushroom-forming fungi, suggesting that the true Basidiomycota tree might be in a part of tree space that is difficult to access using both concatenation and gene tree-based approaches. Inference-based assessments of absolute model fit strongly reject best-fit models for the vast majority of genes, indicating a poor fit of even the most commonly used models. While this is consistent with previous assessments of site-homogenous models of amino acid evolution, this does not appear to be the sole source of confounding signal. Our analyses suggest that topologies uniting smuts with mushroom-forming fungi can arise as a result of inappropriate modeling of amino acid sites that might be prone to systematic bias. We speculate that improved models of sequence evolution could shed more light on basal splits in the Basidiomycota, which, for now, remain unresolved despite the use of whole genome data.

The Prevalence and Impact of Model Violations in Phylogenetic Analysis

In phylogenetic inference, we commonly use models of substitution which assume that sequence evolution is stationary, reversible, and homogeneous (SRH). Although the use of such models is often criticized, the extent of SRH violations and their effects on phylogenetic inference of tree topologies and edge lengths are not well understood. Here, we introduce and apply the maximal matched-pairs tests of homogeneity to assess the scale and impact of SRH model violations on 3,572 partitions from 35 published phylogenetic data sets. We show that roughly one-quarter of all the partitions we analyzed (23.5%) reject the SRH assumptions, and that for 25% of data sets, tree topologies inferred from all partitions differ significantly from topologies inferred using the subset of partitions that do not reject the SRH assumptions. This proportion increases when comparing trees inferred using the subset of partitions that rejects the SRH assumptions, to those inferred from partitions that do not reject the SRH assumptions. These results suggest that the extent and effects of model violation in phylogenetics may be substantial. They highlight the importance of testing for model violations and possibly excluding partitions that violate models prior to tree reconstruction. Our results also suggest that further effort in developing models that do not require SRH assumptions could lead to large improvements in the accuracy of phylogenomic inference. The scripts necessary to perform the analysis are available in https://github.com/roblanf/SRHtests, and the new tests we describe are available as a new option in IQ-TREE (http://www.iqtree.org).

Maximize Resolution or Minimize Error? Using Genotyping-By-Sequencing to Investigate the Recent Diversification of Helianthemum (Cistaceae)

A robust phylogenetic framework, in terms of extensive geographical and taxonomic sampling, well-resolved species relationships and high certainty of tree topologies and branch length estimations, is critical in the study of macroevolutionary patterns. Whereas Sanger sequencing-based methods usually recover insufficient phylogenetic signal, especially in recently diversified lineages, reduced-representation sequencing methods tend to provide well-supported phylogenetic relationships, but usually entail remarkable bioinformatic challenges due to the inherent trade-off between the number of SNPs and the magnitude of associated error rates. The genus Helianthemum (Cistaceae) is a species-rich and taxonomically complex Palearctic group of plants that diversified mainly since the Upper Miocene. It is a challenging case study since previous attempts using Sanger sequencing were unable to resolve the intrageneric phylogenetic relationships. Aiming to obtain a robust phylogenetic reconstruction based on genotyping-by-sequencing (GBS), we established a rigorous methodological workflow in which we i) explored how variable settings during dataset assembly have an impact on error rates and on the degree of resolution under concatenation and coalescent approaches, ii) assessed the effect of two extreme parameter configurations (minimizing error rates vs. maximizing phylogenetic resolution) on tree topology and branch lengths, and iii) evaluated the effects of these two configurations on estimates of divergence times and diversification rates. Our analyses produced highly supported topologically congruent phylogenetic trees for both configurations. However, minimizing error rates did produce more reliable branch lengths, critically affecting the accuracy of downstream analyses (i.e. divergence times and diversification rates). In addition to recommending a revision of intrageneric systematics, our results enabled us to identify three highly diversified lineages in Helianthemum in contrasting geographical areas and ecological conditions, which started radiating in the Upper Miocene.

Bayesian Estimation of Past Population Dynamics in BEAST 1.10 Using the Skygrid Coalescent Model

Inferring past population dynamics over time from heterochronous molecular sequence data is often achieved using the Bayesian Skygrid model, a nonparametric coalescent model that estimates the effective population size over time. Available in BEAST, a cross-platform program for Bayesian analysis of molecular sequences using Markov chain Monte Carlo, this coalescent model is often estimated in conjunction with a molecular clock model to produce time-stamped phylogenetic trees. We here provide a practical guide to using BEAST and its accompanying applications for the purpose of drawing inference under these models. We focus on best practices, potential pitfalls, and recommendations that can be generalized to other software packages for Bayesian inference. This protocol shows how to use TempEst, BEAUti, and BEAST 1.10 (http://beast.community/; last accessed July 29, 2019), LogCombiner as well as Tracer in a complete workflow.

Phylogeny of Hawaiian Melicope (Rutaceae): RAD-seq Resolves Species Relationships and Reveals Ancient Introgression

Hawaiian Melicope are one of the major adaptive radiations of the Hawaiian Islands comprising 54 endemic species. The lineage is monophyletic with an estimated crown age predating the rise of the current high islands. Phylogenetic inference based on Sanger sequencing has not been sufficient to resolve species or deeper level relationships. Here, we apply restriction site-associated DNA sequencing (RAD-seq) to the lineage to infer phylogenetic relationships. We employ Quartet Sampling to assess information content and statistical support, and to quantify discordance as well as partitioned ABBA-BABA tests to uncover evidence of introgression. Our new results drastically improved resolution of relationships within Hawaiian Melicope. The lineage is divided into five fully supported main clades, two of which correspond to morphologically circumscribed infrageneric groups. We provide evidence for both ancestral and current hybridization events. We confirm the necessity for a taxonomic revision of the Melicope section Pelea, as well as a re-evaluation of several species complexes by combining genomic and morphological data.

Quartet-Based Computations of Internode Certainty Provide Robust Measures of Phylogenetic Incongruence

Incongruence, or topological conflict, is prevalent in genome-scale data sets. Internode certainty (IC) and related measures were recently introduced to explicitly quantify the level of incongruence of a given internal branch among a set of phylogenetic trees and complement regular branch support measures (e.g., bootstrap, posterior probability) that instead assess the statistical confidence of inference. Since most phylogenomic studies contain data partitions (e.g., genes) with missing taxa and IC scores stem from the frequencies of bipartitions (or splits) on a set of trees, IC score calculation typically requires adjusting the frequencies of bipartitions from these partial gene trees. However, when the proportion of missing taxa is high, the scores yielded by current approaches that adjust bipartition frequencies in partial gene trees differ substantially from each other and tend to be overestimates. To overcome these issues, we developed three new IC measures based on the frequencies of quartets, which naturally apply to both complete and partial trees. Comparison of our new quartet-based measures to previous bipartition-based measures on simulated data shows that: (1) on complete data sets, both quartet-based and bipartition-based measures yield very similar IC scores; (2) IC scores of quartet-based measures on a given data set with and without missing taxa are more similar than the scores of bipartition-based measures; and (3) quartet-based measures are more robust to the absence of phylogenetic signal and errors in phylogenetic inference than bipartition-based measures. Additionally, the analysis of an empirical mammalian phylogenomic data set using our quartet-based measures reveals the presence of substantial levels of incongruence for numerous internal branches. An efficient open-source implementation of these quartet-based measures is freely available in the program QuartetScores (https://github.com/lutteropp/QuartetScores).

Discovery of All Three Types in Cartilaginous Fishes Enables Phylogenetic Resolution of the Origins and Evolution of Interferons

Interferons orchestrate host antiviral responses in jawed vertebrates. They are categorized into three classes; IFN1 and IFN3 are the primary antiviral cytokine lineages, while IFN2 responds to a broader variety of pathogens. The evolutionary relationships within and between these three classes have proven difficult to resolve. Here, we reassess interferon evolution, considering key phylogenetic pitfalls including taxon sampling, alignment quality, model adequacy, and outgroup choice. We reveal that cartilaginous fishes, and hence the jawed vertebrate ancestor, possess(ed) orthologs of all three interferon classes. We show that IFN3 groups sister to IFN1, resolve the origins of the human IFN3 lineages, and find that intronless IFN3s emerged at least three times. IFN2 genes are highly conserved, except for IFN-γ-rel, which we confirm resulted from a teleost-specific duplication. Our analyses show that IFN1 phylogeny is highly sensitive to phylogenetic error. By accounting for this, we describe a new backbone IFN1 phylogeny that implies several IFN1 genes existed in the jawed vertebrate ancestor. One of these is represented by the intronless IFN1s of tetrapods, including mammalian-like repertoires of reptile IFN1s and a subset of amphibian IFN1s, in addition to newly-identified intron-containing shark IFN1 genes. IFN-f, previously only found in teleosts, likely represents another ancestral jawed vertebrate IFN1 family member, suggesting the current classification of fish IFN1s into two groups based on the number of cysteines may need revision. The providence of the remaining fish IFN1s and the coelacanth IFN1s proved difficult to resolve, but they may also be ancestral jawed vertebrate IFN1 lineages. Finally, a large group of amphibian-specific IFN1s falls sister to all other IFN1s and was likely also present in the jawed vertebrate ancestor. Our results verify that intronless IFN1s have evolved multiple times in amphibians and indicate that no one-to-one orthology exists between mammal and reptile IFN1s. Our data also imply that diversification of the multiple IFN1s present in the jawed vertebrate ancestor has occurred through a rapid birth-death process, consistent with functional maintenance over a 450-million-year host-pathogen arms race. In summary, this study reveals a new model of interferon evolution important to our understanding of jawed vertebrate antiviral immunity.

A Robust Phylogenomic Time Tree for Biotechnologically and Medically Important Fungi in the Genera Aspergillus and Penicillium

Understanding the evolution of traits across technologically and medically significant fungi requires a robust phylogeny. Even though species in the Aspergillus and Penicillium genera (family Aspergillaceae, class Eurotiomycetes) are some of the most significant technologically and medically relevant fungi, we still lack a genome-scale phylogeny of the lineage or knowledge of the parts of the phylogeny that exhibit conflict among analyses. Here, we used a phylogenomic approach to infer evolutionary relationships among 81 genomes that span the diversity of Aspergillus and Penicillium species, to identify conflicts in the phylogeny, and to determine the likely underlying factors of the observed conflicts. Using a data matrix comprised of 1,668 genes, we found that while most branches of the phylogeny of the Aspergillaceae are robustly supported and recovered irrespective of method of analysis, a few exhibit various degrees of conflict among our analyses. Further examination of the observed conflict revealed that it largely stems from incomplete lineage sorting and hybridization or introgression. Our analyses provide a robust and comprehensive evolutionary genomic roadmap for this important lineage, which will facilitate the examination of the diverse technologically and medically relevant traits of these fungi in an evolutionary context.

The filamentous fungal family Aspergillaceae contains >1,000 known species, mostly in the genera Aspergillus and Penicillium. Several species are used in the food, biotechnology, and drug industries (e.g., Aspergillus oryzae and Penicillium camemberti), while others are dangerous human and plant pathogens (e.g., Aspergillus fumigatus and Penicillium digitatum). To infer a robust phylogeny and pinpoint poorly resolved branches and their likely underlying contributors, we used 81 genomes spanning the diversity of Aspergillus and Penicillium to construct a 1,668-gene data matrix. Phylogenies of the nucleotide and amino acid versions of this full data matrix as well as of several additional data matrices were generated using three different maximum likelihood schemes (i.e., gene-partitioned, unpartitioned, and coalescence) and using both site-homogenous and site-heterogeneous models (total of 64 species-level phylogenies). Examination of the topological agreement among these phylogenies and measures of internode certainty identified 11/78 (14.1%) bipartitions that were incongruent and pinpointed the likely underlying contributing factors, which included incomplete lineage sorting, hidden paralogy, hybridization or introgression, and reconstruction artifacts associated with poor taxon sampling. Relaxed molecular clock analyses suggest that Aspergillaceae likely originated in the lower Cretaceous and that the Aspergillus and Penicillium genera originated in the upper Cretaceous. Our results shed light on the ongoing debate on Aspergillus systematics and taxonomy and provide a robust evolutionary and temporal framework for comparative genomic analyses in Aspergillaceae. More broadly, our approach provides a general template for phylogenomic identification of resolved and contentious branches in densely genome-sequenced lineages across the tree of life.

Estimating Improved Partitioning Schemes for Ultraconserved Elements

Ultraconserved (UCEs) are popular markers for phylogenomic studies. They are relatively simple to collect from distantly-related organisms, and contain sufficient information to infer relationships at almost all taxonomic levels. Most studies of UCEs use partitioning to account for variation in rates and patterns of molecular evolution among sites, for example by estimating an independent model of molecular evolution for each UCE. However, rates and patterns of molecular evolution vary substantially within as well as between UCEs, suggesting that there may be opportunities to improve how UCEs are partitioned for phylogenetic inference. We propose and evaluate new partitioning methods for phylogenomic studies of UCEs: Sliding-Window Site Characteristics (SWSC), and UCE Site Position (UCESP). The first method uses site characteristics such as entropy, multinomial likelihood, and GC content to generate partitions that account for heterogeneity in rates and patterns of molecular evolution within each UCE. The second method groups together nucleotides that are found in similar physical locations within the UCEs. We examined the new methods with seven published data sets from a variety of taxa. We demonstrate the UCESP method generates partitions that are worse than other strategies used to partition UCE data sets (e.g., one partition per UCE). The SWSC method, particularly when based on site entropies, generates partitions that account for within-UCE heterogeneity and leads to large increases in the model fit. All of the methods, code, and data used in this study, are available from https://github.com/Tagliacollo/PartitionUCE. Simplified code for implementing the best method, the SWSC-EN, is available from https://github.com/Tagliacollo/PFinderUCE-SWSC-EN.

Minimal standards for the description of new genera and species of rhizobia and agrobacteria

Herein the members of the Subcommittee on Taxonomy of Rhizobia and Agrobacteria of the International Committee on Systematics of Prokaryotes review recent developments in rhizobial and agrobacterial taxonomy and propose updated minimal standards for the description of new species (and genera) in these groups. The essential requirements (minimal standards) for description of a new species are (1) a genome sequence of at least the proposed type strain and (2) evidence for differentiation from other species based on genome sequence comparisons. It is also recommended that (3) genetic variation within the species is documented with sequence data from several clearly different strains and (4) phenotypic features are described, and their variation documented with data from a relevant set of representative strains. Furthermore, it is encouraged that information is provided on (5) nodulation or pathogenicity phenotypes, as appropriate, with relevant gene sequences. These guidelines supplement the current rules of general bacterial taxonomy, which require (6) a name that conforms to the International Code of Nomenclature of Prokaryotes, (7) validation of the name by publication either directly in the International Journal of Systematic and Evolutionary Microbiology or in a validation list when published elsewhere, and (8) deposition of the type strain in two international culture collections in separate countries.

The synergistic effect of concatenation in phylogenomics: the case in Pantoea

With the increased availability of genome sequences for bacteria, it has become routine practice to construct genome-based phylogenies. These phylogenies have formed the basis for various taxonomic decisions, especially for resolving problematic relationships between taxa. Despite the popularity of concatenating shared genes to obtain well-supported phylogenies, various issues regarding this combined-evidence approach have been raised. These include the introduction of phylogenetic error into datasets, as well as incongruence due to organism-level evolutionary processes, particularly horizontal gene transfer and incomplete lineage sorting. Because of the huge effect that this could have on phylogenies, we evaluated the impact of phylogenetic conflict caused by organism-level evolutionary processes on the established species phylogeny for Pantoea, a member of the Enterobacterales. We explored the presence and distribution of phylogenetic conflict at the gene partition and nucleotide levels, by identifying putative inter-lineage recombination events that might have contributed to such conflict. Furthermore, we determined whether smaller, randomly constructed datasets had sufficient signal to reconstruct the current species tree hypothesis or if they would be overshadowed by phylogenetic incongruence. We found that no individual gene tree was fully congruent with the species phylogeny of Pantoea, although many of the expected nodes were supported by various individual genes across the genome. Evidence of recombination was found across all lineages within Pantoea, and provides support for organism-level evolutionary processes as a potential source of phylogenetic conflict. The phylogenetic signal from at least 70 random genes recovered robust, well-supported phylogenies for the backbone and most species relationships of Pantoea, and was unaffected by phylogenetic conflict within the dataset. Furthermore, despite providing limited resolution among taxa at the level of single gene trees, concatenated analyses of genes that were identified as having no signal resulted in a phylogeny that resembled the species phylogeny of Pantoea. This distribution of signal and noise across the genome presents the ideal situation for phylogenetic inference, as the topology from a ≥70-gene concatenated species phylogeny is not driven by single genes, and our data suggests that this finding may also hold true for smaller datasets. We thus argue that, by using a concatenation-based approach in phylogenomics, one can obtain robust phylogenies due to the synergistic effect of the combined signal obtained from multiple genes.

Evolution of the Highly Repetitive PEVK Region of Titin Across Mammals

The protein titin plays a key role in vertebrate muscle where it acts like a giant molecular spring. Despite its importance and conservation over vertebrate evolution, a lack of high quality annotations in non-model species makes comparative evolutionary studies of titin challenging. The PEVK region of titin—named for its high proportion of Pro-Glu-Val-Lys amino acids—is particularly difficult to annotate due to its abundance of alternatively spliced isoforms and short, highly repetitive exons. To understand PEVK evolution across mammals, we developed a bioinformatics tool, PEVK_Finder, to annotate PEVK exons from genomic sequences of titin and applied it to a diverse set of mammals. PEVK_Finder consistently outperforms standard annotation tools across a broad range of conditions and improves annotations of the PEVK region in non-model mammalian species. We find that the PEVK region can be divided into two subregions (PEVK-N, PEVK-C) with distinct patterns of evolutionary constraint and divergence. The bipartite nature of the PEVK region has implications for titin diversification. In the PEVK-N region, certain exons are conserved and may be essential, but natural selection also acts on particular codons. In the PEVK-C, exons are more homogenous and length variation of the PEVK region may provide the raw material for evolutionary adaptation in titin function. The PEVK-C region can be further divided into a highly repetitive region (PEVK-CA) and one that is more variable (PEVK-CB). Taken together, we find that the very complexity that makes titin a challenge for annotation tools may also promote evolutionary adaptation.

Phenomenological Load on Model Parameters Can Lead to False Biological Conclusions

When a substitution model is fitted to an alignment using maximum likelihood, its parameters are adjusted to account for as much site-pattern variation as possible. A parameter might therefore absorb a substantial quantity of the total variance in an alignment (or more formally, bring about a substantial reduction in the deviance of the fitted model) even if the process it represents played no role in the generation of the data. When this occurs, we say that the parameter estimate carries phenomenological load (PL). Large PL in a parameter estimate is a concern because it not only invalidates its mechanistic interpretation (if it has one) but also increases the likelihood that it will be found to be statistically significant. The problem of PL was not identified in the past because most off-the-shelf substitution models make simplifying assumptions that preclude the generation of realistic levels of variation. In this study, we use the more realistic mutation-selection framework as the basis of a generating model formulated to produce data that mimic an alignment of mammalian mitochondrial DNA. We show that a parameter estimate can carry PL when 1) the substitution model is underspecified and 2) the parameter represents a process that is confounded with other processes represented in the data-generating model. We then provide a method that can be used to identify signal for the process that a given parameter represents despite the existence of PL.

Embracing heterogeneity: coalescing the Tree of Life and the future of phylogenomics

Building the Tree of Life (ToL) is a major challenge of modern biology, requiring advances in cyberinfrastructure, data collection, theory, and more. Here, we argue that phylogenomics stands to benefit by embracing the many heterogeneous genomic signals emerging from the first decade of large-scale phylogenetic analysis spawned by high-throughput sequencing (HTS). Such signals include those most commonly encountered in phylogenomic datasets, such as incomplete lineage sorting, but also those reticulate processes emerging with greater frequency, such as recombination and introgression. Here we focus specifically on how phylogenetic methods can accommodate the heterogeneity incurred by such population genetic processes; we do not discuss phylogenetic methods that ignore such processes, such as concatenation or supermatrix approaches or supertrees. We suggest that methods of data acquisition and the types of markers used in phylogenomics will remain restricted until a posteriori methods of marker choice are made possible with routine whole-genome sequencing of taxa of interest. We discuss limitations and potential extensions of a model supporting innovation in phylogenomics today, the multispecies coalescent model (MSC). Macroevolutionary models that use phylogenies, such as character mapping, often ignore the heterogeneity on which building phylogenies increasingly rely and suggest that assimilating such heterogeneity is an important goal moving forward. Finally, we argue that an integrative cyberinfrastructure linking all steps of the process of building the ToL, from specimen acquisition in the field to publication and tracking of phylogenomic data, as well as a culture that values contributors at each step, are essential for progress.

Enhancing Statistical Multiple Sequence Alignment and Tree Inference Using Structural Information

For highly divergent sequences, there is often insufficient information to reliably construct alignments and phylogenetic trees. Since protein structure may be strongly conserved despite large divergences in sequence, structural information can be used to help identify homology in such cases.While there exist well-studied models of sequence evolution, structurally informed alignment methods have typically made use of geometric measures of deviation that do not take into account the underlying mutational processes. In order to integrate structural information into sequence-based evolutionary models, we recently developed a stochastic model of structural evolution on a phylogenetic tree and implemented this as the StructAlign plugin for the StatAlign statistical alignment package.In this chapter, we will outline the types of analyses that can be carried out using StructAlign, illustrating how the inclusion of structural information can be used to inform joint estimation of alignments and trees. StructAlign can also be used to infer branch-specific rates of structural evolution, and analysis of an example globin dataset highlights strong variation in the inferred rate across the tree. While structure is more highly conserved within clades, the rate of structural divergence as a function of sequence variation is larger between functionally divergent proteins. Allowing for the rate of structural divergence to vary over the tree results in an improved fit to the empirically observed pairwise RMSD values.

High-Performance Computing in Bayesian Phylogenetics and Phylodynamics Using BEAGLE

In this chapter, we focus on the computational challenges associated with statistical phylogenomics and how use of the broad-platform evolutionary analysis general likelihood evaluator (BEAGLE), a high-performance library for likelihood computation, can help to substantially reduce computation time in phylogenomic and phylodynamic analyses. We discuss computational improvements brought about by the BEAGLE library on a variety of state-of-the-art multicore hardware, and for a range of commonly used evolutionary models. For data sets of varying dimensions, we specifically focus on comparing performance in the Bayesian evolutionary analysis by sampling trees (BEAST) software between multicore central processing units (CPUs) and a wide range of graphics processing cards (GPUs). We put special emphasis on computational benchmarks from the field of phylodynamics, which combines the challenges of phylogenomics with those of modelling trait data associated with the observed sequence data. In conclusion, we show that for increasingly large molecular sequence data sets, GPUs can offer tremendous computational advancements through the use of the BEAGLE library, which is available for software packages for both Bayesian inference and maximum-likelihood frameworks.

Variation Across Mitochondrial Gene Trees Provides Evidence for Systematic Error: How Much Gene Tree Variation Is Biological?

The use of large genomic data sets in phylogenetics has highlighted extensive topological variation across genes. Much of this discordance is assumed to result from biological processes. However, variation among gene trees can also be a consequence of systematic error driven by poor model fit, and the relative importance of biological vs. methodological factors in explaining gene tree variation is a major unresolved question. Using mitochondrial genomes to control for biological causes of gene tree variation, we estimate the extent of gene tree discordance driven by systematic error and employ posterior prediction to highlight the role of model fit in producing this discordance. We find that the amount of discordance among mitochondrial gene trees is similar to the amount of discordance found in other studies that assume only biological causes of variation. This similarity suggests that the role of systematic error in generating gene tree variation is underappreciated and critical evaluation of fit between assumed models and the data used for inference is important for the resolution of unresolved phylogenetic questions.

Microbial sequence typing in the genomic era

Next-generation sequencing (NGS), also known as high-throughput sequencing, is changing the field of microbial genomics research. NGS allows for a more comprehensive analysis of the diversity, structure and composition of microbial genes and genomes compared to the traditional automated Sanger capillary sequencing at a lower cost. NGS strategies have expanded the versatility of standard and widely used typing approaches based on nucleotide variation in several hundred DNA sequences and a few gene fragments (MLST, MLVA, rMLST and cgMLST). NGS can now accommodate variation in thousands or millions of sequences from selected amplicons to full genomes (WGS, NGMLST and HiMLST). To extract signals from high-dimensional NGS data and make valid statistical inferences, novel analytic and statistical techniques are needed. In this review, we describe standard and new approaches for microbial sequence typing at gene and genome levels and guidelines for subsequent analysis, including methods and computational frameworks. We also present several applications of these approaches to some disciplines, namely genotyping, phylogenetics and molecular epidemiology.

Noise and biases in genomic data may underlie radically different hypotheses for the position of Iguania within Squamata

Squamate reptiles are a major component of vertebrate biodiversity whose crown-clade traces its origin to a narrow window of time in the Mesozoic during which the main subclades diverged in rapid succession. Deciphering phylogenetic relationships among these lineages has proven challenging given the conflicting signals provided by genomic and phenomic data. Most notably, the placement of Iguania has routinely differed between data sources, with morphological evidence supporting a sister relationship to the remaining squamates (Scleroglossa hypothesis) and molecular data favoring a highly nested position alongside snakes and anguimorphs (Toxicofera hypothesis). We provide novel insights by generating an expanded morphological dataset and exploring the presence of phylogenetic signal, noise, and biases in molecular data. Our analyses confirm the presence of strong conflicting signals for the position of Iguania between morphological and molecular datasets. However, we also find that molecular data behave highly erratically when inferring the deepest branches of the squamate tree, a consequence of limited phylogenetic signal to resolve this ancient radiation with confidence. This, in turn, seems to result from a rate of evolution that is too high for historical signals to survive to the present. Finally, we detect significant systematic biases, with iguanians and snakes sharing faster rates of molecular evolution and a similarly biased nucleotide composition. A combination of scant phylogenetic signal, high levels of noise, and the presence of systematic biases could result in the misplacement of Iguania. We regard this explanation to be at least as plausible as the complex scenario of convergence and reversals required for morphological data to be misleading. We further evaluate and discuss the utility of morphological data to resolve ancient radiations, as well as its impact in combined-evidence phylogenomic analyses, with results relevant for the assessment of evidence and conflict across the Tree of Life.

High genomic diversity of multi-drug resistant wastewater Escherichia coli

Wastewater treatment plants play an important role in the emergence of antibiotic resistance. They provide a hot spot for exchange of resistance within and between species. Here, we analyse and quantify the genomic diversity of the indicator Escherichia coli in a German wastewater treatment plant and we relate it to isolates’ antibiotic resistance. Our results show a surprisingly large pan-genome, which mirrors how rich an environment a treatment plant is. We link the genomic analysis to a phenotypic resistance screen and pinpoint genomic hot spots, which correlate with a resistance phenotype. Besides well-known resistance genes, this forward genomics approach generates many novel genes, which correlated with resistance and which are partly completely unknown. A surprising overall finding of our analyses is that we do not see any difference in resistance and pan genome size between isolates taken from the inflow of the treatment plant and from the outflow. This means that while treatment plants reduce the amount of bacteria released into the environment, they do not reduce the potential for antibiotic resistance of these bacteria.

Improving phylogenetic inference of core Chlorophyta using chloroplast sequences with strong phylogenetic signals and heterogeneous models

Phylogenetic relationships within the green algal phylum Chlorophyta have proven difficult to resolve. The core Chlorophyta include Chlorophyceae, Ulvophyceae, Trebouxiophyceae, Pedinophyceae and Chlorodendrophyceae, but the relationships among these classes remain unresolved and the monophyly of Ulvophyceae and Trebouxiophyceae are highly controversial. We analyzed a dataset of 101 green algal species and 73 protein-coding genes sampled from complete and partial chloroplast genomes, including six newly sequenced ulvophyte genomes (Blidingia minima NIES-1837, Ulothrix zonata, Halochlorococcum sp. NIES-1838, Scotinosphaera sp. NIES-154, Caulerpa brownii and Cephaleuros sp. HZ-2017). We applied the Tree Certainty (TC) score to quantify the level of incongruence between phylogenetic trees in chloroplast genomic datasets, and show that the conflicting phylogenetic trees of core Chlorophyta stem from the most GC-heterogeneous sites. With removing the most GC-heterogeneous sites, our chloroplast phylogenomic analyses using heterogeneous models consistently support monophyly of the Chlorophyceae and of the Trebouxiophyceae, but the Ulvophyceae was resolved as polyphyletic. Our analytical framework provides an efficient approach to reconstruct the optimal phylogenetic relationships by minimizing conflicting signals.

GET_PHYLOMARKERS, a Software Package to Select Optimal Orthologous Clusters for Phylogenomics and Inferring Pan-Genome Phylogenies, Used for a Critical Geno-Taxonomic Revision of the Genus Stenotrophomonas

The massive accumulation of genome-sequences in public databases promoted the proliferation of genome-level phylogenetic analyses in many areas of biological research. However, due to diverse evolutionary and genetic processes, many loci have undesirable properties for phylogenetic reconstruction. These, if undetected, can result in erroneous or biased estimates, particularly when estimating species trees from concatenated datasets. To deal with these problems, we developed GET_PHYLOMARKERS, a pipeline designed to identify high-quality markers to estimate robust genome phylogenies from the orthologous clusters, or the pan-genome matrix (PGM), computed by GET_HOMOLOGUES. In the first context, a set of sequential filters are applied to exclude recombinant alignments and those producing anomalous or poorly resolved trees. Multiple sequence alignments and maximum likelihood (ML) phylogenies are computed in parallel on multi-core computers. A ML species tree is estimated from the concatenated set of top-ranking alignments at the DNA or protein levels, using either FastTree or IQ-TREE (IQT). The latter is used by default due to its superior performance revealed in an extensive benchmark analysis. In addition, parsimony and ML phylogenies can be estimated from the PGM. We demonstrate the practical utility of the software by analyzing 170 Stenotrophomonas genome sequences available in RefSeq and 10 new complete genomes of Mexican environmental S. maltophilia complex (Smc) isolates reported herein. A combination of core-genome and PGM analyses was used to revise the molecular systematics of the genus. An unsupervised learning approach that uses a goodness of clustering statistic identified 20 groups within the Smc at a core-genome average nucleotide identity (cgANIb) of 95.9% that are perfectly consistent with strongly supported clades on the core- and pan-genome trees. In addition, we identified 16 misclassified RefSeq genome sequences, 14 of them labeled as S. maltophilia, demonstrating the broad utility of the software for phylogenomics and geno-taxonomic studies. The code, a detailed manual and tutorials are freely available for Linux/UNIX servers under the GNU GPLv3 license at https://github.com/vinuesa/get_phylomarkers. A docker image bundling GET_PHYLOMARKERS with GET_HOMOLOGUES is available at https://hub.docker.com/r/csicunam/get_homologues/, which can be easily run on any platform.

HiMAP: Robust phylogenomics from highly multiplexed amplicon sequencing

High-throughput sequencing has fundamentally changed how molecular phylogenetic data sets are assembled, and phylogenomic data sets commonly contain 50- to 100-fold more loci than those generated using traditional Sanger sequencing-based approaches. Here, we demonstrate a new approach for building phylogenomic data sets using single-tube, highly multiplexed amplicon sequencing, which we name HiMAP (highly multiplexed amplicon-based phylogenomics) and present bioinformatic pipelines for locus selection based on genomic and transcriptomic data resources and postsequencing consensus calling and alignment. This method is inexpensive and amenable to sequencing a large number (hundreds) of taxa simultaneously and requires minimal hands-on time at the bench (<1/2 day), and data analysis can be accomplished without the need for read mapping or assembly. We demonstrate this approach by sequencing 878 amplicons in single reactions for 82 species of tephritid fruit flies across seven genera (384 individuals), including some of the most economically important agricultural insect pests. The resulting filtered data set (>150,000-bp concatenated alignment, ~20% missing character sites across all individuals and amplicons) contained >40,000 phylogenetically informative characters, and although some discordance was observed between analyses, it provided unparalleled resolution of many phylogenetic relationships in this group. Most notably, we found high support for the generic status of Zeugodacus and the sister relationship between Dacus and Zeugodacus. We discuss HiMAP, with regard to its molecular and bioinformatic strengths, and the insight the resulting data set provides into relationships of this diverse insect group.

HiMAP: Robust phylogenomics from highly multiplexed amplicon sequencing

High-throughput sequencing has fundamentally changed how molecular phylogenetic data sets are assembled, and phylogenomic data sets commonly contain 50- to 100-fold more loci than those generated using traditional Sanger sequencing-based approaches. Here, we demonstrate a new approach for building phylogenomic data sets using single-tube, highly multiplexed amplicon sequencing, which we name HiMAP (highly multiplexed amplicon-based phylogenomics) and present bioinformatic pipelines for locus selection based on genomic and transcriptomic data resources and postsequencing consensus calling and alignment. This method is inexpensive and amenable to sequencing a large number (hundreds) of taxa simultaneously and requires minimal hands-on time at the bench (<1/2 day), and data analysis can be accomplished without the need for read mapping or assembly. We demonstrate this approach by sequencing 878 amplicons in single reactions for 82 species of tephritid fruit flies across seven genera (384 individuals), including some of the most economically important agricultural insect pests. The resulting filtered data set (>150,000-bp concatenated alignment, ~20% missing character sites across all individuals and amplicons) contained >40,000 phylogenetically informative characters, and although some discordance was observed between analyses, it provided unparalleled resolution of many phylogenetic relationships in this group. Most notably, we found high support for the generic status of Zeugodacus and the sister relationship between Dacus and Zeugodacus. We discuss HiMAP, with regard to its molecular and bioinformatic strengths, and the insight the resulting data set provides into relationships of this diverse insect group.

Renewing Felsenstein's phylogenetic bootstrap in the era of big data

Felsenstein's application of the bootstrap method to evolutionary trees is one of the most cited scientific papers of all time. The bootstrap method, which is based on resampling and replications, is used extensively to assess the robustness of phylogenetic inferences. However, increasing numbers of sequences are now available for a wide variety of species, and phylogenies based on hundreds or thousands of taxa are becoming routine. With phylogenies of this size Felsenstein's bootstrap tends to yield very low supports, especially on deep branches. Here we propose a new version of the phylogenetic bootstrap in which the presence of inferred branches in replications is measured using a gradual 'transfer' distance rather than the binary presence or absence index used in Felsenstein's original version. The resulting supports are higher and do not induce falsely supported branches. The application of our method to large mammal, HIV and simulated datasets reveals their phylogenetic signals, whereas Felsenstein's bootstrap fails to do so.

Impact of Model Violations on the Inference of Species Boundaries Under the Multispecies Coalescent

The use of genetic data for identifying species-level lineages across the tree of life has received increasing attention in the field of systematics over the past decade. The multispecies coalescent model provides a framework for understanding the process of lineage divergence and has become widely adopted for delimiting species. However, because these studies lack an explicit assessment of model fit, in many cases, the accuracy of the inferred species boundaries are unknown. This is concerning given the large amount of empirical data and theory that highlight the complexity of the speciation process. Here, we seek to fill this gap by using simulation to characterize the sensitivity of inference under the multispecies coalescent (MSC) to several violations of model assumptions thought to be common in empirical data. We also assess the fit of the MSC model to empirical data in the context of species delimitation. Our results show substantial variation in model fit across data sets. Posterior predictive tests find the poorest model performance in data sets that were hypothesized to be impacted by model violations. We also show that while the inferences assuming the MSC are robust to minor model violations, such inferences can be biased under some biologically plausible scenarios. Taken together, these results suggest that researchers can identify individual data sets in which species delimitation under the MSC is likely to be problematic, thereby highlighting the cases where additional lines of evidence to identify species boundaries are particularly important to collect. Our study supports a growing body of work highlighting the importance of model checking in phylogenetics, and the usefulness of tailoring tests of model fit to assess the reliability of particular inferences. [Populations structure, gene flow, demographic changes, posterior prediction, simulation, genetics.].