Distinguishing coral species is not only crucial for physiological, ecological, and evolutionary studies but also to enable effective management of threatened reef ecosystems. However, traditional hypotheses that delineate coral species based on morphological traits from the coral skeleton are frequently at odds with tree-based molecular approaches. Additionally, a dearth of species-level molecular markers has made species delimitation particularly challenging in species-rich coral genera, leading to the widespread assumption that interspecific hybridization might be responsible for this apparent conundrum. Here, we used three lines of evidence-morphology, breeding trials, and molecular approaches-to identify species boundaries in a group of ecologically important tabular Acropora corals. In contrast to previous studies, our morphological analysis yielded groups that were congruent with experimental crosses as well as with coalescent-based and allele sharing-based multilocus approaches to species delimitation. Our results suggest that species of the genus Acropora are reproductively isolated and independently evolving units that can be distinguished morphologically. These findings not only pave the way for a taxonomic revision of coral species but also outline an approach that can provide a solid basis to address species delimitation and provide conservation support to a wide variety of keystone organisms. [Acropora; coral reefs; hybridization; reproductive isolation; taxonomy.].

Phylogenetic trees from real-world data often include short edges with very few substitutions per site, which can lead to partially resolved trees and poor accuracy. Theory indicates that the number of sites needed to accurately reconstruct a fully resolved tree grows at a rate proportional to the inverse square of the length of the shortest edge. However, when inferred trees are partially resolved due to short edges, "accuracy" should be defined as the rate of discovering false splits (clades on a rooted tree) relative to the actual number found. Thus, accuracy can be high even if short edges are common. Specifically, in a "near-perfect" parameter space in which trees are large, the tree length $\xi$ (the sum of all edge lengths) is small, and rate variation is minimal, the expected false positive rate is less than $\xi/3$; the exact value depends on tree shape and sequence length. This expected false positive rate is far below the false negative rate for small $\xi$ and often well below 5% even when some assumptions are relaxed. We show this result analytically for maximum parsimony and explore its extension to maximum likelihood using theory and simulations. For hypothesis testing, we show that measures of split "support" that rely on bootstrap resampling consistently imply weaker support than that implied by the false positive rates in near-perfect trees. The near-perfect parameter space closely fits several empirical studies of human virus diversification during outbreaks and epidemics, including Ebolavirus, Zika virus, and SARS-CoV-2, reflecting low substitution rates relative to high transmission/sampling rates in these viruses.[Ebolavirus; epidemic; HIV; homoplasy; mumps virus; perfect phylogeny; SARS-CoV-2; virus; West Nile virus; Yule-Harding model; Zika virus.].

The species tree paradigm that dominates current molecular systematic practice infers species trees from collections of sequences under assumptions of the multispecies coalescent (MSC), that is, that there is free recombination between the sequences and no (or very low) recombination within them. These coalescent genes (c-genes) are thus defined in an historical rather than molecular sense and can in theory be as large as an entire genome or as small as a single nucleotide. A debate about how to define c-genes centers on the contention that nuclear gene sequences used in many coalescent analyses undergo too much recombination, such that their introns comprise multiple c-genes, violating a key assumption of the MSC. Recently a similar argument has been made for the genes of plastid (e.g., chloroplast) and mitochondrial genomes, which for the last 30 or more years have been considered to represent a single c-gene for the purposes of phylogeny reconstruction because they are nonrecombining in an historical sense. Consequently, it has been suggested that these genomes should be analyzed using coalescent methods that treat their genes-over 70 protein-coding genes in the case of most plastid genomes (plastomes)-as independent estimates of species phylogeny, in contrast to the usual practice of concatenation, which is appropriate for generating gene trees. However, although recombination certainly occurs in the plastome, as has been recognized since the 1970's, it is unlikely to be phylogenetically relevant. This is because such historically effective recombination can only occur when plastomes with incongruent histories are brought together in the same plastid. However, plastids sort rapidly into different cell lineages and rarely fuse. Thus, because of plastid biology, the plastome is a more canonical c-gene than is the average multi-intron mammalian nuclear gene. The plastome should thus continue to be treated as a single estimate of the underlying species phylogeny, as should the mitochondrial genome. The implications of this long-held insight of molecular systematics for studies in the phylogenomic era are explored. [c-gene; coalescent gene; concatalescence; organelle genome; plastome; recombination; species tree.].

Target enrichment (such as Hyb-Seq) is a well-established high throughput sequencing method that has been increasingly used for phylogenomic studies. Unfortunately, current widely used pipelines for analysis of target enrichment data do not have a vigorous procedure to remove paralogs in target enrichment data. In this study, we develop a pipeline we call Putative Paralogs Detection (PPD) to better address putative paralogs from enrichment data. The new pipeline is an add-on to the existing HybPiper pipeline, and the entire pipeline applies criteria in both sequence similarity and heterozygous sites at each locus in the identification of paralogs. Users may adjust the thresholds of sequence identity and heterozygous sites to identify and remove paralogs according to the level of phylogenetic divergence of their group of interest. The new pipeline also removes highly polymorphic sites attributed to errors in sequence assembly and gappy regions in the alignment. We demonstrated the value of the new pipeline using empirical data generated from Hyb-Seq and the Angiosperms353 kit for two woody genera Castanea (Fagaceae, Fagales) and Hamamelis (Hamamelidaceae, Saxifragales). Comparisons of data sets showed that the PPD identified many more putative paralogs than the popular method HybPiper. Comparisons of tree topologies and divergence times showed evident differences between data from HybPiper and data from our new PPD pipeline. We further evaluated the accuracy and error rates of PPD by BLAST mapping of putative paralogous and orthologous sequences to a reference genome sequence of Castanea mollissima. Compared to HybPiper alone, PPD identified substantially more paralogous gene sequences that mapped to multiple regions of the reference genome (31 genes for PPD compared with 4 genes for HybPiper alone). In conjunction with HybPiper, paralogous genes identified by both pipelines can be removed resulting in the construction of more robust orthologous gene data sets for phylogenomic and divergence time analyses. Our study demonstrates the value of Hyb-Seq with data derived from the Angiosperms353 probe set for elucidating species relationships within a genus, and argues for the importance of additional steps to filter paralogous genes and poorly aligned regions (e.g., as occur through assembly errors), such as our new PPD pipeline described in this study. [Angiosperms353; Castanea; divergence time; Hamamelis; Hyb-Seq, paralogs, phylogenomics.].

Whole-genome comparisons based on average nucleotide identities (ANI) and the genome-to-genome distance calculator have risen to prominence in rapidly classifying prokaryotic taxa using whole-genome sequences. Some implementations have even been proposed as a new standard in species classification and have become a common technique for papers describing newly sequenced genomes. However, attempts to apply whole-genome divergence data to the delineation of higher taxonomic units and to phylogenetic inference have had difficulty matching those produced by more complex phylogenetic methods. We present a novel method for generating statistically supported phylogenies of archaeal and bacterial groups using a combined ANI and alignment fraction-based metric. For the test cases to which we applied the developed approach, we obtained results comparable with other methodologies up to at least the family level. The developed method uses nonparametric bootstrapping to gauge support for inferred groups. This method offers the opportunity to make use of whole-genome comparison data, that is already being generated, to quickly produce phylogenies including support for inferred groups. Additionally, the developed ANI methodology can assist the classification of higher taxonomic groups.[Average nucleotide identity (ANI); genome evolution; prokaryotic species delineation; taxonomy.].

The tree of life is the fundamental biological roadmap for navigating the evolution and properties of life on Earth, and yet remains largely unknown. Even angiosperms (flowering plants) are fraught with data gaps, despite their critical role in sustaining terrestrial life. Today, high-throughput sequencing promises to significantly deepen our understanding of evolutionary relationships. Here, we describe a comprehensive phylogenomic platform for exploring the angiosperm tree of life, comprising a set of open tools and data based on the 353 nuclear genes targeted by the universal Angiosperms353 sequence capture probes. The primary goals of this article are to (i) document our methods, (ii) describe our first data release, and (iii) present a novel open data portal, the Kew Tree of Life Explorer (https://treeoflife.kew.org). We aim to generate novel target sequence capture data for all genera of flowering plants, exploiting natural history collections such as herbarium specimens, and augment it with mined public data. Our first data release, described here, is the most extensive nuclear phylogenomic data set for angiosperms to date, comprising 3099 samples validated by DNA barcode and phylogenetic tests, representing all 64 orders, 404 families (96$\%$) and 2333 genera (17$\%$). A "first pass" angiosperm tree of life was inferred from the data, which totaled 824,878 sequences, 489,086,049 base pairs, and 532,260 alignment columns, for interactive presentation in the Kew Tree of Life Explorer. This species tree was generated using methods that were rigorous, yet tractable at our scale of operation. Despite limitations pertaining to taxon and gene sampling, gene recovery, models of sequence evolution and paralogy, the tree strongly supports existing taxonomy, while challenging numerous hypothesized relationships among orders and placing many genera for the first time. The validated data set, species tree and all intermediates are openly accessible via the Kew Tree of Life Explorer and will be updated as further data become available. This major milestone toward a complete tree of life for all flowering plant species opens doors to a highly integrated future for angiosperm phylogenomics through the systematic sequencing of standardized nuclear markers. Our approach has the potential to serve as a much-needed bridge between the growing movement to sequence the genomes of all life on Earth and the vast phylogenomic potential of the world's natural history collections. [Angiosperms; Angiosperms353; genomics; herbariomics; museomics; nuclear phylogenomics; open access; target sequence capture; tree of life.].

Understanding the factors that cause heterogeneity among gene trees can increase the accuracy of species trees. Discordant signals across the genome are commonly produced by incomplete lineage sorting (ILS) and introgression, which in turn can result in reticulate evolution. Species tree inference using the multispecies coalescent is designed to deal with ILS and is robust to low levels of introgression, but extensive introgression violates the fundamental assumption that relationships are strictly bifurcating. In this study, we explore the phylogenomics of the iconic Liolaemus subgenus of South American lizards, a group of over 100 species mostly distributed in and around the Andes mountains. Using mitochondrial DNA (mtDNA) and genome-wide restriction site-associated DNA sequencing (RADseq; nDNA hereafter), we inferred a time-calibrated mtDNA gene tree, nDNA species trees, and phylogenetic networks. We found high levels of discordance between mtDNA and nDNA, which we attribute in part to extensive ILS resulting from rapid diversification. These data also reveal extensive and deep introgression, which combined with rapid diversification, explain the high level of phylogenetic discordance. We discuss these findings in the context of Andean orogeny and glacial cycles that fragmented, expanded, and contracted species distributions. Finally, we use the new phylogeny to resolve long-standing taxonomic issues in one of the most studied lizard groups in the New World.[Andes; ddRADSeq; introgression; lizards; mtDNA; reptiles; SNPs.].

Introgression and hybridization are major impediments to genomic-based species delimitation because many implementations of the multispecies coalescent framework assume no gene flow among species. The sunfish genus Lepomis, one of the world's most popular groups of freshwater sport fish, has a complicated taxonomic history. The results of ddRAD phylogenomic analyses do not provide support for the current taxonomy that recognizes two species, Lepomis megalotis and Lepomis peltastes, in the L. megalotis complex. Instead, evidence from phylogenomics and phenotype warrants recognizing six relatively ancient evolutionary lineages in the complex. The introgressed and hybridizing populations in the L. megalotis complex are localized and appear to be the result of secondary contact or rare hybridization events between nonsister species. Segregating admixed populations from our multispecies coalescent analyses identifies six species with moderate to high genealogical divergence, whereas including admixed populations drives all but one lineage below the species threshold of genealogical divergence. Segregation of admixed individuals also helps reveal phenotypic distinctiveness among the six species in morphological traits used by ichthyologists to discover and delimit species over the last two centuries. Our protocols allow for the identification and accommodation of hybridization and introgression in species delimitation. Genomic-based species delimitation validated with multiple lines of evidence provides a path towards the discovery of new biodiversity and resolving long-standing taxonomic problems.[ddRAD; genealogical divergence index; hybridization; integrative species delimitation; phylogeny; secondary contact; systematics; taxonomy.].

Automated species identification and delimitation is challenging, particularly in rare and thus often scarcely sampled species, which do not allow sufficient discrimination of infraspecific versus interspecific variation. Typical problems arising from either low or exaggerated interspecific morphological differentiation are best met by automated methods of machine learning that learn efficient and effective species identification from training samples. However, limited infraspecific sampling remains a key challenge also in machine learning. In this study, we assessed whether a data augmentation approach may help to overcome the problem of scarce training data in automated visual species identification. The stepwise augmentation of data comprised image rotation as well as visual and virtual augmentation. The visual data augmentation applies classic approaches of data augmentation and generation of artificial images using a generative adversarial networks approach. Descriptive feature vectors are derived from bottleneck features of a VGG-16 convolutional neural network that are then stepwise reduced in dimensionality using Global Average Pooling and principal component analysis to prevent overfitting. Finally, data augmentation employs synthetic additional sampling in feature space by an oversampling algorithm in vector space. Applied on four different image data sets, which include scarab beetle genitalia (Pleophylla, Schizonycha) as well as wing patterns of bees (Osmia) and cattleheart butterflies (Parides), our augmentation approach outperformed a deep learning baseline approach by means of resulting identification accuracy with nonaugmented data as well as a traditional 2D morphometric approach (Procrustes analysis of scarab beetle genitalia). [Deep learning; image-based species identification; generative adversarial networks; limited infraspecific sampling; synthetic oversampling.].

Delimiting species in radiations is notoriously difficult because of the small differences between the incipient species, the star-like tree with short branches between species, incomplete lineage sorting, and the possibility of introgression between several of the incipient species. Next-generation sequencing data may help to overcome some of these problems. We evaluated methods for species delimitation based on genome-wide markers in a land snail radiation on Crete. Species delimitation in the Albinaria cretensis group was based exclusively on shell characters until now and resulted in classifications distinguishing 3-9 species. We generated sequences of 4270 loci for 140 specimens of the A. cretensis group from 48 populations by double-digest restriction site-associated DNA sequencing. We evaluated three methods for species discovery. The multispecies coalescent approach implemented in the program Bayesian Phylogenetics and Phylogeography resulted in a drastic overestimating of the number of species, whereas Gaussian clustering resulted in an overlumping. Primary species hypotheses based on the maximum percentage of the genome of the individuals derived from ancestral populations as estimated with the program ADMIXTURE moderately overestimated the number of species, but this was the only approach that provided information about gene flow between groups. Two of the methods for species validation that we applied, BFD* and delimitR, resulted in an acceptance of almost all primary species hypotheses, even such based on arbitrary subdivisions of hypotheses based on ADMIXTURE. In contrast, secondary species hypotheses, resulting from an evaluation of primary species hypotheses based on ADMIXTURE with isolation by distance tests, approached the morphological classification, but also uncovered two cryptic species and indicated that some of the previously delimited units should be combined. Thus, we recommend this combination of approaches that provided more detailed insights in the distinctness of barriers between the taxa of a species complex and the spatial distribution of admixture between them than the other methods. The recognition and delimitation of undersampled species remained a major challenge. [ADMIXTURE; Clausiliidae; delimitR, Gaussian clustering; isolation-by-distance; land snails; multispecies coalescent; species delimitation.].

Taxa are frequently labeled incertae sedis when their placement is debated at ranks above the species level, such as their subgeneric, generic, or subtribal placement. This is a pervasive problem in groups with complex systematics due to difficulties in identifying suitable synapomorphies. In this study, we propose combining DNA barcodes with a multilocus backbone phylogeny in order to assign taxa to genus or other higher-level categories. This sampling strategy generates molecular matrices containing large amounts of missing data that are not distributed randomly: barcodes are sampled for all representatives, and additional markers are sampled only for a small percentage. We investigate the effects of the degree and randomness of missing data on phylogenetic accuracy using simulations for up to 100 markers in 1000-tips trees, as well as a real case: the subtribe Polyommatina (Lepidoptera: Lycaenidae), a large group including numerous species with unresolved taxonomy. Our simulation tests show that when a strategic and representative selection of species for higher-level categories has been made for multigene sequencing (approximately one per simulated genus), the addition of this multigene backbone DNA data for as few as 5-10% of the specimens in the total data set can produce high-quality phylogenies, comparable to those resulting from 100% multigene sampling. In contrast, trees based exclusively on barcodes performed poorly. This approach was applied to a 1365-specimen data set of Polyommatina (including ca. 80% of described species), with nearly 8% of representative species included in the multigene backbone and the remaining 92% included only by mitochondrial COI barcodes, a phylogeny was generated that highlighted potential misplacements, unrecognized major clades, and placement for incertae sedis taxa. We use this information to make systematic rearrangements within Polyommatina, and to describe two new genera. Finally, we propose a systematic workflow to assess higher-level taxonomy in hyperdiverse groups. This research identifies an additional, enhanced value of DNA barcodes for improvements in higher-level systematics using large data sets. [Birabiro; DNA barcoding; incertae sedis; Kipepeo; Lycaenidae; missing data; phylogenomic; phylogeny; Polyommatina; supermatrix; systematics; taxonomy].

Phylogenetic analyses of genomic data provide a powerful means of reconstructing the evolutionary relationships among organisms, yet such analyses are often hindered by conflicting phylogenetic signals among loci. Identifying the signals that are most influential to species-tree estimation can help to inform the choice of data for phylogenomic analysis. We investigated this in an analysis of 30 phylogenomic data sets. For each data set, we examined the association between several branch-length characteristics of gene trees and the distance between these gene trees and the corresponding species trees. We found that the distance of each gene tree to the species tree inferred from the full data set was positively associated with variation in root-to-tip distances and negatively associated with mean branch support. However, no such associations were found for gene-tree length, a measure of the overall substitution rate at each locus. We further explored the usefulness of the best-performing branch-based characteristics for selecting loci for phylogenomic analyses. We found that loci that yield gene trees with high variation in root-to-tip distances have a disproportionately distant signal of tree topology compared with the complete data sets. These results suggest that rate variation across lineages should be taken into consideration when exploring and even selecting loci for phylogenomic analysis.[Branch support; data filtering; nucleotide substitution model; phylogenomics; substitution rate; summary coalescent methods.].

The geographic distribution of biodiversity is central to understanding evolutionary biology. Paleogeographic and paleoclimatic histories often help to explain how biogeographic patterns unfold through time. However, such patterns are also influenced by a variety of other factors, such as lineage diversification, that may affect the probability of certain types of biogeographic events. The complex and well-known geologic and climatic history of Afro-Arabia, together with the extensive research on reptile systematics in the region, makes Afro-Arabian squamate communities an ideal system to investigate biogeographic patterns and their drivers. Here, we reconstruct the phylogenetic relationships and the ancestral geographic distributions of several Afro-Arabian reptile clades (totaling 430 species) to estimate the number of dispersal, vicariance and range contraction events. We then compare the observed biogeographic history to a distribution of simulated biogeographic events based on the empirical phylogeny and the best-fit model. This allows us to identify periods in the past where the observed biogeographic history was likely shaped by forces beyond the ones included in the model. We find an increase in vicariance following the Oligocene, most likely caused by the fragmentation of the Afro-Arabian plate. In contrast, we did not find differences between observed and expected dispersal and range contraction levels. This is consistent with diversification enhanced by environmental processes and with the establishment of a dispersal corridor connecting Africa, Arabia and Eurasia since the middle Miocene. Finally, here we show that our novel approach is useful to pinpoint events in the evolutionary history of lineages that might reflect external forces not predicted by the underlying biogeographic model. [Dispersal; diversification; model adequacy; paleogeography; reptiles; simulations; vicariance.].

Diversification rates vary across species as a response to various factors, including environmental conditions and species-specific features. Phylogenetic models that allow accounting for and quantifying this heterogeneity in diversification rates have proven particularly useful for understanding clades diversification. Recently, we introduced the cladogenetic diversification rate shift model, which allows inferring multiple rate changes of small magnitude across lineages. Here, we present a new inference technique for this model that considerably reduces computation time through the use of data augmentation and provide an implementation of this method in Julia. In addition to drastically reducing computation time, this new inference approach provides a posterior distribution of the augmented data, that is the tree with extinct and unsampled lineages as well as associated diversification rates. In particular, this allows extracting the distribution through time of both the mean rate and the number of lineages. We assess the statistical performances of our approach using simulations and illustrate its application on the entire bird radiation.[Birth-death model; data augmentation; diversification; macroevolution.].

Many recent phylogenetic methods have focused on accurately inferring species trees when there is gene tree discordance due to incomplete lineage sorting (ILS). For almost all of these methods, and for phylogenetic methods in general, the data for each locus are assumed to consist of orthologous, single-copy sequences. Loci that are present in more than a single copy in any of the studied genomes are excluded from the data. These steps greatly reduce the number of loci available for analysis. The question we seek to answer in this study is: what happens if one runs such species tree inference methods on data where paralogy is present, in addition to or without ILS being present? Through simulation studies and analyses of two large biological data sets, we show that running such methods on data with paralogs can still provide accurate results. We use multiple different methods, some of which are based directly on the multispecies coalescent model, and some of which have been proven to be statistically consistent under it. We also treat the paralogous loci in multiple ways: from explicitly denoting them as paralogs, to randomly selecting one copy per species. In all cases, the inferred species trees are as accurate as equivalent analyses using single-copy orthologs. Our results have significant implications for the use of ILS-aware phylogenomic analyses, demonstrating that they do not have to be restricted to single-copy loci. This will greatly increase the amount of data that can be used for phylogenetic inference.[Gene duplication and loss; incomplete lineage sorting; multispecies coalescent; orthology; paralogy.].

Genome sequencing projects routinely generate haploid consensus sequences from diploid genomes, which are effectively chimeric sequences with the phase at heterozygous sites resolved at random. The impact of phasing errors on phylogenomic analyses under the multispecies coalescent (MSC) model is largely unknown. Here, we conduct a computer simulation to evaluate the performance of four phase-resolution strategies (the true phase resolution, the diploid analytical integration algorithm which averages over all phase resolutions, computational phase resolution using the program PHASE, and random resolution) on estimation of the species tree and evolutionary parameters in analysis of multilocus genomic data under the MSC model. We found that species tree estimation is robust to phasing errors when species divergences were much older than average coalescent times but may be affected by phasing errors when the species tree is shallow. Estimation of parameters under the MSC model with and without introgression is affected by phasing errors. In particular, random phase resolution causes serious overestimation of population sizes for modern species and biased estimation of cross-species introgression probability. In general, the impact of phasing errors is greater when the mutation rate is higher, the data include more samples per species, and the species tree is shallower with recent divergences. Use of phased sequences inferred by the PHASE program produced small biases in parameter estimates. We analyze two real data sets, one of East Asian brown frogs and another of Rocky Mountains chipmunks, to demonstrate that heterozygote phase-resolution strategies have similar impacts on practical data analyses. We suggest that genome sequencing projects should produce unphased diploid genotype sequences if fully phased data are too challenging to generate, and avoid haploid consensus sequences, which have heterozygous sites phased at random. In case the analytical integration algorithm is computationally unfeasible, computational phasing prior to population genomic analyses is an acceptable alternative. [BPP; introgression; multispecies coalescent; phase; species tree.].