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Understanding the evolutionary history of species is at the core of molecular evolution and is done using several inference methods. The critical issue is to quantify the uncertainty of the inference. The posterior probabilities in Bayesian phylogenetic inference and the bootstrap values in frequentist approaches measure the variability of the estimates due to the sampling of sites from genes and the sampling of genes from genomes. However, they do not measure the uncertainty due to taxon sampling. Taxa that experienced molecular homoplasy, recent selection, a spur of evolution, and so forth may disrupt the inference and cause incongruences in the estimated phylogeny. We define a taxon influence index to assess the influence of each taxon on the phylogeny. We found that although most taxa have a weak influence on the phylogeny, a small fraction of influential taxa strongly alter it even in clades only loosely related to them. We conclude that highly influential taxa should be given special attention and sampling them more thoroughly can lead to more dependable phylogenies.

Proper biological interpretation of a phylogeny can sometimes hinge on the placement of key taxa—or fail when such key taxa are not sampled. In this light, we here present the first attempt to investigate (though not conclusively resolve) animal relationships using genome-scale data from all phyla. Results from the site-heterogeneous CAT + GTR model recapitulate many established major clades, and strongly confirm some recent discoveries, such as a monophyletic Lophophorata, and a sister group relationship between Gnathifera and Chaetognatha, raising continued questions on the nature of the spiralian ancestor. We also explore matrix construction with an eye towards testing specific relationships; this approach uniquely recovers support for Panarthropoda, and shows that Lophotrochozoa (a subclade of Spiralia) can be constructed in strongly conflicting ways using different taxon- and/or orthologue sets. Dayhoff-6 recoding sacrifices information, but can also reveal surprising outcomes, e.g. full support for a clade of Lophophorata and Entoprocta + Cycliophora, a clade of Placozoa + Cnidaria, and raising support for Ctenophora as sister group to the remaining Metazoa, in a manner dependent on the gene and/or taxon sampling of the matrix in question. Future work should test the hypothesis that the few remaining uncertainties in animal phylogeny might reflect violations of the various stationarity assumptions used in contemporary inference methods.

Whole-genome sequencing projects are increasingly populating the tree of life and characterizing biodiversity1–4. Sparse taxon sampling has previously been proposed to confound phylogenetic inference5, and captures only a fraction of the genomic diversity. Here we report a substantial step towards the dense representation of avian phylogenetic and molecular diversity, by analysing 363 genomes from 92.4% of bird families—including 267 newly sequenced genomes produced for phase II of the Bird 10,000 Genomes (B10K) Project. We use this comparative genome dataset in combination with a pipeline that leverages a reference-free whole-genome alignment to identify orthologous regions in greater numbers than has previously been possible and to recognize genomic novelties in particular bird lineages. The densely sampled alignment provides a single-base-pair map of selection, has more than doubled the fraction of bases that are confdently predicted to be under conservation and reveals extensive patterns of weak selection in predominantly non-coding DNA. Our results demonstrate that increasing the diversity of genomes used in comparative studies can reveal more shared and lineage-specifc variation, and improve the investigation of genomic characteristics. We anticipate that this genomic resource will ofer new perspectives on evolutionary processes in cross-species comparative analyses and assist in eforts to conserve species.

Phylogenomics, the use of large-scale data matrices in phylogenetic analyses, has been viewed as the ultimate solution to the problem of resolving difficult nodes in the tree of life. However, it has become clear that analyses of these large genomic data sets can also result in conflicting estimates of phylogeny. Here, we use the early divergences in Neoaves, the largest clade of extant birds, as a \"model system\" to understand the basis for incongruence among phylogenomic trees. We were motivated by the observation that trees from two recent avian phylogenomic studies exhibit conflicts. Those studies used different strategies: 1) collecting many characters [∼42 mega base pairs (Mbp) of sequence data] from 48 birds, sometimes including only one taxon for each major clade; and 2) collecting fewer characters (∼0.4 Mbp) from 198 birds, selected to subdivide long branches. However, the studies also used different data types: the taxon-poor data matrix comprised 68% non-coding sequences whereas coding exons dominated the taxon-rich data matrix. This difference raises the question of whether the primary reason for incongruence is the number of sites, the number of taxa, or the data type. To test among these alternative hypotheses we assembled a novel, large-scale data matrix comprising 90% non-coding sequences from 235 bird species. Although increased taxon sampling appeared to have a positive impact on phylogenetic analyses the most important variable was data type. Indeed, by analyzing different subsets of the taxa in our data matrix we found that increased taxon sampling actually resulted in increased congruence with the tree from the previous taxon-poor study (which had a majority of non-coding data) instead of the taxon-rich study (which largely used coding data). We suggest that the observed differences in the estimates of topology for these studies reflect data-type effects due to violations of the models used in phylogenetic analyses, some of which may be difficult to detect. If incongruence among trees estimated using phylogenomic methods largely reflects problems with model fit developing more \"biologically-realistic\" models is likely to be critical for efforts to reconstruct the tree of life.

Although macroscopic plants, animals, and fungi are the most familiar eukaryotes, the bulk of eukaryotic diversity is microbial. Elucidating the timing of diversification among the more than 70 lineages is key to understanding the evolution of eukaryotes. Here, we use taxon-rich multigene data combined with diverse fossils and a relaxed molecular clock framework to estimate the timing of the last common ancestor of extant eukaryotes and the divergence of major clades. Overall, these analyses suggest that the last common ancestor lived between 1866 and 1679 Ma, consistent with the earliest microfossils interpreted with confidence as eukaryotic. During this interval, the Earth's surface differed markedly from today; for example, the oceans were incompletely ventilated, with ferruginous and, after about 1800 Ma, sulfidic water masses commonly lying beneath moderately oxygenated surface waters. Our time estimates also indicate that the major clades of eukaryotes diverged before 1000 Ma, with most or all probably diverging before 1200 Ma. Fossils, however, suggest that diversity within major extant clades expanded later, beginning about 800 Ma, when the oceans began their transition to a more modern chemical state. In combination, paleontological and molecular approaches indicate that long stems preceded diversification in the major eukaryotic lineages.

Targeted sequence capture is becoming a widespread tool for generating large phylogenomic data sets to address difficult phylogenetic problems. However, this methodology often generates data sets in which increasing the number of taxa and loci increases amounts of missing data. Thus, a fundamental (but still unresolved) question is whether sampling should be designed to maximize sampling of taxa or genes, or to minimize the inclusion of missing data cells. Here, we explore this question for an ancient, rapid radiation of lizards, the pleurodont iguanians. Pleurodonts include many well-known clades (e.g., anoles, basilisks, iguanas, and spiny lizards) but relationships among families have proven difficult to resolve strongly and consistently using traditional sequencing approaches. We generated up to 4921 ultraconserved elements with sampling strategies including 16, 29, and 44 taxa, from 1179 to approximately 2.4 million characters per matrix and approximately 30% to 60% total missing data. We then compared mean branch support for interfamilial relationships under these 15 different sampling strategies for both concatenated (maximum likelihood) and species tree (NJst) approaches (after showing that mean branch support appears to be related to accuracy). We found that both approaches had the highest support when including loci with up to 50% missing taxa (matrices with ~40-55% missing data overall). Thus, our results show that simply excluding all missing data may be highly problematic as the primary guiding principle for the inclusion or exclusion of taxa and genes. The optimal strategy was somewhat different for each approach, a pattern that has not been shown previously. For concatenated analyses, branch support was maximized when including many taxa (44) but fewer characters (1.1 million). For species-tree analyses, branch support was maximized with minimal taxon sampling (16) but many loci (4789 of 4921). We also show that the choice of these sampling strategies can be critically important for phylogenomic analyses, since some strategies lead to demonstrably incorrect inferences (using the same method) that have strong statistical support. Our preferred estimate provides strong support for most interfamilial relationships in this important but phylogenetically challenging group.

Abstract Reconstruction of the Tree of Life is a central goal in biology. Although numerous novel phyla of bacteria and archaea have recently been discovered, inconsistent phylogenetic relationships are routinely reported, and many inter-phylum and inter-domain evolutionary relationships remain unclear. Here, we benchmark different marker genes often used in constructing multidomain phylogenetic trees of bacteria and archaea and present a set of marker genes that perform best for multidomain trees constructed from concatenated alignments. We use recently-developed Tree Certainty metrics to assess the confidence of our results and to obviate the complications of traditional bootstrap-based metrics. Given the vastly disparate number of genomes available for different phyla of bacteria and archaea, we also assessed the impact of taxon sampling on multidomain tree construction. Our results demonstrate that biases between the representation of different taxonomic groups can dramatically impact the topology of resulting trees. Inspection of our highest-quality tree supports the division of most bacteria into Terrabacteria and Gracilicutes, with Thermatogota and Synergistota branching earlier from these superphyla. This tree also supports the inclusion of the Patescibacteria within the Terrabacteria as a sister group to the Chloroflexota instead of as a basal-branching lineage. For the Archaea, our tree supports three monophyletic lineages (DPANN, Euryarchaeota, and TACK/Asgard), although we note the basal placement of the DPANN may still represent an artifact caused by biased sequence composition. Our findings provide a robust and standardized framework for multidomain phylogenetic reconstruction that can be used to evaluate inter-phylum relationships and assess uncertainty in conflicting topologies of the Tree of Life.

Progress in sequencing technology allows researchers to assemble ever-larger supermatrices for phylogenomic inference. However, current phylogenomic studies often rest on patchy data sets, with some having 80% missing (or ambiguous) data or more. Though early simulations had suggested that missing data per se do not harm phylogenetic inference when using sufficiently large data sets, Lemmon et al. (Lemmon AR, Brown JM, Stanger-Hall K, Lemmon EM. 2009. The effect of ambiguous data on phylogenetic estimates obtained by maximum likelihood and Bayesian inference. Syst Biol. 58:130–145.) have recently cast doubt on this consensus in a study based on the introduction of parsimony-uninformative incomplete characters. In this work, we empirically reassess the issue of missing data in phylogenomics while exploring possible interactions with the model of sequence evolution. First, we note that parsimony-uninformative incomplete characters are actually informative in a probabilistic framework. A reanalysis of Lemmon’s data set with this in mind gives a very different interpretation of their results and shows that some of their conclusions may be unfounded. Second, we investigate the effect of the progressive introduction of missing data in a complete supermatrix (126 genes × 39 species) capable of resolving animal relationships. These analyses demonstrate that missing data perturb phylogenetic inference slightly beyond the expected decrease in resolving power. In particular, they exacerbate systematic errors by reducing the number of species effectively available for the detection of multiple substitutions. Consequently, large sparse supermatrices are more sensitive to phylogenetic artifacts than smaller but less incomplete data sets, which argue for experimental designs aimed at collecting a modest number (∼50) of highly covered genes. Our results further confirm that including incomplete yet short-branch taxa (i.e., slowly evolving species or close outgroups) can help to eschew artifacts, as predicted by simulations. Finally, it appears that selecting an adequate model of sequence evolution (e.g., the site-heterogeneous CAT model instead of the site-homogeneous WAG model) is more beneficial to phylogenetic accuracy than reducing the level of missing data.

Phylogenetic relationships among the four major lineages of land plants (liverworts, mosses, hornworts, and vascular plants) remain vigorously contested; their resolution is essential to our understanding of the origin and early evolution of land plants. We analyzed three different complementary data sets: a multigene supermatrix, a genomic structural character matrix, and a chloroplast genome sequence matrix, using maximum likelihood, maximum parsimony, and compatibility methods. Analyses of all three data sets strongly supported liverworts as the sister to all other land plants, and analyses of the multigene and chloroplast genome matrices provided moderate to strong support for hornworts as the sister to vascular plants. These results highlight the important roles of liverworts and hornworts in two major events of plant evolution: the water-to-land transition and the change from a haploid gametophyte generation-dominant life cycle in bryophytes to a diploid sporophyte generation-dominant life cycle in vascular plants. This study also demonstrates the importance of using a multifaceted approach to resolve difficult nodes in the tree of life. In particular, it is shown here that densely sampled taxon trees built with multiple genes provide an indispensable test of taxon-sparse trees inferred from genome sequences.

An accurate reconstruction of the eukaryotic tree of life is essential to identify the innovations underlying the diversity of microbial and macroscopic (e.g., plants and animals) eukaryotes. Previous work has divided eukaryotic diversity into a small number of high-level “supergroups,” many of which receive strong support in phylogenomic analyses. However, the abundance of data in phylogenomic analyses can lead to highly supported but incorrect relationships due to systematic phylogenetic error. Furthermore, the paucity of major eukaryotic lineages (19 or fewer) included in these genomic studies may exaggerate systematic error and reduce power to evaluate hypotheses. Here, we use a taxon-rich strategy to assess eukaryotic relationships. We show that analyses emphasizing broad taxonomic sampling (up to 451 taxa representing 72 major lineages) combined with a moderate number of genes yield a well-resolved eukaryotic tree of life. The consistency across analyses with varying numbers of taxa (88–451) and levels of missing data (17–69%) supports the accuracy of the resulting topologies. The resulting stable topology emerges without the removal of rapidly evolving genes or taxa, a practice common to phylogenomic analyses. Several major groups are stable and strongly supported in these analyses (e.g., SAR, Rhizaria, Excavata), whereas the proposed supergroup “Chromalveolata” is rejected. Furthermore, extensive instability among photosynthetic lineages suggests the presence of systematic biases including endosymbiotic gene transfer from symbiont (nucleus or plastid) to host. Our analyses demonstrate that stable topologies of ancient evolutionary relationships can be achieved with broad taxonomic sampling and a moderate number of genes. Finally, taxon-rich analyses such as presented here provide a method for testing the accuracy of relationships that receive high bootstrap support (BS) in phylogenomic analyses and enable placement of the multitude of lineages that lack genome scale data.