Large Phylogenies Research Articles

SuperCRUNCH: A bioinformatics toolkit for creating and manipulating supermatrices and other large phylogenetic datasets

Abstract Phylogenies with extensive taxon sampling have become indispensable for many types of ecological and evolutionary studies. Many large‐scale trees are based on a ‘supermatrix’ approach, which involves amalgamating thousands of published sequences for a group. Constructing up‐to‐date supermatrices can be challenging, especially as new sequences may become available almost constantly. Additionally, genomic datasets (composed of thousands of loci) are becoming common in phylogenetics and phylogeography, and present novel challenges for constructing such datasets. Here we present SuperCRUNCH, a Python toolkit for assembling large phylogenetic datasets. It can be applied to GenBank sequences, unpublished sequences or combinations of GenBank and unpublished data. SuperCRUNCH constructs local databases and uses them to conduct rapid searches for user‐specified sets of taxa and loci. Sequences are parsed into putative loci and passed through rigorous filtering steps. A post‐filtering step allows for selection of one sequence per taxon (i.e. species‐level supermatrix) or retention of all sequences per taxon (i.e. population‐level dataset). Importantly, SuperCRUNCH can generate ‘vouchered’ population‐level datasets, in which voucher information is used to generate multi‐locus phylogeographic datasets. SuperCRUNCH offers many options for taxonomy resolution, similarity filtering, sequence selection, alignment and file manipulation. We demonstrate the range of features available in SuperCRUNCH by generating a variety of phylogenetic datasets. Output datasets include traditional species‐level supermatrices, large‐scale phylogenomic matrices and phylogeographic datasets. Finally, we briefly compare the ability of SuperCRUNCH to construct species‐level supermatrices relative to alternative approaches. SuperCRUNCH generated a large‐scale supermatrix (1,400 taxa and 66 loci) from 16 GB of GenBank data in ~1.5 hr, and generated population‐level datasets (<350 samples, <10 loci) in <1 min. It outperformed alternative methods for supermatrix construction in terms of taxa, loci and sequences recovered. SuperCRUNCH is a modular bioinformatics toolkit that can be used to assemble datasets for any taxonomic group and scale (kingdoms to individuals). It allows rapid construction of supermatrices, greatly simplifying the process of updating large phylogenies with new data. It is also designed to produce population‐level datasets. SuperCRUNCH streamlines the major tasks required to process phylogenetic data, including filtering, alignment, trimming and formatting. SuperCRUNCH is open‐source, documented and available at https://github.com/dportik/SuperCRUNCH.

Convergent adaptation of the genomes of woody plants at the land-sea interface.

Sequencing multiple species that share the same ecological niche may be a new frontier for genomic studies. While such studies should shed light on molecular convergence, genomic-level analyses have been unsuccessful, due mainly to the absence of empirical controls. Woody plant species that colonized the global tropical coasts, collectively referred to as mangroves, are ideal for convergence studies. Here, we sequenced the genomes/transcriptomes of 16 species belonging in three major mangrove clades. To detect convergence in a large phylogeny, a CCS+ model is implemented, extending the more limited CCS method (convergence at conservative sites). Using the empirical control for reference, the CCS+ model reduces the noises drastically, thus permitting the identification of 73 convergent genes with Ptrue (probability of true convergence) > 0.9. Products of the convergent genes tend to be on the plasma membrane associated with salinity tolerance. Importantly, convergence is more often manifested at a higher level than at amino-acid (AA) sites. Relative to >50 plant species, mangroves strongly prefer 4 AAs and avoid 5 others across the genome. AA substitutions between mangrove species strongly reflect these tendencies. In conclusion, the selection of taxa, the number of species and, in particular, the empirical control are all crucial for detecting genome-wide convergence. We believe this large study of mangroves is the first successful attempt at detecting genome-wide site convergence.

Identification of Hidden Population Structure in Time-Scaled Phylogenies.

Population structure influences genealogical patterns, however, data pertaining to how populations are structured are often unavailable or not directly observable. Inference of population structure is highly important in molecular epidemiology where pathogen phylogenetics is increasingly used to infer transmission patterns and detect outbreaks. Discrepancies between observed and idealized genealogies, such as those generated by the coalescent process, can be quantified, and where significant differences occur, may reveal the action of natural selection, host population structure, or other demographic and epidemiological heterogeneities. We have developed a fast non-parametric statistical test for detection of cryptic population structure in time-scaled phylogenetic trees. The test is based on contrasting estimated phylogenies with the theoretically expected phylodynamic ordering of common ancestors in two clades within a coalescent framework. These statistical tests have also motivated the development of algorithms which can be used to quickly screen a phylogenetic tree for clades which are likely to share a distinct demographic or epidemiological history. Epidemiological applications include identification of outbreaks in vulnerable host populations or rapid expansion of genotypes with a fitness advantage. To demonstrate the utility of these methods for outbreak detection, we applied the new methods to large phylogenies reconstructed from thousands of HIV-1 partial pol sequences. This revealed the presence of clades which had grown rapidly in the recent past and was significantly concentrated in young men, suggesting recent and rapid transmission in that group. Furthermore, to demonstrate the utility of these methods for the study of antimicrobial resistance, we applied the new methods to a large phylogeny reconstructed from whole genome Neisseria gonorrhoeae sequences. We find that population structure detected using these methods closely overlaps with the appearance and expansion of mutations conferring antimicrobial resistance. [Antimicrobial resistance; coalescent; HIV; population structure.]

Simulating trees with millions of species.

The birth-death (BD) model constitutes the theoretical backbone of most phylogenetic tools for reconstructing speciation/extinction dynamics over time. Performing simulations of reconstructed trees (linking extant taxa) under the BD model in backward time, conditioned on the number of species sampled at present day and, in some cases, a specific time interval since the most recent common ancestor (MRCA), is needed for assessing the performance of reconstruction tools, for parametric bootstrapping and for detecting data outliers. The few simulation tools that exist scale poorly to large modern phylogenies, which can comprise thousands or even millions of tips (and rising). Here I present efficient software for simulating reconstructed phylogenies under time-dependent BD models in backward time, conditioned on the number of sampled species and (optionally) on the time since the MRCA. On large trees, my software is 1000-10000 times faster than existing tools. The presented software is incorporated into the R package 'castor', which is available on The Comprehensive R Archive Network (CRAN). Supplementary data are available at Bioinformatics online.

A General and Efficient Algorithm for the Likelihood of Diversification and Discrete-Trait Evolutionary Models.

As the size of phylogenetic trees and comparative data continue to grow and more complex models are developed to investigate the processes that gave rise to them, macroevolutionary analyses are becoming increasingly limited by computational requirements. Here, we introduce a novel algorithm, based on the "flow" of the differential equations that describe likelihoods along tree edges in backward time, to reduce redundancy in calculations and efficiently compute the likelihood of various macroevolutionary models. Our algorithm applies to several diversification models, including birth-death models and models that account for state- or time-dependent rates, as well as many commonly used models of discrete-trait evolution, and provides an alternative way to describe macroevolutionary model likelihoods. As a demonstration of our algorithm's utility, we implemented it for a popular class of state-dependent diversification models-BiSSE, MuSSE, and their extensions to hidden-states. Our implementation is available through the R package $\texttt{castor}$. We show that, for these models, our algorithm is one or more orders of magnitude faster than existing implementations when applied to large phylogenies. Our algorithm thus enables the fitting of state-dependent diversification models to modern massive phylogenies with millions of tips and may lead to potentially similar computational improvements for many other macroevolutionary models.

On the origin of the New World Pyrgomorphidae (Insecta: Orthoptera)

The gaudy grasshopper family Pyrgomorphidae (Orthoptera: Caelifera) shows a peculiar geographical distribution. Of the 487 described species, less than 10% of the diversity is found in the New World, while the rest occur throughout Africa, Asia, and Australia. Only 41 species belonging to four tribes are found in Central and South America and Dominican Republic, and the phylogenetic positions of these taxa within the large phylogeny of Pyrgomorphidae and the relationships among them have never been investigated. Regarding the biogeography, three different hypotheses about the origin of the New World Pyrgomorphidae have been proposed, but these have not been empirically tested. In this study, we present the first molecular phylogeny of Pyrgomorphidae that includes the members of all four New World tribes and representative genera from the Old World based on entire mitochondrial genome and four nuclear genes to investigate the biogeography of this fascinating lineage. Our results recover Pyrgomorphidae as monophyletic and the New World Pyrgomorphidae as a paraphyletic group comprising three clades, consisting of: (1) The Caribbean Jaragua + the South American Algete; (2) The Mexican and Central American Sphenarium + Prosphena; and (3) The Mexican lineages Ichthiacridini + Ichthyotettigini. The divergence time estimation analysis suggested that the Pyrgomorphidae diverged from its relatives in the Early Cretaceous (139–104 mya). The biogeographic analysis using BioGeoBEARS showed that after diversifying in the Old World, the first New World Pyrgomorphidae clade (Algete + Jaragua) diverged 96 mya (Late Cretaceous, Cenomanian) and that their current distribution in the New World is explained by two possible events, a transatlantic colonization from Africa to Northern South America or a vicariance event between these two landmasses, followed by a subsequent dispersal to the Caribbean. The second wave of colonization occurred about 69 mya towards the end of the Late Cretaceous (Maastrichtian) with dispersal from Africa to South America and then to North America with a subsequent diversification in Mexico including Baja California.

Tree reconciliation combined with subsampling improves large scale inference of orthologous group hierarchies

BackgroundAn orthologous group (OG) comprises a set of orthologous and paralogous genes that share a last common ancestor (LCA). OGs are defined with respect to a chosen taxonomic level, which delimits the position of the LCA in time to a specified speciation event. A hierarchy of OGs expands on this notion, connecting more general OGs, distant in time, to more recent, fine-grained OGs, thereby spanning multiple levels of the tree of life. Large scale inference of OG hierarchies with independently computed taxonomic levels can suffer from inconsistencies between successive levels, such as the position in time of a duplication event. This can be due to confounding genetic signal or algorithmic limitations. Importantly, inconsistencies limit the potential use of OGs for functional annotation and third-party applications.ResultsHere we present a new methodology to ensure hierarchical consistency of OGs across taxonomic levels. To resolve an inconsistency, we subsample the protein space of the OG members and perform gene tree-species tree reconciliation for each sampling. Differently from previous approaches, by subsampling the protein space, we avoid the notoriously difficult task of accurately building and reconciling very large phylogenies. We implement the method into a high-throughput pipeline and apply it to the eggNOG database. We use independent protein domain definitions to validate its performance.ConclusionThe presented consistency pipeline shows that, contrary to previous limitations, tree reconciliation can be a useful instrument for the construction of OG hierarchies. The key lies in the combination of sampling smaller trees and aggregating their reconciliations for robustness. Results show comparable or greater performance to previous pipelines. The code is available on Github at: https://github.com/meringlab/og_consistency_pipeline.

Distribution and asymptotic behavior of the phylogenetic transfer distance

The transfer distance (TD) was introduced in the classification framework and studied in the context of phylogenetic tree matching. Recently, Lemoine et al. (Nature 556(7702):452–456, 2018. https://doi.org/10.1038/s41586-018-0043-0) showed that TD can be a powerful tool to assess the branch support on large phylogenies, thus providing a relevant alternative to Felsenstein’s bootstrap. This distance allows a reference branchbeta in a reference tree {mathcal {T}} to be compared to a branch b from another tree T (typically a bootstrap tree), both on the same set of n taxa. The TD between these branches is the number of taxa that must be transferred from one side of b to the other in order to obtain beta . By taking the minimum TD from beta to all branches in T we define the transfer index, denoted by phi (beta ,T), measuring the degree of agreement of T with beta . Let us consider a reference branch beta having p tips on its light side and define the transfer support (TS) as 1 - phi (beta ,T)/(p-1). Lemoine et al. (2018) used computer simulations to show that the TS defined in this manner is close to 0 for random “bootstrap” trees. In this paper, we demonstrate that result mathematically: when T is randomly drawn, TS converges in probability to 0 when n tends to infty . Moreover, we fully characterize the distribution of phi (beta ,T) on caterpillar trees, indicating that the convergence is fast, and that even when n is small, moderate levels of branch support cannot appear by chance.

V.PhyloMaker: an R package that can generate very large phylogenies for vascular plants

We present V.PhyloMaker, a freely available package for R designed to generate phylogenies for vascular plants. The mega‐tree implemented in V.PhyloMaker (i.e. GBOTB.extended.tre), which was derived from two recently published mega‐trees and includes 74 533 species and all families of extant vascular plants, is the largest dated phylogeny for vascular plants. V.PhyloMaker can generate phylogenies for very large species lists (the largest species list that we tested included 314 686 species). V.PhyloMaker generates phylogenies at a fast speed, much faster than other phylogeny‐generating packages. Our tests of V.PhyloMaker show that generating a phylogeny for 60 000 species requires less than six hours. V.PhyloMaker includes an approach to attach genera or species to their close relatives in a phylogeny. We provide a simple example in this paper to show how to use V.PhyloMaker to generate phylogenies.

A Machine Learning Method for Detecting Autocorrelation of Evolutionary Rates in Large Phylogenies

New species arise from pre-existing species and inherit similar genomes and environments. This predicts greater similarity of the tempo of molecular evolution between direct ancestors and descendants, resulting in autocorrelation of evolutionary rates in the tree of life. Surprisingly, molecular sequence data have not confirmed this expectation, possibly because available methods lack the power to detect autocorrelated rates. Here, we present a machine learning method, CorrTest, to detect the presence of rate autocorrelation in large phylogenies. CorrTest is computationally efficient and performs better than the available state-of-the-art method. Application of CorrTest reveals extensive rate autocorrelation in DNA and amino acid sequence evolution of mammals, birds, insects, metazoans, plants, fungi, parasitic protozoans, and prokaryotes. Therefore, rate autocorrelation is a common phenomenon throughout the tree of life. These findings suggest concordance between molecular and nonmolecular evolutionary patterns, and they will foster unbiased and precise dating of the tree of life.

Predicting the Impact of Describing New Species on Phylogenetic Patterns.

Although our inventory of Earth’s biodiversity remains incomplete, we still require analyses using the Tree of Life to understand evolutionary and ecological patterns. Because incomplete sampling may bias our inferences, we must evaluate how future additions of newly discovered species might impact analyses performed today. We describe an approach that uses taxonomic history and phylogenetic trees to characterize the impact of past species discoveries on phylogenetic knowledge using patterns of branch-length variation, tree shape, and phylogenetic diversity. This provides a framework for assessing the relative completeness of taxonomic knowledge of lineages within a phylogeny. To demonstrate this approach, we use recent large phylogenies for amphibians, reptiles, flowering plants, and invertebrates. Well-known clades exhibit a decline in the mean and range of branch lengths that are added each year as new species are described. With increased taxonomic knowledge over time, deep lineages of well-known clades become known such that most recently described new species are added close to the tips of the tree, reflecting changing tree shape over the course of taxonomic history. The same analyses reveal other clades to be candidates for future discoveries that could dramatically impact our phylogenetic knowledge. Our work reveals that species are often added non-randomly to the phylogeny over multiyear time-scales in a predictable pattern of taxonomic maturation. Our results suggest that we can make informed predictions about how new species will be added across the phylogeny of a given clade, thus providing a framework for accommodating unsampled undescribed species in evolutionary analyses.

Phylogenies and Diversification Rates: Variance Cannot Be Ignored.

A recent pair of articles published in the journal Evolution presented a test for assessing the validity of hierarchical macroevolutionary models. The premise of the test is to compare numerical point estimates of parameters from two levels of analysis; if the estimates differ, the hierarchical model is purportedly flawed. The articles in question apply their proposed test to BAMM, a scientific software program that uses a Bayesian mixture model to estimate rates of evolution from phylogenetic trees. The authors use BAMM to estimate rates from large phylogenies ($n > 60$ tips) and they apply the method separately to subclades within those phylogenies (median size: $n = 3$ tips); they find that point estimates of rates differ between these levels and conclude that the method is flawed, but they do not test whether the observed differences are statistically meaningful. There is no consideration of sampling variation and its impact at any level of their analysis. Here, I show that numerical differences across groups that they report are fully explained by a failure to account for sampling variation in their point estimates. Variance in evolutionary rate estimates-from BAMM and all other methods-is an inverse function of clade size; this variance is extreme for clades with five or fewer tips (e.g., 70% of clades in the focal study). The articles in question rely on negative results that are easily explained by low statistical power to reject their preferred null hypothesis, and this low power is a trivial consequence of high variance in their point estimates. I describe additional mathematical and statistical mistakes that render the proposed testing framework invalid on first principles. Evolutionary rates are no different than any other population parameters we might wish to estimate, and biologists should use the training and tools already at their disposal to avoid erroneous results that follow from the neglect of variance. [Confidence interval; diversification; estimation; null hypothesis; phylogeny; statistics; type I error].

High-Throughput Reconstruction of Ancestral Protein Sequence, Structure, and Molecular Function.

Ancestral protein sequence reconstruction is a powerful technique for explicitly testing hypotheses about the evolution of molecular function, allowing researchers to meticulously dissect how historical changes in protein sequence impacted functional repertoire by altering the protein's 3D structure. These techniques have provided concrete, experimentally validated insights into ancient evolutionary processes and help illuminate the complex relationship between protein sequence, structure, and function. Inferring the protein family phylogenies on which ancestral sequence reconstruction depends and reconstructing the sequences, themselves, are amenable to high-throughput computational analysis. However, determining the structures of ancestral-reconstructed proteins and characterizing their functions typically rely on time-consuming and expensive laboratory analyses, limiting most current studies to examining a relatively small number of specific hypotheses. For this reason, we have little detailed, unbiased information about how molecular function evolves across large protein family phylogenies. Here we describe a generalized protocol that integrates ancestral sequence reconstruction with structural homology modeling and structure-based molecular affinity prediction to characterize historical changes in protein function across families with thousands of individual sequences. We highlight key steps in the analysis protocol requiring particularly careful attention to avoid introducing potential errors as well as steps for which computationally efficient subroutines can be substituted for more intensive approaches, allowing researchers to scale the analysis up or down, depending on available resources and requirements for reproducibility and scientific rigor. In our view, this approach provides a compelling compliment to more laboratory-intensive procedures, generating important contextual information that can help guide detailed experiments.

Bacterial diversification through geological time.

Numerous studies have estimated plant and animal diversification dynamics; however, no comparable rigorous estimates exist for bacteria-the most ancient and widespread form of life on Earth. Here, we analyse phylogenies comprising up to 448,112 bacterial lineages to reconstruct global bacterial diversification dynamics. To handle such large phylogenies, we developed methods based on the statistical properties of infinitely large trees. We further analysed sequencing data from 60 environmental studies to determine the fraction of extant bacterial diversity missing from the phylogenies-a crucial parameter for estimating speciation and extinction rates. We estimate that there are about 1.4-1.9 million extant bacterial lineages when lineages are defined by 99% similarity in the 16S ribosomal RNA gene, and that bacterial diversity has been continuously increasing over the past 1 billion years (Gyr). Recent bacterial extinction rates are estimated at 0.03-0.05 per lineage per million years (lineage-1 Myr-1), and are only slightly below estimated recent bacterial speciation rates. Most bacterial lineages ever to have inhabited this planet are estimated to be extinct. Our findings disprove the notion that bacteria are unlikely to go extinct, and provide a valuable perspective on the evolutionary history of a domain of life with a sparse and cryptic fossil record.

Corrigendum for Rojas etal. (2018) DOI: 10.1111/ele.12911.

Corrigendum for Rojas etal. (2018) DOI: 10.1111/ele.12911.

BCD Beam Search: considering suboptimal partial solutions in Bad Clade Deletion supertrees.

Supertree methods enable the reconstruction of large phylogenies. The supertree problem can be formalized in different ways in order to cope with contradictory information in the input. Some supertree methods are based on encoding the input trees in a matrix; other methods try to find minimum cuts in some graph. Recently, we introduced Bad Clade Deletion (BCD) supertrees which combines the graph-based computation of minimum cuts with optimizing a global objective function on the matrix representation of the input trees. The BCD supertree method has guaranteed polynomial running time and is very swift in practice. The quality of reconstructed supertrees was superior to matrix representation with parsimony (MRP) and usually on par with SuperFine for simulated data; but particularly for biological data, quality of BCD supertrees could not keep up with SuperFine supertrees. Here, we present a beam search extension for the BCD algorithm that keeps alive a constant number of partial solutions in each top-down iteration phase. The guaranteed worst-case running time of the new algorithm is still polynomial in the size of the input. We present an exact and a randomized subroutine to generate suboptimal partial solutions. Both beam search approaches consistently improve supertree quality on all evaluated datasets when keeping 25 suboptimal solutions alive. Supertree quality of the BCD Beam Search algorithm is on par with MRP and SuperFine even for biological data. This is the best performance of a polynomial-time supertree algorithm reported so far.

Lorenzo Camerano (1856–1917) and his contribution to large mammal phylogeny and taxonomy, with particular reference to the genera Capra, Rupicapra and Rangifer

In this paper, we commemorate the professional activity of Prof. Lorenzo Camerano 100 years after his death on 22 November 1917, with a special emphasis on his mammalogical studies. Our two aims are to widespread some of his little-known results on the systematic and phylogenetics of ungulates (particularly of the genus Capra) and to increase knowledge about that particular period of taxonomic research in Europe before the advent of the New Synthesis. Of particular interest are some of the results concerning the recent evolutionary history of chamois in Western Europe. Camerano, through specimen-based research based on abundant material, was able to design a phylogeographic picture that was confirmed by genetic studies only a few years ago.

Can we build it? Yes we can, but should we use it? Assessing the quality and value of a very large phylogeny of campanulid angiosperms

The study of very large and very old clades holds the promise of greater insights into evolution across the tree of life. However, there has been a fair amount of criticism regarding the interpretations and quality of studies to date, with some suggesting that detailed studies carried out on smaller, tractable scales should be preferred over the increasingly grand syntheses of these data. We provided in detail our trials and tribulations of compiling a large, sparsely sampled matrix from GenBank data and inferring a well-supported, time-calibrated phylogeny of Campanulidae. We also used a simulation approach to assess tree quality and to study the value of using very large, comprehensive phylogenies in a comparative context. A robust and well-supported phylogeny can be produced as long as automated procedures are supplemented with some human intervention. In the case of campanulids, the overall topology may be driven not only by particular genes, but also particular sequences for a gene. We also determined that estimates of divergence times should be fairly robust to issues related to clade-specific heterogeneity. Finally, we demonstrated how relying on results from smaller, younger clades are prone to produce biased interpretations oftropical to temperate evolution across campanulids as a whole. While we were both surprised and encouraged by the robust and fairly well-resolved, comprehensive phylogeny of campanulids, challenges still remain. Nevertheless, large phylogenies are inherently valuable in a comparative context if only toattenuate the issue of ascertainment bias.

Chromploid: An R package for chromosome number evolution across the plant tree of life.

Premise of the StudyPolyploidy has profound evolutionary consequences for land plants. Despite the availability of large phylogenetic and chromosomal data sets, estimating the rates of polyploidy and chromosomal evolution across the tree of life remains a challenging, computationally complex problem. We introduce the R package chromploid, which allows scientists to perform inference of chromosomal evolution rates across large phylogenetic trees.Methods and Resultschromploid is an open‐source package in the R environment that calculates the likelihood function of models of chromosome evolution. Models of discrete character evolution can be customized using chromploid. We demonstrate the performance of the BiChroM model, testing for associations between rates of chromosome doubling (as a proxy for polyploidy) and a binary phenotypic character, within chromploid using simulations and empirical data from Solanum. In simulations, estimated chromosome‐doubling rates were unbiased and the variance decreased with larger trees, but distinguishing small differences in rates of chromosome doubling, even from large data sets, remains challenging. In the Solanum data set, a custom model of chromosome number evolution demonstrated higher rates of chromosome doubling in herbaceous species compared to woody.Conclusionschromploid enables researchers to perform robust likelihood‐based inferences using complex models of chromosome number evolution across large phylogenies.

Constructing a broadly inclusive seed plant phylogeny.

Large phylogenies can help shed light on macroevolutionary patterns that inform our understanding of fundamental processes that shape the tree of life. These phylogenies also serve as tools that facilitate other systematic, evolutionary, and ecological analyses. Here we combine genetic data from public repositories (GenBank) with phylogenetic data (Open Tree of Life project) to construct a dated phylogeny for seed plants. We conducted a hierarchical clustering analysis of publicly available molecular data for major clades within the Spermatophyta. We constructed phylogenies of major clades, estimated divergence times, and incorporated data from the Open Tree of Life project, resulting in a seed plant phylogeny. We estimated diversification rates, excluding those taxa without molecular data. We also summarized topological uncertainty and data overlap for each major clade. The trees constructed for Spermatophyta consisted of 79,881 and 353,185 terminal taxa; the latter included the Open Tree of Life taxa for which we could not include molecular data from GenBank. The diversification analyses demonstrated nested patterns of rate shifts throughout the phylogeny. Data overlap and inference uncertainty show significant variation throughout and demonstrate the continued need for data collection across seed plants. This study demonstrates a means for combining available resources to construct a dated phylogeny for plants. However, this approach is an early step and more developments are needed to add data, better incorporating underlying uncertainty, and improve resolution. The methods discussed here can also be applied to other major clades in the tree of life.