Noor D. White

The exponential growth of molecular sequence data over the past decade has enabled the construction of numerous clade-specific phylogenies encompassing hundreds or thousands of taxa. These independent studies often include overlapping data, presenting a unique opportunity to build macrophylogenies (phylogenies sampling >1000 taxa) for entire classes across the Tree of Life. However, the inference of large trees remains constrained by logistical, computational, and methodological challenges. The Avian Tree of Life provides an ideal model for evaluating strategies to robustly infer macrophylogenies from intersecting data sets derived from smaller studies. In this study, we leveraged a comprehensive resource of sequence capture data sets to evaluate the phylogenetic accuracy and computational costs of four methodological approaches: (1) supermatrix approaches using concatenation, including the “fast” maximum likelihood (ML) methods, (2) filtering data sets to reduce heterogeneity, (3) supertree estimation based on published phylogenomic trees, and (4) a “divide-and-conquer” strategy, wherein smaller ML trees were estimated and subsequently combined using a supertree approach. Additionally, we examined the impact of these methods on divergence time estimation using a data set that includes newly vetted fossil calibrations for the Avian Tree of Life. Our findings highlight the advantages of recently developed fast tree search approaches initiated with parsimony starting trees, which offer a reasonable compromise between computational efficiency and phylogenetic accuracy, facilitating inference of macrophylogenies.

The exponential growth of molecular sequence data over the past decade has enabled the construction of numerous clade-specific phylogenies encompassing hundreds or thousands of taxa. These independent studies often include overlapping data, presenting a unique opportunity to build macrophylogenies (phylogenies sampling > 1,000 taxa) for entire classes across the Tree of Life. However, the inference of large trees remains constrained by logistical, computational, and methodological challenges. The Avian Tree of Life provides an ideal model for evaluating strategies to robustly infer macrophylogenies from intersecting datasets derived from smaller studies. In this study, we leveraged a comprehensive resource of sequence capture datasets to evaluate the phylogenetic accuracy and computational costs of four methodological approaches: (1) supermatrix approaches using concatenation, including the “fast” maximum likelihood (ML) methods, (2) filtering datasets to reduce heterogeneity, (3) supertree estimation based on published phylogenomic trees, and (4) a “divide-and-conquer” strategy, wherein smaller ML trees were estimated and subsequently combined using a supertree approach. Additionally, we examined the impact of these methods on divergence time estimation using a dataset that includes newly vetted fossil calibrations for the Avian Tree of Life. Our findings highlight that recently developed fast tree search approaches offer a reasonable compromise between computational efficiency and phylogenetic accuracy, facilitating inference of macrophylogenies.

The evolutionary histories of different genomic regions typically differ from each other and from the underlying species phylogeny. This makes species tree estimation challenging. Here, we examine the performance of phylogenomic methods using a well-resolved phylogeny that nevertheless contains many difficult nodes, the species tree of living birds. We compared trees generated by maximum likelihood (ML) analysis of concatenated data, gene tree summary methods, and SVDquartets. We also conduct the first empirical test of a “new” method called METAL (Metric algorithm for Estimation of Trees based on Aggregation of Loci), which is based on evolutionary distances calculated using concatenated data. We conducted this test using a novel dataset comprising more than 4,000 ultraconserved element (UCE) loci from almost all bird families and two existing UCE and intron datasets sampled from almost all avian orders. We identified “reliable clades” very likely to be present in the true avian species tree and used them to assess method performance. ML analyses of concatenated data recovered almost all reliable clades with less data and greater robustness to missing data than other methods. METAL recovered many reliable clades, but only performed well with the largest datasets. Gene tree summary methods (weighted ASTRAL and weighted ASTRID) performed well; they required less data than METAL but more data than ML concatenation. SVDquartets exhibited the worst performance of the methods tested. In addition to the methodological insights, this study provides a novel estimate of avian phylogeny with almost 99% of the currently recognized avian families. Only one of the 181 reliable clades we examined was consistently resolved differently by ML concatenation versus other methods, suggesting that it may be possible to achieve consensus on the deep phylogeny of extant birds.

Some phylogenetic problems remain unresolved even when large amounts of sequence data are analyzed and methods that accommodate processes such as incomplete lineage sorting are employed. In addition to investigating biological sources of phylogenetic incongruence, it is also important to reduce noise in the phylogenomic dataset by using appropriate filtering approach that addresses gene tree estimation errors. We present the results of a case study in manakins, focusing on the very difficult clade comprising the genera Antilophia and Chiroxiphia. Previous studies suggest that Antilophia is nested within Chiroxiphia, though relationships among Antilophia+Chiroxiphia species have been highly unstable. We extracted more than 11,000 loci (ultra-conserved elements and introns) from whole genomes and conducted analyses using concatenation and multispecies coalescent methods. Topologies resulting from analyses using all loci differed depending on the data type and analytical method, with 2 clades (Antilophia+Chiroxiphia and Manacus+Pipra+Machaeopterus) in the manakin tree showing incongruent results. We hypothesized that gene trees that conflicted with a long coalescent branch (e.g., the branch uniting Antilophia+Chiroxiphia) might be enriched for cases of gene tree estimation error, so we conducted analyses that either constrained those gene trees to include monophyly of Antilophia+Chiroxiphia or excluded these loci. While constraining trees reduced some incongruence, excluding the trees led to completely congruent species trees, regardless of the data type or model of sequence evolution used. We found that a suite of gene metrics (most importantly the number of informative sites and likelihood of intralocus recombination) collectively explained the loci that resulted in non-monophyly of Antilophia+Chiroxiphia. We also found evidence for introgression that may have contributed to the discordant topologies we observe in Antilophia+Chiroxiphia and led to deviations from expectations given the multispecies coalescent model. Our study highlights the importance of identifying factors that can obscure phylogenetic signal when dealing with recalcitrant phylogenetic problems, such as gene tree estimation error, incomplete lineage sorting, and reticulation events. [Birds; c-gene; data type; gene estimation error; model fit; multispecies coalescent; phylogenomics; reticulation]

The diversity of avian visual phenotypes provides a framework for studying mechanisms of trait diversification generally, and the evolution of vertebrate vision, specifically. Previous research has focused on opsins, but to fully understand visual adaptation, we must study the complete phototransduction cascade (PTC). Here, we developed a probe set that captures exonic regions of 46 genes representing the PTC and other light responses. For a subset of species, we directly compared gene capture between our probe set and low-coverage whole genome sequencing (WGS), and we discuss considerations for choosing between these methods. Finally, we developed a unique strategy to avoid chimeric assembly by using “decoy” reference sequences. We successfully captured an average of 64% of our targeted exome in 46 species across 14 orders using the probe set and had similar recovery using the WGS data. Compared to WGS or transcriptomes, our probe set: (1) reduces sequencing requirements by efficiently capturing vision genes, (2) employs a simpler bioinformatic pipeline by limiting required assembly and negating annotation, and (3) eliminates the need for fresh tissues, enabling researchers to leverage existing museum collections. We then utilized our vision exome data to identify positively selected genes in two evolutionary scenarios—evolution of night vision in nocturnal birds and evolution of high-speed vision specific to manakins (Pipridae). We found parallel positive selection of SLC24A1 in both scenarios, implicating the alteration of rod response kinetics, which could improve color discrimination in dim light conditions and/or facilitate higher temporal resolution.

Strisores is a clade of neoavian birds that include diurnal aerial specialists such as swifts and hummingbirds, as well as several predominantly nocturnal lineages such as nightjars and potoos. Despite the use of genome-scale molecular datasets, the phylogenetic interrelationships among major strisorean groups remain controversial. Given the availability of next-generation sequence data for Strisores and the clade’s rich fossil record, we reassessed the phylogeny of Strisores by incorporating a large-scale sequence dataset with anatomical data from living and fossil strisoreans within a Bayesian total-evidence framework. Combined analyses of molecular and morphological data resulted in a phylogenetic topology for Strisores that is congruent with the findings of two recent molecular phylogenomic studies, supporting nightjars (Caprimulgidae) as the extant sister group of the remainder of Strisores. This total-evidence framework allowed us to identify morphological synapomorphies for strisorean clades previously recovered using molecular-only datasets. However, a combined analysis of molecular and morphological data highlighted strong signal conflict between sequence and anatomical data in Strisores. Furthermore, simultaneous analysis of molecular and morphological data recovered differing placements for some fossil taxa compared with analyses of morphological data under a molecular scaffold, highlighting the importance of analytical decisions when conducting morphological phylogenetic analyses of taxa with molecular phylogenetic data. We suggest that multiple strisorean lineages have experienced convergent evolution across the skeleton, obfuscating the phylogenetic position of certain fossils, and that many distinctive specializations of strisorean subclades were acquired early in their evolutionary history. Despite this apparent complexity in the evolutionary history of Strisores, our results provide fossil support for aerial foraging as the ancestral ecological strategy of Strisores, as implied by recent phylogenetic topologies derived from molecular data.

It has long been appreciated that analyses of genomic data (e.g., whole genome sequencing or sequence capture) have the potential to reveal the tree of life, but it remains challenging to move from sequence data to a clear understanding of evolutionary history, in part due to the computational challenges of phylogenetic estimation using genome-scale data. Supertree methods solve that challenge because they facilitate a divide-and-conquer approach for large-scale phylogeny inference by integrating smaller subtrees in a computationally efficient manner. Here, we combined information from sequence capture and whole-genome phylogenies using supertree methods. However, the available phylogenomic trees had limited overlap so we used taxon-rich (but not phylogenomic) megaphylogenies to weave them together. This allowed us to construct a phylogenomic supertree, with support values, that included 707 bird species (~7% of avian species diversity). We estimated branch lengths using mitochondrial sequence data and we used these branch lengths to estimate divergence times. Our time-calibrated supertree supports radiation of all three major avian clades (Palaeognathae, Galloanseres, and Neoaves) near the Cretaceous-Paleogene (K-Pg) boundary. The approach we used will permit the continued addition of taxa to this supertree as new phylogenomic data are published, and it could be applied to other taxa as well.

Avian diversification has been influenced by global climate change, plate tectonic movements, and mass extinction events. However, the impact of these factors on the diversification of the hyperdiverse perching birds (passerines) is unclear because family level relationships are unresolved and the timing of splitting events among lineages is uncertain. We analyzed DNA data from 4,060 nuclear loci and 137 passerine families using concatenation and coalescent approaches to infer a comprehensive phylogenetic hypothesis that clarifies relationships among all passerine families. Then, we calibrated this phylogeny using 13 fossils to examine the effects of different events in Earth history on the timing and rate of passerine diversification. Our analyses reconcile passerine diversification with the fossil and geological records; suggest that passerines originated on the Australian landmass ∼47 Ma; and show that subsequent dispersal and diversification of passerines was affected by a number of climatological and geological events, such as Oligocene glaciation and inundation of the New Zealand landmass. Although passerine diversification rates fluctuated throughout the Cenozoic, we find no link between the rate of passerine diversification and Cenozoic global temperature, and our analyses show that the increases in passerine diversification rate we observe are disconnected from the colonization of new continents. Taken together, these results suggest more complex mechanisms than temperature change or ecological opportunity have controlled macroscale patterns of passerine speciation.