Brant C. Faircloth’s research while affiliated with Louisiana State University and other places

Recognizing species boundaries in complex speciation scenarios, including those that involve gene flow and demographic fluctuations, combined with the plethora of existing species concepts, is a challenge that has recently been brought to attention. Promising recent approaches consider an integrative taxonomy with multiple sources of evidence (e.g., genetic, morphology, geographic distributions), which can be related to diverse properties associated with the dynamics of the speciation continuum. Also, the use of statistical inferential methods for model comparison, such as approximate Bayesian computation, approximate likelihoods, and machine learning, has allowed a better assessment of species boundaries in such cases. However, most approaches involve analyzing genetic and phenotypic/geographical information separately, followed by visual/qualitative comparison. Methods that integrate genetic information with other sources of evidence have been limited to simple evolutionary models and are not able to analyze more than a few hundred loci across a maximum of a few tens of samples. Here, we present a deep learning approach (DeepID) that combines convolutional neural networks and multilayer perceptrons to integrate both genomic data (thousands of loci or single nucleotide polymorphisms, SNPs) and trait information into a unified framework. By using simulated and empirical datasets, we evaluate the power and accuracy of our approach for discriminating among competing allopatric speciation scenarios when varying the number of SNPs and traits, and the impact of missing data. We found that the accuracy of our method was lower for datasets that included only trait data, but when we combined both genomic and trait data types, the accuracy was similar to when we considered genomic data alone. However, when we violated the simple allopatric speciation model by including migration, the approach based on traits was less affected than analyzing datasets including the genomic information. Moreover, using both sources of data can incorporate complementary information associated with different stages of the speciation process. Our approach was able to recover the expected delimitation scenarios in empirical datasets of one plant (Euphorbia balsamifera) and one fish (Lepomis megalotis) species complex. We argue that our method is a flexible and promising approach, allowing for complex scenario comparison and the use of multiple types of data.

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.

Fungus-farming ants cultivate multiple lineages of fungi for food, but, because fungal cultivar relationships are largely unresolved, the history of fungus-ant coevolution remains poorly known. We designed probes targeting >2000 gene regions to generate a dated evolutionary tree for 475 fungi and combined it with a similarly generated tree for 276 ants. We found that fungus-ant agriculture originated ~66 million years ago when the end-of-Cretaceous asteroid impact temporarily interrupted photosynthesis, causing global mass extinctions but favoring the proliferation of fungi. Subsequently, ~27 million years ago, one ancestral fungal cultivar population became domesticated, i.e., obligately mutualistic, when seasonally dry habitats expanded in South America, likely isolating the cultivar population from its free-living, wet forest–dwelling conspecifics. By revealing these and other major transitions in fungus-ant coevolution, our results clarify the historical processes that shaped a model system for nonhuman agriculture.

Despite tremendous efforts in the past decades, relationships among main avian lineages remain heavily debated without a clear resolution. Discrepancies have been attributed to diversity of species sampled, phylogenetic method and the choice of genomic regions1–3. Here we address these issues by analysing the genomes of 363 bird species⁴ (218 taxonomic families, 92% of total). Using intergenic regions and coalescent methods, we present a well-supported tree but also a marked degree of discordance. The tree confirms that Neoaves experienced rapid radiation at or near the Cretaceous–Palaeogene boundary. Sufficient loci rather than extensive taxon sampling were more effective in resolving difficult nodes. Remaining recalcitrant nodes involve species that are a challenge to model due to either extreme DNA composition, variable substitution rates, incomplete lineage sorting or complex evolutionary events such as ancient hybridization. Assessment of the effects of different genomic partitions showed high heterogeneity across the genome. We discovered sharp increases in effective population size, substitution rates and relative brain size following the Cretaceous–Palaeogene extinction event, supporting the hypothesis that emerging ecological opportunities catalysed the diversification of modern birds. The resulting phylogenetic estimate offers fresh insights into the rapid radiation of modern birds and provides a taxon-rich backbone tree for future comparative studies.

Genome-scale sequencing is important in the study of infectious diseases, but preparing DNA samples for such sequencing can be constrained by the need for specialized equipment, expensive reagents, and higher input DNA than is readily available. Cryptosporidium oocysts are shed into feces, making it difficult and expensive to purify and yielding limited amounts of DNA. To address these constraints, we developed an iNextEra library preparation protocol for Illumina sequencing that works across a broad range of input DNA amounts, requires little bench time and no specialized equipment, succeeds with limited PCR cycles, yet is low-cost per sample. Our method uses 1/20th of the standard amount of the Illumina DNA Prep tagmentation beads, a simplified protocol, custom indexing primers, and common PCR reagents. A single researcher can use these methods to produce ≥ 96 libraries per day at a cost of <5 USD per sample and may pool up to 480 unique dual-indexed or up to 230,400 (480x480) unique combinatorically indexed libraries. We tested this protocol by making libraries from mock communities with known dilutions of Cryptosporidium DNA, and real-world clinical samples of Cryptosporidium infected patients. Overall, our protocol performed well with a wide range of input DNA (<1 ng to >60 ng) and 8-14 PCR cycles, thus reducing bias introduced by amplification. The libraries are compatible with all Illumina sequencers, including NovaSeq X, for low-cost sequencing per sample. This protocol thus opens the potential for many laboratories to process the samples of these important parasites for Illumina sequencing efficiently.

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 ( M etric algorithm for E stimation of T rees based on A ggregation of L oci), which is based on evolutionary distances calculated using concatenated data. We conducted this test using a novel dataset comprising more than 4000 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.

Aim Biotic interchanges between Africa, India, and Eurasia are central to explaining the present‐day distribution and diversity of freshwater organisms across these landmasses. Synbranchiformes is a diverse and species‐rich clade of freshwater acanthomorph fishes found on all southern continents except Antarctica, and include eel‐ and perch‐like, air‐breathing and non‐air‐breathing fishes. Lacking a comprehensive and resolved phylogeny of the entire clade, contemporary interpretations of synbranchiform biogeography invoke scenarios as disparate as Gondwanan vicariance and pan‐global rafting to explain their modern‐day distribution. Here, we study their biogeographic history of continental dispersal events and test whether these are associated with increases in lineage diversification. Location Asia, India, Africa freshwater habitats. Taxon Synbranchiformes (gouramis, snakeheads, swamp eels, and relatives). Methods We used nearly 1000 ultra‐conserved elements (UCEs) and Sanger‐sequenced genes to infer a phylogeny with representatives of all major synbranchiform lineages and nearly two‐thirds of its known species diversity. Incorporating fossil calibrations, we inferred a time‐calibrated phylogeny to which we apply Bayesian methods of ancestral area reconstruction and test for diversification rate shifts. Results Analyses of UCE data provide a resolved phylogeny for major synbranchiform lineages. Divergence times support a most recent common ancestor of the entire clade approximately 79.2 million years ago. We infer significant increases in lineage diversification in both the spiny eels (Mastacembelidae) and the genus Betta (Osphronemidae). Main Conclusions Our results reject the hypothesis of Gondwanan vicariance explaining synbranchiform biogeography. Instead, our analyses reconstruct a southeast Asian origin of the entire clade and independent dispersal events to other continents by snakeheads, anabantids, and spiny eels, with no signal of elevated lineage diversification occurring after these invasions. Higher lineage diversification rates in spiny eels pre‐date their arrival to Africa, while the high diversification rates observed in Betta were initiated prior to the flooding of insular Sundaland in southeast Asia.