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1. Discovering research articles containing evolutionary timetrees by machine learning

   Stanojevic, M. ; Andjelkovic, J. ; Kasprowicz, A. ; Huuki, L.A. ; Chao, J. ; Hedges, S. B. ; Kumar, S. ; Obradovic, Z. ( April 2023 , Bioinformatics)

   Motivation: Timetrees depict evolutionary relationships between species and the geological times of their divergence. Hundreds of research articles containing timetrees are published in scientific journals every year. The TimeTree project has been manually locating, curating, and synthesizing timetrees from these articles for almost two decades into a TimeTree of Life, delivered through a unique, userfriendly web interface (timetree.org). The manual process of finding articles containing timetrees is becoming increasingly expensive and time-consuming. So, we have explored the effectiveness of textmining approaches and developed optimizations to find research articles containing timetrees automatically. Results: We have developed an optimized machine learning (ML) system to determine if a research article contains an evolutionary timetree appropriate for inclusion in the TimeTree resource. We found that BERT classification fine-tuned on whole-text articles achieved an F1 score of 0.67, which we increased to 0.88 by text-mining article excerpts surrounding the mentioning of figures. The new method is implemented in the TimeTreeFinder tool, TTF, which automatically processes millions of articles to discover timetree-containing articles. We estimate that the TTF tool would produce twice as many timetree-containing articles as those discovered manually, whose inclusion in the TimeTree database would potentially double the knowledge accessible to a wider community. Manual inspection showed that the precision on out-of-distribution recently-published articles is 87%. This automation will speed up the collection and curation of timetrees with much lower human and time costs. Availability: https://github.com/marija-stanojevic/time-tree-classification Contact: {marija.stanojevic, s.kumar, zoran.obradovic}@temple.edu Supplementary information: Supplementary data are available at Bioinformatics online 

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2. Discovering research articles containing evolutionary timetrees by machine learning

   https://doi.org/10.1093/bioinformatics/btad035  

   Stanojevic, Marija ; Andjelkovic, Jovan ; Kasprowicz, Adrienne ; Huuki, Louise A. ; Chao, Jennifer ; Hedges, S. Blair ; Kumar, Sudhir ; Obradovic, Zoran ; Wren, ed., Jonathan ( January 2023 , Bioinformatics)

   Timetrees depict evolutionary relationships between species and the geological times of their divergence. Hundreds of research articles containing timetrees are published in scientific journals every year. The TimeTree (TT) project has been manually locating, curating and synthesizing timetrees from these articles for almost two decades into a TimeTree of Life, delivered through a unique, user-friendly web interface (timetree.org). The manual process of finding articles containing timetrees is becoming increasingly expensive and time-consuming. So, we have explored the effectiveness of text-mining approaches and developed optimizations to find research articles containing timetrees automatically.

   We have developed an optimized machine learning system to determine if a research article contains an evolutionary timetree appropriate for inclusion in the TT resource. We found that BERT classification fine-tuned on whole-text articles achieved an F1 score of 0.67, which we increased to 0.88 by text-mining article excerpts surrounding the mentioning of figures. The new method is implemented in the TimeTreeFinder (TTF) tool, which automatically processes millions of articles to discover timetree-containing articles. We estimate that the TTF tool would produce twice as many timetree-containing articles as those discovered manually, whose inclusion in the TT database would potentially double the knowledge accessible to a wider community. Manual inspection showed that the precision on out-of-distribution recently published articles is 87%. This automation will speed up the collection and curation of timetrees with much lower human and time costs.

   https://github.com/marija-stanojevic/time-tree-classification.

   Supplementary data are available at Bioinformatics online.

    

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3. Data-driven speciation tree prior for better species divergence times in calibration-poor molecular phylogenies

   https://doi.org/10.1093/bioinformatics/btab307  

   Tao, Qiqing ; Barba-Montoya, Jose ; Kumar, Sudhir ( July 2021 , Bioinformatics)

   null (Ed.)

   Abstract Motivation Precise time calibrations needed to estimate ages of species divergence are not always available due to fossil records' incompleteness. Consequently, clock calibrations available for Bayesian dating analyses can be few and diffused, i.e. phylogenies are calibration-poor, impeding reliable inference of the timetree of life. We examined the role of speciation birth–death (BD) tree prior on Bayesian node age estimates in calibration-poor phylogenies and tested the usefulness of an informative, data-driven tree prior to enhancing the accuracy and precision of estimated times. Results We present a simple method to estimate parameters of the BD tree prior from the molecular phylogeny for use in Bayesian dating analyses. The use of a data-driven birth–death (ddBD) tree prior leads to improvement in Bayesian node age estimates for calibration-poor phylogenies. We show that the ddBD tree prior, along with only a few well-constrained calibrations, can produce excellent node ages and credibility intervals, whereas the use of an uninformative, uniform (flat) tree prior may require more calibrations. Relaxed clock dating with ddBD tree prior also produced better results than a flat tree prior when using diffused node calibrations. We also suggest using ddBD tree priors to improve the detection of outliers and influential calibrations in cross-validation analyses. These results have practical applications because the ddBD tree prior reduces the number of well-constrained calibrations necessary to obtain reliable node age estimates. This would help address key impediments in building the grand timetree of life, revealing the process of speciation and elucidating the dynamics of biological diversification. Availability and implementation An R module for computing the ddBD tree prior, simulated datasets and empirical datasets are available at https://github.com/cathyqqtao/ddBD-tree-prior. 

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4. Historical biogeography of Heteropterinae skippers via Beringian and post‐Tethyan corridors

   https://doi.org/10.1111/zsc.12457  

   Toussaint, Emmanuel F. A. ; Ellis, Emily A. ; Gott, Riley J. ; Warren, Andrew D. ; Dexter, Kelly M. ; Storer, Caroline ; Lohman, David J. ; Kawahara, Akito Y. ( November 2020 , Zoologica Scripta)

   Skippers are a species rich and widespread group of butterflies with evolutionary patterns and processes largely unstudied despite some recent efforts. Among Hesperiidae, the subfamily Heteropterinae is a moderately diverse clade comprising ca. 200 species distributed from North to South America and from Africa to the Palearctic region. While some regions are species rich, others are far less diverse. Using anchored phylogenomics, we infer a robust timetree and estimate ancestral ranges to understand the biogeographic history of these skippers. Inferences based on up to 383 exons recover a robust backbone for the subfamily along with the monophyly of all genera. Bayesian divergence time estimates suggest an origin of Heteropterinae in the late Eocene, ca. 40 million years ago. Maximum likelihood ancestral range estimates indicate an origin of the group in the New World. The eastern Palearctic was likely colonized via a Beringian route and a reverse colonization event resulted in two independent and extant American clades. We estimate a vicariant event between Central and South America that significantly predates estimates of the proto‐Caribbean seaway closure, indicating active overwater dispersal in the Oligocene. The colonization of Africa from the east Palearctic is synchronous with the closure of the Tethys Ocean, while the colonization of Madagascar appears to be comparatively recent. Our results shed light on the systematics and biogeography of Heteropterinae skippers and unveil the evolutionary history of a new leaf in the skipper tree‐of‐life.

    

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5. A Phylogenomic Supertree of Birds

   https://doi.org/10.3390/d11070109  

   Kimball, Rebecca T. ; Oliveros, Carl H. ; Wang, Ning ; White, Noor D. ; Barker, F. Keith ; Field, Daniel J. ; Ksepka, Daniel T. ; Chesser, R. Terry ; Moyle, Robert G. ; Braun, Michael J. ; et al ( July 2019 , Diversity)

   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. 

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