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1. 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)

   Abstract MotivationTimetrees 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. ResultsWe 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. Availability and implementationhttps://github.com/marija-stanojevic/time-tree-classification. Supplementary informationSupplementary data are available at Bioinformatics online. 

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2. Completing a molecular timetree of apes and monkeys

   https://doi.org/10.3389/fbinf.2023.1284744  

   Craig, Jack M; Bamba, Grace L; Barba-Montoya, Jose; Hedges, S Blair; Kumar, Sudhir (December 2023, Frontiers in Bioinformatics)

   The primate infraorder Simiiformes, comprising Old and New World monkeys and apes, includes the most well-studied species on earth. Their most comprehensive molecular timetree, assembled from thousands of published studies, is found in the TimeTree database and contains 268 simiiform species. It is, however, missing 38 out of 306 named species in the NCBI taxonomy for which at least one molecular sequence exists in the NCBI GenBank. We developed a three-pronged approach to expanding the timetree of Simiiformes to contain 306 species. First, molecular divergence times were searched and found for 21 missing species in timetrees published across 15 studies. Second, untimed molecular phylogenies were searched and scaled to time using relaxed clocks to add four more species. Third, we reconstructed ten new timetrees from genetic data in GenBank, allowing us to incorporate 13 more species. Finally, we assembled the most comprehensive molecular timetree of Simiiformes containing all 306 species for which any molecular data exists. We compared the species divergence times with those previously imputed using statistical approaches in the absence of molecular data. The latter data-less imputed times were not significantly correlated with those derived from the molecular data. Also, using phylogenies containing imputed times produced different trends of evolutionary distinctiveness and speciation rates over time than those produced using the molecular timetree. These results demonstrate that more complete clade-specific timetrees can be produced by analyzing existing information, which we hope will encourage future efforts to fill in the missing taxa in the global timetree of life. 

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3. Completing a molecular timetree of primates

   https://doi.org/10.3389/fbinf.2024.1495417  

   Craig, Jack M; Hedges, S Blair; Kumar, Sudhir (December 2024, Frontiers in Bioinformatics)

   Primates, consisting of apes, monkeys, tarsiers, and lemurs, are among the most charismatic and well-studied animals on Earth, yet there is no taxonomically complete molecular timetree for the group. Combining the latest large-scale genomic primate phylogeny of 205 recognized species with the 400-species literature consensus tree available fromTimeTree.orgyields a phylogeny of just 405 primates, with 50 species still missing despite having molecular sequence data in the NCBI GenBank. In this study, we assemble a timetree of 455 primates, incorporating every species for which molecular data are available. We use a synthetic approach consisting of a literature review for published timetrees,de novodating of untimed trees, and assembly of timetrees from novel alignments. The resulting near-complete molecular timetree of primates allows testing of two long-standing alternate hypotheses for the origins of primate biodiversity: whether species richness arises at a constant rate, in which case older clades have more species, or whether some clades exhibit faster rates of speciation than others, in which case, these fast clades would be more species-rich. Consistent with other large-scale macroevolutionary analyses, we found that the speciation rate is similar across the primate tree of life, albeit with some variation in smaller clades. 

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4. The timetree of phytoplasmas reveals new insights into the relationships with their insect and plant hosts

   Trivellone, Valeria; Cao, Yanghui; Dietrich, Christopher H. (June 2019, Phytopathogenic mollicutes)

   Phytoplasmas are a diverse monophyletic group of phytopathogenic bacteria. No attempts have yet been made to the estimate the divergence times of phytoplasma lineages. Reltime molecular divergence time analyses using 16S rRNA gene sequence data of Acholeplasmataceae was performed. The timetree of phytoplasmas, provided here for the first time, and based on prior divergence time estimates for two nodes within the Mollicutes, estimates the split between phytoplasma and Acholeplasma at about 663 million years ago (Ma), and initial diversification of the crown phytoplasma clade at about 330 Ma. Overall, these results suggest that phytoplasmas have been associated with insect and plant hosts at least since the carboniferous period. 

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5. 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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