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      Phylogenomic analyses of echinoid diversification prompt a re-evaluation of their fossil record


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          Echinoids are key components of modern marine ecosystems. Despite a remarkable fossil record, the emergence of their crown group is documented by few specimens of unclear affinities, rendering their early history uncertain. The origin of sand dollars, one of its most distinctive clades, is also unclear due to an unstable phylogenetic context. We employ 18 novel genomes and transcriptomes to build a phylogenomic dataset with a near-complete sampling of major lineages. With it, we revise the phylogeny and divergence times of echinoids, and place their history within the broader context of echinoderm evolution. We also introduce the concept of a chronospace – a multidimensional representation of node ages – and use it to explore methodological decisions involved in time calibrating phylogenies. We find the choice of clock model to have the strongest impact on divergence times, while the use of site-heterogeneous models and alternative node prior distributions show minimal effects. The choice of loci has an intermediate impact, affecting mostly deep Paleozoic nodes, for which clock-like genes recover dates more congruent with fossil evidence. Our results reveal that crown group echinoids originated in the Permian and diversified rapidly in the Triassic, despite the relative lack of fossil evidence for this early diversification. We also clarify the relationships between sand dollars and their close relatives and confidently date their origins to the Cretaceous, implying ghost ranges spanning approximately 50 million years, a remarkable discrepancy with their rich fossil record.

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          Trimmomatic: a flexible trimmer for Illumina sequence data

          Motivation: Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data. Results: The value of NGS read preprocessing is demonstrated for both reference-based and reference-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested. Availability and implementation: Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at http://www.usadellab.org/cms/index.php?page=trimmomatic Contact: usadel@bio1.rwth-aachen.de Supplementary information: Supplementary data are available at Bioinformatics online.
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            MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability

            We report a major update of the MAFFT multiple sequence alignment program. This version has several new features, including options for adding unaligned sequences into an existing alignment, adjustment of direction in nucleotide alignment, constrained alignment and parallel processing, which were implemented after the previous major update. This report shows actual examples to explain how these features work, alone and in combination. Some examples incorrectly aligned by MAFFT are also shown to clarify its limitations. We discuss how to avoid misalignments, and our ongoing efforts to overcome such limitations.
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              IQ-TREE: A Fast and Effective Stochastic Algorithm for Estimating Maximum-Likelihood Phylogenies

              Large phylogenomics data sets require fast tree inference methods, especially for maximum-likelihood (ML) phylogenies. Fast programs exist, but due to inherent heuristics to find optimal trees, it is not clear whether the best tree is found. Thus, there is need for additional approaches that employ different search strategies to find ML trees and that are at the same time as fast as currently available ML programs. We show that a combination of hill-climbing approaches and a stochastic perturbation method can be time-efficiently implemented. If we allow the same CPU time as RAxML and PhyML, then our software IQ-TREE found higher likelihoods between 62.2% and 87.1% of the studied alignments, thus efficiently exploring the tree-space. If we use the IQ-TREE stopping rule, RAxML and PhyML are faster in 75.7% and 47.1% of the DNA alignments and 42.2% and 100% of the protein alignments, respectively. However, the range of obtaining higher likelihoods with IQ-TREE improves to 73.3-97.1%.

                Author and article information

                Role: Reviewing Editor
                Role: Senior Editor
                eLife Sciences Publications, Ltd
                22 March 2022
                : 11
                : e72460
                [1 ] Department of Earth & Planetary Sciences, Yale University ( https://ror.org/03v76x132) New Haven United States
                [2 ] Scripps Institution of Oceanography, University of California San Diego ( https://ror.org/04v7hvq31) La Jolla United States
                [3 ] Department of Earth Sciences, Natural History Museum ( https://ror.org/039zvsn29) London United Kingdom
                [4 ] University College London Center for Life’s Origins and Evolution ( https://ror.org/02jx3x895) London United Kingdom
                [5 ] Department of Invertebrate Zoology and Geology, California Academy of Sciences ( https://ror.org/02wb73912) San Francisco United States
                [6 ] Bader International Study Centre, Queen's University, Herstmonceux Castle East Sussex United Kingdom
                [7 ] Departamento de Bioquímica y Biología Molecular, Facultad de Ciencias Biológicas, Universidad de Concepción ( https://ror.org/0460jpj73) Concepción Chile
                [8 ] School of Zoology, Faculty of Life Sciences, Tel Aviv University ( https://ror.org/04mhzgx49) Tel Aviv Israel
                [9 ] Steinhardt Museum of Natural History Tel-Aviv Israel
                [10 ] Department of Geology and Palaeontology, Natural History Museum Vienna ( https://ror.org/01tv5y993) Vienna Austria
                Vanderbilt University ( https://ror.org/02vm5rt34) United States
                Pennsylvania State University ( https://ror.org/04p491231) United States
                Vanderbilt University ( https://ror.org/02vm5rt34) United States
                Vanderbilt University ( https://ror.org/02vm5rt34) United States
                University of Goettingen Spain
                Author information
                © 2022, Mongiardino Koch et al

                This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

                : 24 July 2021
                : 03 March 2022
                Funded by: Yale Institute for Biospheric Studies;
                Award ID: Doctoral Dissertation Improvement Grant
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100006069, Society of Systematic Biologists;
                Award ID: Graduate Student Research Award
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100002428, Austrian Science Fund;
                Award ID: P 29708-B25
                Award Recipient :
                Funded by: Agencia Nacional de Investigación;
                Award ID: PAI79170033
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000001, National Science Foundation;
                Award ID: DEB-2036186
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100008982, National Science Foundation;
                Award ID: DEB-2036298
                Award Recipient :
                The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
                Research Article
                Evolutionary Biology
                Custom metadata
                Phylogenomics of sea urchins clarifies their origins and diversification history, reveals surprising discrepancies with their rich fossil record, and serves as basis to explore the sensitivity of time calibration analysis.

                Life sciences
                echinoidea,sea urchins,sand dollars,phylogenomics,time calibration,site-heterogeneous models,divergence time estimation,other


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