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      Mind the Outgroup and Bare Branches in Total-Evidence Dating: a Case Study of Pimpliform Darwin Wasps (Hymenoptera, Ichneumonidae)

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          Abstract

          Taxon sampling is a central aspect of phylogenetic study design, but it has received limited attention in the context of total-evidence dating, a widely used dating approach that directly integrates molecular and morphological information from extant and fossil taxa. We here assess the impact of commonly employed outgroup sampling schemes and missing morphological data in extant taxa on age estimates in a total-evidence dating analysis under the uniform tree prior. Our study group is Pimpliformes, a highly diverse, rapidly radiating group of parasitoid wasps of the family Ichneumonidae. We analyze a data set comprising 201 extant and 79 fossil taxa, including the oldest fossils of the family from the Early Cretaceous and the first unequivocal representatives of extant subfamilies from the mid-Paleogene. Based on newly compiled molecular data from ten nuclear genes and a morphological matrix that includes 222 characters, we show that age estimates become both older and less precise with the inclusion of more distant and more poorly sampled outgroups. These outgroups not only lack morphological and temporal information but also sit on long terminal branches and considerably increase the evolutionary rate heterogeneity. In addition, we discover an artifact that might be detrimental for total-evidence dating: “bare-branch attraction,” namely high attachment probabilities of certain fossils to terminal branches for which morphological data are missing. Using computer simulations, we confirm the generality of this phenomenon and show that a large phylogenetic distance to any of the extant taxa, rather than just older age, increases the risk of a fossil being misplaced due to bare-branch attraction. After restricting outgroup sampling and adding morphological data for the previously attracting, bare branches, we recover a Jurassic origin for Pimpliformes and Ichneumonidae. This first age estimate for the group not only suggests an older origin than previously thought but also that diversification of the crown group happened well before the Cretaceous-Paleogene boundary. Our case study demonstrates that in order to obtain robust age estimates, total-evidence dating studies need to be based on a thorough and balanced sampling of both extant and fossil taxa, with the aim of minimizing evolutionary rate heterogeneity and missing morphological information. [Bare-branch attraction; ichneumonids; fossils; morphological matrix; phylogeny; RoguePlots.]

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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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            MrBayes 3.2: Efficient Bayesian Phylogenetic Inference and Model Choice Across a Large Model Space

            Since its introduction in 2001, MrBayes has grown in popularity as a software package for Bayesian phylogenetic inference using Markov chain Monte Carlo (MCMC) methods. With this note, we announce the release of version 3.2, a major upgrade to the latest official release presented in 2003. The new version provides convergence diagnostics and allows multiple analyses to be run in parallel with convergence progress monitored on the fly. The introduction of new proposals and automatic optimization of tuning parameters has improved convergence for many problems. The new version also sports significantly faster likelihood calculations through streaming single-instruction-multiple-data extensions (SSE) and support of the BEAGLE library, allowing likelihood calculations to be delegated to graphics processing units (GPUs) on compatible hardware. Speedup factors range from around 2 with SSE code to more than 50 with BEAGLE for codon problems. Checkpointing across all models allows long runs to be completed even when an analysis is prematurely terminated. New models include relaxed clocks, dating, model averaging across time-reversible substitution models, and support for hard, negative, and partial (backbone) tree constraints. Inference of species trees from gene trees is supported by full incorporation of the Bayesian estimation of species trees (BEST) algorithms. Marginal model likelihoods for Bayes factor tests can be estimated accurately across the entire model space using the stepping stone method. The new version provides more output options than previously, including samples of ancestral states, site rates, site d N /d S rations, branch rates, and node dates. A wide range of statistics on tree parameters can also be output for visualization in FigTree and compatible software.
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              Geneious Basic: An integrated and extendable desktop software platform for the organization and analysis of sequence data

              Summary: The two main functions of bioinformatics are the organization and analysis of biological data using computational resources. Geneious Basic has been designed to be an easy-to-use and flexible desktop software application framework for the organization and analysis of biological data, with a focus on molecular sequences and related data types. It integrates numerous industry-standard discovery analysis tools, with interactive visualizations to generate publication-ready images. One key contribution to researchers in the life sciences is the Geneious public application programming interface (API) that affords the ability to leverage the existing framework of the Geneious Basic software platform for virtually unlimited extension and customization. The result is an increase in the speed and quality of development of computation tools for the life sciences, due to the functionality and graphical user interface available to the developer through the public API. Geneious Basic represents an ideal platform for the bioinformatics community to leverage existing components and to integrate their own specific requirements for the discovery, analysis and visualization of biological data. Availability and implementation: Binaries and public API freely available for download at http://www.geneious.com/basic, implemented in Java and supported on Linux, Apple OSX and MS Windows. The software is also available from the Bio-Linux package repository at http://nebc.nerc.ac.uk/news/geneiousonbl. Contact: peter@biomatters.com
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                Author and article information

                Contributors
                Role: Associate Editor
                Journal
                Syst Biol
                Syst Biol
                sysbio
                Systematic Biology
                Oxford University Press
                1063-5157
                1076-836X
                March 2021
                15 October 2020
                15 October 2020
                : 70
                : 2
                : 322-339
                Affiliations
                [1 ] Abteilung Wirbellose Tiere Invertebrates, Naturhistorisches Museum der Burgergemeinde Bern , Bernastrasse 15, 3005 Bern, Switzerland
                [2 ] Institute of Ecology and Evolution, Department of Biology, University of Bern , 3012 Bern, Switzerland
                [3 ] Department of Entomology, National Museum of Natural History , Washington, DC 20560, USA
                [4 ] Department of Life Sciences, Natural History Museum , London SW7 5BD, UK
                [5 ] Biodiversity Unit, University of Turku , Turku, Finland
                [6 ] Eben 21 , A-4202 Kirchschlag, Austria
                [7 ] Graduate School of Agricultural Science, Department of Agrobioscience, Kobe University , 657-8501 Japan
                [8 ] Department of Agroecology and Crop Production, Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague , 165 21 Prague 6, Suchdol, Czech Republic
                [9 ] Abteilung für Biowissenschaften, Naturhistorisches Museum Basel , 4051 Basel, Switzerland
                Author notes
                Correspondence to be sent to: Tamara Spasojevic, Department of Entomology, National Museum of Natural History, 10th St. & Constitution Ave. NW, Washington, DC 20560, USA; E-mail: spasojevic.ta@ 123456gmail.com
                Article
                syaa079
                10.1093/sysbio/syaa079
                7875445
                33057674
                2892ccb7-143f-4b13-8f8b-c52e9e3e3efe
                © The Author(s) 2020. Published by Oxford University Press on behalf of the Society of Systematic Biologists.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contactjournals.permissions@ 123456oup.com

                History
                : 28 October 2019
                : 02 October 2020
                : 02 October 2020
                Page count
                Pages: 18
                Funding
                Funded by: Swiss National Science Foundation, DOI 10.13039/501100001711;
                Funded by: SNSF, DOI 10.13039/501100001711;
                Award ID: PZ00P3_154791
                Funded by: SNSF, DOI 10.13039/501100001711;
                Award ID: P2BEP3_1882252
                Funded by: Stanislav Korenko by the Ministry of Education Youth and Sports of Czech Republic;
                Award ID: LTAUSA 19084
                Categories
                Regular Articles
                AcademicSubjects/SCI01130

                Animal science & Zoology
                Animal science & Zoology

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