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      A survey of Hebeloma (Hymenogastraceae) in Greenland

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          This is the first study exclusively dedicated to the study of Hebeloma in Greenland. It is based on almost 400 collections, the great majority of which were collected by three of the co-authors over a period of 40 years and were lodged in the fungarium of the Natural History Museum in Copenhagen. The material was identified using molecular and morphological methods. In total, 28 species were recognized, 27 belonging to three sections, H. sects Hebeloma , Denudata and Velutipes . One species sampled was new to science and is here described as H. arcticum . For all species, a description, a distribution map within Greenland and macro and microphotographs are presented. A key is provided for the 28 species. The distribution of species within Greenland is discussed. The findings are placed in the context of studies of arctic and alpine Hebeloma from other parts of the world where comparable data exist. Notably, H. grandisporum , H. louiseae and H. islandicum , previously only known from Romania, Svalbard, Iceland or Norway, respectively, have been found in Greenland. The latter is also the only species encountered that does not belong to any of the above sections. Hebeloma excedens and H. colvinii – for the latter we here publish the first modern description – are to date only known from continental North America and now Greenland.

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          RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies

          Motivation: Phylogenies are increasingly used in all fields of medical and biological research. Moreover, because of the next-generation sequencing revolution, datasets used for conducting phylogenetic analyses grow at an unprecedented pace. RAxML (Randomized Axelerated Maximum Likelihood) is a popular program for phylogenetic analyses of large datasets under maximum likelihood. Since the last RAxML paper in 2006, it has been continuously maintained and extended to accommodate the increasingly growing input datasets and to serve the needs of the user community. Results: I present some of the most notable new features and extensions of RAxML, such as a substantial extension of substitution models and supported data types, the introduction of SSE3, AVX and AVX2 vector intrinsics, techniques for reducing the memory requirements of the code and a plethora of operations for conducting post-analyses on sets of trees. In addition, an up-to-date 50-page user manual covering all new RAxML options is available. Availability and implementation: The code is available under GNU GPL at https://github.com/stamatak/standard-RAxML. Contact: alexandros.stamatakis@h-its.org Supplementary information: Supplementary data are available at Bioinformatics online.
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            MAFFT online service: multiple sequence alignment, interactive sequence choice and visualization

            Abstract This article describes several features in the MAFFT online service for multiple sequence alignment (MSA). As a result of recent advances in sequencing technologies, huge numbers of biological sequences are available and the need for MSAs with large numbers of sequences is increasing. To extract biologically relevant information from such data, sophistication of algorithms is necessary but not sufficient. Intuitive and interactive tools for experimental biologists to semiautomatically handle large data are becoming important. We are working on development of MAFFT toward these two directions. Here, we explain (i) the Web interface for recently developed options for large data and (ii) interactive usage to refine sequence data sets and MSAs.
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              Application of phylogenetic networks in evolutionary studies.

              The evolutionary history of a set of taxa is usually represented by a phylogenetic tree, and this model has greatly facilitated the discussion and testing of hypotheses. However, it is well known that more complex evolutionary scenarios are poorly described by such models. Further, even when evolution proceeds in a tree-like manner, analysis of the data may not be best served by using methods that enforce a tree structure but rather by a richer visualization of the data to evaluate its properties, at least as an essential first step. Thus, phylogenetic networks should be employed when reticulate events such as hybridization, horizontal gene transfer, recombination, or gene duplication and loss are believed to be involved, and, even in the absence of such events, phylogenetic networks have a useful role to play. This article reviews the terminology used for phylogenetic networks and covers both split networks and reticulate networks, how they are defined, and how they can be interpreted. Additionally, the article outlines the beginnings of a comprehensive statistical framework for applying split network methods. We show how split networks can represent confidence sets of trees and introduce a conservative statistical test for whether the conflicting signal in a network is treelike. Finally, this article describes a new program, SplitsTree4, an interactive and comprehensive tool for inferring different types of phylogenetic networks from sequences, distances, and trees.

                Author and article information

                Pensoft Publishers
                19 April 2021
                : 79
                : 17-118
                [1 ] Staatliches Museum für Naturkunde Stuttgart, Rosenstein 1, D-70191 Stuttgart, Germany
                [2 ] Rue Pére de Deken 19, B-1040 Bruxelles, Belgium
                [3 ] Royal Holloway College, University of London, Egham, UK
                [4 ] Plantentuin Meise, Nieuwelaan 38, B-1860 Meise, Belgium
                [5 ] Sensommervej 142, 8600 Silkeborg, Denmark
                [6 ] Hauchsvej 15, 1825 Frederiksberg, Denmark
                [7 ] Frederik VII´s Vej 29, 3450 Allerød, Denmark
                Author notes
                Corresponding author: Ursula Eberhardt ( ursula.eberhardt@ 123456smns-bw.de )

                Academic editor: M. P. Martín

                Ursula Eberhardt, Henry J. Beker, Torbjørn Borgen, Henning Knudsen, Nicole Schütz, Steen A. Elborne

                This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                Expeditions: Aage V. Jensen Foundation Other: none
                Biodiversity & Conservation
                DNA barcoding
                ecosystems & natural spaces


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