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      Ice-Age Climate Adaptations Trap the Alpine Marmot in a State of Low Genetic Diversity

      brief-report
      1 , 2 , 3 , 4 , 5 , 6 , 7 , 6 , 5 , 8 , 5 , 9 , 10 , 5 , 11 , 12 , 13 , 14 , 9 , 15 , 9 , 16 , 3 , 9 , 3 , 17 , 18 , 9 , 12 , 19 , 20 , 21 , 21 , 22 , 23 , 5 , 23 , 3 , 9 , 16 , 23 , 24 ,
      Current Biology
      Cell Press
      climate adaptation, Alpine marmot, low genetic diversity, NUMT, reference genome, ice age, pleistocene, migration, large population size, lipidomics

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          Summary

          Some species responded successfully to prehistoric changes in climate [ 1, 2], while others failed to adapt and became extinct [ 3]. The factors that determine successful climate adaptation remain poorly understood. We constructed a reference genome and studied physiological adaptations in the Alpine marmot ( Marmota marmota), a large ground-dwelling squirrel exquisitely adapted to the “ice-age” climate of the Pleistocene steppe [ 4, 5]. Since the disappearance of this habitat, the rodent persists in large numbers in the high-altitude Alpine meadow [ 6, 7]. Genome and metabolome showed evidence of adaptation consistent with cold climate, affecting white adipose tissue. Conversely, however, we found that the Alpine marmot has levels of genetic variation that are among the lowest for mammals, such that deleterious mutations are less effectively purged. Our data rule out typical explanations for low diversity, such as high levels of consanguineous mating, or a very recent bottleneck. Instead, ancient demographic reconstruction revealed that genetic diversity was lost during the climate shifts of the Pleistocene and has not recovered, despite the current high population size. We attribute this slow recovery to the marmot’s adaptive life history. The case of the Alpine marmot reveals a complicated relationship between climatic changes, genetic diversity, and conservation status. It shows that species of extremely low genetic diversity can be very successful and persist over thousands of years, but also that climate-adapted life history can trap a species in a persistent state of low genetic diversity.

          Highlights

          • The Alpine marmot is among the least genomically diverse animal species

          • Its diversity was lost during consecutive ice-age climate-related events

          • An extreme lifestyle hampered the subsequent recovery of genetic variation

          • Alpine marmots show why large populations can coexist with very low genetic variation

          Abstract

          Despite being highly abundant and well adapted, Gossmann et al. report that the Alpine marmot is among the least genetically diverse animal species. The low diversity is found to be the consequence of consecutive, climate-related events, including long-term extreme niche adaptation, that also greatly retarded the recovery of its genetic diversity.

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          Most cited references43

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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            PanTHERIA: a species-level database of life history, ecology, and geography of extant and recently extinct mammals

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              eggNOG v4.0: nested orthology inference across 3686 organisms

              With the increasing availability of various ‘omics data, high-quality orthology assignment is crucial for evolutionary and functional genomics studies. We here present the fourth version of the eggNOG database (available at http://eggnog.embl.de) that derives nonsupervised orthologous groups (NOGs) from complete genomes, and then applies a comprehensive characterization and analysis pipeline to the resulting gene families. Compared with the previous version, we have more than tripled the underlying species set to cover 3686 organisms, keeping track with genome project completions while prioritizing the inclusion of high-quality genomes to minimize error propagation from incomplete proteome sets. Major technological advances include (i) a robust and scalable procedure for the identification and inclusion of high-quality genomes, (ii) provision of orthologous groups for 107 different taxonomic levels compared with 41 in eggNOGv3, (iii) identification and annotation of particularly closely related orthologous groups, facilitating analysis of related gene families, (iv) improvements of the clustering and functional annotation approach, (v) adoption of a revised tree building procedure based on the multiple alignments generated during the process and (vi) implementation of quality control procedures throughout the entire pipeline. As in previous versions, eggNOGv4 provides multiple sequence alignments and maximum-likelihood trees, as well as broad functional annotation. Users can access the complete database of orthologous groups via a web interface, as well as through bulk download.
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                Author and article information

                Contributors
                Journal
                Curr Biol
                Curr. Biol
                Current Biology
                Cell Press
                0960-9822
                1879-0445
                20 May 2019
                20 May 2019
                : 29
                : 10
                : 1712-1720.e7
                Affiliations
                [1 ]University of Sheffield, Department of Animal and Plant Sciences, Sheffield S10 2TN, UK
                [2 ]Bielefeld University, Department of Animal Behaviour, 33501 Bielefeld, Germany
                [3 ]Molecular Biology of Metabolism Laboratory, The Francis Crick Institute, 1 Midland Road, London NW1 1AT, UK
                [4 ]Centre for Genomic Research, Institute of Integrative Biology, University of Liverpool, Biosciences Building, Crown Street, Liverpool L69 7ZB, UK
                [5 ]Max Planck Institute for Molecular Genetics, Sequencing Core Facility, Ihnestrasse 73, 14195 Berlin, Germany
                [6 ]IRHS, Université d’Angers, INRA, Agrocampus-Ouest, SFR 4207 QuaSaV, 49071 Beaucouzé, France
                [7 ]BIOGECO, INRA, Université de Bordeaux, 69 Route d'Arcachon, 33612 Cestas, France
                [8 ]Department of Ecophysiology and Aquaculture, Leibniz-Institute of Freshwater Ecology and Inland Fisheries, 12587 Berlin, Germany
                [9 ]Department of Biochemistry and Cambridge Systems Biology Centre, University of Cambridge, 80 Tennis Court Road, Cambridge CB2 1GA, UK
                [10 ]Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds LS2 9JT, UK
                [11 ]Division of Medical Biochemistry, Medical University of Innsbruck, 6020 Innsbruck, Austria
                [12 ]European Molecular Biology Laboratory (EMBL), 69117 Heidelberg, Germany
                [13 ]Earlham Institute, Norwich Research Park, Norwich NR4 7UZ, UK
                [14 ]Gut Health and Microbes Programme, Quadram Institute, Norwich Research Park, Norwich NR4 7UQ, UK
                [15 ]Institute of Avian Research, 26386 Wilhelmshaven, Germany
                [16 ]Department of Biochemistry, Charitè, Am Chariteplatz 1, 10117 Berlin, Germany
                [17 ]Department of Biology and Biological Engineering, Chalmers University of Technology, 412 96 Göteborg, Sweden
                [18 ]Science for Life Laboratory, KTH - Royal Institute of Technology, Stockholm 171 65, Sweden
                [19 ]Max-Delbrück-Centre for Molecular Medicine, 13092 Berlin, Germany
                [20 ]Molecular Medicine Partnership Unit, 69120 Heidelberg, Germany
                [21 ]Université de Lyon, F-69000, Lyon; Université Lyon 1; CNRS, UMR 5558, Laboratoire de Biométrie et Biologie Evolutive, 69622 Villeurbanne, France
                [22 ]Department of Genetics, University of Cambridge, Cambridge CB2 3EH, UK
                Author notes
                []Corresponding author markus.ralser@ 123456crick.ac.uk
                [23]

                These authors contributed equally

                [24]

                Lead Contact

                Article
                S0960-9822(19)30418-X
                10.1016/j.cub.2019.04.020
                6538971
                31080084
                77fed35b-85dc-4e31-9abd-43df88b9b3cf
                © 2019 The Author(s)

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

                History
                : 6 December 2018
                : 16 February 2019
                : 9 April 2019
                Categories
                Article

                Life sciences
                climate adaptation,alpine marmot,low genetic diversity,numt,reference genome,ice age,pleistocene,migration,large population size,lipidomics

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