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  • 1. Ernst, Mario
    et al.
    Jønsson, Knud A.
    Ericson, Per G. P.
    Swedish Museum of Natural History, Department of Bioinformatics and Genetics.
    Blom, Mozes P. K.
    Irestedt, Martin
    Swedish Museum of Natural History, Department of Bioinformatics and Genetics.
    Utilizing museomics to trace the complex history and species boundaries in an avian-study system of conservation concern2022In: Heredity, ISSN 0018-067X, E-ISSN 1365-2540, Vol. 128, no 3, p. 159-168Article in journal (Refereed)
    Abstract [en]

    A taxonomic classification that accurately captures evolutionary history is essential for conservation. Genomics provides powerful tools for delimiting species and understanding their evolutionary relationships. This allows for a more accurate and detailed view on conservation status compared with other, traditionally used, methods. However, from a practical and ethical perspective, gathering sufficient samples for endangered taxa may be difficult. Here, we use museum specimens to trace the evolutionary history and species boundaries in an Asian oriole clade. The endangered silver oriole has long been recognized as a distinct species based on its unique coloration, but a recent study suggested that it might be nested within the maroon oriole-species complex. To evaluate species designation, population connectivity, and the corresponding conservation implications, we assembled a de novo genome and used whole-genome resequencing of historical specimens. Our results show that the silver orioles form a monophyletic lineage within the maroon oriole complex and that maroon and silver forms continued to interbreed after initial divergence, but do not show signs of recent gene flow. Using a genome scan, we identified genes that may form the basis for color divergence and act as reproductive barriers. Taken together, our results confirm the species status of the silver oriole and highlight that taxonomic revision of the maroon forms is urgently needed. Our study demonstrates how genomics and Natural History Collections (NHC) can be utilized to shed light on the taxonomy and evolutionary history of natural populations and how such insights can directly benefit conservation practitioners when assessing wild populations.

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  • 2.
    Irestedt, Martin
    et al.
    Swedish Museum of Natural History, Department of Bioinformatics and Genetics. Department of Bioinformatics and Genetics Swedish Museum of Natural History Stockholm Sweden.
    Thörn, Filip
    Swedish Museum of Natural History, Department of Bioinformatics and Genetics. Department of Bioinformatics and Genetics Swedish Museum of Natural History Stockholm Sweden;Department of Zoology Stockholm University Stockholm Sweden.
    Müller, Ingo A.
    Swedish Museum of Natural History, Department of Bioinformatics and Genetics. Department of Bioinformatics and Genetics Swedish Museum of Natural History Stockholm Sweden;Department of Zoology Stockholm University Stockholm Sweden.
    Jønsson, Knud A.
    Natural History Museum of Denmark University of Copenhagen Copenhagen Denmark.
    Ericson, Per G. P.
    Swedish Museum of Natural History, Department of Bioinformatics and Genetics. Department of Bioinformatics and Genetics Swedish Museum of Natural History Stockholm Sweden.
    Blom, Mozes P. K.
    Museum für Naturkunde Leibniz Institut für Evolutions‐ und Biodiversitätsforschung Berlin Germany.
    A guide to avian museomics: Insights gained from resequencing hundreds of avian study skins2022In: Molecular Ecology Resources, ISSN 1755-098X, E-ISSN 1755-0998, Vol. 22, no 7, p. 2672-2684Article in journal (Refereed)
    Abstract [en]

    Biological specimens in natural history collections constitute a massive repository of genetic information. Many specimens have been collected in areas in which they no longer exist or in areas where present-day collecting is not possible. There are also specimens in collections representing populations or species that have gone extinct. Furthermore, species or populations may have been sampled throughout an extensive time period, which is particularly valuable for studies of genetic change through time. With the advent of high-throughput sequencing, natural history museum resources have become accessible for genomic research. Consequently, these unique resources are increasingly being used across many fields of natural history. In this paper, we summarize our experiences of resequencing hundreds of genomes from historical avian museum specimens. We publish the protocols we have used and discuss the entire workflow from sampling and laboratory procedures, to the bioinformatic processing of historical specimen data.

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  • 3.
    Kennedy, Jonathan D.
    et al.
    Natural History Museum of Denmark University of Copenhagen Copenhagen Ø Denmark.
    Marki, Petter Z.
    Natural History Museum of Denmark University of Copenhagen Copenhagen Ø Denmark;Division of Research Management University of Agder Kristiansand Norway.
    Reeve, Andrew H.
    Natural History Museum of Denmark University of Copenhagen Copenhagen Ø Denmark.
    Blom, Mozes P. K.
    Museum für Naturkunde Berlin Leibniz Institut für Evolutions und Biodiversitätsforschung Berlin Germany.
    Prawiradilaga, Dewi M.
    Museum Zoologicum Bogoriense LIPI/The National Research and Innovation Agency of the Republic of Indonesia (BRIN) Cibinong Science Center Cibinong Indonesia.
    Haryoko, Tri
    Museum Zoologicum Bogoriense LIPI/The National Research and Innovation Agency of the Republic of Indonesia (BRIN) Cibinong Science Center Cibinong Indonesia.
    Koane, Bonny
    The New Guinea Binatang Research Centre Madang Papua New Guinea.
    Kamminga, Pepijn
    <idGroup xmlns="http://www.wiley.com/namespaces/wiley"> <id type="ringgold" value="4503"></id> </idGroup> Naturalis Biodiversity Center Leiden The Netherlands.
    Irestedt, Martin
    Swedish Museum of Natural History, Department of Bioinformatics and Genetics. Department of Bioinformatics and Genetics Swedish Museum of Natural History Stockholm Sweden.
    Jønsson, Knud A.
    Natural History Museum of Denmark University of Copenhagen Copenhagen Ø Denmark.
    Diversification and community assembly of the world’s largest tropical island2022In: Global Ecology and Biogeography, ISSN 1466-822X, E-ISSN 1466-8238, Vol. 31, no 6, p. 1078-1089Article in journal (Refereed)
    Abstract [en]

    Aim

    The species diversity and endemism of tropical biotas are major contributors to global biodiversity, but the factors underlying the formation of these systems remain poorly understood.

    Location

    The world's largest tropical island, New Guinea.

    Time period

    Miocene to present.

    Major taxa studied

    Passerine birds.

    Methods

    We first generated a species-level phylogeny of all native breeding passerine birds to analyse spatial and elevational patterns of species richness, species age and phylogenetic diversity. Second, we used an existing dataset on bill morphology to analyse spatial and elevational patterns of functional diversity.

    Results

    The youngest New Guinean species are principally distributed in the lowlands and outlying mountain ranges, with the lowlands also maintaining the majority of non-endemic species. In contrast, many species occurring in the central mountain range are phylogenetically distinct, range-restricted, endemic lineages. Centres of accumulation for the oldest species are in montane forest, with these taxa having evolved unique bill forms in comparison to the remaining New Guinean species. For the morphological generalists, attaining a highland distribution does not necessarily represent the end to dispersal and diversification, because a number of new species have formed in the outlying mountain ranges, following recent colonization from the central range.

    Main conclusions

    We conclude that a general model of tropical montane diversification is that lineages commonly colonize the lowlands, shifting their ranges upslope through time to become range-restricted montane forest endemics, attaining novel functional adaptations to these environments.

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  • 4.
    Peona, Valentina
    et al.
    Department of Ecology and Genetics—Evolutionary Biology Science for Life Laboratories Uppsala University Uppsala Sweden;Department of Organismal Biology—Systematic Biology Science for Life Laboratories Uppsala University Uppsala Sweden.
    Blom, Mozes P. K.
    Department of Bioinformatics and Genetics Swedish Museum of Natural History Stockholm Sweden;Museum für Naturkunde Leibniz Institut für Evolutions‐ und Biodiversitätsforschung Berlin Germany.
    Xu, Luohao
    Department of Neurosciences and Developmental Biology University of Vienna Vienna Austria.
    Burri, Reto
    Department of Population Ecology Institute of Ecology and Evolution Friedrich‐Schiller‐University Jena Jena Germany.
    Sullivan, Shawn
    Phase Genomics Seattle WA USA.
    Bunikis, Ignas
    Department of Immunology, Genetics and Pathology Science for Life Laboratory Uppsala Genome CenterUppsala University Uppsala Sweden.
    Liachko, Ivan
    Phase Genomics Seattle WA USA.
    Haryoko, Tri
    Research Centre for Biology Museum Zoologicum BogorienseIndonesian Institute of Sciences (LIPI) Cibinong Indonesia.
    Jønsson, Knud A.
    Natural History Museum of Denmark University of Copenhagen Copenhagen Denmark.
    Zhou, Qi
    Department of Neurosciences and Developmental Biology University of Vienna Vienna Austria;MOE Laboratory of Biosystems Homeostasis &amp; Protection Life Sciences Institute Zhejiang University Hangzhou China;Center for Reproductive Medicine The 2nd Affiliated Hospital School of Medicine Zhejiang University Hangzhou China.
    Irestedt, Martin
    Swedish Museum of Natural History, Department of Bioinformatics and Genetics. Department of Bioinformatics and Genetics Swedish Museum of Natural History Stockholm Sweden.
    Suh, Alexander
    Department of Ecology and Genetics—Evolutionary Biology Science for Life Laboratories Uppsala University Uppsala Sweden;Department of Organismal Biology—Systematic Biology Science for Life Laboratories Uppsala University Uppsala Sweden;School of Biological Sciences—Organisms and the Environment University of East Anglia Norwich UK.
    Identifying the causes and consequences of assembly gaps using a multiplatform genome assembly of a bird‐of‐paradise2020In: Molecular Ecology Resources, ISSN 1755-098X, E-ISSN 1755-0998, Vol. 21, no 1, p. 263-286Article in journal (Refereed)
    Abstract [en]

    Genome assemblies are currently being produced at an impressive rate by consortia and individual laboratories. The low costs and increasing efficiency of sequencing technologies now enable assembling genomes at unprecedented quality and contiguity. However, the difficulty in assembling repeat-rich and GC-rich regions (genomic “dark matter”) limits insights into the evolution of genome structure and regulatory networks. Here, we compare the efficiency of currently available sequencing technologies (short/linked/long reads and proximity ligation maps) and combinations thereof in assembling genomic dark matter. By adopting different de novo assembly strategies, we compare individual draft assemblies to a curated multiplatform reference assembly and identify the genomic features that cause gaps within each assembly. We show that a multiplatform assembly implementing long-read, linked-read and proximity sequencing technologies performs best at recovering transposable elements, multicopy MHC genes, GC-rich microchromosomes and the repeat-rich W chromosome. Telomere-to-telomere assemblies are not a reality yet for most organisms, but by leveraging technology choice it is now possible to minimize genome assembly gaps for downstream analysis. We provide a roadmap to tailor sequencing projects for optimized completeness of both the coding and noncoding parts of nonmodel genomes.

  • 5.
    Peona, Valentina
    et al.
    Department of Organismal Biology – Systematic Biology Science for Life Laboratory Uppsala University Uppsala Sweden.
    Kutschera, Verena E.
    Department of Biochemistry and Biophysics National Bioinformatics Infrastructure Sweden Science for Life Laboratory Stockholm University Solna Sweden.
    Blom, Mozes P. K.
    Department of Bioinformatics and Genetics Swedish Museum of Natural History Stockholm Sweden;Museum für Naturkunde Leibniz Institut für Evolutions‐ und Biodiversitätsforschung Berlin Germany.
    Irestedt, Martin
    Swedish Museum of Natural History, Department of Bioinformatics and Genetics. Department of Bioinformatics and Genetics Swedish Museum of Natural History Stockholm Sweden.
    Suh, Alexander
    Department of Organismal Biology – Systematic Biology Science for Life Laboratory Uppsala University Uppsala Sweden;School of Biological Sciences—Organisms and the Environment University of East Anglia Norwich UK.
    Satellite DNA evolution in Corvoidea inferred from short and long reads2022In: Molecular Ecology, ISSN 0962-1083, E-ISSN 1365-294XArticle in journal (Refereed)
    Abstract [en]

    Satellite DNA (satDNA) is a fast-evolving portion of eukaryotic genomes. The homogeneous and repetitive nature of such satDNA causes problems during the assembly of genomes, and therefore it is still difficult to study it in detail in nonmodel organisms as well as across broad evolutionary timescales. Here, we combined the use of short- and long-read data to explore the diversity and evolution of satDNA between individuals of the same species and between genera of birds spanning ~40 millions of years of bird evolution using birds-of-paradise (Paradisaeidae) and crow (Corvus) species. These avian species highlighted the presence of a GC-rich Corvoidea satellitome composed of 61 satellite families and provided a set of candidate satDNA monomers for being centromeric on the basis of length, abundance, homogeneity and transcription. Surprisingly, we found that the satDNA of crow species rapidly diverged between closely related species while the satDNA appeared more similar between birds-of-paradise species belonging to different genera.

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