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      Revealing environmentally driven population dynamics of an Arctic diatom using a novel microsatellite PoolSeq barcoding approach

      한글로보기

      https://www.riss.kr/link?id=O107075759

      • 저자
      • 발행기관
      • 학술지명
      • 권호사항
      • 발행연도

        2021년

      • 작성언어

        -

      • Print ISSN

        1462-2912

      • Online ISSN

        1462-2920

      • 등재정보

        SCIE;SCOPUS

      • 자료형태

        학술저널

      • 수록면

        3809-3824   [※수록면이 p5 이하이면, Review, Columns, Editor's Note, Abstract 등일 경우가 있습니다.]

      • 구독기관
        • 전북대학교 중앙도서관  
        • 성균관대학교 중앙학술정보관  
        • 부산대학교 중앙도서관  
        • 전남대학교 중앙도서관  
        • 제주대학교 중앙도서관  
        • 중앙대학교 서울캠퍼스 중앙도서관  
        • 인천대학교 학산도서관  
        • 숙명여자대학교 중앙도서관  
        • 서강대학교 로욜라중앙도서관  
        • 충남대학교 중앙도서관  
        • 한양대학교 백남학술정보관  
        • 이화여자대학교 중앙도서관  
        • 고려대학교 도서관  
      • ⓒ COPYRIGHT THE BRITISH LIBRARY BOARD: ALL RIGHT RESERVED
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      다국어 초록 (Multilingual Abstract)

      Ecological stability under environmental change is determined by both interspecific and intraspecific processes. Particularly for planktonic microorganisms, it is challenging to follow intraspecific dynamics over space and time. We propose a new method, microsatellite PoolSeq barcoding (MPB), for tracing allele frequency changes in protist populations. We successfully applied this method to experimental community incubations and field samples of the diatom Thalassiosira hyalina from the Arctic, a rapidly changing ecosystem. Validation of the method found compelling accuracy in comparison with established genotyping approaches within different diversity contexts. In experimental and environmental samples, we show that MPB can detect meaningful patterns of population dynamics, resolving allelic stability and shifts within a key diatom species in response to experimental treatments as well as different bloom phases and years. Through our novel MPB approach, we produced a large dataset of populations at different time‐points and locations with comparably little effort. Results like this can add insights into the roles of selection and plasticity in natural protist populations under stable experimental but also variable field conditions. Especially for organisms where genotype sampling remains challenging, MPB holds great potential to efficiently resolve eco‐evolutionary dynamics and to assess the mechanisms and limits of resilience to environmental stressors.
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      Ecological stability under environmental change is determined by both interspecific and intraspecific processes. Particularly for planktonic microorganisms, it is challenging to follow intraspecific dynamics over space and time. We propose a new metho...

      Ecological stability under environmental change is determined by both interspecific and intraspecific processes. Particularly for planktonic microorganisms, it is challenging to follow intraspecific dynamics over space and time. We propose a new method, microsatellite PoolSeq barcoding (MPB), for tracing allele frequency changes in protist populations. We successfully applied this method to experimental community incubations and field samples of the diatom Thalassiosira hyalina from the Arctic, a rapidly changing ecosystem. Validation of the method found compelling accuracy in comparison with established genotyping approaches within different diversity contexts. In experimental and environmental samples, we show that MPB can detect meaningful patterns of population dynamics, resolving allelic stability and shifts within a key diatom species in response to experimental treatments as well as different bloom phases and years. Through our novel MPB approach, we produced a large dataset of populations at different time‐points and locations with comparably little effort. Results like this can add insights into the roles of selection and plasticity in natural protist populations under stable experimental but also variable field conditions. Especially for organisms where genotype sampling remains challenging, MPB holds great potential to efficiently resolve eco‐evolutionary dynamics and to assess the mechanisms and limits of resilience to environmental stressors.

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