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A transcriptomic analysis of land-use impacts on the oyster, Crassostrea virginica, in the South Atlantic bight

Authors

  • ROBERT W. CHAPMAN,

    1. South Carolina Department of Natural Resources, PO Box 12559 Charleston, SC 29422-2559, USA
    2. Marine Biomedicine and Environmental Science Center, Medical University of South Carolina, 331 Fort Johnson Road, Charleston, SC 29412, USA
    3. The Grice Marine Laboratory, College of Charleston, 221 Fort Johnson Road, Charleston, SC 29412, USA
    4. The Hollings Marine Laboratory, 331 Fort Johnson Road, Charleston, SC 29412, USA
    5. The Clemson University Genomics Institute, Clemson, SC 29412, USA
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  • ANNALAURA MANCIA,

    1. Marine Biomedicine and Environmental Science Center, Medical University of South Carolina, 331 Fort Johnson Road, Charleston, SC 29412, USA
    2. The Hollings Marine Laboratory, 331 Fort Johnson Road, Charleston, SC 29412, USA
    3. Department of Experimental Evolutionary Biology, University of Bologna, Via Selmi 3, Bologna 40126, Italy
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  • MARION BEAL,

    1. South Carolina Department of Natural Resources, PO Box 12559 Charleston, SC 29422-2559, USA
    2. The Hollings Marine Laboratory, 331 Fort Johnson Road, Charleston, SC 29412, USA
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  • ARTUR VELOSO,

    1. The Grice Marine Laboratory, College of Charleston, 221 Fort Johnson Road, Charleston, SC 29412, USA
    2. The Hollings Marine Laboratory, 331 Fort Johnson Road, Charleston, SC 29412, USA
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  • CHARLES RATHBURN,

    1. The Grice Marine Laboratory, College of Charleston, 221 Fort Johnson Road, Charleston, SC 29412, USA
    2. The Hollings Marine Laboratory, 331 Fort Johnson Road, Charleston, SC 29412, USA
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  • ANNE BLAIR,

    1. The Hollings Marine Laboratory, 331 Fort Johnson Road, Charleston, SC 29412, USA
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  • DENISE SANGER,

    1. The Hollings Marine Laboratory, 331 Fort Johnson Road, Charleston, SC 29412, USA
    2. South Carolina Sea Grant Consortium, Charleston, SC 29412, USA
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  • A. F. HOLLAND,

    1. The Hollings Marine Laboratory, 331 Fort Johnson Road, Charleston, SC 29412, USA
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  • GREGORY W. WARR,

    1. Marine Biomedicine and Environmental Science Center, Medical University of South Carolina, 331 Fort Johnson Road, Charleston, SC 29412, USA
    2. The Grice Marine Laboratory, College of Charleston, 221 Fort Johnson Road, Charleston, SC 29412, USA
    3. The Hollings Marine Laboratory, 331 Fort Johnson Road, Charleston, SC 29412, USA
    4. The Clemson University Genomics Institute, Clemson, SC 29412, USA
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    • ‡‡

      Present address: Division of Molecular and Cellular Biosciences, National Science Foundation, Arlington, VA 22230, USA.

  • GUY DIDONATO

    1. The Hollings Marine Laboratory, 331 Fort Johnson Road, Charleston, SC 29412, USA
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  • This material is based in part on work supported by the National Science Foundation. Any opinion, finding, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.

Robert W. Chapman, Fax: 843-762-8737; E-mail: chapmanr@dnr.sc.gov

Abstract

Increasing utilization and human population density in the coastal zone is widely believed to place increasing stresses on the resident biota, but confirmation of this belief is somewhat lacking. While we have solid evidence that highly disturbed estuarine systems have dramatic changes in the resident biota (black and white if you will), we lack tools that distinguish the shades of grey. In part, this lack of ability to distinguish shades of grey stems from the analytical tools that have been applied to studies of estuarine systems, and perhaps more important, is the insensitivity of the biological end points that we have used to assess these impacts. In this study, we will present data on the phenotypic adjustments as measured by transcriptomic signatures of a resilient organism (oysters) to land-use practices in the surrounding watershed using advanced machine-learning algorithms. We will demonstrate that such an approach can reveal subtle and meaningful shifts in oyster gene expression in response to land use. Further, the data show that gill tissues are far more responsive and provide superior discrimination of land-use classes than hepatopancreas and that transcripts encoding proteins involved in energy production, protein synthesis and basic metabolism are more robust indicators of land use than classic biomarkers such as metallothioneins, GST and cytochrome P-450.

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