title: A transcriptomic analysis of land-use impacts on the oyster, Crassostrea virginica, in the South Atlantic bight.
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.
authors.affiliation: South Carolina Department of Natural Resources, PO Box 12559 Charleston, SC 29422-2559, USA. chapmanr@dnr.sc.gov
authors.forename: Robert W
authors.initials: RW
authors.lastname: Chapman
authors.forename: Annalaura
authors.initials: A
authors.lastname: Mancia
authors.forename: Marion
authors.initials: M
authors.lastname: Beal
authors.forename: Artur
authors.initials: A
authors.lastname: Veloso
authors.forename: Charles
authors.initials: C
authors.lastname: Rathburn
authors.forename: Anne
authors.initials: A
authors.lastname: Blair
authors.forename: Denise
authors.initials: D
authors.lastname: Sanger
authors.forename: A F
authors.initials: AF
authors.lastname: Holland
authors.forename: Gregory W
authors.initials: GW
authors.lastname: Warr
authors.forename: Guy
authors.initials: G
authors.lastname: Didonato
mesh_terms: D000465:Algorithms; D000818:Animals; D015415:Biomarkers; D049896:Crassostrea / Q000235:genetics* / Q000378:metabolism; D017753:Ecosystem; D004784:Environmental Monitoring; D004785:Environmental Pollutants / Q000378:metabolism; D020869:Gene Expression Profiling; D005880:Gills / Q000378:metabolism; D043143:Hepatopancreas / Q000378:metabolism; D008954:Models, Biological; D016571:Neural Networks, Computer; D020411:Oligonucleotide Array Sequence Analysis; D011157:Population Dynamics; D012680:Sensitivity and Specificity
chemical_list: D015415:Biomarkers; D004785:Environmental Pollutants