Project description: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 paper 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 shows that gill tissues are far more responsive and provide superior discrimination of land use classes than hepatopancreas and that transcript encoding proteins involved in energy productions, protein synthesis and basic metabolism are more robust indicators of land use than classic biomarkers such as metallothioneins, GST and cytochrome P450. Keywords: Comparative genomics, ecogenomics. Tissue differences, impacts of land use and contaminants on gene expression.

2009-07-01 | GSE14793 | GEO

LAND-USE_LTO_2014

Project description:Shifts in microbial diversity through land use intensity as drivers of C-cycling in soil

| PRJEB6118 | ENA

A Transcriptomic Analysis of Land Use Impacts on the Oyster, Crassostrea virginica, in the South Atlantic Bight.

2009-07-01 | E-GEOD-14793 | biostudies-arrayexpress

Targeting the treponemal microbiome of digital dermatitis infections by deep coverage pyrosequencing

Project description:We examined 36 biopsies taken from digital dermatitis lesions of Holstein cows. The target was the V3 -V4 variable region of 16S rRNA using Treponema specific primers. We identified 20 different taxa of Treponema using this approach.

2013-06-25 | GSE42426 | GEO