Dissertation/Thesis Abstract

Genetic and environmental contributions to gene expression variations in the Eastern oyster (<i>Crassostrea virginica</i>) from three locations in Mississippi
by Johns, Christopher David, M.S., College of Charleston, 2010, 60; 1478262
Abstract (Summary)

The role of the contribution of genetics to variations in gene expression has not been well studied. Studies on gene expression often attribute variation in gene expression to differences in environmental parameters while ignoring that population structure or random genetic variation could also be associated with the differential expression. To address this, 25 Eastern oysters ( Crassostrea virginica) were sampled from each of three sites in Mississippi. Two of the sites were located within urban watersheds, while the other was located within a forested watershed. Water quality parameters were measured at each sampling site. The expression of 5,573 oyster genes derived from an expressed sequence tag (EST) library was measured in each oyster using a long oligo microarray. Genetic data were collected using eight previously described microsatellites. A machine-learning method, Artificial Neural Networks, with sensitivity analysis was used to determine the percent contributions of the environmental and genetic input factors toward variations in gene expression. Genetic variation was found to explain 12.22% of the gene expression variation across the 5,573 genes surveyed. Further cluster analysis revealed a small group of 28 genes that had a genetic contribution toward variation in gene expression as high as 38.72%. These results support the premise that genetic variation affects gene expression and should be taken into account in future environmental genetics studies. This study has also identified a group of potential genes for the development of biosensors.

Indexing (document details)
Advisor: Chapman, Robert W.
Commitee: Kingsley-Smith, Peter, McCandless, Amy T., Sotka, Erik E., Zimmerman, Anastasia M.
School: College of Charleston
Department: Marine Biology
School Location: United States -- South Carolina
Source: MAI 48/06M, Masters Abstracts International
Source Type: DISSERTATION
Subjects: Molecular biology, Biostatistics, Genetics
Keywords: Artificial neural networks, Crassostrea virginica, Gene expression, Oyster, Transcriptomes
Publication Number: 1478262
ISBN: 9781124083520