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.
|Advisor:||Chapman, Robert W.|
|Commitee:||Kingsley-Smith, Peter, McCandless, Amy T., Sotka, Erik E., Zimmerman, Anastasia M.|
|School:||College of Charleston|
|School Location:||United States -- South Carolina|
|Source:||MAI 48/06M, Masters Abstracts International|
|Subjects:||Molecular biology, Biostatistics, Genetics|
|Keywords:||Artificial neural networks, Crassostrea virginica, Gene expression, Oyster, Transcriptomes|
Copyright in each Dissertation and Thesis is retained by the author. All Rights Reserved
The supplemental file or files you are about to download were provided to ProQuest by the author as part of a
dissertation or thesis. The supplemental files are provided "AS IS" without warranty. ProQuest is not responsible for the
content, format or impact on the supplemental file(s) on our system. in some cases, the file type may be unknown or
may be a .exe file. We recommend caution as you open such files.
Copyright of the original materials contained in the supplemental file is retained by the author and your access to the
supplemental files is subject to the ProQuest Terms and Conditions of use.
Depending on the size of the file(s) you are downloading, the system may take some time to download them. Please be