27th Annual Student Research Conference
Improving Statistical Measures of Genetic Diversity to Reconstruct Evolutionary History
Nathan Wikle* and Ian P. Kotthoff
Mr. Pamela J. Ryan and Dr. Anton Weisstein, Faculty Mentors
Studying the genetic variation of a population gives insight into the evolutionary history of populations. However, most existing diversity statistics cannot differentiate between variation influenced by selection and genetic drift, and the evolutionary mechanisms that have been active on the population remain unknown. By classifying the synonymous and nonsynonymous mutations into separate sets, we can compare the change in genetic diversity attributed to genetic drift (Dsyn) and natural selection (Dnon - Dsyn), where Dnon and Dsyn are modifications of Tajima's D statistic, a standard measure of diversity. Such a distinction gives insight into the sources of genetic variation - for example, whether a decrease in diversity is the result of a population bottleneck or purifying selection. Our goals are to improve the resolution of the evolutionary mechanisms within our model using computational methods such as neural networks, and to assess the accuracy of the synonymous and nonsynonymous classification process.
Keywords: molecular evolution, population genetics, Tajima's D, mathematical biology
Topic(s):Mathematical Biology
Presentation Type: Oral Paper
Session: 103-1
Location: MG 1098
Time: 8:00