Abstract
The goal of this thesis was to examine the genetic diversity of two diverse seagrass species, Amphibolis antarctica and Halodule wrightii, using microsatellite markers. Microsatellite primers previously did not exist for Amphibolis antarctica and were developed as described in the first chapter. From 48 primer candidates, 14 polymorphic loci were arranged into a 3-panel multiplex. The microsatellite primers successfully amplified and distinguished multi-locus genotypes of samples from two test populations. Genotypic richness varied between populations at 0.26 and 0.85, and an FST = 0.318 indicated population differentiation has occurred. Contrary to previous study, genetic diversity was observed in A. antarctica meadows. Further studies will be able to use these primers for more extensive analysis of the dispersal and recruitment mechanisms, evolutionary history, and connectivity of A. antarctica. The second chapter utilized microsatellite primers in a genetic population study for edge-of-range populations of the tropical/subtropical seagrass Halodule wrightii. Sampling occurred at 15 sites representing the Florida gulf coast, Florida Bay, Indian River Lagoon, North Carolina, and Bermuda. Eleven microsatellites were amplified and allelic diversity, genotypic richness, population differentiation, gene flow, principal components analysis, and k-means population clustering analyses were performed. Diploid, triploid, and tetraploid genotypes were observed. Aneuploidy from somatic mutation may be a way for edge-of-range populations to achieve genetic diversity without sexual reproduction, as sites were highly clonal (R = 0.00 – 0.20). Population clustering and principal components analysis grouped sites into 2 main populations. Sites were highly structured (RhoST = 0.297) and genetic differentiation occurred between populations following an isolation-by-distance model. The microsatellite analyses of this thesis allowed for the characterization of genetic diversity and population differentiation of the studied species. Such information can allow restoration and conservation managers to infer genetic processes that are important for mitigation success.
