Technologies for tracking genome variations in duckweed and other species

Near-term and future increases in global population overburden our energy resources as we seek solutions to unstable foreign petroleum pricing and its associated problems with climate change and ecological biosphere integrity. Renewable and sustainable biofuels have the potential to replace existing transportation fuels and dampen their related problems. Small but versatile, duckweed is an aquatic plant that can be used in a variety of applications such as biofuels, animal feed, and wastewater remediation. This dissertation addresses the need for quick and reliable typing of duckweed species and lower taxonomic levels. First, a sequence database for two plastidic barcodes, atpF-atpH and psbK-psbI was created representing all 37 known duckweed species. Using a BLAST-based protocol, our approach can distinguish 30 out of the 37 species. To distinguish clones of the duckweed species Spirodela polyrhiza, a bioinformatics pipeline was developed that identifies hyperpolymorphic regions of the NB-LRR-based plant disease resistance protein-encoding genes, which can be used as genotyping markers. We demonstrate that a combination of seven hyperpolymorphic regions from six loci using fragment analysis and Sanger sequencing post-PCR can distinguish 20 out of the 23 S. polyrhiza clones tested. A subset of these markers can be used to clearly separate S. polyrhiza clones from the closely related S. intermedia. Finally, our bioinformatics pipeline was applied to Arabidopsis thaliana to locate NB-LRR markers that can computationally distinguish all 1,135 A. thaliana accessions, and to validate the efficacy of the pipeline at identifying hyperpolymorphic genic regions. This novel method can be used to track accessions for a species of interest using polymorphisms from sequenced genomes, in addition to assisting a better understanding of the differential frequency of mutations across the genome.