IDENTIFICATION OF SNP DATA FROM DIFFERENT E. VAGINATUM POPULATIONS USING BIOINFORMATICS
Armando Lerma, Jonathon Mohl, Ming-Ying Leung, Michael Moody.
The University of Texas at El Paso, El Paso, TX.
Eriophorum vaginatum is an ecologically important Arctic plant lineage, and it serves as a model for understanding home site advantage in light of climate change. Ecophysiological research has recognized distinct ecotypes from the north and south of its range in Alaska; analysis of its genetic structure can help to predict how these populations will respond to climate change. This research employs double-digest restriction-associated DNA (RAD) sequencing, a next generation sequencing technique, to identify single nucleotide polymorphism (SNP) data for distinguishing the ecotypes at the genetic level and ultimately levels of gene flow among populations. In a preliminary analysis, a script was written in Python computer language to create a workflow that filtered, processed, and analyzed the RAD sequence data using different programs (FASTX, STACKS). Subsequently, a tree-building program, Geneious, was used to evaluate genetic variation, structure, and relatedness between ecotypes. After completing the analysis, a significant number of SNPs were identified, and neighbor-joining trees allowed us to observe an expected north/south split. The resolution suggested that inclusion of more loci may be more important than using only loci with high sample coverage for an increased resolution. A variant call format (VCF) file was produced containing genotype information on each sample. By parsing and manipulating this file, we will be able to identify specific SNPs that varied among the different populations for further analysis.