Troy LaPolice

Conduct full time lab and field research

Operate a small private business

The processing and quality of genetic data is vital for studying the genetic code of organisms. Researchers often move on to downstream data analysis and overlook the quality of their upstream genomic assemblies. This study examined if the quality of the assembled genetic data affected the resulting inferences about the relatedness between species. It also examined which quality metrics are the best for assessing the quality of assemblies with the goal of making a phylogeny. I assembled sequence data from vertebrates into transcriptomes using the multiple assembler, multiple kmer approach built into the Oyster River Protocol. I took the best and worst assemblies from each organism generated from this process and compiled each into datasets, one with high- and one with low-quality data. I did this for three different quality metrics and created phylogenetic trees for each dataset. I then compared the trees made from the high- and low-quality datasets to an accepted vertebrate tree to assess the differences in the datasets. I show that poor assembly quality does have a significant effect on the amount of downstream data and the quality of phylogenetic results. I also developed an understanding of the strengths and weaknesses of each assembly software and assembly quality metric.

Amphibian genomes are notoriously difficult to assemble because of their extremely large size and repetitive content. For this project, I will examine the origin of the repetitive content found in these genomes using the non-model organism, the poison frog Ranitomeya imitator. This study is important because it can help to resolve either the evolutionary history of these bloated genomes or serve to highlight whether the duplicate content found arises from inaccuracies related to the inability of the genome assembly software to process the non-model genomes. I will take a draft Ranitomeya imitator genome, locate the duplicates and align them to each other, checking for matches that could have arisen from systematic error. I will then use a software that willsystematically compare the duplicates to a database of known genes to find where evolutionarily, these genes could have arisenclassify these repeats. My work not only will lend itself my undergraduate thesis, but will help inform a project researchers are currently working on that aims to identify the genetic mechanisms of toxin acquisition and variable colors and patterns in poison frogs. My project will look into a specific aspect of the dataset in hopes of resolving critical and biologically relevant questions that the answers to, will dramatically improve the overall final product of the larger poison frog project.