Dinoflagellate Genomic Organization and Phylogenetic Marker Discovery Utilizing Deep Sequencing Data

Dinoflagellates possess large genomes in which most genes are present in many copies. This has made studies of their genomic organization and phylogenetics challenging. Recent advances in sequencing technology have made deep sequencing of dinoflagellate transcriptomes feasible. This dissertation investigates the genomic organization of dinoflagellates to better understand the challenges of assembling dinoflagellate transcriptomic and genomic data from short read sequencing methods, and develops new techniques that utilize deep sequencing data to identify orthologous genes across a diverse set of taxa. To better understand the genomic organization of dinoflagellates, a genomic cosmid clone of the tandemly repeated gene Alchohol Dehydrogenase (AHD) was sequenced and analyzed. The organization of this clone was found to be counter to prevailing hypotheses of genomic organization in dinoflagellates. Further, a new non-canonical splicing motif was described that could greatly improve the automated modeling and annotation of genomic data. A custom phylogenetic marker discovery pipeline, incorporating methods that leverage the statistical power of large data sets was written. A case study on Stramenopiles was undertaken to test the utility in resolving relationships between known groups as well as the phylogenetic affinity of seven unknown taxa. The pipeline generated a set of 373 genes useful as phylogenetic markers that successfully resolved relationships among the major groups of Stramenopiles, and placed all unknown taxa on the tree with strong bootstrap support. This pipeline was then used to discover 668 genes useful as phylogenetic markers in dinoflagellates. Phylogenetic analysis of 58 dinoflagellates, using this set of markers, produced a phylogeny with good support of all branches. The Suessiales were found to be sister to the Peridinales. The Prorocentrales formed a monophyletic group with the Dinophysiales that was sister to the Gonyaulacales. The Gymnodinales was found to be paraphyletic, forming three monophyletic groups. While this pipeline was used to find phylogenetic markers, it will likely also be useful for finding orthologs of interest for other purposes, for the discovery of horizontally transferred genes, and for the separation of sequences in metagenomic data sets.

Studies on Understanding Individual Willingness to Disclose Genetic Information to Public and Private Stakeholders

While technologies for genetic sequencing have increased the promise of personalized medicine, they simultaneously pose threats to personal privacy. The public’s desire to protect itself from unauthorized access to information may limit the uses of this valuable resource. To date, there is limited understanding about the public’s attitudes toward the regulation and sharing of such information. We sought to understand the drivers of individuals’ decisions to disclose genetic information to a third party in a setting where disclosure potentially creates both private and social benefits, but also carries the risk of potential misuse of private information. We conducted two separate but related studies. First, we administered surveys to college students and parents, to determine individual attitudes toward and inter-generational influences on the disclosure decision. Second, we conducted a game-theory based experiment that assessed how participants’ decisions to disclose genetic information are influenced by societal and health factors. Key survey findings indicate that concerns about genetic information privacy negatively impact the likelihood of disclosure while the perceived benefits of disclosure and trust in the institution receiving the information have a positive influence. The experiment results also show that the risk of discrimination negatively affects the likelihood of disclosure, while the positive impact that disclosure has on the probability of finding a cure and the presence of a monetary incentive to disclose, increase the likelihood. We also study the determinants of individuals’ decision to be informed of findings about their health, and how information about health status is used for financial decisions.