Gamma radiation is a potent environmental mutagen capable of causing large scale genomic alterations through direct DNA damage and indirectly through the generation of reactive oxygen species. While the effects of gamma radiation have been studied extensively in many plant and animal systems, mutation rate is poorly characterized in many animal systems. In this study, we investigated the rate and spectrum of mutations arising from gamma radiation in the microcrustacean species Daphnia pulex using whole-genome sequencing. This study aims to develop this technique for forward genetics experiments and to establish a bioinformatic pipeline for the analysis of mutants.

Daphnia were exposed to controlled doses of gamma radiation under varying exposure times (9.5, 12 and 24 hours) and dose rates (4, 10 and 62 mGy/hour). Following exposure, mutant populations were generated and offspring from multiple broods were collected and sequenced. The variants were then identified through a combination of standard genomic workflows, custom pipelines and manual validation. Mutation rates, variant counts and spectrum were compared across treatment groups, reproductive time points and to similar studies in plants. Observed mutation rates saw a significant increase in the mutation rate when compared to the spontaneous rate, with a fold increase ranging from 63 to almost 400. 

Our results demonstrate that mutations are not solely determined by total accumulated dose, but also by time, rate and other biological processes. Amongst subsequent broods, mutations became more pronounced and the rate increased. This indicates a delay in expression of the mutations caused by direct and indirect effects of radiation, along with DNA repair pathways. The results and conclusions made are consistent with existing literature and the accepted mode of action of gamma radiation. 

This study provides new insight into the dynamics of radiation induced mutagenesis, as well as furthering knowledge in an ecologically relevant model system. The results also provide a framework for future forward genetics experiments, the bioinformatic analysis of variants and also highlight the complexities associated with performing mutagenesis, namely that dose is not the only determinant of mutational outcomes. 

Thesis Committee

• Dr. Sen Xu, Chair
• Dr. Pamela Brown
• Dr. Jie Zhu
• Dr. John Brockman