Analysis of Somatic Mutations in Longitudinal Whole-genome Sequencing Data

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PROJECT SUMMARY While recent efforts have focused on better understanding the germline mutation rate of different types of DNA variants, the dynamics of somatic mutations in the human genome are poorly understood. Somatic mutations are a well-known cause of cancer and may play a causative role in other diseases and aging. Analyses of somatic mutations have generally been limited to single-cell or low-coverage studies. To accurately assess the rate of somatic mutations over time would require a longitudinal, high coverage dataset. For ~450 individuals in the Utah CEPH (Centre d'Etude du Polymorphism Humain) pedigrees, blood was drawn at two timepoints approximately 15 years apart. This proposal describes experiments to determine the rate of somatic mutations throughout the human genome by utilizing high-coverage (720x) whole-genome sequencing data at both of these timepoints in a subset of CEPH individuals. The genomes included in this study will be used to determine the rate of somatic mutations and improve our understanding of differences in this rate between individuals. Building on previous work performed at the University of Utah, we will determine the relationship between the germline and somatic mutation rate. Further, using detailed phenotypic data collected for these individuals, experiments will be performed to determine how this rate is correlated with disease outcomes such as cancer and cardiovascular disease. From this work, a series of filtering algorithms will be produced to allow for comprehensive analysis of somatic mutations occurring between two timepoints in the same individual. This dataset provides me with a unique opportunity to study somatic mutations over time using high-quality data. This proposal builds upon my experience in analyzing mobile element-mediated somatic mutations in longitudinal whole-genome data of cancer patients, and my recent work analyzing germline short tandem repeat mutations in the CEPH pedigrees. The K99 portion of this project will focus on determining the rate of somatic mutations in longitudinal, high-coverage whole-genome sequencing data while creating filtering algorithms to improve our detection capabilities. The additional training I will receive during this period will lay the foundation of an independent research program that will determine the significance of somatic mutations in the human genome and how these relate to disease outcomes.