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Rates and patterns of de novo mutation in large human pedigrees
September 26 @ 11:00 am - 2:00 pm PDT
Thomas Sasani, Graduate Student
Department of Human Genetics, Quinlan Lab, University of Utah
Thursday, September 26, 2019
Engineering Building 2 – 599
11:30 a.m – 12:30 p.m.
I am a Ph.D candidate in Aaron Quinlan’s group at the University of Utah, and received my B.A. in Biochemistry from Lawrence University (Appleton, WI) in 2015. My thesis work is broadly focused on investigating genome evolution and structural variation using next-generation sequencing data. Early in my graduate work, I used the Oxford Nanopore platform to characterize adaptive copy number variation in a species of DNA virus undergoing experimental evolution, as part of a collaboration with Nels Elde’s lab (also at the University of Utah). Currently, I am analyzing the dynamics of the human mutation rate using sequencing data from large pedigrees.
Developing an accurate estimate of the human mutation rate is critical to our understanding of evolution, demography, and genetic disease. Early phylogenetic analyses inferred mutation rates from the observed sequence divergence between humans and related primate species at particular pseudogenes, as well as archaeological evidence for species split times. However, as whole genome sequencing has become ubiquitous, these estimates have been refined using pedigree-based approaches. By identifying mutations present in offspring that are absent from their parents (de novo mutations), it is possible to more accurately approximate the human mutation rate. To obtain a precise, unbiased estimate of the mutation rate in humans, we performed deep whole-genome sequencing on blood-derived DNA from 33 of the original three-generation CEPH families from Utah, which together comprise a total of 603 individuals. These families, which each contain grandparents (1st generation), parents (2nd), and their children (3rd), are considerably larger than any used in prior estimates of the human mutation rate, and offer unique power to detect and validate de novo mutations. Using this dataset, we have generated a high-confidence estimate of the human mutation rate, observe significant parental age effects on the rate of de novo mutation, and identify wide variability in family-specific age effects across CEPH pedigrees. Additionally, we have identified recurrent de novo variants present in multiple 3rd-generation offspring, which are likely the result of mosaicism in parental germlines. Finally, we discovered that nearly 10% of candidate de novo mutations in the second generation were post-zygotic and present in both somatic and germ cells; these “gonosomal” mutations occurred at equivalent frequencies on both parental haplotypes. Our results demonstrate that the rate of germline mutation accumulation varies among families with similar genetic ancestry, and confirm that post-zygotic mosaicism is a substantial source of de novo mutations in humans.