Parental influence on human germline de novo mutations in 1,548 trios from Iceland
The characterization of mutational processes that generate sequence diversity in the human genome is of paramount importance both to medical genetics1, 2 and to evolutionary studies3. To understand how the age and sex of transmitting parents affect de novo mutations, here we sequence 1,548 Icelanders, their parents, and, for a subset of 225, at least one child, to 35× genome-wide coverage. We find 108,778 de novo mutations, both single nucleotide polymorphisms and indels, and determine the parent of origin of 42,961. The number of de novo mutations from mothers increases by 0.37 per year of age (95% CI 0.32–0.43), a quarter of the 1.51 per year from fathers (95% CI 1.45–1.57). The number of clustered mutations increases faster with the mother’s age than with the father’s, and the genomic span of maternal de novo mutation clusters is greater than that of paternal ones. The types of de novomutation from mothers change substantially with age, with a 0.26% (95% CI 0.19–0.33%) decrease in cytosine–phosphate–guanine to thymine–phosphate–guanine (CpG>TpG) de novo mutations and a 0.33% (95% CI 0.28–0.38%) increase in C>G de novo mutations per year, respectively. Remarkably, these age-related changes are not distributed uniformly across the genome. A striking example is a 20 megabase region on chromosome 8p, with a maternal C>G mutation rate that is up to 50-fold greater than the rest of the genome. The age-related accumulation of maternal non-crossover gene conversions also mostly occurs within these regions. Increased sequence diversity and linkage disequilibrium of C>G variants within regions affected by excess maternal mutations indicate that the underlying mutational process has persisted in humans for thousands of years. Moreover, the regional excess of C>G variation in humans is largely shared by chimpanzees, less by gorillas, and is almost absent from orangutans. This demonstrates that sequence diversity in humans results from evolving interactions between age, sex, mutation type, and genomic location.