Timing, rates and spectra of human germline mutation.

Germline mutations are a driving force behind genome evolution and genetic disease. We investigated genome-wide mutation rates and spectra in multi-sibling families. The mutation rate increased with paternal age in all families, but the number of additional mutations per year differed by more than twofold between families. Meta-analysis of 6,570 mutations showed that germline methylation influences mutation rates. In contrast to somatic mutations, we found remarkable consistency in germline mutation spectra between the sexes and at different paternal ages. In parental germ line, 3.8% of mutations were mosaic, resulting in 1.3% of mutations being shared by siblings. The number of these shared mutations varied significantly between families. Our data suggest that the mutation rate per cell division is higher during both early embryogenesis and differentiation of primordial germ cells but is reduced substantially during post-pubertal spermatogenesis. These findings have important consequences for the recurrence risks of disorders caused by de novo mutations

Large scale variation in the rate of germ-line de novo mutation, base composition, divergence and diversity in humans

It has long been suspected that the rate of mutation varies across the human genome at a large scale based on the divergence between humans and other species. However, it is now possible to directly investigate this question using the large number of de novo mutations (DNMs) that have been discovered in humans through the sequencing of trios. We investi- gate a number of questions pertaining to the distribution of mutations using more than 130,000 DNMs from three large datasets. We demonstrate that the amount and pattern of variation differs between datasets at the 1MB and 100KB scales probably as a consequence of differences in sequencing technology and processing. In particular, datasets show differ- ent patterns of correlation to genomic variables such as replication time. Never-the-less there are many commonalities between datasets, which likely represent true patterns. We show that there is variation in the mutation rate at the 100KB, 1MB and 10MB scale that can- not be explained by variation at smaller scales, however the level of this variation is modest at large scales–at the 1MB scale we infer that ~90% of regions have a mutation rate within 50% of the mean. Different types of mutation show similar levels of variation and appear to vary in concert which suggests the pattern of mutation is relatively constant across the genome. We demonstrate that variation in the mutation rate does not generate large-scale variation in GC-content, and hence that mutation bias does not maintain the isochore struc- ture of the human genome. We find that genomic features explain less than 40% of the explainable variance in the rate of DNM. As expected the rate of divergence between spe- cies is correlated to the rate of DNM. However, the correlations are weaker than expected if all the variation in divergence was due to variation in the mutation rate. We provide evidence that this is due the effect of biased gene conversion on the probability that a mutation will become fixed. In contrast to divergence, we find that most of the variation in diversity can be explained by variation in the mutation rate. Finally, we show that the correlation between divergence and DNM density declines as increasingly divergent species are considered

Genome-wide patterns and properties of de novo mutations in humans

Mutations create variation in the population, fuel evolution, and cause genetic diseases. Current knowledge about de novo mutations is incomplete and mostly indirect 1–10. Here, we analyze 11,020 de novo mutations from whole-genomes of 250 families. We show that de novo mutations in offspring of older fathers are not only more numerous 11–13 but also occur more frequently in early-replicating, genic regions. Functional regions exhibit higher mutation rates due to CpG dinucleotides and reveal signatures of transcription-coupled repair, while mutation clusters with a unique signature point to a novel mutational mechanism. Mutation and recombination rates independently associate with nucleotide diversity, and regional variation in human-chimpanzee divergence is only partly explained by mutation rate heterogeneity. Finally, we provide a genome-wide mutation rate map for medical and population genetics applications. Our results reveal novel insights and refine long-standing hypotheses about human mutagenesis