De novo mutations across 1,465 diverse genomes reveal mutational insights and reductions in the Amish founder population

Abstract

De novo mutations (DNMs), or mutations that appear in an individual despite not being seen in their parents, are an important source of genetic variation whose impact is relevant to studies of human evolution, genetics, and disease. Utilizing high-coverage whole-genome sequencing data as part of the Trans-Omics for Precision Medicine (TOPMed) Program, we called 93,325 single-nucleotide DNMs across 1,465 trios from an array of diverse human populations, and used them to directly estimate and analyze DNM counts, rates, and spectra. We find a significant positive correlation between local recombination rate and local DNM rate, and that DNM rate explains a substantial portion (8.98 to 34.92%, depending on the model) of the genome-wide variation in population-level genetic variation from 41K unrelated TOPMed samples. Genome-wide heterozygosity does correlate with DNM rate, but only explains <1% of variation. While we are underpowered to see small differences, we do not find significant differences in DNM rate between individuals of European, African, and Latino ancestry, nor across ancestrally distinct segments within admixed individuals. However, we did find significantly fewer DNMs in Amish individuals, even when compared with other Europeans, and even after accounting for parental age and sequencing center. Specifically, we found significant reductions in the number of C→A and T→C mutations in the Amish, which seem to underpin their overall reduction in DNMs. Finally, we calculated near-zero estimates of narrow sense heritability (h2), which suggest that variation in DNM rate is significantly shaped by nonadditive genetic effects and the environment.

A natural mutator allele shapes mutation spectrum variation in mice

“…Many other mutation types exhibit subtle differences in abundance between human continental groups (7), and there are pronounced differences between the mutation spectra of great ape species (8), suggesting that small-effect mutator alleles may be segregating in every hominin lineage. Direct measurements of mutation rates also vary among human families and between some ethnic groups (9)(10)(11); however, it is unclear how much variation in mutation rates and spectra is driven by genetics as opposed to the environment (12).…”

Age-related accumulation of de novo mitochondrial mutations in mammalian oocytes and somatic tissues

“…Mutations generate genetic variation, making evolution possible. Substantial progress has been made in our understanding of mutation rates and patterns because of the application of next generation sequencing (NGS) to interspecies genomic alignments (reviewed in [1]), familial trios [2][3][4][5][6][7][8][9], mutation accumulation lines (reviewed in [10]), and mutator animal models [11,12]. Yet the error rates of available NGS technologies (e.g., 10 −3 to 10 −2 for Illumina [13] and even higher for others) are several orders of magnitude higher than the mutation rates themselves (e.g., 3.5-5.4 × 10 −9 and 7.69 × 10 −8 mutations per base pair per generation in mouse germline and brain, respectively, for nuclear DNA [14,15]).…”

Automatic inference of demographic parameters using Generative Adversarial Networks

“…We do not always have a good sense of what these parameters should be, especially in understudied populations and non-model species. For example, mutation and recombination rates estimated in one population are frequently used to simulate data for another, despite the fact that these rates differ between populations [22–26].…”