Signals of variation in human mutation rate at multiple levels of sequence context

ABSTRACTOur understanding of mutation rate helps us build evolutionary models and make sense of genetic variation. Recent work indicates that the frequencies of specific mutation types have been elevated in Europe, and that many more, subtler signatures of global polymorphism variation may yet remain unidentified. Here, we present an analysis of the 1,000 Genomes Project (phase 3), suggesting additional putative signatures of mutation rate variation across populations and the extent to which they are shaped by local sequence context. First, we compiled a list of the most significantly variable polymorphism types in a cross-continental statistical test. Clustering polymorphisms together, we observed four sets of substitution types that showed similar trends of relative mutation rate across populations, and describe the patterns of these mutational clusters among continental groups. For the majority of these signatures, we found that a single flanking base pair of sequence context was sufficient to determine the majority of enrichment or depletion of a mutation type. However, local genetic context up to 2-3 base pairs away contributes additional variability, and helps to interpret a previously noted enrichment of certain polymorphism types in some East Asian groups. Building our understanding of mutation rate in this way can help us to construct more accurate evolutionary models and better understand the mechanisms that underlie genetic change.

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How sequence context-dependent mutability drives mutation rate variation in the genome

10.1101/2021.07.20.453104 ◽

2021 ◽

Author(s):

Madeleine Oman ◽

Aqsa Alam ◽

Rob Ness

Keyword(s):

Dna Damage ◽

Mutation Rate ◽

Genetic Diseases ◽

Purifying Selection ◽

Rate Variation ◽

Sequence Evolution ◽

Sequence Context ◽

Simple Process ◽

Human Mutation ◽

Mutation Rate Variation

The rate of mutations varies >100-fold across the genome, altering the rate of evolution, and susceptibility to genetic diseases. The strongest predictor of mutation rate is the sequence itself, varying 75-fold between trinucleotides. The fact that DNA sequence drives its own mutation rate raises a simple but important prediction; highly mutable sequences will mutate more frequently and eliminate themselves in favour of sequences with lower mutability, leading to a lower equilibrium mutation rate. However, purifying selection constrains changes in mutable sequences, causing higher rates of mutation. We conduct a simulation using real human mutation data to test if (1) DNA evolves to a low equilibrium mutation rate and (2) purifying selection causes a higher equilibrium mutation rate in the most important regions of the genome. We explore how this simple process affects sequence evolution in the genome, and discuss the implications for modelling evolution and susceptibility to DNA damage.

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Signals of Variation in Human Mutation Rate at Multiple Levels of Sequence Context

Molecular Biology and Evolution ◽

10.1093/molbev/msz023 ◽

2019 ◽

Vol 36 (5) ◽

pp. 955-965 ◽

Cited By ~ 8

Author(s):

Rachael C Aikens ◽

Kelsey E Johnson ◽

Benjamin F Voight

Keyword(s):

Mutation Rate ◽

Sequence Context ◽

Multiple Levels ◽

Human Mutation

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Nucleosome positioning stability is a significant modulator of germline mutation rate variation across the human genome

10.1101/494914 ◽

2018 ◽

Cited By ~ 3

Author(s):

Cai Li ◽

Nicholas M. Luscombe

Keyword(s):

Human Genome ◽

Genome Evolution ◽

Mutation Rate ◽

Germline Mutation ◽

De Novo ◽

Mutation Rates ◽

Rate Variation ◽

Nucleosome Organization ◽

Local Sequence ◽

Mutation Rate Variation

AbstractUnderstanding the patterns and genesis of germline de novo mutations is important for studying genome evolution and human diseases. Nucleosome organization is suggested to be a contributing factor to mutation rate variation across the genome. However, the small number of published de novo mutations and the low resolution of earlier nucleosome maps limited our understanding of how nucleosome organization affects germline mutation rates in the human genome. Here, we systematically investigated the relationship between nucleosome organization and fine-scale mutation rate variation by analyzing >300,000 de novo mutations from whole-genome trio sequencing and high-resolution nucleosome maps in human. We found that de novo mutation rates are elevated around strong, translationally stable nucleosomes, a previously under-appreciated aspect. We confirmed this observation having controlled for local sequence context and other potential confounding factors. Analysis of the underlying mutational processes suggests that the increased mutation rates around strong nucleosomes are shaped by a combination of low-fidelity replication, frequent DNA damage and insufficient/error-prone repair in these regions. Interestingly, strong nucleosomes are preferentially located in young SINE/LINE elements, implying frequent nucleosome re-positioning (i.e. shifting of dyad position) and their contribution to hypermutation at new retrotransposons during evolution. These findings provide novel insights into how chromatin organization affects germline mutation rates and have important implications in human genetics and genome evolution.

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Nucleosome positioning stability is a modulator of germline mutation rate variation across the human genome

Nature Communications ◽

10.1038/s41467-020-15185-0 ◽

2020 ◽

Vol 11 (1) ◽

Author(s):

Cai Li ◽

Nicholas M. Luscombe

Keyword(s):

Human Genome ◽

Mutation Rate ◽

Germline Mutation ◽

Nucleosome Positioning ◽

Rate Variation ◽

Mutation Rate Variation

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Minisatellite mutation rate variation associated with a flanking DNA sequence polymorphism

Nature Genetics ◽

10.1038/ng1094-162 ◽

1994 ◽

Vol 8 (2) ◽

pp. 162-170 ◽

Cited By ~ 62

Author(s):

Darren G. Monckton ◽

Rita Neumann ◽

Tara Guram ◽

Neale Fretwell ◽

Keiji Tamaki ◽

...

Keyword(s):

Dna Sequence ◽

Mutation Rate ◽

Sequence Polymorphism ◽

Rate Variation ◽

Dna Sequence Polymorphism ◽

Mutation Rate Variation

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Mutation Biases and Mutation Rate Variation Around Very Short Human Microsatellites Revealed by Human–Chimpanzee–Orangutan Genomic Sequence Alignments

Journal of Molecular Evolution ◽

10.1007/s00239-010-9377-4 ◽

2010 ◽

Vol 71 (3) ◽

pp. 192-201 ◽

Cited By ~ 14

Author(s):

William Amos

Keyword(s):

Mutation Rate ◽

Genomic Sequence ◽

Rate Variation ◽

Sequence Alignments ◽

Mutation Rate Variation

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Extensivede novomutation rate variation between individuals and across the genome ofChlamydomonas reinhardtii

10.1101/015693 ◽

2015 ◽

Cited By ~ 1

Author(s):

Rob W Ness ◽

Andrew D Morgan ◽

Radhakrishnan B Vasanthakrishnan ◽

Nick Colegrave ◽

Peter D Keightley

Keyword(s):

Mutation Rate ◽

Evolutionary Biology ◽

De Novo ◽

Spontaneous Mutation ◽

Gc Content ◽

Rate Variation ◽

De Novo Mutations ◽

Local Sequence ◽

Wild Strains ◽

Genomic Regions

Describing the process of spontaneous mutation is fundamental for understanding the genetic basis of disease, the threat posed by declining population size in conservation biology, and in much evolutionary biology. However, directly studying spontaneous mutation is difficult because of the rarity of de novo mutations. Mutation accumulation (MA) experiments overcome this by allowing mutations to build up over many generations in the near absence of natural selection. In this study, we sequenced the genomes of 85 MA lines derived from six genetically diverse wild strains of the green algaChlamydomonas reinhardtii. We identified 6,843 spontaneous mutations, more than any other study of spontaneous mutation. We observed seven-fold variation in the mutation rate among strains and that mutator genotypes arose, increasing the mutation rate dramatically in some replicates. We also found evidence for fine-scale heterogeneity in the mutation rate, driven largely by the sequence flanking mutated sites, and by clusters of multiple mutations at closely linked sites. There was little evidence, however, for mutation rate heterogeneity between chromosomes or over large genomic regions of 200Kbp. Using logistic regression, we generated a predictive model of the mutability of sites based on their genomic properties, including local GC content, gene expression level and local sequence context. Our model accurately predicted the average mutation rate and natural levels of genetic diversity of sites across the genome. Notably, trinucleotides vary 17-fold in rate between the most mutable and least mutable sites. Our results uncover a rich heterogeneity in the process of spontaneous mutation both among individuals and across the genome.

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