Inferring evolutionary dynamics of mutation rates through the lens of mutation spectrum variation

Carlson, Jedidiah; DeWitt, William S; Harris, Kelley

doi:10.1016/j.gde.2020.05.024

Cited by 29 publications

(27 citation statements)

References 66 publications

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“…Our analysis of present-day trios did not show this mutational signature, confirming that 1000G-Sig2 has an ancient source 3,4,27,28 . The signature 1000G-Sig2 can be modelled by a linear combination of two cancer signatures SBS7a and SBS11.…”

Section: Discussionsupporting

confidence: 55%

“…Our analyses revealed that present-day de novo germline mutations can be described using a single mutational signature, which is population independent. We also identified a European-specific signature reported previously [3][4][5]17,27,28 and a novel mutational signature that is specific to mitochondria DNA.…”

Section: Introductionmentioning

confidence: 67%

“…The second signature (1000G-Sig2) is composed, almost exclusively, of highly context-specific C>T mutations (TCC>TTC, TCT>TTT, ACC>ATC, and CCC>CTC) and is significantly more prevalent in European populations. Previous studies have identified most of these trinucleotide motifs within which C>T changes are enriched in Europeans [3][4][5]17,28 . Our matrix deconvolution approaches precisely identified these mutation types and grouped them into a distinct mutational signature.…”

Section: Discussionmentioning

confidence: 99%

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Signatures of Mutational Processes in Human DNA Evolution

Hamidi

Alinejad‐Rokny

Coorens

et al. 2021

Preprint

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The human genome contains over 100 million SNPs, most of which are C/T (G/A) variations. The type and sequence context of these SNPs are not random, suggesting that they are caused by distinct mutational processes. Deciphering the mutational signatures is a crucial step to discovering the molecular processes responsible for DNA variations across human populations, and potentially for causing genetic diseases. Our analyses of the 1000 Genomes Project SNPs and germline de novo mutations suggest that at least four mutational processes are responsible for human genetic variations. One process is European-specific and no longer active. The remaining three processes are currently active in all human populations. Two of the active processes co-occur and leave a single joint mutational signature in human nuclear DNA. The third active process is specific to mitochondrial DNA, and inflicts C-to-T mutations at mostly non-CG sites. We found neither evidence of APOBEC-induced cytosine deamination in the human germline, nor de novo mutation enrichment within certain regions of the human genome.

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Section: Discussionsupporting

confidence: 55%

Section: Introductionmentioning

confidence: 67%

Section: Discussionmentioning

confidence: 99%

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Signatures of Mutational Processes in Human DNA Evolution

Hamidi

Alinejad‐Rokny

Coorens

et al. 2021

Preprint

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“…An independent source of information for estimating differences in generation time is the rate and spectrum of derived alleles accumulating in genomes over a given amount of time 9,10 . Pedigree studies have shown that the yearly mutation rate slightly decreases when the generation time increases because the mutational burst in the germline before puberty represents a high proportion of new mutations in young parents 4 .…”

Section: Introductionmentioning

confidence: 99%

Different historical generation intervals in human populations inferred from Neanderthal fragment lengths and patterns of mutation accumulation

Skov

Peter

et al. 2021

Preprint

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After the main out-of-Africa event, humans interbred with Neanderthals leaving 1-2% of Neanderthal DNA scattered in small fragments in all non-African genomes today1,2. Here we investigate the size distribution of these fragments in non-African genomes3. We find consistent differences in fragment length distributions across Eurasia with 11% longer fragments in East Asians than in West Eurasians. By comparing extant populations and ancient samples, we show that these differences are due to a different rate of decay in length by recombination since the Neanderthal admixture. In line with this, we observe a strong correlation between the average fragment length and the accumulation of derived mutations, similar to what is expected by changing the ages at reproduction as estimated from trio studies4. Altogether, our results suggest consistent differences in the generation interval across Eurasia, by up to 20% (e.g. 25 versus 30 years), over the past 40,000 years. We use sex-specific accumulations of derived alleles to infer how these changes in generation intervals between geographical regions could have been mainly driven by shifts in either male or female age of reproduction, or both. We also find that previously reported variation in the mutational spectrum5 may be largely explained by changes to the generation interval and not by changes to the underlying mutational mechanism. We conclude that Neanderthal fragment lengths provide unique insight into differences of a key demographic parameter among human populations over the recent history.

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“…Diverse mutational processes can reveal themselves in tell-tale mutation signatures left in the nucleotide sequence contexts in which they tend to be active. Population genomics has given increasing attention to nucleotide sequence context in the study of the germline mutation process (reviewed by Carlson et al 2020). SNPs can be assigned mutation context based on an estimate of the ancestral background they occurred on.…”

Section: Introductionmentioning

confidence: 99%

mutyper: assigning and summarizing mutation types for analyzing germline mutation spectra

DeWitt

2020

Preprint

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AbstractSummaryCharacterization of germline mutation spectrum variation from population genomics data has shed light on the biological complexity of the mutation process, and its evolution within and between species. This analysis augments available population SNP data with estimates of local ancestral genomic context to assign mutation types and aggregate summary statistics thereof, and is increasingly common. There is a need for standardized computational tools to extract mutation spectrum information from sequencing data. Here I describe mutyper, a command-line utility and Python package that uses an ancestral genome estimate to assign mutation types to SNP data, compute mutation spectra for individuals, and compute sample frequency spectra resolved by mutation type for population genetic inference.Availability and implementationmutyper can be installed using the pip package manager and is compatible with Python 3.6+. Documentation is provided at https://harrispopgen.github.io/mutyper; source code is available at https://github.com/harrispopgen/mutyper.

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Inferring evolutionary dynamics of mutation rates through the lens of mutation spectrum variation

Cited by 29 publications

References 66 publications

Signatures of Mutational Processes in Human DNA Evolution

Signatures of Mutational Processes in Human DNA Evolution

Different historical generation intervals in human populations inferred from Neanderthal fragment lengths and patterns of mutation accumulation

mutyper: assigning and summarizing mutation types for analyzing germline mutation spectra

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