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

DeWitt, William S

doi:10.1101/2020.07.01.183392

Cited by 6 publications

(5 citation statements)

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“…We considered all possible triplet changes (3-mers), first quantifying the number of ancestral GC bases and triplets in SDs (Fig. 4a) (Jiang et al 2007; Harris 2015; DeWitt 2020). A PCA of these normalized mutational spectra shows clear discrimination (Fig.…”

Section: Resultsmentioning

confidence: 99%

“…To further investigate the changes in GC content and their effect on variation in SDs, we compared the triplet mutational spectra of SNVs from unique and duplicated regions of the genome to determine if there were significant shifts in the predominant modes of mutation (DeWitt 2020; Carlson, DeWitt, and Harris 2020). We considered all possible triplet changes (3-mers), first quantifying the number of ancestral GC bases and triplets in SDs (Fig.…”

Section: Resultsmentioning

confidence: 99%

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Increased mutation rate and interlocus gene conversion within human segmental duplications

DeWitt

Dishuck

Harvey

et al. 2022

Preprint

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Single-nucleotide variants (SNVs) within segmental duplications (SDs) have not been systematically assessed because of the difficulty in mapping short-read sequence data to virtually identical repetitive sequences. Using 102 phased human haplotypes, we constructed 1:1 unambiguous alignments spanning high-identity SDs and compared the pattern of SNVs between unique and SD regions. We find that human SNVs are elevated 60% in SDs compared to unique regions. We estimate that at least 23% of this increase is due to interlocus gene conversion (IGC) with >7 Mbp of SD sequence converted on average per human haplotype. We develop a genome-wide map of IGC donors and acceptors, including 498 acceptor and 454 donor hotspots affecting the exons of ~800 protein-coding genes. The latter includes 171 genes that have "relocated" on average 1.61 Mbp in a subset of human haplotypes. Using a coalescent framework, we show that SD regions are evolutionarily older when compared to unique sequences with most of this signal originating from putative IGC loci. SNVs within SDs, however, also exhibit a distinct mutational spectrum where there is a 27.1% increase in transversions that convert cytosine to guanine or the reverse across all triplet contexts. In addition, we observe a 7.6% reduction in the frequency of CpG associated mutations when compared to unique DNA. We hypothesize that these distinct mutational properties help to maintain an overall higher GC content of SD DNA when compared to unique DNA, and we show that these GC-favoring mutational events are likely driven by GC-biased conversion between paralogous sequences.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Increased mutation rate and interlocus gene conversion within human segmental duplications

DeWitt

Dishuck

Harvey

et al. 2022

Preprint

Self Cite

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“…We generated

-SFS data for each 1KG population using mutyper ( 80 , 81 ) and BCFtools ( 82 , 83 ). High-coverage 1KG variant call data ( 27 ) were accessed from ref.…”

Section: Software Implementation Methodsmentioning

confidence: 99%

Nonparametric coalescent inference of mutation spectrum history and demography

DeWitt

Harris

Ragsdale

et al. 2021

Proc. Natl. Acad. Sci. U.S.A.

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As populations boom and bust, the accumulation of genetic diversity is modulated, encoding histories of living populations in present-day variation. Many methods exist to decode these histories, and all must make strong model assumptions. It is typical to assume that mutations accumulate uniformly across the genome at a constant rate that does not vary between closely related populations. However, recent work shows that mutational processes in human and great ape populations vary across genomic regions and evolve over time. This perturbs the mutation spectrum (relative mutation rates in different local nucleotide contexts). Here, we develop theoretical tools in the framework of Kingman’s coalescent to accommodate mutation spectrum dynamics. We present mutation spectrum history inference (mushi), a method to perform nonparametric inference of demographic and mutation spectrum histories from allele frequency data. We use mushi to reconstruct trajectories of effective population size and mutation spectrum divergence between human populations, identify mutation signatures and their dynamics in different human populations, and calibrate the timing of a previously reported mutational pulse in the ancestors of Europeans. We show that mutation spectrum histories can be placed in a well-studied theoretical setting and rigorously inferred from genomic variation data, like other features of evolutionary history.

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“…The inference of the mutation spectra was performed using Mutyper (v0.6.1) 50 and the sequential dinucleotide mutation (SDM) approach from Prendergast et al 6 . The two algorithms were implemented into nSPECTRa (nextflow SPECTRum analysis), a novel Nextflow mutation spectrum analysis workflow that performs the analyses in a species-agnostic, low-interaction and highly parallelised fashion.…”

Section: Methodsmentioning

confidence: 99%

“…Consequently, despite the importance of better understanding how patterns of mutation differ between individuals, little work has been done to study mutation spectra differences outside of the major model organisms 18,19 due to a lack of suitable large whole-genome sequenced cohorts and easy-to-use software tools. However, factors such as the ever-decreasing costs of whole-genome sequencing and the availability of tools for studying SNV mutation rates, such as mutyper 20 and Relate 21 , have now enabled the potential application of these approaches across a wider range of species. In this study, we expand on these tools to develop a unified, reusable workflow and analysis approach that can characterise different types of SNV and SDM mutation spectra in any diploid species and apply it to study the evolution and convergence of mutation spectra.…”

Section: Introductionmentioning

confidence: 99%

The evolution and convergence of mutation spectra across mammals

Talenti,

Wilkinson,

Morrison

et al. 2023

Preprint

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Despite the key role genetic mutations play in shaping phenotypic differences between species, little is currently known about the evolution of germline mutation spectra across mammals. Domesticated species are likely particularly interesting case studies because of their high mutation rates and complex evolutionary histories, which can span multiple founding events and genetic bottlenecks. Here we have developed a new reusable workflow, nSPECTRa, that can undertake the key steps in characterising mutation spectra, from determining ancestral alleles to characterising multiple forms of variation. We apply nSPECTRa to seven species, including several that have undergone domestication, and highlight how nSPECTRa can provide important novel insights into mutation rate evolution. While mutation spectra most often show marked differences between species and even breeds, certain mutation types have risen to a high frequency in subpopulations of different species, indicative of convergent evolution in mutation rates. This includes the previously characterized TCC->TTC change enriched among European humans, which is also enriched among East Asian cattle. We show Indicine cattle are particularly interesting examples of how different mutation spectra segregate within a population and subsequently spread across the globe. Together, this work has important implications for understanding the control and evolution of mammalian mutation rates.

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

Cited by 6 publications

References 10 publications

Increased mutation rate and interlocus gene conversion within human segmental duplications

Increased mutation rate and interlocus gene conversion within human segmental duplications

Nonparametric coalescent inference of mutation spectrum history and demography

The evolution and convergence of mutation spectra across mammals

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