Abstract
De novo mutations occur at substantially different rates depending on genomic location, sequence context and DNA strand. The success of methods to estimate selection intensity, infer demographic history and map rare disease genes, depends strongly on assumptions about the local mutation rate. Here we present Roulette, a genome-wide mutation rate model at basepair resolution that incorporates known determinants of local mutation rate. Roulette is shown to be more accurate than existing models. We use Roulette to refine the estimates of population growth within Europe by incorporating the full range of human mutation rates. The analysis of significant deviations from the model predictions revealed a tenfold increase in mutation rate in nearly all genes transcribed by polymerase III (Pol III), suggesting a new mutagenic mechanism. We also detected an elevated mutation rate within transcription factor binding sites restricted to sites actively used in testis and residing in promoters.
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Data availability
Polymorphism data used in the study is freely available at https://gnomad.broadinstitute.org/.
De novo mutations have been aggregated from supplementary materials to refs. 13,18.
Mutation rate estimates for autosomes http://genetics.bwh.harvard.edu/downloads/Vova/Roulette/.
Shet values, which measure gene constraints, recalculated with the help of Roulette could be found here http://genetics.bwh.harvard.edu/genescores/selection.html.
Code availability
All the code used to perform the analysis is available at https://github.com/vseplyarskiy/Roulette.
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Acknowledgements
We thank J. Wakeley and L. Fan for helpful suggestions on population genetics theory. We thank D. J. Balick for providing a forward Wright–Fisher simulator. This research was supported by National Institutes of Health under grants R35-GM127131, R01-MH101244, U01-HG012009 and R01-HG010372 along with funding from NGM Biopharmaceuticals. D.J.L. was supported by NLM T15LM007092.
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V.S., E.M.K. and D.J.L. analyzed the data. V.S., E.M.K., D.J.L. and S.S. wrote the paper. All authors designed the study and read and corrected the paper. V.S., E.M.K. and D.J.L. have agreed to alternate the order of their names for respective individual citations.
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J.S.L. and H.H.L. are employed by NGM Biopharmaceuticals Inc. V.S., E.M.K. and S.R.S. are partially funded by NGM Biopharmaceuticals Inc. D.J.L. declares no competing interests.
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Extended data
Extended Data Fig. 1 Effect of replication fork direction on the rate of rare synonymous SNVs.
Four contexts with strongest replication asymmetry. Mutation rate calculated for the regions with the strongest replication fork polarity (top quartile). Mutation rate is relative to the least mutable strand. Error bars show 95% confidence intervals for the ratio of two Poisson variables.
Extended Data Fig. 2 Roulette captures mutation rate variation associated with epigenetic features.
Ten pairs of mutation type and epigenetic features with the strongest effects on mutation rate. To generate bins, we subdivided the genome into five equal size bins by the value of genomic features and then calculated observed and expected mutation rates for each trinucleotide context among synonymous sites. This test was performed on synonymous SNVs and mutation rates were normalized to the rate observed in the first epigenetic bin. RT stands for replication timing. Overall, we analyzed the effect of replication timing, H3k27me3, H3k27me1 and recombination.
Extended Data Fig. 3 Roulette captures accelerated mutation rate in ‘maternal’ regions.
De novo mutation rate inside and outside of maternal regions. Maternal regions are defined as in ref. 5.
Extended Data Fig. 4 Roulette predicts the rate of triallelic SNVs.
Multiple derived alleles could co-occur in the same genomic site. Using Roulette, we predicted the probability of a site containing two derived variants simultaneously (triallelic site) by multiplying the probabilities of each derived allele (this is the correct procedure if derived alleles accumulated independently). In contrast to early studies of multiallelic variants, we do not find deviation from independence.
Extended Data Fig. 5 Pseudo-R2 for noncoding regions.
Pseudo-R2 is calculated for noncoding regions for two datasets: gnomAD v3 and UK Biobank. Since Roulette was trained on noncoding variants from the gnomAD v3, it is expected that Roulette performs better for noncoding variants than synonymous variants. De novo sequencing and UK Biobank population sequencing is an independent dataset from trained data.
Extended Data Fig. 6 An elevated number of de novo mutations at sites with observed SNVs.
Sites were divided into mutation rate bins for the three different models. De novo mutation rates were calculated from whole-genome family sequencing data. Horizontal bars represent 95% Poisson confidence intervals for the de novo mutation rate within each bin. Vertical bars represent 95% confidence intervals for the ratio of Poisson rates between SNV and non-SNV sites within each bin.
Extended Data Fig. 7 Recurrence affects site frequency spectra (SFS).
Proportion of sites in five different classes: monomorphic sites, singletons, doubletons, tripletons and other SNVs with higher allele counts. X-axis shows the per-generation mutation rate, as estimated by Roulette. The dotted line is the expected trend under the infinite sites model.
Extended Data Fig. 8 Roulette performance at different DNA regions, as annotated by ENCODE.
Observed to expected ratio of rare SNVs at different ENCODE annotations. PLS stands for promoters, ELS for enhancers, pPLS and pELS are proximal promoters/enhancers (less than 2 KB from transcription start site), dPLS and dELS (more than 2 KB from transcription start site), DNAse-H3K4me3 are sites that are both hypersensitive to DNase and have signal of H3K4me3, CTCF stands for binding sites of CTCF, multiple labels corresponding to overlapping annotations.
Extended Data Fig. 9 Mutation rate around RNU genes.
Shaded area is 95% Poisson confidence intervals.
Extended Data Fig. 10
Deviation from Roulette’s predictions for three hypermutable classes of genes (RNU, tRNA and Imunoglobulins) and for other sites in the genome (Remaning genome).
Supplementary information
Supplementary Information
Supplementary methods and Supplementary Figs. 1–12.
Supplementary Tables
Supplementary Tables 1–3.
Supplementary Data
Data to draw figures.
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Seplyarskiy, V., Koch, E.M., Lee, D.J. et al. A mutation rate model at the basepair resolution identifies the mutagenic effect of polymerase III transcription. Nat Genet 55, 2235–2242 (2023). https://doi.org/10.1038/s41588-023-01562-0
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DOI: https://doi.org/10.1038/s41588-023-01562-0
