The mutationathon highlights the importance of reaching standardization in estimates of pedigree-based germline mutation rates

In the past decade, several studies have estimated the human per-generation germline mutation rate using large pedigrees. More recently, estimates for various non-human species have been published. However, methodological differences among studies in detecting germline mutations and estimating mutation rates make direct comparisons difficult. Here, we describe the many different steps involved in estimating pedigree-based mutation rates, including sampling, sequencing, mapping, variant calling, filtering, and how to appropriately account for false-positive and false-negative rates. For each step, we review the different methods and parameter choices that have been used in the recent literature. Additionally, we present the results from a 'Mutationathon', a competition organized among five research labs to compare germline mutation rate estimates for a single pedigree of rhesus macaques. We report almost a two-fold variation in the final estimated rate among groups using different post-alignment processing, calling, and filtering criteria and provide details into the sources of variation across studies. Though the difference among estimates is not statistically significant, this discrepancy emphasizes the need for standardized methods in mutation rate estimations and the difficulty in comparing rates from different studies. Finally, this work aims to provide guidelines for computational and statistical benchmarks for future studies interested in identifying germline mutations from pedigrees.

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Mutationathon: towards standardization in estimates of pedigree-based germline mutation rates

10.1101/2021.08.30.458162 ◽

2021 ◽

Author(s):

Lucie A. Bergeron ◽

Søren Besenbacher ◽

Tychele N. Turner ◽

Cyril J. Versoza ◽

Richard Wang ◽

...

Keyword(s):

Mutation Rate ◽

Germline Mutation ◽

Rhesus Macaques ◽

False Negative ◽

Variant Calling ◽

Germline Mutations ◽

Mutation Rates ◽

Sources Of Variation ◽

The Difference ◽

The Many

In the past decade, several studies have estimated the human per-generation germline mutation rate using large pedigrees. More recently, estimates for various non-human species have been published. However, methodological differences among studies in detecting germline mutations and estimating mutation rates make direct comparisons difficult. Here, we describe the many different steps involved in estimating pedigree-based mutation rates, including sampling, sequencing, mapping, variant calling, filtering, and how to appropriately account for false-positive and false-negative rates. For each step, we review the different methods and parameter choices that have been used in the recent literature. Additionally, we present the results from a "Mutationathon", a competition organized among five research labs to compare germline mutation rate estimates for a single pedigree of rhesus macaques. We report almost a two-fold variation in the final estimated rate among groups using different post-alignment processing, calling, and filtering criteria and provide details into the sources of variation across studies. Though the difference among estimates is not statistically significant, this discrepancy emphasizes the need for standardized methods in mutation rate estimations and the difficulty in comparing rates from different studies. Finally, this work aims to provide guidelines for computational and statistical benchmarks for future studies interested in identifying germline mutations from pedigrees.

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Studying mutation rate evolution in primates—a need for systematic comparison of computational pipelines

GigaScience ◽

10.1093/gigascience/giab072 ◽

2021 ◽

Vol 10 (10) ◽

Author(s):

Lucie A Bergeron ◽

Søren Besenbacher ◽

Mikkel H Schierup ◽

Guojie Zhang

Keyword(s):

Best Practices ◽

Mutation Rate ◽

Germline Mutation ◽

Macaca Mulatta ◽

A comparison of humans and baboons suggests germline mutation rates do not track cell divisions

10.1101/844910 ◽

2019 ◽

Cited By ~ 1

Author(s):

Felix L. Wu ◽

Alva Strand ◽

Carole Ober ◽

Jeffrey D. Wall ◽

Priya Moorjani ◽

...

Keyword(s):

Mutation Rate ◽

Divergence Time ◽

Germline Mutations ◽

Mutation Rates ◽

Papio Anubis ◽

Male Bias ◽

Olive Baboons ◽

Replication Errors ◽

Cell Divisions ◽

Stem Cell Divisions

AbstractIn humans, most germline mutations are inherited from the father. This observation is widely interpreted as resulting from the replication errors that accrue during spermatogenesis. If so, the male bias in mutation should be substantially lower in a closely related species with similar rates of spermatogonial stem cell divisions but a shorter mean age of reproduction. To test this hypothesis, we resequenced two 3–4 generation nuclear families (totaling 29 individuals) of olive baboons (Papio anubis), who reproduce at ~10 years of age on average. We inferred sex-specific mutation rates by analyzing the data in parallel with three three-generation human pedigrees (26 individuals). The mutation rate per generation in baboons is 0.55×10−8 per base pair, approximately half that of humans. Strikingly, however, the degree of male mutation bias is approximately 3:1, similar to that of humans; in fact, a similar male bias is seen across mammals that reproduce months, years or decades after birth. These results echo findings in humans that the male bias is stable with parental ages and cast further doubt on the assumption that germline mutations track cell divisions. Our mutation rate estimates for baboons raise a further puzzle in suggesting a divergence time between apes and Old World Monkeys of 67 My, too old to be consistent with the fossil record; reconciling them now requires not only a slowdown of the mutation rate per generation in humans but also in baboons.

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Spontaneous mutation rate estimates for the principal malaria vectors Anopheles coluzzii and Anopheles stephensi

Scientific Reports ◽

10.1038/s41598-021-03943-z ◽

2022 ◽

Vol 12 (1) ◽

Author(s):

Iliyas Rashid ◽

Melina Campos ◽

Travis Collier ◽

Marc Crepeau ◽

Allison Weakley ◽

...

Keyword(s):

Confidence Interval ◽

Mutation Rate ◽

Anopheles Stephensi ◽

Spontaneous Mutation ◽

False Negative ◽

False Negative Rate ◽

Mutation Rates ◽

Malaria Vectors ◽

Base Substitution ◽

Anopheles Coluzzii

AbstractUsing high-depth whole genome sequencing of F0 mating pairs and multiple individual F1 offspring, we estimated the nuclear mutation rate per generation in the malaria vectors Anopheles coluzzii and Anopheles stephensi by detecting de novo genetic mutations. A purpose-built computer program was employed to filter actual mutations from a deep background of superficially similar artifacts resulting from read misalignment. Performance of filtering parameters was determined using software-simulated mutations, and the resulting estimate of false negative rate was used to correct final mutation rate estimates. Spontaneous mutation rates by base substitution were estimated at 1.00 × 10−9 (95% confidence interval, 2.06 × 10−10—2.91 × 10−9) and 1.36 × 10−9 (95% confidence interval, 4.42 × 10−10—3.18 × 10−9) per site per generation in A. coluzzii and A. stephensi respectively. Although similar studies have been performed on other insect species including dipterans, this is the first study to empirically measure mutation rates in the important genus Anopheles, and thus provides an estimate of µ that will be of utility for comparative evolutionary genomics, as well as for population genetic analysis of malaria vector mosquito species.

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Appropriate Assignment of Fossil Calibration Information Minimizes the Difference between Phylogenetic and Pedigree Mutation Rates in Humans

Life ◽

10.3390/life8040049 ◽

2018 ◽

Vol 8 (4) ◽

pp. 49 ◽

Cited By ~ 1

Author(s):

Renata Capellão ◽

Elisa Costa-Paiva ◽

Carlos Schrago

Keyword(s):

Mutation Rate ◽

Divergence Time ◽

Mutation Rates ◽

Human Populations ◽

Fossil Calibration ◽

Divergence Time Estimates ◽

Time Estimates ◽

The Mean ◽

The Difference ◽

Coalescent Time

Studies that measured mutation rates in human populations using pedigrees have reported values that differ significantly from rates estimated from the phylogenetic comparison of humans and chimpanzees. Consequently, exchanges between mutation rate values across different timescales lead to conflicting divergence time estimates. It has been argued that this variation of mutation rate estimates across hominoid evolution is in part caused by incorrect assignment of calibration information to the mean coalescent time among loci, instead of the true genetic isolation (speciation) time between humans and chimpanzees. In this study, we investigated the feasibility of estimating the human pedigree mutation rate using phylogenetic data from the genomes of great apes. We found that, when calibration information was correctly assigned to the human–chimpanzee speciation time (and not to the coalescent time), estimates of phylogenetic mutation rates were statistically equivalent to the estimates previously reported using studies of human pedigrees. We conclude that, within the range of biologically realistic ancestral generation times, part of the difference between whole-genome phylogenetic and pedigree mutation rates is due to inappropriate assignment of fossil calibration information to the mean coalescent time instead of the speciation time. Although our results focus on the human–chimpanzee divergence, our findings are general, and relevant to the inference of the timescale of the tree of life.

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A deep learning-based framework for estimating fine-scale germline mutation rates

10.1101/2021.10.25.465689 ◽

2021 ◽

Author(s):

Yiyuan Fang ◽

Shuyi Deng ◽

Cai Li

Keyword(s):

Deep Learning ◽

Mutation Rate ◽

Germline Mutation ◽

Homo Sapiens ◽

Predictive Performance ◽

Training Data ◽

Mutation Rates ◽

Fine Scale ◽

Current State ◽

Genome Wide

Germline mutation rates are essential for genetic and evolutionary analyses. Yet, estimating accurate fine-scale mutation rates across the genome is a great challenge, due to relatively few observed mutations and intricate relationships between predictors and mutation rates. Here we present MuRaL (Mutation Rate Learner), a deep learning-based framework to predict fine-scale mutation rates using only genomic sequences as input. Harnessing human germline variants for comprehensive assessment, we show that MuRaL achieves better predictive performance than current state-of-the-art methods. Moreover, MuRaL can build models with relatively few training mutations and a moderate number of sequenced individuals. It can leverage transfer learning to build models with further less training data and time. We apply MuRaL to produce genome-wide mutation rate profiles for four species - Homo sapiens, Macaca mulatta, Arabidopsis thaliana and Drosophila melanogaster, demonstrating its high applicability. The generated mutation rate profiles and open source software can greatly facilitate related research.

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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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Extremely rare variants reveal patterns of germline mutation rate heterogeneity in humans

10.1101/108290 ◽

2017 ◽

Cited By ~ 10

Author(s):

Jedidiah Carlson ◽

Adam E Locke ◽

Matthew Flickinger ◽

Matthew Zawistowski ◽

Shawn Levy ◽

...

Keyword(s):

Mutation Rate ◽

Germline Mutation ◽

De Novo ◽

Gc Content ◽

Mutation Rates ◽

Rate Heterogeneity ◽

Genomic Features ◽

Genome Wide ◽

Wide Variability ◽

Nucleotide Context

AbstractA detailed understanding of the genome-wide variability of single-nucleotide germline mutation rates is essential to studying human genome evolution. Here we use ∼36 million singleton variants from 3,560 whole-genome sequences to infer fine-scale patterns of mutation rate heterogeneity. Mutability is jointly affected by adjacent nucleotide context and diverse genomic features of the surrounding region, including histone modifications, replication timing, and recombination rate, sometimes suggesting specific mutagenic mechanisms. Remarkably, GC content, DNase hypersensitivity, CpG islands, and H3K36 trimethylation are associated with both increased and decreased mutation rates depending on nucleotide context. We validate these estimated effects in an independent dataset of ∼46,000 de novo mutations, and confirm our estimates are more accurate than previously published estimates based on ancestrally older variants without considering genomic features. Our results thus provide the most refined portrait to date of the factors contributing to genome-wide variability of the human germline mutation rate.

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Striking differences in patterns of germline mutation between mice and humans

10.1101/082297 ◽

2016 ◽

Cited By ~ 10

Author(s):

Sarah J. Lindsay ◽

Raheleh Rahbari ◽

Joanna Kaplanis ◽

Thomas Keane ◽

Matthew E. Hurles

Keyword(s):

Mutation Rate ◽

Germline Mutation ◽

Purifying Selection ◽

Germline Mutations ◽

Spermatogonial Stem Cell ◽

Paternal Age ◽

Effective Population ◽

Population Sizes ◽

Species Specific ◽

Biological Differences

SummaryRecent whole genome sequencing (WGS) studies have estimated that the human germline mutation rate per basepair per generation (∼1.2−10−8) 1,2 is substantially higher than in mice (3.5-5.4−10−9) 3,4, which has been attributed to more efficient purifying selection due to larger effective population sizes in mice compared to humans.5,6,7. In humans, most germline mutations are paternal in origin and the numbers of mutations per offspring increase markedly with paternal age 2,8,9 and more weakly with maternal age 10. Germline mutations can arise at any stage of the cellular lineage from zygote to gamete, resulting in mutations being represented in different proportion and types of cells, with the earliest embryonic mutations being mosaic in both somatic and germline cells. Here we use WGS of multi-sibling mouse and human pedigrees to show striking differences in germline mutation rate and spectra between the two species, including a dramatic reduction in mutation rate in human spermatogonial stem cell (SSC) divisions, which we hypothesise was driven by selection. The differences we observed between mice and humans result from both biological differences within the same stage of embryogenesis or gametogenesis and species-specific differences in cellular genealogies of the germline.

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De Novo Mutation Rate Estimation in Wolves of Known Pedigree

Molecular Biology and Evolution ◽

10.1093/molbev/msz159 ◽

2019 ◽

Vol 36 (11) ◽

pp. 2536-2547 ◽

Cited By ~ 4

Author(s):

Evan M Koch ◽

Rena M Schweizer ◽

Teia M Schweizer ◽

Daniel R Stahler ◽

Douglas W Smith ◽

...

Keyword(s):

Mutation Rate ◽

De Novo ◽

Demographic History ◽

Full Range ◽

False Negative ◽

False Negative Rate ◽

De Novo Mutation ◽

Mutation Rates ◽

Point Estimate ◽

De Novo Mutations

Abstract Knowledge of mutation rates is crucial for calibrating population genetics models of demographic history in units of years. However, mutation rates remain challenging to estimate because of the need to identify extremely rare events. We estimated the nuclear mutation rate in wolves by identifying de novo mutations in a pedigree of seven wolves. Putative de novo mutations were discovered by whole-genome sequencing and were verified by Sanger sequencing of parents and offspring. Using stringent filters and an estimate of the false negative rate in the remaining observable genome, we obtain an estimate of ∼4.5 × 10−9 per base pair per generation and provide conservative bounds between 2.6 × 10−9 and 7.1 × 10−9. Although our estimate is consistent with recent mutation rate estimates from ancient DNA (4.0 × 10−9 and 3.0–4.5 × 10−9), it suggests a wider possible range. We also examined the consequences of our rate and the accompanying interval for dating several critical events in canid demographic history. For example, applying our full range of rates to coalescent models of dog and wolf demographic history implies a wide set of possible divergence times between the ancestral populations of dogs and extant Eurasian wolves (16,000–64,000 years ago) although our point estimate indicates a date between 25,000 and 33,000 years ago. Aside from one study in mice, ours provides the only direct mammalian mutation rate outside of primates and is likely to be vital to future investigations of mutation rate evolution.

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