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

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.

Download Full-text

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

eLife ◽

10.7554/elife.73577 ◽

2022 ◽

Vol 11 ◽

Author(s):

Lucie A Bergeron ◽

Søren Besenbacher ◽

Tychele Turner ◽

Cyril J Versoza ◽

Richard J 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.

Download Full-text

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.

Download Full-text

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.

Download Full-text

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.

Download Full-text

Human germline mutation and the erratic evolutionary clock

10.1101/058024 ◽

2016 ◽

Cited By ~ 4

Author(s):

Priya Moorjani ◽

Ziyue Gao ◽

Molly Przeworski

Keyword(s):

Human Evolution ◽

Mutation Rate ◽

Germline Mutation ◽

Molecular Clock ◽

Mutation Rates ◽

Evolutionary Lineage ◽

Precise Characterization ◽

Evolutionary Clock ◽

Males And Females

AbstractOur understanding of the chronology of human evolution relies on the “molecular clock” provided by the steady accumulation of substitutions on an evolutionary lineage. Recent analyses of human pedigrees have called this understanding into question, by revealing unexpectedly low germline mutation rates, which imply that substitutions accrue more slowly than previously believed. Translating mutation rates estimated from pedigrees into substitution rates is not as straightforward as it may seem, however. We dissect the steps involved, emphasizing that dating evolutionary events requires not “a mutation rate,” but a precise characterization of how mutations accumulate in development, in males and females—knowledge that remains elusive.

Download Full-text