ArticleGenetics2009
Measuring the rates of spontaneous mutation from deep and large-scale polymorphism data.
Article in Genetics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.
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Who cites it
35 citing papers in PubMed.
- Evolution of the rate, molecular spectrum, and fitness effects of mutation under minimal selection in Caenorhabditis elegans.Genetics · 2026Article
- Evolution of the rate, molecular spectrum, and fitness effects of mutation under minimal selection inbioRxiv : the preprint server for biology · 2026Article
- Evolutionary Insights from a Large-Scale Survey of Population-Genomic Variation.Molecular biology and evolution · 2023Article
- Evolutionary Genomics of Sister Species Differing in Effective Population Sizes and Recombination Rates.Genome biology and evolution · 2023Article
- Evolutionary Insights from a Large-scale Survey of Population-genomic Variation.bioRxiv : the preprint server for biology · 2023Article
- Article
- Evolutionary Genomics of a Subdivided Species.Molecular biology and evolution · 2022Article
- Mutational bias in spermatogonia impacts the anatomy of regulatory sites in the human genome.Genome research · 2021Article
- Mutability of mononucleotide repeats, not oxidative stress, explains the discrepancy between laboratory-accumulated mutations and the natural allele-frequency spectrum inGenome research · 2021Article
- The Effects of GC-Biased Gene Conversion on Patterns of Genetic Diversity among and across Butterfly Genomes.Genome biology and evolution · 2021Article
- Inference of Historical Population-Size Changes with Allele-Frequency Data.G3 (Bethesda, Md.) · 2020Article
- Extremely rare variants reveal patterns of germline mutation rate heterogeneity in humans.Nature communications · 2018Article
- Development of the variant calling algorithm, ADIScan, and its use to estimate discordant sequences between monozygotic twins.Nucleic acids research · 2018Article
- Transfer RNA genes experience exceptionally elevated mutation rates.Proceedings of the National Academy of Sciences of the United States of America · 2018Article
- Transcription-Associated Compositional Skews in Drosophila Genes.Genome biology and evolution · 2018Article
- Deep sequencing of natural and experimental populations ofGenome research · 2017Article
- Population Genomics ofGenetics · 2017Article
- Extremely Rare Polymorphisms in Saccharomyces cerevisiae Allow Inference of the Mutational Spectrum.PLoS genetics · 2017Article
- Selection on Inversion Breakpoints Favors Proximity to Pairing Sensitive Sites in Drosophila melanogaster.Genetics · 2016Article
- Mutation--The Engine of Evolution: Studying Mutation and Its Role in the Evolution of Bacteria.Cold Spring Harbor perspectives in biology · 2015Review
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Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The rates and patterns of spontaneous mutation are fundamental parameters of molecular evolution. Current methodology either tries to measure such rates and patterns directly in mutation-accumulation experiments or tries to infer them indirectly from levels of divergence or polymorphism. While experimental approaches are constrained by the low rate at which new mutations occur, indirect approaches suffer from their underlying assumption that mutations are effectively neutral. Here I present a maximum-likelihood approach to estimate mutation rates from large-scale polymorphism data. It is demonstrated that the method is not sensitive to demography and the distribution of selection coefficients among mutations when applied to mutations at sufficiently low population frequencies. With the many large-scale sequencing projects currently underway, for instance, the 1000 genomes project in humans, plenty of the required low-frequency polymorphism data will shortly become available. My method will allow for an accurate and unbiased inference of mutation rates and patterns from such data sets at high spatial resolution. I discuss how the assessment of several long-standing problems of evolutionary biology would benefit from the availability of accurate mutation rate estimates.
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