ArticleGenetics2011
A method for inferring the rate of occurrence and fitness effects of advantageous mutations.
Article in Genetics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 77 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
77 citing papers in PubMed.
- What has population genomics told us about the dynamics of selection and plant adaptation?Molecular biology and evolution · 2026Review
- Inferring Patterns of Purifying, Positive, and Balancing Selection in the Coppery Titi Monkey (Plecturocebus cupreus) Utilizing a Well-Fit Evolutionary Baseline Model.Genome biology and evolution · 2026Article
- Polarising SNPs Without Outgroup.Molecular ecology resources · 2026Article
- Recent Insights Into the Evolutionary Genomics of the Critically Endangered Aye-Aye (Daubentonia madagascariensis).American journal of primatology · 2025Review
- Article
- Estimating the Distribution of Fitness Effects in Aye-Ayes (Daubentonia madagascariensis), Accounting for Population History as Well as Mutation and Recombination Rate Heterogeneity.American journal of primatology · 2025Article
- Inferring demographic and selective histories from population genomic data using a 2-step approach in species with coding-sparse genomes: an application to human data.G3 (Bethesda, Md.) · 2025Article
- Inferring demographic and selective histories from population genomic data using a two-step approach in species with coding-sparse genomes: an application to human data.bioRxiv : the preprint server for biology · 2024Article
- Genomic evidence for rediploidization and adaptive evolution following the whole-genome triplication.Nature communications · 2024Article
- Inferring the mode and strength of ongoing selection.Genome research · 2023Article
- On the prospect of achieving accurate joint estimation of selection with population history.Genome biology and evolution · 2022Article
- A Nearly Neutral Model of Molecular Signatures of Natural Selection after Change in Population Size.Genome biology and evolution · 2022Article
- Dominance shifts increase the likelihood of soft selective sweeps.Evolution; international journal of organic evolution · 2022Article
- Recommendations for improving statistical inference in population genomics.PLoS biology · 2022Article
- Population-Genomic Analysis Identifies a Low Rate of Global Adaptive Fixation in the Proteins of the Cyclical Parthenogen Daphnia magna.Molecular biology and evolution · 2022Article
- Inferring the distribution of fitness effects in patient-sampled and experimental virus populations: two case studies.Heredity · 2022Article
- Hunting for Beneficial Mutations: Conditioning on SIFT Scores When Estimating the Distribution of Fitness Effect of New Mutations.Genome biology and evolution · 2022Article
- Selection on Accessible Chromatin Regions in Capsella grandiflora.Molecular biology and evolution · 2021Article
- Recombination Facilitates Adaptive Evolution in Rhizobial Soil Bacteria.Molecular biology and evolution · 2021Article
- Evidence for a force favoring GC over AT at short intronic sites in Drosophila simulans and Drosophila melanogaster.G3 (Bethesda, Md.) · 2021Article
17 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
The distribution of fitness effects (DFE) of new mutations is of fundamental importance in evolutionary genetics. Recently, methods have been developed for inferring the DFE that use information from the allele frequency distributions of putatively neutral and selected nucleotide polymorphic variants in a population sample. Here, we extend an existing maximum-likelihood method that estimates the DFE under the assumption that mutational effects are unconditionally deleterious, by including a fraction of positively selected mutations. We allow one or more classes of positive selection coefficients in the model and estimate both the fraction of mutations that are advantageous and the strength of selection acting on them. We show by simulations that the method is capable of recovering the parameters of the DFE under a range of conditions. We apply the method to two data sets on multiple protein-coding genes from African populations of Drosophila melanogaster. We use a probabilistic reconstruction of the ancestral states of the polymorphic sites to distinguish between derived and ancestral states at polymorphic nucleotide sites. In both data sets, we see a significant improvement in the fit when a category of positively selected amino acid mutations is included, but no further improvement if additional categories are added. We estimate that between 1% and 2% of new nonsynonymous mutations in D. melanogaster are positively selected, with a scaled selection coefficient representing the product of the effective population size, N(e), and the strength of selection on heterozygous carriers of ∼2.5.
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