ArticleGenetics2016
Triallelic Population Genomics for Inferring Correlated Fitness Effects of Same Site Nonsynonymous Mutations.
Article in Genetics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed.
- Allelic gene conversion softens selective sweeps.Genetics · 2026Article
- Accessible, Realistic Genome Simulation with Selection Using stdpopsim.Molecular biology and evolution · 2025Article
- Accessible, realistic genome simulation with selection using stdpopsim.bioRxiv : the preprint server for biology · 2025Article
- Isolating selective from non-selective forces using site frequency ratios.PLoS genetics · 2025Article
- Population size rescaling significantly biases outcomes of forward-in-time population genetic simulations.Genetics · 2025Article
- Detection of domestication signals through the analysis of the full distribution of fitness effects.Peer community journal · 2025Article
- Population size rescaling significantly biases outcomes of forward-in-time population genetic simulations.bioRxiv : the preprint server for biology · 2024Article
- Identifying rare variants inconsistent with identity-by-descent in population-scale whole-genome sequencing data.Methods in ecology and evolution · 2022Article
- Article
- Article
- Inferring Genome-Wide Correlations of Mutation Fitness Effects between Populations.Molecular biology and evolution · 2021Article
- Inferring Demographic History Using Two-Locus Statistics.Genetics · 2017Article
- Inference of the Distribution of Selection Coefficients for New Nonsynonymous Mutations Using Large Samples.Genetics · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The distribution of mutational effects on fitness is central to evolutionary genetics. Typical univariate distributions, however, cannot model the effects of multiple mutations at the same site, so we introduce a model in which mutations at the same site have correlated fitness effects. To infer the strength of that correlation, we developed a diffusion approximation to the triallelic frequency spectrum, which we applied to data from Drosophila melanogaster We found a moderate positive correlation between the fitness effects of nonsynonymous mutations at the same codon, suggesting that both mutation identity and location are important for determining fitness effects in proteins. We validated our approach by comparing it to biochemical mutational scanning experiments, finding strong quantitative agreement, even between different organisms. We also found that the correlation of mutational fitness effects was not affected by protein solvent exposure or structural disorder. Together, our results suggest that the correlation of fitness effects at the same site is a previously overlooked yet fundamental property of protein evolution.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.