Biomedical subjects

Christian D Huber

Publications and source records attributed to Christian D Huber.

5 recordsLinked to original sources

PubMed2026

The distribution of fitness effects of nonsynonymous mutations varies phylogenetically across animals.

The distribution of fitness effects (DFE) describes the selection coefficients of newly arising mutations and fundamentally influences population genetic processes. However, the extent and mechanisms of differences in the DFE for non-synonymous mutations have not been systematically investigated across species with divergent phylogenetic histories and ecologies. Here, we inferred the DFE in natural populations of 11 animal (sub)species, including humans, mice, fin whales, vaquitas, wolves, collared flycatchers, pied flycatchers, halictid bees, Drosophila, and mosquitoes. We found that mammals have a higher proportion of strongly deleterious mutations (defined as s≤-0.01; 22% to 47% in mammals; 0.0% to 5.4% in insects and birds) and a lower proportion of weakly deleterious mutations than insects and birds. Further, the DFE co-varies with phylogeny, such that the mean mutation effects are more similar in closely related species (Pagel's λ = 0.84, P = 0.01). Next, we investigated whether various summary statistics of the DFE were related to variation in life-history traits across these organisms. We found some support for genome size, body mass, and long-term effective population size being correlated with the DFE. Overall, our findings are consistent with predictions derived independently from the Fisher's Geometric Model (FGM), which defines organismal complexity as the number of phenotypes under selection. FGM predicts that mutations are more deleterious in complex organisms, while strongly deleterious mutations occur more frequently in smaller populations. Our study demonstrates strong phylogenetic signal in the evolution of a fundamental population genetics parameter, and proposes that, through mechanisms of epistasis, long-term population size and organismal complexity could be underlying variation in the DFE across animals.

Journal Article↗

PubMed2026

Seasonal fluctuations in fitness result in severe reductions in effective population size.

Genetic evidence for fluctuating selection has begun to accumulate for different species over the past few decades, especially for the Drosophila genus where studies have reported hundreds of loci undergoing putatively adaptive oscillations across successive seasons. However, most theoretical and simulation studies of fluctuating selection have relied on abstract or weakly parameterized models, making it difficult to assess their relevance for natural populations. In this study, we simulate multilocus seasonally fluctuating selection acting on standing genetic variation under a recently developed model and examine its effect on the variance effective population size (Ne) at a genome-wide scale. By recapitulating genomic, demographic, and evolutionary parameters from natural Drosophila populations in our simulations, we were able to reproduce allele frequency oscillations reported in recent studies and show that these lead to ∼50% genome-wide reductions in Ne. We also demonstrate that Ne reductions are well predicted by the maximum frequency amplitude among all adaptively fluctuating loci, and that the frequency amplitudes are largely determined by the number of adaptively fluctuating loci and the strength of their epistatic interactions. Our results demonstrate that fluctuating selection can substantially reduce effective population size and underscore the importance of temporally variable selection in shaping genome-wide patterns of variation beyond classical models.

Drosophila melanogaster↗

PubMed2026

Seasonal fluctuations in fitness result in severe reductions in effective population size.

Genetic evidence for fluctuating selection has begun to accumulate for different species over the past few decades, especially for the Drosophila genus where studies have reported hundreds of loci undergoing putatively adaptive oscillations across successive seasons. However, most theoretical and simulation studies of fluctuating selection have relied on abstract or weakly parameterized models, making it difficult to assess their relevance for natural populations. In this study, we simulate multilocus seasonally fluctuating selection under a recently developed model and examine its effect on the variance effective population size (Ne ) at a genome-wide scale. By recapitulating genomic, demographic, and evolutionary parameters from natural Drosophila populations in our simulations, we were able to reproduce allele frequency oscillations reported in recent studies and show that these lead to ~50% genome-wide reductions in Ne . We also demonstrate that Ne reductions are well predicted by the maximum frequency amplitude among all adaptively fluctuating loci, and that the frequency amplitudes are largely determined by the number of adaptively fluctuating loci and the strength of their epistatic interactions. Our results demonstrate that fluctuating selection can substantially reduce effective population size and underscore the importance of temporally variable selection in shaping genome-wide patterns of variation beyond classical models.

Drosophila melanogaster↗

PubMed2025

Accessible, realistic genome simulation with selection using stdpopsim.

Selection is a fundamental evolutionary force that shapes patterns of genetic variation across species. However, simulations incorporating realistic selection along heterogeneous genomes in complex demographic histories are challenging, limiting our ability to benchmark statistical methods aimed at detecting selection and to explore theoretical predictions. stdpopsim is a community-maintained simulation library that already provides an extensive catalog of species-specific population genetic models. Here we present a major extension to the stdpopsim framework that enables simulation of various modes of selection, including background selection, selective sweeps, and arbitrary distributions of fitness effects (DFE) acting on annotated subsets of the genome (for instance, exons). This extension maintains stdpopsim's core principles of reproducibility and accessibility while adding support for species-specific genomic annotations and published DFE estimates. We demonstrate the utility of this framework by comparing methods for demographic inference, DFE estimation, and selective sweep detection across several species and scenarios. Our results demonstrate the robustness of demographic inference methods to selection on linked sites, reveal the sensitivity of DFE-inference methods to model assumptions, and show how genomic features, like recombination rate and functional sequence density, influence power to detect selective sweeps. This extension to stdpopsim provides a powerful new resource for the population genetics community to explore the interplay between selection and other evolutionary forces in a reproducible, user-friendly framework.

Journal Article↗

PubMed2025

The distribution of fitness effects varies phylogenetically across animals.

The distribution of fitness effects (DFE) describes the selection coefficients () of newly arising mutations and fundamentally influences population genetic processes. However, the extent and mechanisms of DFE variation have not been systematically investigated across species with divergent phylogenetic histories and ecological functions. Here, we inferred the DFE in natural populations of eleven animal (sub)species, including humans, mice, fin whales, vaquitas, wolves, collared flycatchers, pied flycatchers, halictid bees, Drosophila, and mosquitoes. We find that the DFE co-varies with phylogeny, where the expected mutation effects are more similar in closely related species (). Additionally, mammals have a higher proportion of strongly deleterious mutations (22% to 47% in mammals; 0.0% to 5.4% in insects and birds) and a lower proportion of weakly deleterious mutations than insects and birds. Population size is significantly negatively correlated with the expected impact of new deleterious mutations (), and the proportion of new beneficial mutations (). These findings align with Fisher's Geometric Model (FGM), which defines organismal complexity as the number of phenotypes under selection. Consistent with the FGM's predictions, we observe that mutations are more deleterious in complex organisms, while beneficial mutations occur more frequently in smaller populations to compensate for the drift load. Our study demonstrates strong phylogenetic constraints in the evolution of a fundamental population genetics parameter, and proposes that, through mechanisms of global epistasis, long-term population size and organismal complexity drive variation in the DFE across animals.

Fisher’s geometric model↗