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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↗
PubMed2025

Inference and visualization of complex genotype-phenotype maps with gpmap-tools.

Understanding how biological sequences give rise to observable traits, that is, how genotype maps to phenotype, is a central goal in biology. Yet our knowledge of genotype-phenotype maps in natural systems is limited due to the high dimensionality of sequence space and the context-dependent effects of mutations. The emergence of Multiplex assays of variant effect (MAVEs), along with large collections of natural sequences, offer new opportunities to empirically characterize these maps at an unprecedented scale. However, tools for statistical and exploratory analysis of these high-dimensional data are still needed. To address this gap, we developed gpmap-tools (https://github.com/cmarti/gpmap-tools), a python library that integrates a series of models for inference, phenotypic imputation, and error estimation from MAVE data or collections of natural sequences in the presence of genetic interactions of every possible order. gpmap-tools also provides methods for summarizing patterns of epistasis and visualization of genotype-phenotype maps containing up to millions of genotypes. To demonstrate its utility, we used gpmap-tools to infer genotype-phenotype maps containing 262,144 variants of the Shine-Dalgarno sequence from both genomic 5'UTR sequences and experimental MAVE data. Visualization of the inferred landscapes consistently revealed high-fitness ridges that link core motifs at different distances from the start codon. In summary, gpmap-tools provides a flexible, interpretable framework for studying complex genotype-phenotype maps, opening new avenues for understanding the architecture of genetic interactions and their evolutionary consequences.

Gaussian process↗
PubMed2026

Genetic and environmental interactions outweigh mitonuclear coevolution for complex traits in Drosophila.

The interdependent relationship between mitochondrial and nuclear genomes is a powerful model for understanding how epistasis shapes the architecture and evolution of complex traits. Once considered a neutral marker, mitochondrial DNA variation is now recognized as critical to phenotypic evolution because of its epistatic interactions and history of coevolution with the nuclear genome. A central challenge in evolutionary genetics is to quantify the relative importance of stabilizing and directional selection shaping complex trait distributions within and among species. Both can act on interacting and/or co-evolving genes contributing to quantitative traits, but resolving their relative roles is complicated by the complex architecture of most traits. Here, we use a panel of 90 Drosophila mitonuclear genotypes to quantify the relative contributions of mitochondrial, nuclear, and environmental variation and their interactions to four metabolically demanding complex traits. We sample both within-species and between-species mitochondrial variation and observe stronger interaction effects attributable to within-species variation, consistent with stabilizing selection maintaining mitonuclear function. Additionally, culturing the flies on a mitochondrial Complex I inhibitor, rotenone, reveals significant genotype x environment (G×E and G×G×E) interaction effects, providing insight into how genetic variation can be maintained across changing environments. Our results have broader implications in medicine, where mitochondrial DNA donors with longer purifying selection histories may be safer for mitochondrial replacement therapies.

Journal Article↗
PubMed2025

Compensatory Evolution Following Deleterious Episodes of GC-biased Gene Conversion in Rodents.

GC-biased gene conversion (gBGC) is a widespread evolutionary force associated with meiotic recombination that favors the accumulation of deleterious AT to GC substitutions in proteins, moving them away from their fitness optimum. In many mammals, recombination hotspots have a rapid turnover, leading to episodic gBGC, with the accumulation of deleterious mutations stopping when the recombination hotspot dies. Selection is therefore expected to act to repair the damage caused by gBGC episodes through compensatory evolution. However, this process has never been studied or quantified so far. Here, we analyzed the nucleotide substitution pattern in coding sequences of a highly diversified group of Murinae rodents. Using phylogenetic analyses of about 70,000 coding exons, we identified numerous exon-specific, lineage-specific gBGC episodes, characterized by a clustering of synonymous AT to GC substitutions and by an increasing rate of nonsynonymous AT to GC substitutions, many of which are potentially deleterious. Analyzing the molecular evolution of the affected exons in downstream lineages, we found evidence for pervasive compensatory evolution after deleterious gBGC episodes. Compensation appears to occur rapidly after the end of the episode and to be driven by the standing genetic variation rather than new mutations. Our results demonstrate the impact of gBGC on the evolution of amino-acid sequences and underline the key role of epistasis in protein adaptation. This study contributes to a growing body of literature emphasizing that adaptive mutations, which arise in response to environmental changes, are just 1 subset of beneficial mutations, alongside mutations resulting from oscillations around the fitness optimum.

Gene Conversion↗
PubMed2026

Mice humanized by syntenic replacement with full-length NLRP3 disease-associated variants model the clinical cryopyrinopathy continuum.

Next-generation sequencing technologies are increasingly used to diagnose genetic disorders, particularly immunological diseases with broad and overlapping immune dysregulation. Cryopyrin-associated periodic syndromes (CAPS) are caused by gain-of-function mutations in NLRP3 and include 3 autoinflammatory diseases spanning a continuum of severity: familial cold autoinflammatory syndrome (FCAS), Muckle-Wells syndrome (MWS), and neonatal-onset multisystem inflammatory disease (NOMID). Linking NLRP3 variants to protein dysfunction and clinical phenotype remains challenging because of genetic modifiers and environmental factors. We report the generation and phenotyping of 5 mouse lines expressing either the common human NLRP3 allele or 1 of 4 CAPS mutations spanning the disease spectrum from FCAS to NOMID. In these lines, the murine Nlrp3 locus is replaced by syntenic integration of the human NLRP3 locus, yielding 1 line with the common allele and 4 lines each carrying a distinct CAPS mutation. Unlike models in which a human mutation is introduced into the mouse protein, these lines recapitulate the spectrum of disease severity observed in humans. These findings support a model in which evaluation of nonsynonymous mutations in mice is optimized when introduced in the context of the human gene. This suggests that species-specific regulation and/or intramolecular epistasis may impact modeling of disease-associated variants.

Animals↗
PubMed2026

Epistasis and the changing fitness landscapes of SARS-CoV-2.

Since its emergence in late 2019, millions of SARS-CoV-2 genomes have been generated as part of global efforts to monitor the evolution and spread of the virus. This unprecedented volume of data provides a unique opportunity to study viral evolution at unparalleled resolution. In particular, individual genomic sites can be observed to have mutated independently thousands of times. These mutation counts have been used to estimate site-specific mutation rates and fitness effects for most mutations across the viral genome. Here, we use these data to investigate how the landscape of mutational fitness costs has changed over the course of the pandemic. SARS-CoV-2 evolution over the past 6 years has been characterized by the emergence of distinct variants separated by long branches corresponding to evolutionary saltations involving up to 50 mutations. We compare inferred fitness landscapes of the Spike protein across these variants and find that shifts in the estimated effects of non-synonymous mutations are linked to genetic differences between them. Sites with altered fitness costs are enriched near positions where the genetic backgrounds differ. To explain the observed changes, we introduce a model with pairwise epistatic interactions between mutations and residues that differ between variants. This model is able to explain about half of the variance in the shifts of fitness effects and suggests that each mismatch between variants substantially alters mutation effects at typically 1 to 3 additional positions.

SARS-CoV-2↗
PubMed2026

Functional genomic screens uncover FERMT2 as a critical regulator of YAP/TAZ-driven tumorigenicity.

YAP and TAZ are transcriptional regulators essential for mechanotransduction, development, and tissue homeostasis, whose dysregulation is implicated in multiple diseases, including cancer. To identify key regulators of YAP/TAZ signaling required for breast cancer cell fitness, we performed CRISPR/Cas9-based loss-of-function genetic screens both in vitro and in vivo. A custom sgRNA library targeting 216 candidate YAP/TAZ modulators was screened across three breast cancer cell lines. Among these, FERMT2, a component of the integrin signaling pathway, consistently emerged as a strong drop-out hit, highlighting its essential role in sustaining YAP/TAZ-dependent fitness. Bioinformatic analysis of large-scale cancer datasets further revealed genetic co-dependency between FERMT2, YAP, and TAZ, particularly in tumors with high YAP/TAZ expression. Functional validation through FERMT2 knockout and silencing demonstrated its requirement for proliferation, anchorage-independent growth, and tumorigenicity in triple-negative breast cancer cells. FERMT2 loss impaired YAP/TAZ nuclear accumulation, reduced the expression of YAP/TAZ target genes, and decreased phosphorylation at key tyrosine residues. Mechanistically, FERMT2 regulates YAP/TAZ independently of the canonical Hippo pathway through integrin-mediated activation of FAK. Consistent with this, glucocorticoid-driven FAK activation restored YAP/TAZ signaling in FERMT2-depleted cells. Partial epistasis analyses also indicate that FERMT2 modulates actin-dependent regulation of YAP/TAZ. Together, these findings identify FERMT2 as a pivotal upstream regulator of YAP/TAZ via FAK signaling, demonstrate that YAP/TAZ are principal effectors of integrin activity, and suggest that FERMT2 may represent a selective vulnerability in cancers with elevated YAP/TAZ signaling.

Humans↗
PubMed2026

Dissecting contributions of directional and balancing selection to trajectories of mitochondrial haplotype evolution in Drosophila melanogaster.

Emerging evidence suggests mtDNA haplotypes contribute to fitness variation and local adaptation, with directional thermal selection and negative frequency-dependent selection shaping haplotype diversity. However, their interplay remains unexplored. We conducted experimental evolution using Drosophila melanogaster populations from opposite ends of an Australian latitudinal cline (Melbourne and Townsville), exposing them to contrasting temperatures (17°C versus 27°C) and varying starting frequencies of two mtDNA haplotypes (A1 and B1) that occur at appreciable frequencies in these populations. We paired this with population genetic simulations to estimate selection and its influence on haplotype trajectories. Haplotype frequencies were influenced by interactions involving temperature, starting frequency, and nuclear genomic background (Melbourne, Townsville, or admixed). Although prior work predicted A1 should be favoured at the warmer temperature and B1 at the cooler temperature, A1 was generally favoured across both temperatures. Simulations supported directional selection in populations evolving at 17°C in the Melbourne background; otherwise dynamics were best explained by balancing selection shaped by negative frequency-dependent fitness effects. Patterns also varied across nuclear backgrounds, suggestive of mito-nuclear epistasis. These findings challenge a simple thermal adaptation model of mtDNA dynamics, suggesting that mtDNA evolution is shaped by interacting effects of temperature, frequency-dependence, nuclear background and experimental environment.

adaptation↗
PubMed2025

A gene-based model of fitness and its implications for genetic variation: Linkage disequilibrium.

A widely used model of the effects of mutations on fitness (the "sites" model) assumes that heterozygous recessive or partially recessive deleterious mutations at different sites in a gene complement each other, similarly to mutations in different genes. However, the general lack of complementation between major effect allelic mutations suggests an alternative possibility, which we term the "gene" model. This assumes that a pair of heterozygous deleterious mutations in trans behave effectively as homozygotes, so that the fitnesses of trans heterozygotes are lower than those of cis heterozygotes. We examine the properties of the two different models, using both analytical and simulation methods. We show that the gene model predicts positive linkage disequilibrium (LD) between deleterious variants within the coding sequence, under conditions when the sites model predicts zero or slightly negative LD. We also show that focussing on rare variants when examining patterns of LD, especially with Lewontin's´ measure, is likely to produce misleading results with respect to inferences concerning the causes of the sign of LD. Synergistic epistasis between pairs of mutations was also modeled; it is less likely to produce negative LD under the gene model than the sites model. The theoretical results are discussed in relation to patterns of LD in natural populations of several species.

complementation↗