Julien F. Ayroles

How natural populations maintain genetic variation for fitness remains a central problem in evolutionary biology. Theory predicts that opposing selective pressures across environments can preserve fitness-associated polymorphism, but how interactions among species contribute to this process remains poorly understood. Here we show that host diversity preserves standing genetic variation within sexual populations of the leafmining fly Scaptomyza flava . We evolved twelve populations for ten generations on either of two naturally co-occurring host plants or on both, pooling survivors from the two hosts before mating. Single-host populations evolved reciprocal fitness trade-offs, whereas two-host populations maintained relatively even performance across hosts. Whole-genome time series dynamics identified a linked region in which alleles increased on one host and decreased on the other, while showing little net change under two-host conditions. Wild flies reared from the two hosts showed corresponding allele-frequency differences within this region. Across the genome, two-host populations retained more rare variants than populations evolving on either host alone. These findings show that selection imposed by different host species in sympatry can maintain standing genetic diversity within an herbivore population.

Objectives: Effective communication about genetics concepts is essential for collaborative anthropological genetics research. However, communication can be challenging because many ideas are abstract and may be especially unfamiliar to communities with limited access to formal education. Indeed, there are no widely adopted models for communicating such information, nor a clear understanding of the social factors that may shape participant engagement. Here, we conducted a qualitative and quantitative, community-driven study to understand how illustrations can be useful to support concept sharing with two Indigenous groups—the Orang Asli of Peninsular Malaysia and the Turkana of Kenya. Methods: We used a two phase approach to create and evaluate how illustrations can bolster communication about genetics concepts. First, we created images illustrating answers to frequently asked questions about genetics, iteratively updating the illustrations based on participant feedback. Second, we conducted 92 interviews to evaluate the finalized illustrations’ effectiveness. Finally, we analyzed the interview data using thematic analyses, multivariable modeling, and multiple correspondence analyses to identify patterns in participant understanding and feedback, including age, sex, market integration, and schooling. Results: Participants reported high interest in genetics research (92%) and broadly positive perceptions of the illustrations. Familiar, locally-grounded imagery was preferred and associated with greater perceived clarity, while more technical illustrations were more frequently reported as confusing. Quantitative analyses showed strong internal consistency across measures of engagement and understanding, with modest variation by degree of market-integration, schooling, and sex. Discussion: Our findings demonstrate that community-specific visualizations, co-developed through iterative feedback, can effectively support engagement with genetics research in participant communities.

Environmental perturbation reshapes phenotypes not only by shifting trait means but also by modulating phenotypic variability. Whether environmentally induced changes in variability -environmental robustness- are genetically regulated remains unclear. To address this question, we collected nearly 2,000 matched genomes and transcriptomes from an outbred population of Drosophila melanogaster before and after exposure to a high-sugar diet, and quantified how dietary stress remodels expression variability and its genetic architecture. We find that environmental perturbation induces a transcriptome-wide increase in expression variability, with the notable exception of key developmental pathways. At the same time, stress unmasks pervasive genetic regulation for expression variability (veQTL). These loci are mostly environment-dependent, show distinct functional and evolutionary constraints from mean-regulating loci, and appeared detrimental when they confer to much robustness to dietary perturbation. Together, our findings establish gene expression variability as a central dimension of the organismal response to environmental changes, and uncover its genetic basis as a distinct, evolutionary constrained layer of phenotypic regulation beyond mean effects.

Genomic diversity within species encompasses a range of sequence-related, structural, and regulatory features. To illustrate their complexity, we invoke the analogy of a kaleidoscope: while the DNA sequence represents its core, the genome has a dynamic, multidimensional configuration shaped by interactions across these features, generating an array of dimensions of genomic variation. In this perspective, we highlight underexplored dimensions of genomic variation that contribute to phenotypic diversity. We begin by revisiting the existence of noncanonical chromosomes and by emphasizing the role of large-scale structural changes and the 3D genome architecture in modulating genomic function. We then examine the regulatory mechanisms shaping transcriptional activity and genetic variation that, instead of regulating mean trait values, defines the degree of trait variability. Finally, we discuss the influence of sequence composition on its mutational potential. These dimensions, though rooted in sequence, are context dependent, interconnected, and often difficult to disentangle, reflecting a level of structural and regulatory complexity that challenges traditional genotype–phenotype models. By synthesizing recent findings across these dimensions, we argue for a broader framework for studying within-species genomic diversity: one that accounts for the diverse molecular architectures underlying phenotypic output. This expanded view not only deepens our knowledge of the genome itself but also contributes to our understanding of genome evolution and within-species phenotypic variation.

The Turkana pastoralists of Kenya inhabit arid, water-limited environments and rely largely on livestock for subsistence. Working with Turkana communities, we sequenced 367 whole genomes and identified eight regions with evidence for recent positive selection. One of these regions includes a putative regulatory element for STC1 —a kidney-expressed gene involved in metabolism and the response to dehydration. We show that STC1 is induced by antidiuretic hormone in human cells, is associated with urea levels in the Turkana themselves, and is under strong and recent selection in this population as well as a second East African population, the Daasanach. This work highlights how integrating anthropological and genomic approaches can lead to a new understanding of human physiology with biomedical relevance.

Evolutionary adaptation to new environments likely results from a combination of selective sweeps and polygenic shifts, depending on the genetic architecture of traits under selection. While selective sweeps have been widely studied, polygenic responses are thought to be more prevalent but remain challenging to quantify. The infinitesimal model makes explicit the hypothesis about the dynamics of changes in allele frequencies under selection, where only allelic effect sizes, frequencies, linkage, and gametic disequilibrium matter. Departures from this, like long-range correlations of allele frequency changes, could be a signal of epistasis in polygenic response. We performed an Evolve & Resequence experiment in Drosophila melanogaster exposing flies to a high-sugar diet for over 100 generations. We tracked allele frequency changes in >3000 individually sequenced flies and population pools and searched for loci under selection by identifying sites with allele frequency trajectories that differentiated selection regimes consistently across replicates. We estimate that at least 4% of the genome was under positive selection, indicating a highly polygenic response. The response was dominated by small, consistent allele frequency changes, with few loci exhibiting large shifts. We then searched for signatures of selection on pairwise combinations of alleles in the new environment and found several strong signals of putative epistatic interactions across unlinked loci that were consistent across selected populations. Finally, we measured differentially expressed genes (DEGs) across treatments and show that DEGs are enriched for selected SNPs. Our results suggest that epistatic contributions to polygenic selective response are common and lead to detectable signatures.

Can the microbiome serve as a reservoir of adaptive potential for hosts? To address this question, we leveraged approximately 150 generations of experimental evolution in Drosophila melanogaster on a stressful, high-sugar diet. We performed a fully reciprocal transplant experiment using the control and high-sugar bacteria. If the microbiome confers benefits to hosts, then transplant recipients should gain fitness benefits compared with controls. Interestingly, we found that such benefits exist, but their magnitude depends on evolutionary history—mismatches between fly evolution and microbiome reduced fecundity and potentially exerted fitness costs, especially in the stressful high-sugar diet. The dominant high-sugar bacteria ( Acetobacter pasteurianus ) uniquely encoded several genes to enable uric acid degradation, mediating the toxic effects of uric acid accumulation due to the high-sugar diet for flies. Our study demonstrates that host genotype × microbiome × environment interactions have substantial effects on host phenotype, highlighting how host evolution and ecological context together shape the adaptive potential of the microbiome.

Finding communities in gene co-expression networks is a common first step toward extracting biological insight from these complex datasets. Most community detection algorithms expect genes to be organized into assortative modules, that is, groups of genes that are more associated with each other than with genes in other groups. While it is reasonable to expect that these modules exist, using methods that assume they exist a priori is risky, as it guarantees that alternative organizations of gene interactions will be ignored. Here, we ask: can we find meaningful communities without imposing a modular organization on gene co-expression networks, and how modular are these communities? For this, we use a recently developed community detection method, the weighted degree corrected stochastic block model (SBM), that does not assume that assortative modules exist. Instead, the SBM attempts to efficiently use all information contained in the co-expression network to separate the genes into hierarchically organized blocks of genes. Using RNAseq gene expression data measured in two tissues derived from an outbred population of Drosophila melanogaster, we show that (a) the SBM is able to find ten times as many groups as competing methods, that (b) several of those gene groups are not modular, and that (c) the functional enrichment for non-modular groups is as strong as for modular communities. These results show that the transcriptome is structured in more complex ways than traditionally thought and that we should revisit the long-standing assumption that modularity is the main driver of the structuring of gene co-expression networks.

The microbiome contributes to many different host traits, but its role in host adaptation remains enigmatic. The fitness benefits of the microbiome often depend on ecological conditions, but theory suggests that fluctuations in both the microbiome and environment modulate these fitness benefits. Moreover, vertically transmitted bacteria might constrain the ability of both the microbiome and host to respond to changing environments. Drosophila melanogaster provides an excellent system to investigate the impacts of interactions between the microbiome and the environment. To address this question, we created field mesocosms of D. melanogaster undergoing seasonal environmental change with and without the vertically transmitted bacteria, Wolbachia pipientis. Sampling temporal patterns in the microbiome revealed that Wolbachia constrained microbial diversity. Furthermore, Wolbachia and a dominant member of the microbiome, Commensalibacter, were associated with differences in two higher‐order fitness traits, starvation resistance and lifespan. Our work here suggests that the interplay between the abiotic context and microbe–microbe interactions may shape key host phenotypes that underlie adaptation to changing environments. We conclude by exploring the consequences of complex interactions between Wolbachia and the microbiome for our understanding of eco‐evolutionary processes that shape host‐microbiome interactions.