The genomic mechanisms underlying large-scale chromosomal rearrangements and their evolutionary consequences remain poorly understood. Here, we generated chromosome-level genomes for two sister species pairs of blind mole rats that differ in chromosome numbers. We identified five chromosome fusions during the divergence from a common ancestor (2n = 60). Three shared fusions gave rise to the Spalax galili (2n = 52)-S. golani (2n = 54) clade and accompanied its divergence from the S. carmeli (2n = 58)-S. judaei (2n = 60) clade. Both S. galili and S. carmeli further underwent an independent fusion. These fusions, facilitated by repetitive elements, were associated with changes in three-dimensional genome architecture. Notably, we found reduced gene flow near fusion points. Chromosomal fusions correlated with signatures of selection and may have become fixed through centromeric repeat expansion. Together, these findings provide a genome-wide framework for investigating how chromosomal fusions relate to genome organization and lineage divergence.

Abstract Genomic forecasting approaches based on genotype-environment associations (GEAs) are increasingly used to estimate genomic offsets (GOs), which predict population maladaptation and extinction risk under current or future climatic conditions. Despite their widespread use, only a subset of studies have evaluated how accurately GOs predict (mal)adaptation, limiting their interpretation and application in policy and management. Here, we used GEA analyses to estimate GOs for past, present, and future climates in Lycaeides butterflies, focusing on the causes of variation in GOs among populations and their relationships with demographic parameters inferred from population genomic data. Using multivariate linear regression and genotyping-by-sequencing data from 42 Lycaeides populations (922 butterflies), we found that mean annual temperature, cumulative annual precipitation, and hybridization history together explained 47.6% of variation in genome-wide allele frequencies. Genomic offsets differed substantially among populations and across past, present, and future climates, with evidence for increasing maladaptation under more distant future climate scenarios. We found no relationship between GOs for present climates and contemporary effective population size. In contrast, genetic diversity, which reflects long-term effective population size, and local rates of gene flow together explained 27.3% of variation in contemporary GOs. Populations with higher genetic diversity and more gene flow exhibited lower GOs, consistent with the hypothesis that genetic diversity enhances adaptive capacity and that gene flow may introduce adaptive alleles. Overall, our results support the utility of GO predictions, particularly when validated with independent measures of adaptation, while cautioning against simplistic interpretations of GO as a direct measure of maladaptation in conservation and management contexts.

SUMMARY:Hybrid zones represent powerful natural systems for studying reproductive isolation and speciation. One key genomic signature of genetic incompatibilities and epistatic interactions is linkage disequilibrium (LD)-non-random associations between loci from different lineage backgrounds, generated by selection against maladaptive allele combinations. However, admixture alone induces strong genome-wide LD in hybrid populations, obscuring selection-driven signals. Here, we present AdmixLD, a fast, scalable C++ tool for genome-wide LD scanning in hybrid zones that estimates LD using partial correlation to control for individual hybrid index. By removing admixture-driven covariance, AdmixLD enhances detection of locus-specific associations and enables genome-scale identification of candidate barrier loci and interacting genomic regions. AVAILABILITY:The software and its code source are available at https://github.com/yzfranci/AdmixLD, and scripts for the data analysis are available at https://github.com/yzfranci/AdmixLDAnalysis.

Genomic offset (GO) is increasingly used to predict population maladaptation risk under climate change, with larger offsets assumed to indicate greater vulnerability. Despite rapid adoption in conservation planning, it remains unclear how sensitive GO estimates are to key methodological choices, including SNP set composition, genotype-environment association (GEA) methods, and the specific GO metric used. Empirical validation against observed population dynamics also remains limited. Here, we evaluate the methodological robustness and predictive performance of GO using multidecadal demographic monitoring data from Lycaeides butterflies, a system with short generation times and high fecundity that may facilitate rapid adaptive responses. GO estimates were broadly consistent across SNP sets, regardless of composition or size, with climate-associated and randomly selected SNPs yielding largely concordant values. Consistency across GEA methods was moderate and depended on the SNP set used. In contrast, GO metrics differed substantially in the magnitude of maladaptation estimated, suggesting they capture distinct biological signals and should not be treated as interchangeable. Crucially, GO was a poor predictor of observed population trends, regardless of SNP set composition, GO metric, or GEA method, both at sites used to fit GEA models and when extrapolated to independent demographic sites. These findings suggest that, while GO provides a valuable conceptual framework for assessing potential maladaptation, its quantitative estimates and predictive power are sensitive to methodological choices and species-specific biological context. We therefore urge careful alignment of GO metric assumptions with conservation objectives, along with rigorous empirical validation, before GO estimates are used to inform management decisions.

Research-based learning is among the highest impact experiences college students can have. For the last four years, undergraduate students from the Honors Program enrolled in the introductory-level biology lab course at Utah State University have been filling gaps in the scientific community’s knowledge about the abiotic and biotic factors that affect a mutualistic relationship between caterpillars and ants. Sugar-consuming-ants protect caterpillars from predators and parasitoids, and the caterpillars feed the ants honeydew from a dorsal organ and communicate with them through skin chemicals (cuticular hydrocarbons or CHCs). Students begin by learning about the scientific method, as well as developing collaboration and communication skills, through instructional videos and standalone experiments, which they then apply to this 7-week research experience. They work in small groups to make general observations about the study system, search and read the published literature, build off of what previous students have learned, and write a short research proposal. One of the proposed experiments is chosen for the class. Students use caterpillars hatched from hibernating eggs collected from multiple Lycaeides populations the previous summer by scientists. A small support team rears the caterpillars until they have developed their ant-tending organs. This ensures students have adequate sample sizes for data analysis. Through these experiments, the students have shown that Lycaeides population affects the amount of attention received by ants, and that different ant species interact with the caterpillars to different extents. The project concludes when students individually produce and record a 5-minute “lightning talk”. This classroom research filters into a larger project about the long-term effects of natural selection in wild Lycaeides populations, funded by an NSF CAREER grant. The student discoveries have indicated that Lycaeides ant-tending traits are good candidates for studying rapid evolution. Students have felt this experience prepares them for their future STEM careers.

Climate change has substantially shifted the phenology of many organisms. These shifts vary across species and habitats and are shaped by species' natural history traits and local environmental conditions, yet the relative importance of these drivers remains unclear. Moreover, climate can have diverse effects on different aspects of phenology, such as the timing and duration of activity, but this complexity is rarely captured by commonly used phenological metrics. We used multidecadal butterfly surveys and climate data from five montane sites spanning an elevational gradient to investigate how climate affects different aspects of the annual flight period of 135 butterfly species. Using a hierarchical Bayesian framework, we modeled annual probability of occurrence distributions for species using polynomial models that capture changes in abundance, timing, and length of flight. Spring maximum and minimum temperatures and winter precipitation were the best predictors of interannual variation in phenology. High winter precipitation, which usually comes in the form of snow, delayed phenology, while warmer spring maximum temperatures advanced phenology across elevations. Even modest increases in spring minimum (nighttime) temperatures caused strong phenological shifts. Climate effects varied among sites, among species within sites, and even among populations of the same species across sites, with particularly pronounced variation among species at a single location. Variation in climate effects was slightly better explained by local climate than by natural history traits. Among natural history traits, voltinism and overwintering stage were particularly influential. Importantly, climate influenced different aspects of the flight period (e.g., timing versus duration) in distinct ways, with both natural history traits and local climate modulating these responses. Our findings highlight the often-overlooked importance of winter precipitation and nighttime temperatures in shaping phenology and demonstrate the value of considering the entire flight period, rather than distinct aspects alone, to improve our understanding and predictions of species response to climate change.

Genomic coupling theory predicts that progress towards speciation involves a transition from the dominant effects of selection on individual barrier loci to the aggregate effects of direct and indirect selection across loci that collectively produce stronger barriers to gene flow through genetic associations. However, our ability to test this prediction and to understand the factors that lead to the buildup and maintenance of these associations has been limited by a lack of methods to estimate variation in coupling across the genome. Here we develop approaches to quantify coupling using window-based estimates of Barton's coupling coefficient and apply these to a dataset of 118 genomes from a rattlesnake hybrid zone. Our results provide empirical evidence for genomic coupling that is consistent with the predicted relationships of coupling with recombination, linkage, and inferences of selection. Applying these approaches, we find evidence for coupling within and among chromosomes, and highlight the roles of coupling in complex barrier effects, including the Large-Z effect, cytonuclear incompatibilities, and incompatibilities related to venom resistance. Together, our findings demonstrate the mechanism by which coupling is predicted to lead to speciation, and highlight how genome-wide quantification of coupling presents a promising framework for understanding progress towards speciation and the processes that underlie this progress.

ABSTRACTKarst ecosystems often contain extraordinary biodiversity, but the complex underground aquifers of karst regions present challenges for assessing and conserving stygobiont diversity and investigating their evolutionary history. We examined the karst‐obligate salamanders of the Eurycea neotenes species complex in the Edwards Plateau region of central Texas using population genomics data to address questions about population connectivity and the potential for gene exchange within the underlying aquifer system. The E. neotenes species complex has historically been divided into three nominal species, but their status, and spatial extent of species ranges, have remained uncertain. We discovered evidence of extensive admixture among species within the complex and with adjacent lineages. We observed relatively low levels of differentiation among all sampling localities which supports the hypothesis of recent divergence. Nominal taxonomy, aquifer region and geography each accounted for a modest amount of the overall population genomic variation; however, these predictors were largely confounded and difficult to disentangle. Importantly, current taxonomy of the three nominal species does not reflect the admixture apparent in clustering analyses. Inference of migration events revealed a complex pattern of gene exchange, suggesting that Eurycea salamanders have a dynamic history of dispersal through the aquifer system. These results highlight the need for greater understanding of how stygobiont populations are connected via dispersal and gene exchange through karst aquifers. These results also highlight the applicability of population genomics data as a powerful lever for investigating connectivity among populations in systems where direct detection of dispersal paths is difficult, as in underground, aquatic systems.

Migration between populations homogenizes genetic divergence and can thus prevent speciation. However, environmentally induced epigenetic marks can remain divergent between populations despite migration. Thus, epigenetic variation might facilitate speciation under conditions where it is challenging for genetic barriers to gene flow to establish. Here, we develop a model to test this hypothesis by quantifying reproductive isolation (RI) at a neutral genetic locus linked with an epigenetic locus under divergent selection. This also allows us to test how RI is influenced by (i) the degree of induction of epigenetic state by the environment and (ii) the transmission of epigenetic state between generations. With a high migration rate, we find that an epigenetic locus, which is highly inducible, produces stronger RI than an equivalent genetic locus. Furthermore, at lower migration rates, the strength of RI produced by an epigenetic locus increases when epigenetic state is more transmissible between generations. Our findings suggest three regimes of speciation by divergent selection at an epigenetic locus, whereby highly inducible epigenetic marks could give way to more transmissible epigenetic marks and ultimately genetic differentiation, as ecological speciation progresses.

Hybridization and admixture give rise to populations with mosaic genomes composed of ancestry segments with distinct origins and histories. Despite a growing number of documented cases of admixture in nature, relatively little is known about how mosaic patterns of ancestry vary simultaneously across the genome and among multiple populations or lineages of hybridizing species. Here, using pooled whole-genome sequence data from more than 20 populations representing three nominal species and multiple admixed or taxonomically ambiguous populations, we show that widespread admixture in Lycaeides butterflies has resulted in distinct evolutionary histories within and among chromosomes, with the most notable differences between the autosomes and the Z sex chromosome. Many populations exhibit substantial evidence of mixed ancestry on the autosomes, whereas the Z chromosome shows a more tree-like evolutionary history. In some cases, the predominant ancestry of the autosomes and the Z chromosome differ. We also find evidence of variation in ancestry within chromosomes, though this appears more idiosyncratic. We also show that differences in autosomal versus Z-chromosome ancestry have the potential to shape ecologically important trait variation. Specifically, using genome-wide association mapping, we demonstrate that wing-pattern elements-traits known to influence mate preference-are affected by genetic variants on both the autosomes and the Z chromosome. In sum, our results show that different chromosomes can exhibit distinct evolutionary histories, with the Z chromosome suggesting more discrete evolutionary lineages or species than the autosomes. These findings have implications both for our basic understanding of species and species boundaries and for how we view the sources of genetic and phenotypic variation that fuel ongoing evolutionary change.

While evolutionary biology traditionally focuses on the spread of mutations within populations, the dynamics of mutational spread within individuals, particularly in long-lived clonally, spreading organisms remain poorly understood. Here we examine the genetic structure of 'Pando', Earth's largest known quaking aspen (Populus tremuloides) clone. We sequenced over 500 samples across Pando and neighboring clones, including multiple tissue types. At fine spatial scales, we detected significant genetic structure, particularly in leaf tissue, but this signal weakened across larger distances, suggesting either rapid root growth homogenizes the system over time or mechanisms exist that prevent widespread mutation transmission. Phylogenetic analyses date Pando between ~12,000 and 37,000 years old, supported by continuous aspen pollen presence in nearby lake sediments. Tissues accumulated mutations at different rates, with leaves showing significantly higher mutation loads than roots or branches. This work provides the first quantitative age estimate for this remarkable organism and reveals how massive clonal plants maintain genetic integrity while accumulating potentially adaptive variation over millennia. Our findings illuminate evolutionary processes in long-lived modular organisms and demonstrate how within-organism selection might operate in species lacking regular unicellular bottlenecks.

Gene body methylation is one of the most taxonomically widespread epigenetic marks, yet its function and evolutionary history are poorly understood. While there is a positive association between gene body methylation and gene expression in many organisms, the mechanisms behind this relationship are unclear. Here, we investigate the function of gene body methylation in the stick insect Timema cristinae . We compare patterns of genome-wide gene body methylation to gene expression, open chromatin peaks, and chromatin compartments. We find that 95% of genes with gene body methylation occur in open chromatin compartments (euchromatin). Furthermore, highly expressed genes are impoverished in methylation at their transcription start site (TSS), which is associated with a peak of open chromatin. These findings suggest that the positive correlation between gene body methylation and gene expression is due to chromatin compartment structure. Yet, methylation around the TSS is associated with gene expression, possibly playing an inhibitory role as in vertebrates. Lastly, comparative analysis of Apis mellifera reveals a similar relationship between methylation and chromatin compartments, but not gene expression. These results suggest a possible explanation for the heterogeneous association between gene body methylation and gene expression and give insight into DNA methylations role in regulating gene expression. ### Competing Interest Statement The authors have declared no competing interest. European Research Council, https://ror.org/0472cxd90, Grant agreement No.770826 EE-Dynamics Laboratoire d'Excellence TULIP, Senior Package to P.N.

Structural elements are widespread across genomes, but their complexity and role in repeatedly driving local adaptation remain unclear. In this work, we use phased genome assemblies to show that adaptive divergence in cryptic color pattern in a stick insect is repeatedly underlain by structural variation, but not a simple chromosomal inversion. We found that color pattern in populations of stick insects on two mountains is associated with translocations that have also been inverted. These translocations differ in size and origin on each mountain, but they overlap partially and involve some of the same gene regions. Moreover, this structural variation is subject to divergent selection and arose without introgression between species. Our results show how the origin of structural variation provides a mechanism for repeated bouts of adaptation.

Climate change has substantially altered the phenology of many organisms, with profound implications for biodiversity and species interactions. However, phenological studies of insects have often focused on shifts over time, without explicitly examining how climate drives these changes. In addition, the metrics used to measure changes in phenology often capture only limited information about the flight period. In this study, we analyzed multidecadal observational and climate data using a hierarchical Bayesian framework to model the annual probability of occurrence distributions for 135 butterfly species across five montane sites along an elevational gradient. Our analysis used polynomial models that account for shifts in abundance and the timing and length of flight periods to investigate the effect of climate on butterfly phenology. We found that spring maximum and minimum temperatures, as well as winter precipitation, are important predictors of butterfly phenology. High winter precipitation delayed phenology at high-elevation sites where substantial snowfall occurs, while increased spring maximum temperatures generally advanced phenology across all elevations. Even modest increases in spring minimum temperatures caused substantial shift in phenology. We documented variability in the effect of climate on phenology across sites, among species within a site and among populations of the same species across different sites with variability among species within a site being especially pronounced. We also found that climate influences different aspects of the flight period differently (e.g., timing versus duration), underscoring the need to move beyond single metrics such as day of first flight. These findings highlight the importance of examining the entire flight period and considering the interplay of species-specific traits to improve predictions of how climate change impacts phenology. Such approaches might be essential for designing more targeted and effective conservation strategies in response to ongoing climate change. ### Competing Interest Statement The authors have declared no competing interest.

The formation of new species often involves the correlated divergence of multiple traits and genetic regions. However, the mechanisms by which such trait covariation builds up remain poorly understood. In this context, we consider two non-exclusive hypotheses. First, genetic covariance between traits can cause divergent selection on one trait to promote population divergence in correlated traits (a genetic covariation hypothesis). Second, correlated environmental pressures can generate selection on multiple traits, facilitating the evolution of trait complexes (an environmental covariation hypothesis). Here, we test these hypotheses using cryptic colouration (controlled by a likely incipient supergene) and chemical traits (i.e., cuticular hydrocarbons, CHCs) involved in desiccation resistance and mate choice in Timema cristinae stick insects. We first demonstrate that population divergence in colour-pattern is correlated with divergence in some (but not all) CHC traits. We show that correlated population divergence is unlikely to be explained by genetic covariation, as our analyses using genotyping-by-sequencing data reveal weak within-population genetic covariance between colour-pattern and CHC traits. In contrast, we find that correlated geographic variation in climate and host plant likely generates selection jointly on colour-pattern and some CHC traits. This supports the environmental covariation hypothesis, likely via the effects of two correlated environmental axes selecting on different traits. Finally, we provide evidence that misalignment between natural and sexual selection also contributes to patterns of correlated trait divergence. Our results shed light on transitions between phases of speciation by showing that environmental factors can promote population divergence in trait complexes, even without strong genetic covariance.

Speciation involves the development of reproductive isolation between diverging populations. A potential key driver of reproductive isolation is mate choice, a behavioural mechanism that can limit gene flow based on divergence in signal traits. While the genetic basis of mating signal traits has been extensively studied, the contribution of epigenetic modifications to their variation remains underexplored, leaving the role of DNA methylation in mate choice unclear. Here, we focus on epigenetic variation and cuticular hydrocarbons (CHCs), the latter being chemical traits used for mate choice in insects. Specifically, we investigate the association between DNA methylation and regions associated with CHC variation in Timema cristinae stick insects. We integrate analyses of differentially methylated regions (DMRs) between individuals from different host-plant ecotypes with genomic sequencing and phenotypic data on CHCs. We find that DMRs are significantly enriched in genetic loci associated with CHCs, suggesting a non-random relationship between DNA methylation and loci associated with these signal traits. While further work is required to clarify causality, our results highlight the potential for epigenetic marks to be associated with traits involved in mate choice. Future studies should thus aim to establish causal links between DNA methylation and signal trait variation, which would clarify the contribution of methylation to mate choice, prezygotic isolation, and ultimately, speciation. ### Competing Interest Statement The authors have declared no competing interest. Royal Society of London, RG140369 French Laboratory of Excellence project “TULIP”, ANR-10-LABX-41

Hybridisation and admixture are common in nature and can serve as important sources of adaptive potential by generating novel genotype combinations and phenotypes. However, hybrid incompatibilities can also reduce hybrid fitness. Given the pervasiveness of admixture and its potential role in facilitating adaptation, understanding how admixture influences the rate and repeatability of evolution is critical for advancing our understanding of evolutionary dynamics. Yet, few studies have examined how patterns of evolutionary repeatability in admixed lineages are shaped by strong ecological pressures. In this experiment, we evaluated patterns of evolution and repeatability in admixed and non-admixed cowpea seed beetles (Callosobruchus maculatus) adapting to a novel, stressful host: lentil. Specifically, we asked (1) whether admixture facilitates adaptation to lentil, (2) whether repeatability is greater in admixed or non-admixed lineages, and (3) to what extent repeatability in admixed lineages is driven by selection on globally adaptive alleles versus epistatic effects and hybrid incompatibilities. We found that admixture facilitated adaptation to lentil, and evolutionary rescue-defined as adaptation that prevents population extinction-occurred in all lineages. Evolutionary repeatability was highest in two admixed lineages, though evident across all lineages. Adaptation to lentil appeared largely driven by selection on globally adaptive alleles. Nevertheless, even under conditions of evolutionary rescue in a marginal environment, the purging of hybrid incompatibilities contributed substantially to repeated evolution in admixed lineages.

Understanding speciation is a fundamental goal in evolutionary biology. Genome scans of genetic differentiation (FST) have become a cornerstone of speciation research, helping identify genomic regions likely involved in population divergence and speciation. While such studies have advanced our understanding, the relationship between epigenetic mechanisms and genetic differentiation remains unclear. Here, we present evidence that DNA methylation is associated with regions exhibiting accentuated genetic differentiation between populations of Timema cristinae stick insects. We do so by integrating analyses of differentially methylated regions (DMRs) between individuals from different host-plant species with genomic sequencing. Our results reveal that DMRs often show greater FST than expected by chance. Strikingly, the magnitude of this accentuation of FST in DMRs increases with the geographical distance between populations. We present results evaluating the contributions of mutation, reduced recombination, gene flow, and selection to these divergence patterns. The overall results are consistent with a role for a balance between selection and gene flow, a finding further supported by a previously published survival field experiment. Nevertheless, details of our results suggest that selection on DMRs might be indirect and not strictly host-related. Our results establish associations between methylation and genetic change, but further work is required to clarify the causes of this association. Nonetheless, our results provide insight into how the interplay of epigenetic and genetic variation may influence population divergence and potentially contribute to speciation.