Molecular Biology and Evolution

Ancestral sequence reconstruction (ASR) is a powerful approach for studying molecular evolution and the emergence of protein function. Yet most ASR methods assume that sites evolve independently, neglecting the epistatic constraints that shape protein structure, stability, and function. This simplification affects both ancestral inference and its evaluation: maximum-a-posteriori reconstructions may over-concentrate probability into a single over-idealized sequence, whereas independent posterior sampling can generate implausible or poorly functional ancestors. Here, we introduce a coevolution-aware ASR framework that combines standard phylogenetic inference with Direct Coupling Analysis (DCA), thereby preserving site-wise ancestral uncertainty while enforcing residue-residue constraints learned from extant protein families. To benchmark the method, we develop a controlled forward-evolution framework based on a DCA evolutionary sampler, allowing reconstructed ancestors to be compared with known ground-truth sequences generated under realistic epistatic constraints. Applied to {beta}-lactamases and DNA-binding domains, the approach improves reconstruction when ancestral states are epistatically constrained, and yields ensembles of candidate ancestors that are both phylogenetically consistent and statistically compatible with natural protein families. This framework bridges the gap between single-sequence MAP reconstruction and unconstrained posterior sampling, providing a practical route toward ancestral reconstructions that better reflect the coupled nature of protein evolution. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=106 SRC="FIGDIR/small/731024v1_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@1248f23org.highwire.dtl.DTLVardef@13176b5org.highwire.dtl.DTLVardef@688789org.highwire.dtl.DTLVardef@9a66df_HPS_FORMAT_FIGEXP M_FIG Graphical abstract Our procedure works as follows: we take as input a Multiple Sequence Alignment of extant sequences [D]extant, and infer in parallel both a phylogenetic tree[T] (phylogenetic signal) and a Direct Coupling Analysis model of coevolution (generative model with energy EDCA). The two models are then combined to form a general, coevolution-aware framework for Ancestral Sequence Reconstruction, which can be benchmarked against in silico data generated by the DCA forward evolver. C_FIG

A fundamental unresolved question in molecular evolution is how novel genes arise from noncoding DNA and become fixed within stable gene repertoires. Here, we performed comparative genomic analyses across evolutionary timescales in insects using chromosome-scale genome assemblies of two cricket species, Teleogryllus occipitalis and Tarbinskiellus portentosus. Using conservative criteria, we identified 41 de novo gene candidates derived from intergenic regions in the Te. occipitalis lineage. These genes are simple and compact, exhibit hallmarks of evolutionarily young genes, and frequently contain fragments of transposable elements and simple sequence repeats. Across insects, such repetitive sequence fragments show positional homology but lack sequence conservation in older genes, suggesting that they serve as sequence material for gene emergence during early stages of gene evolution. In contrast, insertions after gene establishment are strongly constrained. We propose a model in which stages of gene evolution are characterized by shifts in selective pressure on the incorporation of sequence material.

To preserve homeostasis in the face of continual chemical insult, animals evolved dedicated molecular systems that detect, detoxify, and eliminate foreign compounds. Collectively, these enzymes, transporters, and regulatory pathways constitute the chemical defensome. In cetaceans, the loss of two key nuclear receptors (NR1I2/PXR and NR1I3/CAR) suggests a profound rearrangement of the chemical defense systems. Therefore, we investigated the gene inventory of the chemical defensome in Cetacea and two other major marine mammal lineages (Pinnipedia and Sirenia), using their closest terrestrial relatives to understand the extent and patterns of chemical defensome remodelling. We demonstrate large-scale gene loss in chemical defensome genes of cetaceans, as well as smaller scale gene loss in the other two marine mammal lineages, indicating possible convergent evolution. Gene loss occurred predominantly in phase I and phase II biotransformation enzymes, including CYPs, FMOs, SULTs, and GSTs. Many of the lost genes in cetaceans are known to be regulated by PXR and/or CAR, while genes lost in multiple marine mammal lineages are often not regulated by these transcription factors. We hypothesize that the transition to aquatic environments, often accompanied by corresponding changes in feeding habits, led to convergent loss of chemical defensome genes, and loss of PXR and CAR in cetaceans accelerated these losses. These findings reveal systematic erosion of chemical defense capabilities across marine mammal lineages, suggesting that adaptation to marine life involves trade-offs in detoxification capacity that may have significant implications for these species responses to increasing chemical pollution in present-day ocean environments.

Long runtime, high memory demands, and reliance on high-performance computing increasingly limit the evolutionary analysis of long phylogenomic datasets. We review a scalable framework based on phylogenomic subsampling and upsampling (PSU), in which many small subsamples of sites from a long concatenated sequence alignment are extended by upsampling prior to inference, and the resulting analyses are then aggregated to obtain stable evolutionary estimates. PSU exploits a useful distinction between the computational burden and the inferential power of statistical methods in molecular phylogenetics: computational cost is strongly influenced by the number of distinct site patterns in the concatenated alignment, whereas statistical power depends primarily on the amount of evolutionary information represented by sites and substitutions. By reducing the former while restoring the latter through upsampling, PSU can approximate many full-data analyses at substantially lower computational cost. Evidence from simulated and empirical datasets shows that PSU can accurately estimate bootstrap support values, select optimal substitution models, test evolutionary hypotheses, and infer branch lengths, divergence times, and associated uncertainty measures, while often reducing runtime and memory requirements by orders of magnitude. The same subsampling-upsampling-aggregation principle underlies all of these applications. PSU also provides distributions of inferred clade support across independent subsamples, enabling detection of concordant and conflicting phylogenetic signals that may remain hidden in conventional concatenated phylogenomic analyses. Adaptive procedures for selecting the subsample size, the number of subsamples, and the number of upsampling replicates make the framework practical across diverse datasets. We suggest that PSU is a general strategy for scalable phylogenomic inference across a broad range of statistical methods. By enabling rigorous analyses of genome-scale alignments on standard computing hardware, PSU expands access to computationally intensive evolutionary methods while reducing the environmental and infrastructural costs of big-data phylogenomics.

The transition of vertebrates from aquatic to terrestrial environments represents one of the most profound evolutionary events in their history, involving extensive physiological and morphological innovations. Key adaptations included the transformation of fins into limbs with digits to enable efficient terrestrial locomotion, the ability to perceive novel environmental stimuli, and the emergence of reproductive strategies suited to life on land, processes in which ion channels played fundamental roles. Accordingly, understanding the genetic basis of vertebrate terrestrialization requires investigating the evolution of this group of membrane proteins. Our analyses reveal that the proportion of ion channel genes is highly conserved, representing approximately 1.4% to 1.6% of total protein-coding genes in most lineages, with a notable increase to [~]1.9% in teleost fishes. Our natural selection analyses revealed an overrepresentation of specific ion channel gene families, including TRP, RyR, HTR3, and HCN. We identified 29 ion channel genes showing signatures of positive selection, many of which are associated with key physiological functions such as nociception and thermosensation. We also detected an elevated rate of gene turnover in the common ancestor of terrestrial vertebrates, indicative of substantial genomic remodeling through gene gain and loss. Together, these findings suggest that, despite overall conservation in the proportions of ion channel genes, specific gene families underwent changes that were likely critical to meeting the physiological demands of terrestrial life. These results provide a foundation for future comparative and functional studies aimed at elucidating the molecular mechanisms underlying major environmental transitions.

Whole-genome alignment (WGA) is widely used for genome-scale phylogenetic inference, and most scalable WGA pipelines rely on progressive alignment guided by a pre-specified tree. Among progressive whole-genome aligners, Progressive Cactus is a successful state-of-the-art method. However, analyses of real and simulated avian data indicate that guide-tree choice can influence downstream tree inference; star guide trees do not remove this effect and can exacerbate long-branch attraction artefacts. We have developed a consensus strategy based on the Progressive Cactus framework by generating a small set of alternative guide-tree alignments and retaining only homology relationships consistently recovered across all alignments. In simulation experiments, consensus alignments improve precision, bring inferred site-pattern frequency distributions closer to those of the true alignments, and recover more true splits than single guide-tree alignments. In a real landbird (Telluraves) dataset, we observe a strong bias towards single binary guide trees and long-branch attraction for less resolved trees. While the reconstructed tree still depends on the phylogenetic method and taxa sampling, our consensus alignment has no clear bias. We implemented a hierarchical consensus workflow that only locally resolves uncertainty in the guide tree. Therefore, the computational cost increases only moderately, for example by an estimated 68 percent for a recently published large-scale alignment of more than 300 modern birds (Neoaves) taxa.

Models of genome evolution often account for different evolutionary rates at different genome positions due to, e.g., varying selective pressures or mutation rates. Recent evidence from millions of publicly shared SARS-CoV-2 genomes has revealed a more complex mutational landscape than can be modeled with existing approaches. Here, mutation rates are in fact not only highly position-specific, as currently modeled, but also nucleotide-specific; for example, specific mutations can occur very often at certain determined genome positions, while at the same positions other mutations might not be highly recurrent. Here, we propose and investigate a general model of genome evolution where each genome position is allowed to evolve under an independent, non-normalized substitution rate matrix describing site-specific rates of all mutation types ("Site-Specific Matrix" model, or SSM). We implement SSM in the efficient pandemic-scale phylogenetic inference software CMAPLE. Large-scale genomic epidemiological simulations suggest that, given enough data, SSM can accurately infer position- and nucleotide-specific substitution rates for more frequently observed nucleotides (typically the reference nucleotide), while other rates require higher levels of divergence. Simulations also show that SSM has a modest impact on the accuracy of phylogenetic tree estimation. We use SSM to analyze the evolution of millions of SARS-CoV-2 genomes and observe substantial mismatches between the substitution rates of classical rate variation models and our SSM estimates. These results suggest that classical models of rate variation are inadequate for modeling site-specific mutation patterns and that SSM is a useful alternative for large-scale genome analyses.

Evolutionary rates vary widely among sites in protein sequences, reflecting differences in functional constraints across residues. Individual sites can also experience lineage-specific shifts in substitution rates--a process known as heterotachy--when selective pressures change during evolution. Although such temporal variation has long been recognized, the mechanisms underlying lineage-specific rate shifts and the factors shaping their distribution across protein families remain poorly understood. Here we map site-specific rate shifts across thousands of orthologous protein families spanning the tree of life. Among more than 1.8 million aligned amino-acid sites, over one quarter show evidence of lineage-specific rate changes. Rate shifts are more frequent in families with deep evolutionary origins, including those tracing back to LUCA, whereas younger clade-specific families generally show lower proportions of rate-shifting sites. We next examined whether local structural features predict where rate shifts occur. Residue burial shows only a weak association with rate-shift probability, and its direction differs across domains, with buried residues enriched for rate shifts in Archaea but surface-exposed residues showing slightly higher probabilities in Eukaryota. Moreover, rate-shifting sites rarely form spatial clusters within protein structures, indicating that structural constraints do not globally determine their locations. Despite their widespread occurrence, rate-shifting sites have limited impact on phylogenetic reconstruction beyond random site variation. Together, these results show that lineage-specific rate shifts are a pervasive feature of protein evolution shaped primarily by evolutionary ancestry and phylogenetic depth.

Odorant receptors (Ors) are the interface between an animals nervous system and its olfactory environment. In insect genomes, the Ors are often the largest gene family, and their rapid duplications and deletions result in extensive copy-number differences between species. Because olfactory sensory neurons (OSNs) typically express only one Or (the so-called one-receptor one-neuron rule), this dynamism at the level of Or genes raises fundamental questions regarding their cellular regulation: How do new Or duplicates gain their own neuron-specific expression? Such Or-OSN changes are thought to provide a key evolutionary path for modifying olfactory perception and related behaviours, but the absence of examples of these transitions has prevented an understanding of how they occur. Using a highly duplicated Drosophila Or subfamily (the Or67a subfamily) as a model system, we discovered parallel instances of Or67a duplicates gaining new OSN expression and reconstructed their evolutionary histories. Functional work in D. suzukii, a species with two novel Or67a-expressing OSN populations, revealed that their Or67a expression has arisen in preexisting OSNs, which have lost their ancestral Ors. As a result, these neurons were recoded and acquired new olfactory identities, thereby demonstrating the diversification of an OSN repertoire without the invention of developmentally new OSN lineages.

Co-evolution between genes can occur for a variety of reasons, including co-expression of genes, epistatic interactions between them, physical interactions of gene products and many others. Co-evolutionary partners of a gene are therefore of great interest in identifying potential factors that contribute to any phenotype of interest. State-of-the-art approaches to detect these interactions use correlations of evolutionary rates across a broader phylogeny, and so by necessity identify interactions only among genes that are present across long evolutionary time periods. This makes the methods unwieldy when interest lies in a single focal organism in which the genes of interest may have evolved in the recent evolutionary past. Here, we present a new approach to calculating evolutionary rate correlations which focuses on extracting maximum coverage for a single focal species, while retaining signals of co-evolution across large clades. We show how this approach is able to identify potential interactions even in highly studied species and highly studied genes, with a focus on the D. melanogaster sex-determiner, Sxl, using data from 72 species of Dipterans.

Chemosensory systems play a central role in host detection, feeding behavior, and habitat selection in hematophagous insects. Here, we performed a comparative evolutionary analysis of chemosensory gene repertoires across 13 species of the Chagas disease vector genus Rhodnius. While gustatory receptors (GRs), ionotropic receptors (IRs), odorant-binding proteins (OBPs), and chemosensory proteins (CSPs) remained globally conserved, odorant receptors (ORs) displayed extensive lineage-specific expansions, tandem duplications, dynamic transcriptomic regulation, and recurrent signatures of positive selection. Major OR expansions were observed in Rhodnius robustus and Rhodnius colombiensis, suggesting increased sensory diversification in ecologically heterogeneous lineages. In contrast, conserved GR1 expression supports the maintenance of ancestral sugar-detection pathways despite hematophagy lifestyle. We further found no evidence of the canonical insect CO2-associated GRs, suggesting alternative molecular mechanisms for CO2 perception in Triatominae. Several receptors, including Orco, also displayed shifts in selective constraints between sylvatic and domiciliary species, consistent with sensory remodeling associated with adaptation to domestic habitats. Together, our results identify ORs as the most evolutionarily dynamic component of the Rhodnius chemosensory repertoire and highlight contrasting evolutionary trajectories among chemosensory gene families during ecological diversification and vector adaptation.

Transposable elements are a highly diverse group of selfish genomic elements, prevalent across the tree of life, whose uncontrolled propagation poses a threat to genome stability. Recent studies have explored the evolution of Drosophila melanogaster transposable elements, their co-evolution with the host genome, and mechanisms that regulate their activity. However, little is known about their cross-species evolutionary patterns. Long terminal repeat (LTR) retrotransposons are the most active group of transposable elements in Drosophila. They are broadly separated into retroelements, which are active in the germline, and insect endogenous retroviruses that are active in the soma. Somatic elements are hypothesised to infect the germline through their acquisition of virus-derived proteins such as Envelope and sORF2, thus multiplying through successive generations. In this study, we curated the sequences of LTR retrotransposons in 249 drosophilid genomes, allowing us to study their evolution across these species and highlight their varying degrees of conservation. Furthermore, we reveal multiple instances of Envelope protein loss or inactivation that suggest shifts in the expression pattern of these transposons, likely accompanied by adopting different transcriptional control mechanisms. We contrast this with the evolutionary history of sORF2, which we found to be much more stable. Lastly, we examined variations in transposon LTR regions responsible for transcriptional regulation and use predictive modelling to suggest six transcription factors likely involved in their tissue-specific expression. Altogether, we reveal complex, interspecies evolutionary patterns of Gypsy-family LTR retrotransposons and highlight examples of their co-evolution with their host genome.

O_LISynonymous nucleotide variation, which is remarkably high in Mimulus guttatus, can be affected by both codon usage selection (translational efficiency) and linked selection (hitchhiking effects). C_LIO_LICodon usage reflects a genome-wide tug-of-war between mutational pressure toward A/T-ending codons and weak selection favoring G/C-ending codons. The outcome is determined largely by gene expression level and localized variation in recombination rate. C_LIO_LIUsing both mechanistic (ROC-SEMPPR) and population genetic models, we find that most genes are weakly selected for codon usage, about 76% yielding scaled selection coefficients (S = 4Nes) in the range of 0 to 1. Additionally, 4029 genes, primarily involved in photosynthesis, translation, defense, and phosphate scavenging, experience strong selection (S > 1). C_LIO_LILevels of nucleotide variation within genes indicate a strong effect of linked selection. Non-synonymous polymorphism declines in genes with strong purifying selection, and as the rate of (intra-genic) recombination declines. Levels of synonymous polymorphism usually track non-synonymous (owing to background selection), except in genes under the strongest translational selection. C_LIO_LICounterintuitively, we find that codon usage selection has a generally positive effect on synonymous nucleotide diversity at 4-fold degenerate positions. Since mutation strongly disfavors the optimal base in M. guttatus, codon selection in the range of 0 < S < 2 evens the balance (between selection and mutation) and thus inflates heterozygosity. C_LI

Reticulate evolutionary processes (events in which lineages merge, such as hybridization, recombination, and horizontal gene transfer) are widespread across nature but cannot be represented by phylogenetic trees alone. Phylogenetic networks have therefore become an important modelling tool, yet existing software is typically tied to specific inference paradigms and provides limited support for working with multiple network representations in a unified and programmable environment. PhyloZoo is an open-source Python framework that lowers the barrier to developing practical, easy-to-use software for phylogenetic network analysis. It provides data structures and algorithms covering the main representations used in the field, together with dedicated visualization tools and robust I/O for all major phylogenetic file formats. A particular emphasis lies on semi-directed phylogenetic networks, which explicitly represent root uncertainty and have so far received limited support in existing software. By offering a shared foundation for developing interoperable tools and a combinatorial layer that supports computational proofs and theoretical exploration, PhyloZoo enables reproducible workflows for applied, methodological, and theoretical studies of reticulate evolution. Availability and implementationPhyloZoo is implemented in Python and installable from PyPI, with source code, documentation, and examples available at https://github.com/nholtgrefe/phylozoo. Contactn.a.l.holtgrefe@tudelft.nl

Comparative transcriptomic datasets are increasingly used to investigate the molecular basis of phenotypic diversification across species. However, finding genes that are differentially expressed (DE) between lineages remains challenging, for two main reasons. First, the random evolutionary drift can blur the signal left by lineage-specific shifts in mean expression, and induces phylogenetic correlations that, if ignored, can widely inflate the False Discovery Rate (FDR), i.e., the amount of spuriously detected genes. Second, DE analysis from RNA-Seq data involves multiple testing on many genes for a small number of individual measurements with high noise, and requires dedicated statistical tools. Traditional DE tools, such as limma, and classical Phylogenetic Comparative Methods (PCMs), such as the Expression Variance and Evolution (EVE) model, are both designed to tackle one of these two challenges alone, but both fail in the context of inter-species RNA-Seq data. In this work, we present phyloDE, a new tool for inter-species DE, that aims at taking the best from both approaches. On simulations based on a recently published four-species rodent dataset, we show that, contrary to other methods, phyloDE correctly controls the FDR in all settings, while keeping a reasonable power. When reanalyzing the empirical dataset, phyloDE discovers more DE genes that exhibit consistent changes in their cis-regulatory landscape compared to EVE in all the experimental settings. The method is implemented in R, with an interface inheriting from limma.

Given their rapid evolutionary dynamics, viruses offer a powerful system to investigate the mechanisms underlying host jumps. Here, we experimentally evolved endive necrotic mosaic virus (ENMV) in five plant hosts within the family Asteraceae: two putative ancestral hosts (Lactuca sativa and Tragopogon pratensis), and three alternative crop or weed species (Cichorium endivia, Zinnia elegans and Calendula arvensis). The resulting evolved viral populations, together with the ancestral strain, were then evaluated in a reciprocal cross-inoculation experiment across all five host species. ENMV exhibited clear adaptive responses in two hosts, Z. elegans and C. arvensis, with increased infection success and higher systemic viral accumulation compared to the ancestral virus. In contrast, no evidence of adaptation was detected in L. sativa, T. pratensis and C. endivia. Strikingly, strong cross-adaptation emerged between Z. elegans and C. arvensis: viral populations evolved in either host consistently outperformed those evolved in other hosts, as well as the ancestral strain, when infecting the reciprocal host. Sequencing of the VPg cistron in adapted populations revealed multiple nonsynonymous mutations, several of which arose independently across evolutionary lineages and in both Z. elegans and C. arvensis selection regimes. Functional assays using an infectious ENMV cDNA clone demonstrated that seven of these substitutions, individually or in combination, significantly increased the infection rate in both Z. elegans and C. arvensis. Notably, several of these substitutions also enhanced infectivity across four additional Asteraceae species among the eleven tested, without a clear relationship to host phylogenetic distance. Remarkably, all identified substitutions map to amino acid positions or adjacent residues in VPg previously implicated in the breakdown of recessive resistance genes against potyviruses in both crop and model plant systems. Together, these results suggest that adaptation to host resistance and host range expansion in potyviruses may rely, at least in part, on shared molecular pathways.

Site rate and profile mixture models capture the heterogeneity of the amino acid substitution process across sites. However, these models typically use a single matrix of amino acid exchangeabilities and ignore potential heterogeneities of these exchangeabilities across sites. Simply combining multiple exchangeability matrices with rate and profile mixtures leads to a combinatorial explosion of mixture components and a prohibitive increase in free parameters. Here, we introduce GTRspmix, a novel framework that incorporates multiple exchangeability matrices into profile and site rate mixture models while effectively managing model complexity. GTRspmix employs a clustering-based strategy that groups profiles and assigns a distinct exchangeability matrix to each profile cluster. Evaluations using both empirical and simulated datasets demonstrate that GTRspmix fits empirical data significantly better than conventional models, and that overparameterization does not present a problem for sufficiently large alignments. Based on these results, we estimated general-purpose empirical models (SXXpfamCYY series available in IQ-TREE3) from the Pfam database. These general-purpose models not only fit data much better, but they also influence branch length and tree topology estimates, effectively mitigating long-branch attraction artifacts. Because the total number of rate matrices remains manageable, the computational efficiency of the inference is identical to that of conventional profile mixture models (e.g., LG+C60+G4). GTRspmix provides a more realistic and flexible model of protein evolution, offering a robust foundation for the inference of reliable phylogenetic trees.

Interspecific comparisons of cell-type-specific gene expression levels can provide information about the evolutionary processes that drove divergence between species. From these comparisons, it is now evident that the predominant mode of gene expression evolution has been stabilizing selection, both on the steady-state (mean) protein levels as well as on the mRNA levels with additional lineage-specific shifts resulting from directional selection. However, as all previous work has used bulk RNA measurements, it has been impossible to determine which of the many cellular processes that contribute to mean abundances are highly constrained and which are more evolutionary labile. Assessing this is further complicated by the expectation that components of complex systems will evolve over time independent of changes in the selective regime so long as the net output of a system (i.e., mean expression) remains near the evolutionary optima. This process, known as evolutionary systems drift (ESD), has been frequently invoked as a non-adaptive explanation for changes in cellular phenotypes but has never been quantitatively tested or accounted for in any statistical test for selective constraints. Here, we develop a new paradigm that addresses both of these open problems simultaneously. Using single-cell expression data and biophysical models, we estimate mRNA transcriptional bursting rates, splicing rates, and decay rates across multiple vertebrate species. We then derive new mathematical results that describe how these various biophysical parameters are expected to co-evolve under ESD and then test whether we need additional evolutionary constraints to explain the divergences in these parameters. We find evidence that the biophysical parameters are indeed evolving in a coordinated manner as predicted by ESD and that there are additional strong constraints on transcriptional bursting, likely as a consequence of selection to reduce noise in expression. More broadly, this work opens up a whole new approach for studying the evolutionary dynamics of complex cellular systems.

Genetic variation is the raw material for evolution. One source of variation is chromosomal rearrangements, which can bring genes together and form genetic linkage. Rearrangements can also suppress recombination and gene flow, as in the case of sex chromosome evolution. We conducted the first population genomic study of the red harvester ant Pogonomyrmex barbatus to investigate genomic rearrangements that differentiate the lineages J1 and J2 in the "dependent-lineage system" (also known as "social hybridogenesis"). In this unusual reproductive system, males and females from different lineages mate to create hybrids, yet these hybrids develop into sterile offspring (workers), and so the two lineages remain reproductively isolated. We sequenced high-quality reference genomes for the two lineages to search for a potential explanation of the suppression of gene flow between them. Comparison of the two genome assemblies revealed multiple large-scale genomic rearrangements, all of which occurred in the J1 lineage. The rearrangements formed some of the largest J1 chromosomes, including the largest scaffold in the assembly that was formed by at least two translocation events and additional intra-chromosomal rearrangements. The translocations brought together 118 odorant receptor (OR) genes on this rearranged chromosome, 44 of which are 9-exon ORs, which are implicated in chemical communication in ants. We also identified an enrichment of transposable elements in a large synteny gap between the translocated segments. The discovery of multiple translocations that formed large rearranged chromosomes provides a potential explanation for the reproductive isolation between the pair of dependent lineages in this system, and opens the way for the study of the molecular genetic basis of an intriguing evolutionary phenomenon in these and in other ant lineages.

Whole-genome duplication (WGD) is hypothesized to spur evolutionary diversification by producing genome-wide duplicate gene sets (Ohnologs) that are initially functionally redundant but can diverge markedly as the effects of relaxed selection accumulate over time. However, the underlying mechanisms remain unclear, in part because genomic studies often reconstruct Ohnolog evolution over millions of years, during which subsequent mutations can obscure deep-time signals. Investigating the relationship between Ohnolog evolution and diversification on a contemporary timescale offers clearer insights. We explore this relationship in Lake Charr (Salvelinus namaycush), where ~10% of genes are retained highly conserved polyploid duplicates following the Salmonid-Specific Fourth Round WGD. Using 31 chromosome-level assemblies of Lake Charr from morphologically and ecologically diverse populations, joined into a pangenome graph, we characterized 189,555 structural variants (SVs) that were significantly less likely to affect genes retained as sequence-conserved Ohnolog pairs, nuancing the hypothesis that gene redundancy, relaxed selection, and functional diversification are intertwined. However, we found that SVs affecting such conserved Ohnologs may be potent drivers of adaptive evolution. Notably, we identified a putative 938-Kb interchromosomal translocation containing 25 genes with highly conserved Ohnologs in a paralogous (but untranslocated) genomic block. This putative translocation appears to have facilitated Ohnolog divergence in ankrd11 and hp, genes putatively linked to craniofacial and lipid metabolic diversity in sympatric Lake Superior morphs. This research reveals that conserved Ohnologs previously presumed to be redundant remain a reservoir for adaptive change.