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bioRxiv2026

The shape of evolution: persistent homology of genetic-distancedata as an observable of reticulate processes in pathogen andplant genomes

Evolutionary biology has long theorized processes--recombination, lineage divergence, drug-resistance sweeps, introgression, refugial persistence--whose signatures in genomic data are incompatible with tree structure. We argue that the shape of genetic-distance data, formalized through simplicial complexes and quantified through persistent homology, is a direct observable of these processes. The Vietoris--Rips filtration of a genetic-distance matrix yields the Betti numbers {beta}0 (connected components), {beta}1 (loops), and {beta}2 (cavities); we read {beta}1 not as a literal count of recombination events but as a quantity that is monotone in effective recombination above a sampling-dependent geometric baseline, and we organise the resulting shapes into a four-letter alphabet of topological primitives (K1 clonal, K2 divergence, K3 reticulation, K4 higher-order reticulation). Coalescent and Wright--Fisher simulations establish the two load-bearing claims: {beta}1 rises monotonically with the recombination rate over six orders of magnitude, and persistent-homology features separate reticulate from non-reticulate histories with 98--100% recall (the residual confusion falls entirely within the non-reticulate K1/K2 pair, which {beta}1 does not distinguish). We then apply the pipeline to four empirical systems. (i) On the MalariaGEN Pf7 Plasmodium falciparum dataset (n = 20,864, 33 countries), per-population {beta}1 spans two orders of magnitude and diverges significantly from a label--shuffle null (median 20.5, range 8-32); the ordering runs opposite to recombination rate-freely-recombining African populations sit lowest and clonal/swept Southeast Asian and Papuan populations highest--because at the population scale {beta}1 is dominated by demographic structure rather than recombination rate, a point we reconcile explicitly with the controlled dose-response. (ii) Colombian Cauca SP-resistant samples carry {beta}1 = 12 against a near-clonal SP-sensitive baseline of {beta}1 = 5 (and two orders of magnitude more total persistence), the high-{beta}1, multi-origin band of K3 consistent with resistance carried on several genomic backgrounds. (iii) The Cambodia artemisinin sweep (2008-2018) traces a K3 [->] K1 trajectory, {beta}1 rising to a mid-sweep peak of 45 and collapsing to 13 at fixation--to our knowledge the first direct observation of a selective-sweep transient in topological coordinates, with the caveat that the per-bin values are medians of three subsamples with wide bars. (iv) On Arabidopsis thaliana 1001 Genomes data, Iberian relict populations (Spain, {beta}1/n = 0.64) exceed post-glacial-expansion populations (Sweden 0.54; United Kingdom 0), generalising the framework beyond pathogens. A P. falciparum mitochondrial negative control recovers {beta}1 = 0 across all subsamples, establishing pipeline specificity. Moving above the 1-skeleton, {beta}2 is zero at the clonal/expansion limits and positive across the reticulate systems; a controlled two-vs-three-way admixture simulation confirms that {beta}2 separates regimes that share a {beta}1 profile, while the further suggestion that the ratio = {beta}2/{beta}1 separates microevolutionary from macroevolutionary timescales is presented, given the small number of systems and the absence of a {beta}2 null, as a hypothesis for future testing. Together these results demonstrate that the topology of genetic-distance data is an evolutionary observable, with immediate implications for drug-resistance surveillance in P. falciparum. Author summaryBiologists usually picture the history of life as a tree, in which lineages split and never rejoin. Many of the most consequential evolutionary events break that picture: malaria parasites recombine in the mosquito gut, drug-resistant strains arise repeatedly on different genetic backgrounds, and plant populations that survived the Ice Age in southern refuges carry tangled ancestry that no tree can represent. We ask a different question of genetic data--not "what tree fits?" but "what shape does the data make?" --and answer it with topological data analysis, which measures shape through three counts (the Betti numbers) of clusters, loops, and higher-order cavities. Loops appear when lineages recombine and rejoin. We show, in simulations and in real Plasmodium falciparum and Arabidopsis thaliana genomes, that the loop count rises with recombination above a baseline set by finite sampling, cleanly separates recombining from clonal histories, and tracks a real artemisinin-resistance sweep in Cambodia as it rises and collapses over a decade. A non-recombining mitochondrial control correctly shows no loops. The shape of genetic data is thus a direct, tree-free readout of evolutionary process, with immediate value for drug-resistance surveillance.

evolutionary biology↗

bioRxiv2026

Optimal virulence in ageing populations

Global populations are ageing at an unprecedented rate. For many diseases, age is a strong indicator of susceptibility, morbidity, or mortality. Principles of evolutionary biology can be leveraged to understand how pathogens may optimally exploit new populations, and the impact of this on the global burden of infectious-disease-induced mortality. We parameterised an age-specific R0 model with 2017 epidemiological data on Measles, Tuberculosis, Meningitis, and Ebola, and age-specific demographic estimates for 2017 and 2050, for the seven Global Burden of Disease super-regions. We explored the theoretical trade-offs between pathogen virulence & transmission, and virulence & host recovery, parameterising trade-off parameters using Latin Hypercube Sampling. Population ageing between 2017-2050 saw an increase in virulence induced mortality in four settings: 1) Ebola in sub-Saharan Africa, 2) Measles in central/eastern Europe & central Asia region, 3) Measles in North Africa & the Middle East and 4) Tuberculosis in the central/eastern Europe & central Asia region. The decrease in infection duration due to an increase of elderly people drives pathogen virulence down for diseases in the remaining settings. Understanding the mechanisms that shape pathogen dynamics and leveraging this to predict future challenges is key to endemic disease management in a rapidly changing world. Author SummaryKey aspects of disease transmission including susceptibility to infection, the severity of infection, and the probability of dying from that infection, are affected by host age. Global populations are rapidly ageing, so that the mean age of most populations is generally higher than it used to be and is set to continue on this trajectory. This suggests that the dynamics of infectious diseases are also likely to change, although infectious disease dynamics tend to be non-linear as these key parameters interact. We have developed a dynamic modelling framework to explore how changes in population age structure might impact the optimal level of pathogen virulence in a population. We have chosen four infectious diseases as case studies, that differentially impact certain age classes to illustrate these dynamics. We have parameterised this framework with open access data for each of the seven Global Burden of Disease super-regions and show that population ageing can increase virulence for several diseases in differing global regions, whilst increased background rates of mortality can drive virulence down in others.

evolutionary biology↗

bioRxiv2025

Computer Simulations and Analyses of Coupling Among Reproductive Barriers in Late-Stage Sympatric Speciation

The mechanisms driving sympatric speciation remain an unresolved challenge in evolutionary biology. In nature, closely related "good" species are observed to possess multiple different barriers in their genomes that collectively generate strong and irreversible reproductive isolation (RI). Theorists hypothesize that early-stage mechanisms responsible for establishing an initial reproductive barrier differ from those driving the coupling of barriers in later stages of sympatric speciation. In a prior study, we developed a two-allele mathematical model of mating-bias traits to demonstrate how initial premating RI can arise in a sympatric population under disruptive ecological selection. Here, we extend this model to investigate how different pre- and post-mating barriers can couple with such an initial barrier and with one another during late-stage sympatric speciation to establish strong and irreversible RI. We developed computer applications to examine the properties of various barrier mechanisms and the conditions required for their invasion and coupling. Early-stage, adaptive premating barriers, driven by maladaptive hybrid loss, are effective in establishing initial RI and coupling with other barriers but are easily reversed if disruptive ecological selection weakens. Late-stage barriers, by contrast, often rely on earlier barriers to create an environment of reduced gene flow to facilitate their invasion and coupling. Mutations reducing hybrid viability are underdominant in inter-niche matings and can only invade by hitchhiking with barriers conferring a fitness advantage. Chromosomal inversions, an adaptive late-stage mechanism, can combine different barrier properties into a supergene and gain a net fitness advantage to invade and couple with other barriers to create strong and less reversible RI. Late-stage nonadaptive Bateson-Dobzhansky-Muller (BDM) barriers evolve more slowly but confer the strongest and least reversible RI. Our findings reveal a positive feedback loop in which early-stage barriers facilitate the establishment of late-stage barriers, while late-stage barriers strengthen and secure early-stage barriers. This positive reinforcement progressively strengthens overall RI until it becomes irreversible. By examining the properties and invasion dynamics of various barrier mechanisms, this study complements our previous study to propose a comprehensive process of sympatric speciation that explains how barriers emerge and couple to complete the speciation process.

evolutionary biology↗

bioRxiv2024

The key role of cheaters in the persistence of cooperation

Evolution of cooperation is a major, extensively studied problem in evolutionary biology. Cooperation is beneficial for a population as a whole but costly for the bearers of social traits such that cheaters enjoy a selective advantage over cooperators. Here we focus on coevolution of cooperators and cheaters in a multi-level selection framework, by modeling competition among groups composed of cooperators and cheaters. Cheaters enjoy a reproductive advantage over cooperators at the individual level, independent of the presence of cooperators in the group. Cooperators carry a social trait that provides a fitness advantage to the respective groups. In the case of absolute fitness advantage, where the survival probability of a group is independent of the composition of other groups, the survival of cooperators does not correlate with the presence of cheaters. By contrast, in the case of relative fitness advantage, where the survival probability of a group depends on the composition of all groups, the survival of cooperators positively correlates with the presence of cheaters. Increasing the strength of the social trait alone fails to ensure survival of cooperators, and the increase of the reproduction advantage of the cheaters is necessary to avoid population extinction. We validate these theoretical results with an agent-based model of a bacterial biofilm where emergence of the cooperative trait is facilitated by the presence of cheaters, leading to evolution of spatial organization. This finding contrasts the classical view that spatial organization facilitates cooperation. Our results suggest that, counterintuitively, cheaters often promote, not destabilize, evolution of cooperation. SignificanceCooperation is central to the evolution of life and the emergence of multicellularity. Social traits stabilize populations against environmental volatility and enable division of labor. However, evolution of cooperation is beset by cheaters that benefit from cooperation without paying the cost. Analysis of a multilevel selection model of population evolution shows that, counterintuitively, the presence of cheaters can be beneficial or even essential for the survival of cooperators. This unexpected effect comes from multilevel selection whereby cheaters at the individual level become altruists at the group level, enabling overall growth of the population that is essential for the persistence of cooperators. These findings have broad implications for understanding the emergence of cooperation and host-parasite coevolution throughout the history of life.

evolutionary biology↗

bioRxiv2019

Divergent selection and primary gene flow shape incipient speciation of a riparian tree on Hawaii Island

A long-standing goal of evolutionary biology is to understand the mechanisms underlying the formation of species. Of particular interest is whether or not speciation can occur in the presence of gene flow and without a period of physical isolation. Here, we investigated this process within Hawaiian Metrosideros, a hyper-variable and highly dispersible woody species complex that dominates the Hawaiian Islands in continuous stands. Specifically, we investigated the origin of Metrosideros polymorpha var. newellii (newellii), a riparian ecotype endemic to Hawaii Island that is purportedly derived from the archipelago-wide M. polymorpha var. glaberrima (glaberrima). Disruptive selection across a sharp forest-riparian ecotone contributes to the isolation of these varieties and is a likely driver of newelliis origin. We examined genome-wide variation of 42 trees from Hawaii Island and older islands. Results revealed a split between glaberrima and newellii within the past 0.3-1.2 million years. Admixture was extensive between lineages within Hawaii Island and between islands, but introgression from populations on older islands (i.e. secondary gene flow) did not appear to contribute to the emergence of newellii. In contrast, recurrent gene flow (i.e. primary gene flow) between glaberrima and newellii contributed to the formation of genomic islands of elevated absolute and relative divergence. These regions were enriched for genes with regulatory functions as well as for signals of positive selection, especially in newellii, consistent with divergent selection underlying their formation. In sum, our results support riparian newellii as a rare case of incipient ecological speciation with primary gene flow in trees.\n\nAuthor summaryA long-standing question in evolution is whether or not new species can arise in the presence of gene flow, which is expected to inhibit the formation of reproductive isolating barriers. We investigated the genomics underlying the origin of a Hawaii Island-endemic riparian tree and purported case of incipient sympatric speciation due to disruptive selection across a sharp forest-riparian ecotone. We find extensive evidence of ongoing gene flow between the riparian tree and its closest relative along with local genomic regions resistant to admixture that likely formed through selection on genes for ecological adaptation and/or reproductive isolation. These results strongly suggest that where disruptive selection is strong, incipient speciation with gene flow is possible even in long-lived, highly dispersible trees.

evolutionary biology↗

bioRxiv2019

The great tit HapMap project: a continental-scale analysis of genomic variation in a songbird

A major aim of evolutionary biology is to understand why patterns of genomic diversity vary among populations and species. Large-scale genomic studies of widespread species are useful for studying how the environment and demographic history shape patterns of genomic divergence, and with the continually decreasing cost of sequencing and genotyping, such studies are now becoming feasible. Here, we carry out one of the most geographically comprehensive surveys of genomic variation in a wild vertebrate to date; the great tit (Parus major) HapMap project. We screened ca 500,000 SNP markers across 647 individuals from 29 populations, spanning almost the entire geographic range of the European great tit subspecies. We found that genome-wide variation was consistent with a recent colonisation across Europe from a single refugium in South-East Europe, with bottlenecks and reduced genetic diversity in island populations. Differentiation across the genome was highly heterogeneous, with clear "islands of differentiation" even among populations with very low levels of genome-wide differentiation. Low local recombination rate in the genome was a strong predictor of high local genomic differentiation (FST), especially in island and peripheral mainland populations, suggesting that the interplay between genetic drift and recombination is a key driver of highly heterogeneous differentiation landscapes. We also detected genomic outlier regions that were confined to one or more peripheral great tit populations, most likely as a result of recent directional selection at the range edges of this species. Haplotype-based measures of selection were also related to recombination rate, albeit less strongly, and highlighted population-specific sweeps that likely resulted from positive selection. These regions under positive selection contained candidate genes associated with morphology, thermal adaptation and colouration, providing promising avenues for future investigation. Our study highlights how comprehensive screens of genomic variation in wild organisms can provide unique insights into evolution.

evolutionary biology↗

bioRxiv2024

Capturing changes to animal complexity from quantifiable patterns in genomic data

A prevailing problem in evolutionary biology is elucidating the "genotype-phenotype map" that characterizes how genomic activities regulate different aspects of organismal morphology and their variability in both space and time. Here, we explore potential causality between genome content and both morphological complexity and disparity by compiling the regulatory components (i.e., transcription factors, RNA binding proteins, and microRNA families) as well as a representative set of non-regulatory "housekeeping genes" in 32 species belonging to a wide variety of animal phyla, altogether encapsulating a number of varying genomic characteristics and morphological diversities. A principal component analysis of these four non-overlapping genomic components from each of these 32 species in relation to their last common ancestor revealed that no relationship exists between genome space and disparity, as changes to animal body plans appear to be largely the result of changes to the gene regulatory networks that govern animal development rather than gaining or losing specific sets of regulatory genes. However, using both phylogenetically correlated as well as phylogenetically uncorrelated statistical tests, we find a strong relationship between the loss of all considered gene types and the advent of some parasitic taxa, as well as between microRNA innovations and organismal complexity. While this analysis of genomic features suggests how complexity and disparity are each encoded in the genome, further analysis of the regulatory networks in which they participate should provide a more comprehensive description of how organisms diversify their morphologies over time through alterations in their genomic components. SIGNIFICANCE STATEMENTVariation in morphological form can be measured by considering either disparity (i.e., the amount of variance in morphological form) or complexity (i.e., the difference in the number of their "parts" including genes or cells). To date, discerning the genomic basis of either has remained largely unknown. Here, we compile the regulatory genome of the last common ancestor of bilaterian metazoans, including its transcription factors, RNA-binding proteins and microRNA families, and ask how changes to these repertoires potentially reflects changes in either disparity or complexity. We find that although there is no relationship between the regulatory genome and disparity, there is a robust relationship between the loss of regulatory genes relative to housekeeping genes, especially in parasitic taxa. Further, there is a strong relationship between increases to microRNAs and complexity, which likely reflects the unique role microRNAs play in increasing both the accuracy and the precision of gene expression during development.

evolutionary biology↗

bioRxiv2019

The contribution of ancient admixture to reproductive isolation between European sea bass lineages

Understanding how new species arise through the progressive establishment of reproductive isolation barriers between diverging populations is a major goal in Evolutionary Biology. One important result of speciation genomics studies is that the genomic regions involved in reproductive isolation frequently harbor anciently diverged haplotypes that predate the reconstructed history of species divergence. The possible origins of these old alleles remain highly debated, since they relate to contrasted mechanisms of speciation that are not fully understood yet. In the European sea bass (Dicentrarchus labrax), the genomic regions involved in reproductive isolation between Atlantic and Mediterranean lineages are enriched for anciently diverged alleles of unknown origin. Here, we used haplotype-resolved whole-genome sequences to test whether divergent haplotypes could have originated from a closely related species, the spotted sea bass (Dicentrarchus punctatus). We found that an ancient admixture event between D. labrax and D. punctatus is responsible for the presence of shared derived alleles that segregate at low frequencies in both lineages of D. labrax. An exception to this was found within regions involved in reproductive isolation between the two D. labrax lineages. In those regions, archaic tracts originating from D. punctatus locally reached high frequencies or even fixation in Atlantic genomes but were almost absent in the Mediterranean. We showed that the ancient admixture event most likely occurred between D. punctatus and the D. labrax Atlantic lineage, while Atlantic and Mediterranean D. labrax lineages were experiencing allopatric isolation. Our results suggest that local adaptive introgression and/or the resolution of genomic conflicts provoked by ancient admixture have probably participated to the establishment of reproductive isolation between the two D. labrax lineages.\n\nAuthor summarySpeciation is often viewed as a progressive accumulation of reproductive isolation barriers between two diverging lineages through the time. When initiated, the speciation process may however take different routes, sometimes leading to the erosion of an established species barrier or to the acquisition of new speciation genes transferred from another species boundary. Here, we describe such a case in the European sea bass. This marine fish species has split 300,000 years ago into an Atlantic and a Mediterranean lineage, which remained partially reproductively isolated after experiencing postglacial secondary contact. For unknown reasons, genomic regions involved in reproductive isolation between lineages have started to diverge well before the split. We here show that diverged alleles were acquired by the Atlantic lineage from an ancient event of admixture with a parapatric sister species about 80,000 years ago. Introgressed foreign alleles that were locally driven to high frequencies in the Atlantic have subsequently resisted to introgression within the Mediterranean during the postglacial secondary contact, thus contributing to increased reproductive isolation between two sea bass lineages. These results support the view that reproductive isolation barriers can evolve via reticulate gene flow across multiple species boundaries.

evolutionary biology↗

bioRxiv2024

L-Shaped Distributions of the Relative Substitution Rates (c/micro) in SARS-COV-2 with or without Molecular Clocks, Challenging Mainstream Evolutionary Theories

A definitive test to quantify fitness changes of mutations is required to end a continuing 50-year "neutralist-selectionist" debate in evolutionary biology. Our previous work introduced a substitution-mutation rate ratio c/{micro} test (c: substitution rate in Translated Region/TR or UnTranslated Region/UTR; {micro}: mutation rate) to quantify the selection pressure and thus the proportions of strictly neutral, nearly neutral, beneficial, and deleterious mutations in a genome. Intriguingly, both a L-shaped probability distribution of c/{micro} and molecular clock were observed for SARS-COV-2s genome. We found that the proportion of the different mutation types from the distribution is not consistent with the hypotheses of the three existing evolution theories (Kimuras Neutral Theory/KNT, Ohtas Nearly Neutral Theory/ONNT and the Selectionist Theory/ST), and a balance condition explains the molecular clock, thus we proposed a new theory named as Near-Neutral Balanced Selectionist Theory (NNBST). In this study, the c/{micro} analysis was extended beyond the genome to 26 TRs, 12 UTRs, and 10 TRSs (Transcriptional Regulatory Sequences) of SARS-COV-2. While L-shaped probability distributions of c/{micro} were observed for all of 49 segments, molecular clocks were observed for only 24 segments, supporting NNBST and Near-Neutral Unbalanced Selectionist Theory (NNUST) to explain the molecular evolution of 24/25 segments with/without molecular clocks. Thus, the Near-Neutral Selectionist Theory (NNST) integrates traditional neutral and selectionist theories to deepen our understanding of how mutation, selection, and genetic drift influence genomic evolution. Author SummaryThe "neutralist-selectionist" debate in molecular evolution has been unresolved for 50 years due to the three main theories of molecular evolution (Kimuras Neutral Theory/KNT, Ohtas Nearly-Neutral Theory/ONNT, Selectionist Theory/ST) disagreeing on the proportion of neutral mutations (KNT), nearly-neutral deleterious mutations (ONNT) and adaptive mutations (ST) within species. We recently developed a robust method, the c/{micro} relative substitution rate test, to quantify the proportion of each mutation type within >11K genomic sequences of SARS-COV-2 RNA virus. Our previous analysis revealed an L-shaped c/{micro} probability distribution and a constant substitution rate (e.g., molecular clock) for the SARS-COV-2 genome over 19 months, and the proportions of mutation types were inconsistent with those predicted by the three theories. We thus proposed the Near-Neutral Balanced Selectionist Theory (NNBST) to explain the molecular clock-feature and L-shaped probability distribution for SARS-COV-2. In this study, we extended this analysis to the 25 protein-coding gene segments and 24 non-protein-coding segments of SARS-COV-2. We observed that all 49 segments exhibited an L-shaped probability distribution and 24 out of the 49 segments exhibited a molecular clock, however the remaining 25 segments did not exhibit a molecular clock. We thus propose the Near-Neutral Unbalanced Selectionist Theory (NNUST) and NNBST to explain the segments without/with molecular clock features, respectively. We also coin the Near-Neutral Selectionist Theory (NNST) to combine traditional KNT, ONNT and ST to deepen our understanding of how mutation, selection, and genetic drift influence genomic evolution.

evolutionary biology↗

bioRxiv2024

A high-resolution microscopy system for biological studies of cold-adapted species under physiological conditions

The fundamental processes governing life are sensitively dependent on temperature. Whilst much is known about the constraints on how proteins operate at 37{degrees}C, little knowledge exists about how biological function is maintained sub-zero temperature conditions, where proteins are less stable and oxidative damage is high. However, almost 90% of habitable environments on Earth are permanently below 5{degrees}C (i.e. the deep sea and polar regions). This means that we do not understand how a large and diverse proportion of the global biome functions. To address this question at the cellular level, tools are required for imaging biological systems at high resolution under physiological conditions. This poses severe technical challenges that cannot be addressed with traditional optical microscopy techniques. High-resolution imaging objectives require short working distances and the use of immersion media, which lead to rapid heat transfer from the microscope to the sample. This affects the viability of live specimens and the interpretability of the results when the sample function optimally at low temperatures. Condensation and temperature-induced shrinking of components pose further challenges, reducing image resolution and contrast. Here, we address these issues and provide a method for high-fidelity imaging of live biological samples at temperatures of around, or below, 0{degrees}C. Our method is compatible with different microscopy modalities, including super-resolution imaging. It relies on hardware additions to traditional microscopy systems that can be straightforwardly implemented, namely, a cooling collar, 10% ethanol as an immersion medium, and nitrogen flow to mitigate condensation. We demonstrate the method in live cell cultures derived from Antarctic fish species and highlight the need to maintain physiological conditions for these fragile biological samples. Future applications are diverse and include evolutionary biology and the study of cold-adapted organisms, as well as cellular biophysics and several applications in biotechnology.

biophysics↗

bioRxiv2024

Entangled Evolution Model: Application to Adaptive Mutation

Adaptive mutation, the phenomenon where organisms appear to increase beneficial mutation rates in response to environmental stress, has challenged the traditional understanding of random mutations in evolutionary biology. Here, we present a novel computational model, the Entangled Evolution Model, which integrates quantum game theory and quantum walks to provide a new approach to understanding mutation dynamics. By applying the Clauser-Horne-Shimony-Holt (CHSH) quantum game within a modified Lotka-Volterra framework, we simulate how quantum entanglement can accelerate the rate of adaptive mutations in Escherichia coli populations. Our simulations reveal that entangled bacterial populations achieve successful adaptive mutations with an 85% probability, significantly surpassing the classical theoretical maximum. These results introduce a new perspective on computational approaches to evolutionary adaptation, offering an efficient algorithmic framework to explore the role of quantum effects in biological systems.

evolutionary biology↗

bioRxiv2025

Generative continuous time model reveals epistatic signatures in protein evolution

Protein evolution is fundamentally shaped by epistasis, where the effect of a mutation depends on the sequence context. As standard phylogenetic methods assume independently evolving sites, there is a need for more complex models based on accurate estimations of the fitness landscape. Good candidates are modern generative models - such as the Potts model - which successfully capture epistatic effects. However, recent works on generative evolutionary models usually use discrete time, making them difficult to integrate with the standard frameworks in evolutionary biology. We introduce a continuous-time sequence evolution model using the Gillespie algorithm and parameterized by a generative Potts model. This approach enables us to simulate realistic, family-specific evolutionary trajectories and allows for direct comparison with independent-site models. Surprisingly, we find that while epistasis significantly slows down evolution, it does not change the average evolutionary rates at individual sites. This is explained by the rate heterogeneity caused by context-dependence: we show that the rate at some positions varies between null to high values depending on the context, while other positions are essentially independent from the context. Finally, we show that epistasis leads to a systematic underestimation bias in the inference of evolutionary distance between sequences. Overall, our work provides a new tool for simulating realistic protein evolution and offers novel insights into the complex interplay between epistasis and evolutionary dynamics. Significance statementUnderstanding how proteins evolve is central to molecular biology and phylogenetics. Traditional evolutionary models assume that mutations act independently at each position in a sequence. This neglects epistasis -- the fact that the effect of a mutation depends on the rest of the sequence -- which is known to be ubiquitous in proteins. By simulating protein evolution in continuous time using a generative model, our approach produces realistic sequences and reveals how epistasis shapes evolutionary dynamics. We find that epistasis slows down evolution and can mislead common methods for estimating evolutionary timescales. This work bridges modern generative models of proteins and phylogenetics, providing new tools to better understand molecular evolution.

bioinformatics↗

bioRxiv2024

Interindividual vocal tract diversity influences the phonetic diversification of spoken languages

Vocal tracts, like other physical traits, exhibit extensive interindividual variation. However, little is known about how this variation translates into phonetic diversity between speakers, and ultimately, across languages. We demonstrate that different vocal tract shapes and associated articulatory strategies leave consistent acoustic signatures, which show congruent patterns of phonetic variation both within and across speech communities. Recalling a central tenet of evolutionary biology - that within-group variation feeds processes of between-group diversification - our findings suggest that the sounds of language evolve according to a neutral-like evolutionary process. Our "neutral-like evolution model" serves as a null hypothesis for disentangling the biological versus cultural mechanisms at play in phonetic diversification, where deviations from the neutral expectation indicate culturally mediated processes of language change at work.

evolutionary biology↗

bioRxiv2020

Genetic algorithms and evolutionary landscapes

The metaphor of fitness landscapes is common in evolutionary biology, as a way to visualise the change in allele or phenotypic frequencies of a population under selection. Understanding how different factors in the evolutionary process affect the trajectory of the population across the landscape is of interest to both theoretical and empirical evolutionary biologists. However, fitness landscape studies often have to rely heavily on mathematical methods that are not easy to access by biologically trained researchers. Here, we used a method borrowed from engineering - genetic algorithms - to simulate the evolutionary process and study how different components affect the path taken through a phenotypic fitness landscape. In a simple study, we compare five selection models that reflect different degrees of dependency of fitness on trait quality: this includes strengths of selection, trait-quality dependent reproductive hierarchy and the amount of stochasticity in the reproductive process. We include an analysis of other evolutionary variables such as population size and mutation rate. We analyse a game theory problem, as a test landscape, that lends itself to analysis through a deterministic mathematical simulation, which we use for comparison. Our results show that there are differences in the speed with which different models of selection lead to the fitness optimum. Author summaryEvolution and adaptation in biology occurs in fitness landscapes, multidimensional spaces representing all possible genotypic or phenotypic combinations, where population adapt by following the cline of the fitness dimension. The study of adaptation on complex fitness landscapes has so far been limited by the need for mathematically heavy methods. Here, we present a simulation modelling framework, genetic algorithms, that can be used for evolutionary simulations of a population on a fitness landscape of chosen features and with custom evolutionary parameters.

evolutionary biology↗

bioRxiv2018

Models of archaic admixture and recent history from two-locus statistics

We learn about population history and underlying evolutionary biology through patterns of genetic polymorphism. Many approaches to reconstruct evolutionary histories focus on a limited number of informative statistics describing distributions of allele frequencies or patterns of linkage disequilibrium. We show that many commonly used statistics are part of a broad family of two-locus moments whose expectation can be computed jointly and rapidly under a wide range of scenarios, including complex multi-population demographies with continuous migration and admixture events. A full inspection of these statistics reveals that widely used models of human history fail to predict simple patterns of linkage disequilibrium. To jointly capture the information contained in classical and novel statistics, we implemented a tractable likelihood-based inference framework for demographic history. Using this approach, we show that human evolutionary models that include archaic admixture in Africa, Asia, and Europe provide a much better description of patterns of genetic diversity across the human genome. We estimate that an unidentified, deeply diverged population admixed with modern humans within Africa both before and after the split of African and Eurasian populations, contributing 4 - 8% genetic ancestry to individuals in world-wide populations.\n\nAuthor SummaryThroughout human history, populations have expanded and contracted, split and merged, and ex-changed migrants. Because these events affected genetic diversity, we can learn about human history by comparing predictions from evolutionary models to genetic data. Here, we show how to rapidly compute such predictions for a wide range of diversity measures within and across populations under complex demographic scenarios. While widely used models of human history accurately predict common measures of diversity, we show that they strongly underestimate the co-occurence of low frequency mutations within human populations in Asia, Europe, and Africa. Models allowing for archaic admixture, the relatively recent mixing of human populations with deeply diverged human lineages, resolve this discrepancy. We use such models to infer demographic models that include both recent and ancient features of human history. We recover the well-characterized admixture of Neanderthals in Eurasian populations, as well as admixture from an as-yet unknown diverged human population within Africa, further suggesting that admixture with deeply diverged lineages occurred multiple times in human history. By simultaneously testing model predictions for a broad range of diversity statistics, we can assess the robustness of common evolutionary models, identify missing historical events, and build more informed models of human demography.

genetics↗

bioRxiv2025

Cytosolic mannosyltransferases involved in the ER N-glycosylation pathway exhibit bacterial ancestry

N-glycosylation in eukaryotes begins with the assembly of a lipid-linked oligosaccharide on the endoplasmic reticulum membrane. As a pivotal post-translational protein modification, it is conserved across all three domains of life. However, the evolutionary origins of the N-glycosylation pathway remain a subject of ongoing debate in evolutionary biology, largely due to the limited availability of robust data regarding the evolutionary trajectories of the glycosyltransferases involved in this process. Here, we present phylogenetic analyses of the eukaryotic ALG1 and ALG2 mannosyltransferases (MTases), which are crucial for constructing the core trimannosyl Man3GlcNAc2 structure conserved in eukaryotic N-glycans. Our comprehensive phylogenetic study, combined with functional and structural analyses, suggests that the ALG2 MTase likely originated from a bacterial ancestor. This inference is further supported by the identification of sequential and functional ALG1 homologs exclusively within bacterial lineages, rather than in Asgard archaea or other archaeal groups. Our findings challenge the prevailing hypothesis that the eukaryotic N-glycosylation pathway primarily evolved from archaeal ancestors, instead suggesting a chimeric origin involving contributions from both bacterial and archaeal lineages. Synopsis O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=109 SRC="FIGDIR/small/682550v1_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@1ac81a8org.highwire.dtl.DTLVardef@746054org.highwire.dtl.DTLVardef@604bdborg.highwire.dtl.DTLVardef@14235d_HPS_FORMAT_FIGEXP M_FIG C_FIG The ALG glycosyltransferase (GTases) involved in the initial stage of eukaryotic N-glycosylation on the cytosolic side of the ER membrane exhibit chimeric evolutionary origins. LUCA: Last Universal Common Ancestor; LECA: Last Eukaryotic Common Ancestor. HighlightsO_LIThe evolutionary trajectories of cytosolic ALG mannosyltransferases (MTases) were studied C_LIO_LIThe ancestor of ALG2 exhibited in the LUCA but evolved its MTase activity in bacterial lineages C_LIO_LIThe ALG1 MTase originated from bacterial lineages C_LI

molecular biology↗

bioRxiv2022

THEWEIGHT: A simple and flexible algorithm for simulating non-ideal, age-structured populations

O_LIThe Wright-Fisher model, which directs how matings occur and how genes are transmitted across generations, has long been a lynchpin of evolutionary biology. This model is elegantly simple, analytically tractable, and easy to implement, but it has one serious limitation: essentially no real species satisfies its many assumptions. With growing awareness of the importance of jointly considering both ecology and evolution in eco-evolutionary models, this limitation has become more apparent, causing many researchers to search for more realistic simulation models. C_LIO_LIA recently described variation retains most of the Wright-Fisher simplicity but provides greater flexibility to accommodate departures from model assumptions. This generalized Wright-Fisher model relaxes the assumption that all individuals have identical expected reproductive success by introducing a vector of parental weights w that specifies relative probabilities different individuals have of producing offspring. With parental weights specified this way, expectations of key demographic parameters are simple functions of w. This allows researchers to quantitatively predict the consequences of non-Wright-Fisher features incorporated into their models. C_LIO_LIAn important limitation of the Wright-Fisher model is that it assumes discrete generations, whereas most real species are age-structured. Here I show how an algorithm (TO_SCPLOWHEC_SCPLOWWO_SCPLOWEIGHTC_SCPLOW) that implements the generalized Wright-Fisher model can be used to model evolution in age-structured populations with overlapping generations. Worked examples illustrate simulation of seasonal and lifetime reproductive success and show how the user can pick vectors of weights expected to produce a desired level of reproductive skew or a desired Ne/N ratio. Alternatively, weights can be associated with heritable traits to provide a simple, quantitative way to model natural selection. Using TO_SCPLOWHEC_SCPLOWWO_SCPLOWEIGHTC_SCPLOW, it is easy to generate positive or negative correlations of individual reproductive success over time, thus allowing explicit modeling of common biological processes like skip breeding and persistent individual differences. C_LIO_LICode is provided to implement basic features of TO_SCPLOWHEC_SCPLOWWO_SCPLOWEIGHTC_SCPLOW and applications described here. However, required coding changes to the Wright-Fisher model are modest, so the real value of the new algorithm is to encourage users to adopt its features into their own or others models. C_LI

evolutionary biology↗

bioRxiv2020

Phylogenomic assessment of the role of hybridization and introgression in trait evolution

Trait evolution among a set of species--a central theme in evolutionary biology--has long been understood and analyzed with respect to a species tree. However, the field of phylogenomics, which has been propelled by advances in sequencing technologies, has ushered in the era of species/gene tree incongruence and, consequently, a more nuanced understanding of trait evolution. For a trait whose states are incongruent with the branching patterns in the species tree, the same state could have arisen independently in different species (homoplasy) or followed the branching patterns of gene trees, incongruent with the species tree (hemiplasy). Another evolutionary process whose extent and significance are better revealed by phylogenomic studies is gene flow between different species. In this work, we present a phylogenomic method for assessing the role of hybridization and introgression in the evolution of polymorphic or monomorphic binary traits. We apply the method to simulated evolutionary scenarios to demonstrate the interplay between the parameters of the evolutionary history and the role of introgression in a binary traits evolution (which we call xenoplasy). Very importantly, we demonstrate, including on a biological data set, that inferring a species tree and using it for trait evolution analysis in the presence of gene flow could lead to misleading hypotheses about trait evolution.

evolutionary biology↗