Evolution Research Articles

Eels' individual migratory behavior stems from a complex syndrome involving cognition, behavior, physiology, and life history.

Variability within species is key for adaptability and biological evolution. To understand individualities in the context of animal movement, we focused on one of the most remarkable migrations-the journey of the endangered European eel from their birthplace in the Sargasso Sea to freshwater environments. Laboratory observations unveiled a continuum of diverse phenotypes of migrating eels: Some displayed a heightened tendency to swim against a constant water flow, while others a greater propensity to climb obstacles. Looking for the biological underpinnings of this migratory diversity, we characterized the eels' individual differences in traits of four key domains: life history, physiology, behavior, and cognition, among which we found significant variance and interconnectedness. Upon reducing this variance to its primary multivariate axes, we found that these predict the migratory types. Eels with 1) low exploration, high activity, low boldness, and high lateralization; 2) strong lateralization, enhanced quantitative abilities, short problem-solving time, high boldness, and low growth rates; or 3) enhanced problem-solving, reduced spatial learning, high cognitive flexibility, and shorter time to solve the cognitive tasks were more likely to display the climbing migratory type. Field sampling revealed how specific traits' combinations seemed to influence the distribution of eels once they begin to settle in the freshwater environment. Our study underscores the impressive diversity of individuals during this critical migration, emphasizing an intrinsic connection to multidomain trait variance. Preserving this diversity becomes paramount, as it likely contributes to the resilience and adaptability of endangered migratory species.

Evolutionary Game Theory: A General Review

This article explores the Evolutionary Game Theory (now EGT), encompassing its historical underpinnings, recent advancements, and future potential. Originating in the 1970s through the pioneering work of John Maynard Smith and George R. Price, EGT leverages game-theoretic concepts to elucidate the evolution of strategies within various populations across biological, economic, and social domains. Notably, recent progress has seen the integration of advanced large language models (LLMs) such as GPT-3.5 and GPT-4 into agent-based simulations, thereby enriching the authenticity and intricacy of strategic interactions. Additionally, the study addresses the complexities associated with modeling diverse behaviors and bridging the insights derived from LLMs to practical applications in fields like biology, healthcare, education, and social sciences. Furthermore, it underscores the significance of interdisciplinary collaboration and innovative methodologies in addressing the multifaceted challenges within EGT. Finally, the article contemplates the potential avenues for future research, emphasizing the fusion of EGT with real-world applications and the necessity for comprehensive models that encompass the complexities of evolutionary dynamics in adaptive systems.

Research on the Collaborative Mechanism of Value Creation in Public–Private Partnership Projects Under Dynamic Trust

ABSTRACTPublic–private partnership (PPP) is now focused on project value creation, with trust playing a crucial role. This study models trust evolution among stakeholders using evolutionary game theory and simulations, revealing that higher initial and sustained trust boosts project value. However, overreliance on trust can lead to deregulation and neglect of contracts, harming outcomes. Spillover effects and speculative behavior also threaten value creation. The study identifies an optimal incentive range for reputation gains, highlighting the need for balanced trust mechanisms, effective incentives, and penalties to ensure collaboration and project success.

A tale of two cultures: How L. Luca Cavalli-Sforza bridged the gap between science and the humanities

This article retraces the career of geneticist L. Luca Cavalli-Sforza, from his days as a student researcher to his tenure as a Stanford University professor, and beyond. We show how Cavalli-Sforza’s untiring curiosity, enthusiasm, and global knowledge led him to make incisive contributions to topics as diverse as bacterial genetics and human evolution, both biological and cultural. In an academic world where hyperspecialization is the norm, Cavalli-Sforza stood out as a scientist unafraid to promulgate and apply multidisciplinary approaches to complex issues of human origins and culture.

Gene Co-Expression Network Analysis Associated with Endometrial Cancer Tumorigenesis and Survival Outcomes.

Endometrial cancer (EC) presents a substantial health challenge, with increasing incidence and mortality rates. Despite advances in diagnosis and treatment, understanding the molecular underpinnings of EC progression remains unknown. In this study, we conducted a comprehensive investigation utilizing The Cancer Genome Atlas (TCGA-UCEC n = 588) data to analyze gene co-expression patterns, elucidate biological process pathways, and identify potential prognostic and diagnostic biomarkers for EC, using weighted gene co-expression network analysis (WGCNA), differential gene expression, survival analysis, and functional analysis, respectively. We determined that the Green module (M5) was significantly correlated with patient survival. Functional analysis of the genes in module M5 indicates involvement in cell cycle regulation, mitotic spindle assembly, and intercellular signaling. TPX2, BUB1, and ESPL1 were among the top differentially expressed genes in the Green module, suggesting their involvement in critical pathways that contribute to disease progression and patient survival outcomes. The biological and clinical assessments of our findings provide an understanding of the molecular landscape of EC and identified several potential prognostic markers for patient risk stratification and treatment selection.

Trade-offs, control conditions, and alternative designs in the experimental study of cultural evolution.

Although the theoretical foundations of the modern field of cultural evolution have been in place for over 50 y, laboratory experiments specifically designed to test cultural evolutionary theory have only existed for the last two decades. Here, we review the main experimental designs used in the field of cultural evolution, as well as major findings related to the generation of cultural variation, content- and model-based biases, cumulative cultural evolution, and nonhuman culture. We then identify methodological advances that demonstrate the iterative improvement of cultural evolution experimental methods. Finally, we focus on one common critique of cultural evolution experiments, the appropriate individual learning control condition needed to demonstrate cumulative culture, and present an original experimental investigation relevant to this critique. Participants completed a combinatorial innovation task allowing for cumulative improvement over time in one of four commonly used experimental designs/conditions: social learners in chains, social learners in groups, individual learners experiencing an extended session lasting the same accumulated time as an entire chain or group, and individual learners experiencing repeated sessions adding up to the same total time. We found that repeated individual learning resulted in superior performance to any other condition. We discuss these findings in light of the relevance of the specific criticism of previous experimental studies that purport to have demonstrated cumulative culture. We also use our findings to discuss the broad trade-offs that participants face when learning individually and socially in different contexts, including variable acquisition costs, redundancy of effort in groups, and cognitive and motivational fatigue.

Bridging theory and data: A computational workflow for cultural evolution

Cultural evolution applies evolutionary concepts and tools to explain the change of culture over time. Despite advances in both theoretical and empirical methods, the connections between cultural evolutionary theory and evidence are often vague, limiting progress. Theoretical models influence empirical research but rarely guide data collection and analysis in logical and transparent ways. Theoretical models themselves are often too abstract to apply to specific empirical contexts and guide statistical inference. To help bridge this gap, we outline a quality-assurance computational workflow that starts from generative models of empirical phenomena and logically connects statistical estimates to both theory and real-world explanatory goals. We emphasize and demonstrate validation of the workflow using synthetic data. Using the interplay between conformity, migration, and cultural diversity as a case study, we present coded and repeatable examples of directed acyclic graphs, tailored agent-based simulations, a probabilistic transmission model for longitudinal data, and an approximate Bayesian computation model for cross-sectional data. We discuss the assumptions, opportunities, and pitfalls of different approaches to generative modeling and show how each can be used to improve data analysis depending on the structure of available data and the depth of theoretical understanding. Throughout, we highlight the significance of ethnography and of collecting basic cultural and demographic information about study populations and call for more emphasis on logical and theory-driven workflows as part of science reform.

Forward and backward modeling of cultural evolutionary processes

Modern cultural evolution theory adopts a variety of concepts and methods developed in mathematical biology, in particular population genetics theory. In addition to forward-looking approaches such as two-locus models, backward-looking approaches such as coalescent theory, which describe ancestral states of the current population, have played an important role in population genetics. Here, we show how forward and backward approaches can be applied to two examples in cultural evolution. The first example deals with the number of cultural traits, which can be analyzed by a backward approach. Cultural coalescent theory illustrates many unique aspects of cultural processes such as information transfer (i.e., social learning) from many donors ("cultural parents"), including or excluding the biological parents. Theory predicts that many cultural traits of intermediate (or higher) frequency (popularity) can exist that are surprisingly old. Many unsolved issues remain, however, such as how to incorporate social structure as well as natural and/or cultural selection, which we believe to be an urgent agenda. The second example is the punishment of sibling incest, a problem to which cultural coalescent theory cannot currently be usefully applied. By analyzing forward recursions, we show that punishment is ineffective in suppressing incest, unless the incestuous inclination is diminished by the presence of punishers. Based on these examples, we discuss the merits and demerits of forward and backward approaches.

Molecular epidemiology and pathogenicity of Wesselsbron virus circulating in Africa

Wesselsbron is a neglected, mosquito-borne zoonotic disease transmitted by several species of virus-infected Aedes mosquitoes endemic to tropical regions in Africa. It affects primarily domestic livestock species with teratogenic effects, but can jump to humans. Herein, we investigated the molecular epidemiology of Wesselsbron virus in Africa using whole genome sequencing and structural analysis, and assessed its pathogenicity and tropism through in vivo experiments. A total of twenty-five isolates collected from three countries were successfully characterized. Our study is noteworthy by identifying, for the first time, inter-clade recombination events on the genome of Wesselsbron virus. However, more investigations on the precise molecular mechanisms conducting the occurrence of recombination on the genome of Wesselsbron virus, are warranted. The identification of polymorphisms on motifs of virulence and selection pressures on major proteins showed evidence of genetic evolution for Wesselsbron virus. The clade 1 was more pathogenic and neurotropic in suckling mice and the intramuscular route was found to be the best transmission mode. Our findings also provide new insights in the pathogenicity and tropism of Wesselsbron virus, which could be useful for prevention, preparedness and future outbreak response. Considering its high prevalence in mosquito populations and the increasing number of sporadic human cases, Wesselsbron virus merits more attention in terms of prevention and preparedness, as its mosquito vectors continue to globally expand and there is no vaccine.

A Decade of Vertebrate Palaeontology Research in the UK: Bibliometric and Topic Modelling Analysis

The study of vertebrate palaeontology in the United Kingdom holds a significant position in global research. This study conducts a comprehensive bibliometric analysis and topic modelling of UK vertebrate palaeontology from 2014 to 2023, utilizing data from the DeepBone database and Web of Science. A total of 2884 publications were analysed using bibliometric methods and Latent Dirichlet Allocation (LDA) to identify key research themes, institutional contributions, and international collaborations. The results reveal a significant increase in publication volume over the decade, peaking in 2021 with 374 papers. High-impact journals such as Nature and Science published approximately 6.60% of the total papers. The LDA analysis identified seven primary research themes, including morphology, palaeoanthropology, evolutionary biology, and geological periods. The Natural History Museum, University of Bristol, and University of Oxford emerged as major contributing institutions. Scientists from the United States were found to be the most frequent international collaborator. The average impact factor of the top journals in the field was 8.28 in 2024, highlighting the high quality of UK vertebrate palaeontology research. This study provides objective insights into the current state of vertebrate palaeontology in the UK, emphasizing its multidisciplinary nature, the importance of international cooperation in the field.

Models of Fluctuating Selection Between Generations: A Solution for the Theoretical Inconsistency.

The theory of selection fluctuation between generations has been a topic with much activities in population genetics and molecular evolution in 1970's. Most studies suggested that, as the result of fluctuating selection between generations, the frequency of an (on average) neutral mutation may fluctuate around 0.5 during the long-term evolution before it was ultimately fixed or lost. However, this pattern can only be derived from a specific type Wright-Fisher additive model, coined by the Nei-Yokoyama puzzle. In this commentary, I revisited this issue and figured out a theoretical assumption that has never been claimed explicitly, the notion of reference phenotype. Consider one locus with two-alleles: A is the wildtype allele and A' is the mutation. The fluctuating selection model actually requires a constraint that one of three genotypes (AA, AA', or A'A') must maintain a constant fitness without fluctuating between generations. It appears that the balancing selection at a frequency of 0.5 emerges only when the heterozygote (AA') is the reference genotype. Because it is difficult to determine which genotype could be the reference genotype in a real population, a desirable population genetics model should take all three possibilities into account. To this end, I propose a mixture model, where each genotype has a certain chance to be the reference genotype. My analysis showed that the emergence of balancing selection depends on the relative proportions of three different reference genotypes.

The clinical impact of EGFR alterations in elderly glioblastoma patients: results from a real-life cohort.

The incidence of glioblastoma in the elderly population is increasing as the worldwide population ages. The differential and poorer survival in the elderly population compared to younger patients is partially explained. The present study aimed to investigate the clinical impact of epidermal growth factor receptor EGFR-altered glioblastoma in a real-life elderly glioblastoma population. A bicentric and retrospective study was conducted. Patients were 70years or older and suffering from histomolecularly confirmed glioblastoma. Single nucleotide variants (SNV), amplification, or chromosome 7 polysomy were sought. The primary endpoint was the comparison of overall survival (OS) in patients with or without EGFR alteration. Secondary objectives were to determine other clinical parameters correlated with EGFR alteration status. Seventy-three patients were analyzed: 41.1% had at least one EGFR alteration. The presence of EGFR alteration did not impact overall survival: HR 0.97 [0.6-1.57], p = 0.9; the median overall survival was 6.5months [5.3-9.3] in the EGFR-altered group versus 7months [4.5-10] in the EGFR wild-type group, p = 0.75. In multivariate analysis, tumor resection was associated with a significant overall survival improvement: the median OS in the resected group (n = 20) was 11months [95% CI 7.8-22] versus a median OS of 5.5months [4.6-7.8] in the unresected group (n = 53), without correlation to EGFR alteration status. In the modern era of molecular characterization and improved treatment modalities, the presence of at least one EGFR alteration did not influence survival outcomes in an elderly population of glioblastoma patients.

Propagation Dynamics in Time‐Periodic Reaction–Diffusion Systems with Network Structures

ABSTRACTThe main purpose of this paper is to study the propagation dynamics for a class of time‐periodic reaction–diffusion systems with network structures. In the first part, by using the persistence theory, we obtain threshold results for the extinction and uniform persistence of the corresponding periodic ordinary differential system. The second part is concerned with the asymptotic speed of spread and traveling wave solutions. The uniform boundedness of solutions is proved by employing the refined high‐dimensional local ‐estimate and abstract periodic evolution theories and the spreading properties of the corresponding solutions are established. We also prove the existence of the critical periodic traveling wave with wave speed by using a delicate limitation argument. Finally, these results are applied to a multistage epidemiological model.

Are there “Ratatouille” restaurants? On anticorrelation of food quality and hygiene

We study the empirical relationship between restaurants’ hygiene standards and their food quality scores, as evaluated by professional reviewers. By using data from the UK high-end restaurants, we show that this relationship is negative, observed across several econometric specifications and food quality measurements. We report that 3% of Michelin-starred restaurants have poor hygiene, while the same is true for 2.5% of high-end guidebook-listed restaurants in our dataset. We highlight two possibilities for this observed negative association: a strategic hypothesis (capturing restaurants’ choices trading off hygiene for quality), and a selection hypothesis (reflecting restaurants’ differential survival rates under competition). Our results indicate that the latter has more support. Our findings also illuminate potential channels through which the anticorrelation between hygiene and food quality could be mitigated and can be informative for hygiene inspectors in order to prioritize restaurants in their inspection schedule based on observable characteristics.

An open letter to evolutionary and human sciences; Statistics has moved on and so should we. A proposal for more transparent research, and some notes on p < 0.003

Statistical reasoning and inference have become integral to how we reach conclusions as scientists. Few papers in evolutionary, biological, and human sciences, are published at present without at least one report of a p-value, or the term “statistically significant”. As a product of this, discoveries and results often hinge on p-values below the infamous threshold of 0.05. This is due to how well ingrained these notions are in many of our higher education systems, and our practices as researchers. Nevertheless, the concept of a p-value, borrowed from statistics, and dating as far back as the late 20th and early 21st century, has undergone an evolution that we may not be completely aware of, if we do not follow or keep ourselves up to date with the most recent advances in statistical research. The present short communication can be framed as an opinion piece that simply aims to call our attention to the fact that statisticians, in recent years, have asked that we completely abandon the notion of “statistically significant (p < 0.05)”. It is important to point out that none of these observations are new, however certainly merit being re-addressed. Here I attempt to open a dialogue among archaeologists, palaeontologists, palaeoanthropologists, biological anthropologists, evolutionary biologists, and all researchers in related fields, about such statistical research. Finally, I propose a means of moving forward, suggesting we move from a world where p < 0.05 is considered a binary threshold for conclusive results, to a more nuanced practice where different gradients, down to p < 0.003, are interpreted as increasingly suggestive evidence – provided that findings are supported by additional, transparently reported corroborative data.

Genomic Architecture Underlying the Striking Colour Variation in the Presence of Gene Flow for the Guinan Toad-Headed Lizard.

How divergence occurs between closely related organisms in the absence of geographic barriers to gene flow stands as one of the long-standing questions in evolutionary biology. Previous studies suggested that the interplay between selection, gene flow and recombination strongly affected the process of divergence with gene flow. However, the extent to which these forces interact to drive divergence remains largely ambiguous. Guinan toad-headed lizards (Phrynocephalus guinanensis) in the Mugetan Desert exhibit striking colour differences from lizards outside the desert and provide an excellent model to address this question. Through extensive sampling and whole genome sequencing, we obtained genotypes for 191 samples from 14 populations inside and outside the desert. Despite the colour differences, continuous and asymmetric gene flow was detected across the desert border. More importantly, 273 highly diverged regions (HDRs) were identified between them, accounting only for 0.47% of the genome but widely distributed across 20 (out of the total 24) chromosomes. Strong signatures of selection were identified in HDRs, and local recombination rates were repressed. Furthermore, five HDRs exhibited significantly higher divergence, which contained key genes associated with crucial functions in animal coloration, including pteridine and melanocyte pigmentation. Genes related to retinal cells and steroid hormones were identified in other HDRs, which might have also contributed to the formation of colour variation in the presence of gene flow. This study provided novel insights into the understanding of the evolutionary mechanisms of genetic divergence in the presence of gene flow.

Phylogenetic Trees Defined by at Most Three Characters

In evolutionary biology, phylogenetic trees are commonly inferred from a set of characters (partitions) of a collection of biological entities (e.g., species or individuals in a population). Such characters naturally arise from molecular sequences or morphological data. Interestingly, it has been known for some time that any binary phylogenetic tree can be (convexly) defined by a set of at most four characters, and that there are binary phylogenetic trees for which three characters are not enough. Thus, it is of interest to characterise those phylogenetic trees that are defined by a set of at most three characters. In this paper, we provide such a characterisation, in particular proving that a binary phylogenetic tree $T$ is defined by a set of at most three dcharacters precisely if $T$ has no internal subtree isomorphic to a certain tree.

A conserved sequence that sparked the field of evo-devo

The discovery that homeotic genes in Drosophila are conserved and utilized for embryonic development throughout the animal kingdom, including humans, revolutionized the fields of developmental biology and evolutionary developmental biology (evo-devo). In a pair of back-to-back papers published in Cell in 1984, researchers at the Biozentrum in Basel, Switzerland, showed that the homeobox – previously identified as a sequence shared by homeotic genes in Drosophila – was also present in the genome of diverse animals. The first paper (McGinnis et al., 1984a) showed that genomes of both invertebrates and vertebrates contain sequences that cross-hybridized with Drosophila homeobox probes. The second paper (Carrasco et al., 1984) identified a cross-hybridizing sequence in the model system Xenopus laevis. They then isolated the first vertebrate homeobox-containing gene by cloning and sequencing of the corresponding genomic region. Finally, they showed that this gene (AC1, later renamed HoxC6) was expressed during embryonic development, the first evidence that developmentally expressed Drosophila genes could be used to isolate regulators of vertebrate embryonic development. These findings led to a flurry of activity in the evo-devo field, initially focused on isolating Hox genes across diverse species, and then expanding to isolation of other gene families based on Drosophila orthologs, an approach that continues today. This led to the notion of a conserved genetic toolkit for embryonic development, currently accepted, but unexpected at the time of its discovery. We attempt to provide some context for the sea-change in thinking that these discoveries brought about by referring to Jean Piaget's theories about the sequential acquisition of scientific knowledge.

Mechanism and simulation of intensive use of urban inefficient land based on evolutionary game theory

Intensive utilization of urban inefficient land is crucial for achieving sustainable urban development. This study constructs an evolutionary game model of urban inefficient land redevelopment involving three main actors: the government, developers, and the public. The model reveals the staged characteristics of the redevelopment process and the dynamic evolution of decision-making behaviors among the actors. The study finds that the redevelopment process can be divided into three stages: initial, development, and mature, with significant differences in the decision-making behaviors of developers, the government, and the public at each stage. Developers' decisions are influenced by redevelopment benefits and costs, the government's decisions are affected by regulatory benefits, and the public's decisions are impacted by participation benefits and costs. The initial strategy configuration has a significant influence on the system's evolutionary trend. Economic incentives, cost constraints, and public participation are the three pillars driving redevelopment. The study recommends adopting differentiated and dynamic policy combinations, improving the redevelopment benefit distribution mechanism, and strengthening public participation capacity building to promote positive interactions among the actors and achieve efficient land resource utilization. This research systematically analyzes the mechanism of inefficient land redevelopment from a dynamic game perspective, providing a scientific basis for policy formulation and holding great significance for promoting sustainable urban development.

Unraveling the dynamics of drug resistance: Insights from molecular epidemiology

Abstract. Drug-resistant bacterial strains pose significant challenges to public health worldwide. Molecular epidemiology studies employing cutting-edge techniques such as whole-genome sequencing and pulsed-field gel electrophoresis have shed light on the genetic diversity, transmission dynamics, and evolution of drug resistance mechanisms. This review explores the current state of knowledge in this field, highlighting key findings on genetic diversity, transmission dynamics within healthcare facilities and communities, and factors influencing resistance evolution. By elucidating the intricate interplay between genetic determinants, transmission pathways, and selective pressures, molecular epidemiology provides critical insights for guiding infection control measures and developing strategies to mitigate the spread of drug resistance. Embracing a One Health perspective and strengthening global surveillance efforts are essential for addressing the transboundary dissemination of drug-resistant pathogens and preserving antimicrobial efficacy.