Exploring the role of candidalysin in the pathogenicity of Candida albicans by gene set enrichment analysis and evolutionary dynamics.

AIMS: To explore the pathogenic mechanisms of Candida albicans (C. albicans), focusing on its impact on human health, particularly through invasive infections in the gastrointestinal and respiratory tracts. METHODS: In this study, we evaluated the demographic and clinical profiles of 7 pneumonia patients. Meanwhile, we used Gene Set Enrichment Analysis (GSEA) and Evolutionary Dynamics method to analyze the role of candidalysin in C. albicans pathogenicity. RESULTS: By analyzing genomic data and conducting biomedical text mining, we identified novel mutation sites in the candidalysin coding gene ECE1-III, shedding light into the genetic diversity within C. albicans strains and their potential implications for antifungal resistance. Our results revealed significant associations between C. albicans and respiratory as well as gastrointestinal diseases, emphasizing the fungus's role in the pathogenesis of these diseases. Additionally, we identified a new mutation site in the C. albicans strain YF2-5, isolated from patients with pneumonia. This mutation may be associated with its heightened pathogenicity. CONCLUSION: Our research advances the understanding of C. albicans pathogenicity and opens new avenues for developing targeted antifungal therapies. By focusing on the molecular basis of fungal virulence, we aim to contribute to the development of more effective treatment strategies, addressing the challenge of multidrug resistance in invasive fungal infections.

Genome-wide identification, and gene expression analysis of NBS-LRR domain containing R genes in Chenopodium quinoa for unveiling the dynamic contribution in plant immunity against Cercospora cf. chenopodii.

The plant R genes encode the NLR proteins comprising nucleotide-binding sites (NBS) and variable-length C-terminal leucine-rich repeat domains. The proteins act as intracellular immune receptors and recognize effector proteins of phytopathogens, which convene virulence. Among stresses, diseases contribute majorly to yield loss in crop plants, and R genes confer disease resistance against phytopathogens. We investigated the NLRome of Chenopodium quinoa for intraspecific diversity, characterization, and contribution to immune response regulation against phytopathogens. One eighty-three NBS proteins were identified and grouped into four distinct classes. Exon-intron organization displayed discrimination in gene structure patterns among NLR proteins. Thirty-eight NBS proteins revealed ontology with defense response, ADP binding, and inter alia cellular components. These proteins had shown functional homology with disease-resistance proteins involved in the plant-pathogen interaction pathway. Likewise, expression analysis demonstrated that NLRs encoding genes showed differential expression patterns. However, most genes displayed high expression levels in plant defense response with varying magnitude compared to ADP binding and cellular components. Twenty-four NBS genes were selected based on Heatmap analysis for quantitative polymerase chain reaction under Cercospora disease stress, and their progressive expression pattern provides insights into their functional role under stress conditions. The protein-protein interaction analysis revealed functional enrichment of NLR proteins in regulating hypersensitive, immune, and stress responses. This study, the first to identify and characterize NBS genes in C. quinoa, reveals their contribution to disease response and divulges their dynamic involvement in inducing plant immunity against phytopathogens. Supplementary Information: The online version contains supplementary material available at 10.1007/s12298-024-01475-0.

Genomic underpinnings of Cytoplasmic Incompatibility: CIF gene-neighborhood diversification through extensive lateral transfers and recombination in Wolbachia.

Cytoplasmic incompatibility (CI), a non-Mendelian genetic phenomenon, involves manipulation of host reproduction by Wolbachia, a maternally transmitted alphaproteobacterium. The underlying mechanism is centered around the CIF system governed by two genes, cifA and cifB, where cifB induces embryonic lethality, and cifA counteracts it. Recent investigations have unveiled intriguing facets of this system, including diverse cifB variants, prophage association in specific strains, copy-number variation, and rapid component divergence, hinting at a complex evolutionary history. We utilized comparative genomics to systematically classify CIF systems, analyze their locus structure and domain architectures, and reconstruct their diversification and evolutionary trajectories. Our new classification identifies ten distinct CIF types, featuring not just versions present in Wolbachia, but also other intracellular bacteria, and eukaryotic hosts. Significantly, our analysis of CIF loci reveals remarkable variability in gene composition and organization, encompassing an array of diverse endonucleases, variable toxin domains, deubiquitinating peptidases (DUBs), prophages, and transposons. We present compelling evidence that the components within the loci have been diversifying their sequences and domain architectures through extensive, independent lateral transfers and inter-locus recombination involving gene conversion. The association with diverse transposons and prophages, coupled with selective pressures from host immunity, likely underpins the emergence of CIF loci as recombination hotspots. Our investigation also posits the origin of CifB-REase domains from mobile elements akin to CR-effectors and Tribolium Medea1 factor, which is linked to another non-Mendelian genetic phenomenon. This comprehensive genomic analysis offers novel insights into the molecular evolution and genomic foundations of Wolbachia-mediated host reproductive control.

Salmon hatchery strays can demographically boost wild populations at the cost of diversity: quantitative genetic modelling of Alaska pink salmon.

Hatcheries are vital to many salmon fisheries, with inherent risks and rewards. While hatcheries can increase the returns of adult fish, the demographic and evolutionary consequences for natural populations interacting with hatchery fish on spawning grounds remain unclear. This study examined the impacts of stray hatchery-origin pink salmon on natural population productivity and resilience. We explored temporal assortative mating dynamics using a quantitative genetic model that assumed the only difference between hatchery- and natural-origin adults was their return timing to natural spawning grounds. This model was parameterized with empirical data from an intensive multi-generational study of hatchery-wild interactions in the world's largest pink salmon fisheries enhancement program located in Prince William Sound, Alaska. Across scenarios of increasing hatchery fish presence on spawning grounds, our findings underscore a trade-off between demographic enhancement and preservation of natural population diversity. While enhancement bolstered natural population sizes towards local carrying capacities, hatchery introgression reduced variation in adult return timing by up to 20%. Results indicated that hatchery-origin alleles can rapidly assimilate into natural populations, despite the reduced fitness of hatchery fish attributable to phenotypic mismatches. These findings elucidate the potential for long-term demographic and evolutionary consequences arising from specific hatchery-wild interactions, emphasizing the need for management strategies that balance demographic enhancement with the conservation of natural diversity.

'Drifting' Buchnera genomes track the microevolutionary trajectories of their aphid hosts.

Evolution of Buchnera-aphid host symbioses is often studied among species at macroevolutionary scales. Investigations within species offer a different perspective about how eco-evolutionary processes shape patterns of genetic variation at microevolutionary scales. Our study leverages new and publicly available whole-genome sequencing data to study Buchnera-aphid host evolution in Myzus persicae, the peach potato aphid, a globally invasive and polyphagous pest. Across 43 different asexual, clonally reproducing isofemale strains, we examined patterns of genomic covariation between Buchnera and their aphid host and considered the distribution of mutations in protein-coding regions of the Buchnera genome. We found Buchnera polymorphisms within aphid strains, suggesting the presence of genetically different Buchnera strains within the same clonal lineage. Genetic distance between pairs of Buchnera samples was positively correlated to genetic distance between their aphid hosts, indicating shared evolutionary histories. However, there was no segregation of genetic variation for both M. persicae and Buchnera with plant host (Brassicaceae and non-tobacco Solanaceae) and no associations between genetic and geographic distance at global or regional spatial scales. Abundance patterns of non-synonymous mutations were similar to synonymous mutations in the Buchnera genome, and both mutation classes had similar site frequency spectra. We hypothesize that a predominance of neutral processes results in the Buchnera of M. persicae to simply 'drift' with the evolutionary trajectory of their aphid hosts. Our study presents a unique microevolutionary characterization of Buchnera-aphid host genomic covariation across multiple aphid clones. This provides a new perspective on the eco-evolutionary processes generating and maintaining polymorphisms in a major pest aphid species and its obligate primary endosymbiont.

Evolution of reciprocity with limited payoff memory.

Direct reciprocity is a mechanism for the evolution of cooperation in repeated social interactions. According to the literature, individuals naturally learn to adopt conditionally cooperative strategies if they have multiple encounters with their partner. Corresponding models have greatly facilitated our understanding of cooperation, yet they often make strong assumptions on how individuals remember and process payoff information. For example, when strategies are updated through social learning, it is commonly assumed that individuals compare their average payoffs. This would require them to compute (or remember) their payoffs against everyone else in the population. To understand how more realistic constraints influence direct reciprocity, we consider the evolution of conditional behaviours when individuals learn based on more recent experiences. Even in the most extreme case that they only take into account their very last interaction, we find that cooperation can still evolve. However, such individuals adopt less generous strategies, and they cooperate less often than in the classical setup with average payoffs. Interestingly, once individuals remember the payoffs of two or three recent interactions, cooperation rates quickly approach the classical limit. These findings contribute to a literature that explores which kind of cognitive capabilities are required for reciprocal cooperation. While our results suggest that some rudimentary form of payoff memory is necessary, it suffices to remember a few interactions.

Evolutionary rescue in resistance to pesticides.

Evolutionary rescue occurs when the genetic evolution of adaptation saves a population from decline or extinction after environmental change. The evolution of resistance to pesticides is a special scenario of abrupt environmental change, where rescue occurs under (very) strong selection for one or a few de novo resistance mutations of large effect. Here, a population genetic model of evolutionary rescue with density-dependent population change is developed, with a focus on deriving results that are important to resistance management. Massive stochastic simulations are used to generate observations, which are accurately predicted using analytical approximations. Key results include the probability density function for the time to resistance and the probability of population extinction. The distribution of resistance times shows a lag period, a narrow peak and a long tail. Surprisingly, the mean time to resistance can increase with the strength of selection because, if a mutation does not occur early on, then its emergence is delayed by the pesticide reducing the population size. The probability of population extinction shows a sharp transition, in that when extinction is possible, it is also highly likely. Consequently, population suppression and (local) eradication can be theoretically achievable goals, as novel strategies to delay resistance evolution.

Heterologous survey of 130 DNA transposons in human cells highlights their functional divergence and expands the genome engineering toolbox.

Experimental studies on DNA transposable elements (TEs) have been limited in scale, leading to a lack of understanding of the factors influencing transposition activity, evolutionary dynamics, and application potential as genome engineering tools. We predicted 130 active DNA TEs from 102 metazoan genomes and evaluated their activity in human cells. We identified 40 active (integration-competent) TEs, surpassing the cumulative number (20) of TEs found previously. With this unified comparative data, we found that the Tc1/mariner superfamily exhibits elevated activity, potentially explaining their pervasive horizontal transfers. Further functional characterization of TEs revealed additional divergence in features such as insertion bias. Remarkably, in CAR-T therapy for hematological and solid tumors, Mariner2_AG (MAG), the most active DNA TE identified, largely outperformed two widely used vectors, the lentiviral vector and the TE-based vector SB100X. Overall, this study highlights the varied transposition features and evolutionary dynamics of DNA TEs and increases the TE toolbox diversity.

Stability, resilience and eco-evolutionary feedbacks of mutualistic networks to rising temperature.

Ecological networks comprising of mutualistic interactions can suddenly transition to undesirable states, such as collapse, due to small changes in environmental conditions such as a rise in local environmental temperature. However, little is known about the capacity of such interaction networks to adapt to a rise in temperature and the occurrence of critical transitions. Here, combining quantitative genetics and mutualistic dynamics in an eco-evolutionary framework, we evaluated the stability and resilience of mutualistic networks to critical transitions as environmental temperature increases. Specifically, we modelled the dynamics of an optimum trait that determined the tolerance of species to local environmental temperature as well as to species interaction. We then evaluated the impact of individual trait variation and evolutionary dynamics on the stability of feasible equilibria, the occurrence of threshold temperatures at which community collapses, and the abruptness of such community collapses. We found that mutualistic network architecture, that is the size of the community and the arrangement of species interactions, interacted with evolutionary dynamics to impact the onset of network collapses. Some networks had more capacity to track the rise in temperatures than others and thereby increased the threshold temperature at which the networks collapsed. However, such a result was modulated by the amount of heritable trait variation species exhibited, with high trait variation in the mean optimum phenotypic trait increasing the environmental temperature at which networks collapsed. Furthermore, trait variation not only increased the onset of temperatures at which networks collapsed but also increased the local stability of feasible equilibria. Our study argued that mutualistic network architecture interacts with species evolutionary dynamics and increases the capacity of networks to adapt to changes in temperature and thereby delayed the occurrence of community collapses.

Evolutionary and Phylogenetic Dynamics of SARS-CoV-2 Variants: A Genetic Comparative Study of Taiyuan and Wuhan Cities of China.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a positive-sense, single-stranded RNA genome-containing virus which has infected millions of people all over the world. The virus has been mutating rapidly enough, resulting in the emergence of new variants and sub-variants which have reportedly been spread from Wuhan city in China, the epicenter of the virus, to the rest of China and all over the world. The occurrence of mutations in the viral genome, especially in the viral spike protein region, has resulted in the evolution of multiple variants and sub-variants which gives the virus the benefit of host immune evasion and thus renders modern-day vaccines and therapeutics ineffective. Therefore, there is a continuous need to study the genetic characteristics and evolutionary dynamics of the SARS-CoV-2 variants. Hence, in this study, a total of 832 complete genomes of SARS-CoV-2 variants from the cities of Taiyuan and Wuhan in China was genetically characterized and their phylogenetic and evolutionary dynamics studied using phylogenetics, genetic similarity, and phylogenetic network analyses. This study shows that the four most prevalent lineages in Taiyuan and Wuhan are as follows: the Omicron lineages EG.5.1.1, followed by HK.3, FY.3, and XBB.1.16 (Pangolin classification), and clades 23F (EG.5.1), followed by 23H (HK.3), 22F (XBB), and 23D (XBB.1.9) (Nextclade classification), and lineage B followed by the Omicron FY.3, lineage A, and Omicron FL.2.3 (Pangolin classification), and the clades 19A, followed by 22F (XBB), 23F (EG.5.1), and 23H (HK.3) (Nextclade classification), respectively. Furthermore, our genetic similarity analysis show that the SARS-CoV-2 clade 19A-B.4 from Wuhan (name starting with 412981) has the least genetic similarity of about 95.5% in the spike region of the genome as compared to the query sequence of Omicron XBB.2.3.2 from Taiyuan (name starting with 18495234), followed by the Omicron FR.1.4 from Taiyuan (name starting with 18495199) with ~97.2% similarity and Omicron DY.3 (name starting with 17485740) with ~97.9% similarity. The rest of the variants showed ≥98% similarity with the query sequence of Omicron XBB.2.3.2 from Taiyuan (name starting with 18495234). In addition, our recombination analysis results show that the SARS-CoV-2 variants have three statistically significant recombinant events which could have possibly resulted in the emergence of Omicron XBB.1.16 (recombination event 3), FY.3 (recombination event 5), and FL.2.4 (recombination event 7), suggesting some very important information regarding viral evolution. Also, our phylogenetic tree and network analyses show that there are a total of 14 clusters and more than 10,000 mutations which may have probably resulted in the emergence of cluster-I, followed by 47 mutations resulting in the emergence of cluster-II and so on. The clustering of the viral variants of both cities reveals significant information regarding the phylodynamics of the virus among them. The results of our temporal phylogenetic analysis suggest that the variants of Taiyuan have likely emerged as independent variants separate from the variants of Wuhan. This study, to the best of our knowledge, is the first ever genetic comparative study between Taiyuan and Wuhan cities in China. This study will help us better understand the virus and cope with the emergence and spread of new variants at a local as well as an international level, and keep the public health authorities informed for them to make better decisions in designing new viral vaccines and therapeutics. It will also help the outbreak investigators to better examine any future outbreak.

Improved prediction of site-rates from structure with averaging across homologs.

Variation in mutation rates at sites in proteins can largely be understood by the constraint that proteins must fold into stable structures. Models that calculate site-specific rates based on protein structure and a thermodynamic stability model have shown a significant but modest ability to predict empirical site-specific rates calculated from sequence. Models that use detailed atomistic models of protein energetics do not outperform simpler approaches using packing density. We demonstrate that a fundamental reason for this is that empirical site-specific rates are the result of the average effect of many different microenvironments in a phylogeny. By analyzing the results of evolutionary dynamics simulations, we show how averaging site-specific rates across many extant protein structures can lead to correct recovery of site-rate prediction. This result is also demonstrated in natural protein sequences and experimental structures. Using predicted structures, we demonstrate that atomistic models can improve upon contact density metrics in predicting site-specific rates from a structure. The results give fundamental insights into the factors governing the distribution of site-specific rates in protein families.

Genetic divergence and one-way gene flow influence contemporary evolution and ecology of a partially migratory fish.

Recent work has revealed the importance of contemporary evolution in shaping ecological outcomes. In particular, rapid evolutionary divergence between populations has been shown to impact the ecology of populations, communities, and ecosystems. While studies have focused largely on the role of adaptive divergence in generating ecologically important variation among populations, much less is known about the role of gene flow in shaping ecological outcomes. After divergence, populations may continue to interact through gene flow, which may influence evolutionary and ecological processes. Here, we investigate the role of gene flow in shaping the contemporary evolution and ecology of recently diverged populations of anadromous steelhead and resident rainbow trout (Oncorhynchus mykiss). Results show that resident rainbow trout introduced above waterfalls have diverged evolutionarily from downstream anadromous steelhead, which were the source of introductions. However, the movement of fish from above to below the waterfalls has facilitated gene flow, which has reshaped genetic and phenotypic variation in the anadromous source population. In particular, gene flow has led to an increased frequency of residency, which in turn has altered population density, size structure, and sex ratio. This result establishes gene flow as a contemporary evolutionary process that can have important ecological outcomes. From a management perspective, anadromous steelhead are generally regarded as a higher conservation priority than resident rainbow trout, even when found within the same watershed. Our results show that anadromous and resident O. mykiss populations may be connected via gene flow, with important ecological consequences. Such eco-evolutionary processes should be considered when managing recently diverged populations connected by gene flow.

Species interactions and eco-evolutionary dynamics of dispersal: the diversity dependence of dispersal.

Dispersal plays a pivotal role in the eco-evolutionary dynamics of spatially structured populations, communities and ecosystems. As an individual-based trait, dispersal is subject to both plasticity and evolution. Its dependence on conditions and context is well understood within single-species metapopulations. However, species do not exist in isolation; they interact locally through various horizontal and vertical interactions. While the significance of species interactions is recognized for species coexistence and food web functioning, our understanding of their influence on regional dynamics, such as their impact on spatial dynamics in metacommunities and meta-food webs, remains limited. Building upon insights from behavioural and community ecology, we aim to elucidate biodiversity as both a driver and an outcome of connectivity. By synthesizing conceptual, theoretical and empirical contributions from global experts in the field, we seek to explore how a more mechanistic understanding of diversity-dispersal relationships influences the distribution of species in spatially and temporally changing environments. Our findings highlight the importance of explicitly considering interspecific interactions as drivers of dispersal, thus reshaping our understanding of fundamental dynamics including species coexistence and the emergent dynamics of metacommunities and meta-ecosystems. We envision that this initiative will pave the way for advanced forecasting approaches to understanding biodiversity dynamics under the pressures of global change. This article is part of the theme issue 'Diversity-dependence of dispersal: interspecific interactions determine spatial dynamics'.

Online toolkits for collaborative and inclusive global research in urban evolutionary ecology.

Urban evolutionary ecology is inherently interdisciplinary. Moreover, it is a field with global significance. However, bringing researchers and resources together across fields and countries is challenging. Therefore, an online collaborative research hub, where common methods and best practices are shared among scientists from diverse geographic, ethnic, and career backgrounds would make research focused on urban evolutionary ecology more inclusive. Here, we describe a freely available online research hub for toolkits that facilitate global research in urban evolutionary ecology. We provide rationales and descriptions of toolkits for: (1) decolonizing urban evolutionary ecology; (2) identifying and fostering international collaborative partnerships; (3) common methods and freely-available datasets for trait mapping across cities; (4) common methods and freely-available datasets for cross-city evolutionary ecology experiments; and (5) best practices and freely available resources for public outreach and communication of research findings in urban evolutionary ecology. We outline how the toolkits can be accessed, archived, and modified over time in order to sustain long-term global research that will advance our understanding of urban evolutionary ecology.

High Diversity of Long Terminal Repeat Retrotransposons in Compact Vertebrate Genomes: Insights from Genomes of Tetraodontiformes.

This study aimed to investigate the evolutionary profile (including diversity, activity, and abundance) of retrotransposons (RTNs) with long terminal repeats (LTRs) in ten species of Tetraodontiformes. These species, Arothron firmamentum, Lagocephalus sceleratus, Pao palembangensis, Takifugu bimaculatus, Takifugu flavidus, Takifugu ocellatus, Takifugu rubripes, Tetraodon nigroviridis, Mola mola, and Thamnaconus septentrionalis, are known for having the smallest genomes among vertebrates. Data mining revealed a high diversity and wide distribution of LTR retrotransposons (LTR-RTNs) in these compact vertebrate genomes, with varying abundances among species. A total of 819 full-length LTR-RTN sequences were identified across these genomes, categorized into nine families belonging to four different superfamilies: ERV (Orthoretrovirinae and Epsilon retrovirus), Copia, BEL-PAO, and Gypsy (Gmr, Mag, V-clade, CsRN1, and Barthez). The Gypsy superfamily exhibited the highest diversity. LTR family distribution varied among species, with Takifugu bimaculatus, Takifugu flavidus, Takifugu ocellatus, and Takifugu rubripes having the highest richness of LTR families and sequences. Additionally, evidence of recent invasions was observed in specific tetraodontiform genomes, suggesting potential transposition activity. This study provides insights into the evolution of LTR retrotransposons in Tetraodontiformes, enhancing our understanding of their impact on the structure and evolution of host genomes.

Adaptive colonization across a parasitism-mutualism gradient.

Adaptive colonization is a process wherein a colonizing population exhibits an adaptive change in response to a novel environment, which may be critical to its establishment. To date, theoretical models of adaptive colonization have been based on single-species introductions. However, given their pervasiveness, symbionts will frequently be co-introduced with their hosts to novel areas. We present an individual-based model to investigate adaptive colonization by hosts and their symbionts across a parasite-mutualist continuum. The host must adapt in order to establish itself in the novel habitat, and the symbiont must adapt to track evolutionary change in the host. First, we classify the qualitative shifts in the outcome that can potentially be driven by non-neutral effects of the symbiont-host interaction into three main types: parasite-driven co-extinction, parasite release, and mutualistic facilitation. Second, we provide a detailed description of a specific example for each type of shift. Third, we disentangle how the interplay between symbiont transmissibility, host migration, and selection strength determines: (a) which type of shift is more likely to occur and (b) the size of the interaction effects necessary to produce it. Overall, we demonstrate the crucial role of host and symbiont dispersal scales in shaping the impacts of parasitism and mutualism on adaptive colonization.

Dispersal evolution and eco-evolutionary dynamics in antagonistic species interactions.

Dispersal evolution modifies diverse spatial processes, such as range expansions or biological invasions of single species, but we are currently lacking a realistic vision for metacommunities. Focusing on antagonistic species interactions, we review existing theory of dispersal evolution between natural enemies, and explain how this might be relevant for classic themes in host-parasite evolutionary ecology, namely virulence evolution or local adaptation. Specifically, we highlight the importance of considering the simultaneous (co)evolution of dispersal and interaction traits. Linking such multi-trait evolution with reciprocal demographic and epidemiological feedbacks might change basic predictions about coevolutionary processes and spatial dynamics of interacting species. Future challenges concern the integration of system-specific disease ecology or spatial modifiers, such as spatial network structure or environmental heterogeneity.

A Procedure for Testing for Tokyo Type 1 Open-Ended Evolution.

Tokyo Type 1 open-ended evolution (OEE) is a category of OEE that includes systems exhibiting the ongoing generation of adaptive novelty and ongoing growth in complexity. It can be considered as a necessary foundation for Tokyo Type 2 OEE (ongoing evolution of evolvability) and Tokyo Type 3 OEE (ongoing generation of major transitions). This article brings together five methods of analysis to form a procedure for testing for Tokyo Type 1 OEE. The procedure is presented as simply as possible, isolated from the complexities of any particular evolutionary system, and with a clear rationale for each step. In developing these steps, we also identify five key challenges in OEE. The last of these (achieving a higher order of complexity growth within a system exhibiting indefinitely scalable complexity) can be considered a grand challenge for Tokyo Type 1 OEE. Promising approaches to this grand challenge include also achieving one or both of Tokyo Types 2 and 3 OEE; this can be seen as one answer to why these other types of OEE are important, providing a unified view of OEE.

Nonlinear social evolution and the emergence of collective action.

Organisms from microbes to humans engage in a variety of social behaviors, which affect fitness in complex, often nonlinear ways. The question of how these behaviors evolve has consequences ranging from antibiotic resistance to human origins. However, evolution with nonlinear social interactions is challenging to model mathematically, especially in combination with spatial, group, and/or kin assortment. We derive a mathematical condition for natural selection with synergistic interactions among any number of individuals. This result applies to populations with arbitrary (but fixed) spatial or network structure, group subdivision, and/or mating patterns. In this condition, nonlinear fitness effects are ascribed to collectives, and weighted by a new measure of collective relatedness. For weak selection, this condition can be systematically evaluated by computing branch lengths of ancestral trees. We apply this condition to pairwise games between diploid relatives, and to dilemmas of collective help or harm among siblings and on spatial networks. Our work provides a rigorous basis for extending the notion of "actor", in the study of social evolution, from individuals to collectives.

Accumulation Dynamics of Defective Genomes during Experimental Evolution of Two Betacoronaviruses.

Virus-encoded replicases often generate aberrant RNA genomes, known as defective viral genomes (DVGs). When co-infected with a helper virus providing necessary proteins, DVGs can multiply and spread. While DVGs depend on the helper virus for propagation, they can in some cases disrupt infectious virus replication, impact immune responses, and affect viral persistence or evolution. Understanding the dynamics of DVGs alongside standard viral genomes during infection remains unclear. To address this, we conducted a long-term experimental evolution of two betacoronaviruses, the human coronavirus OC43 (HCoV-OC43) and the murine hepatitis virus (MHV), in cell culture at both high and low multiplicities of infection (MOI). We then performed RNA-seq at regular time intervals, reconstructed DVGs, and analyzed their accumulation dynamics. Our findings indicate that DVGs evolved to exhibit greater diversity and abundance, with deletions and insertions being the most common types. Notably, some high MOI deletions showed very limited temporary existence, while others became prevalent over time. We observed differences in DVG abundance between high and low MOI conditions in HCoV-OC43 samples. The size distribution of HCoV-OC43 genomes with deletions differed between high and low MOI passages. In low MOI lineages, short and long DVGs were the most common, with an additional cluster in high MOI lineages which became more prevalent along evolutionary time. MHV also showed variations in DVG size distribution at different MOI conditions, though they were less pronounced compared to HCoV-OC43, suggesting a more random distribution of DVG sizes. We identified hotspot regions for deletions that evolved at a high MOI, primarily within cistrons encoding structural and accessory proteins. In conclusion, our study illustrates the widespread formation of DVGs during betacoronavirus evolution, influenced by MOI and cell- and virus-specific factors.