Cryptic female choice - female-mediated bias in fertilization after mating - is well established in animals and can also occur in plants when multiple pollens compete on the same pistil. However, whether interactions between pollen and pistil tissues after pollen deposition contribute to this process remains unknown. Here, we experimentally test whether such interactions mediate cryptic female choice in the angiosperm Brassica rapa. We quantified fertilization success of pollen donors competing on the same pistil using paternity analyses, and in parallel, made semi-in vivo assays to measure pollen tubes trajectories emerging from the excised styles and growing toward unfertilized ovules for each donor-recipient pair. We show that pollen tube growth towards ovules predicts higher fertilization success under pollen competition. Thus, we document a previously unobserved mechanism of cryptic female choice based on physical interactions between male and female components of reproduction. In addition, different recipient plants favour different pollen donors, consistent with non-directional female choice. Plants with longer styles bias paternities more strongly towards the most successful pollen donor. Overall, our study demonstrates that interactions between pollen tubes and pistil tissues after pollen germination enable plants to bias paternity toward particular donors.

Simulation-based methods such as approximate Bayesian computation (ABC) are widely used to infer the evolutionary history of populations from molecular genetic data. We describe and evaluate a new iterative method of statistical inference about model parameters, which revisits the idea of inferring a likelihood surface using simulation when the likelihood function cannot be evaluated. It is based on combining the random forest machine learning method, and multivariate Gaussian mixture (MGM) models, in an effective inference workflow, here used to fit models with up to 15 variable parameters. In addition to the traditional assessment of precision in terms of bias and mean square error, we also evaluate the coverage of confidence intervals. The method is compared with approximate Bayesian computation using random forests (ABC-RF), a non-iterative method sharing some technical features with the proposed approach, across scenarios of historical demographic inference from population genetic data. It is also compared to another iterative method, sequential neural likelihood estimation (SNLE). These comparisons highlight the importance of an iterative workflow for exploring the parameter space efficiently. For equivalent simulation effort of the data-generating process, the new summary-likelihood method provides intervals whose coverage is better controlled than the marginal coverage of intervals provided by ABC with random forests, and than generally reported for ABC methods. The iterative workflow can also yield greater improvements in estimator precision when larger datasets are used.

Sexual selection is a cornerstone of evolutionary biology potentially operating in all sexually-reproducing organisms. Modern developments in the field revealed that this selective force extends beyond Darwin’s initial focus on access to mates in terms of competition for access to gametes of the other sex. Despite its presumed universality, sexual selection theory remains largely untested in plants compared to animals. This gap may partly stem from challenges in quantifying sexual selection using approaches that account for a critical plant-specific factor: the reliance on pollinators as third-party agents for accessing mates. Here, we quantified sexual selection along consecutive episodes of selection in the hermaphroditic plant Brassica rapa by integrating the monitoring of pollinator movements with genetic paternity analyses in experimental populations. Our approach identifies pollen competition for ovules as the primary arena for sexual selection in B. rapa. Darwinian competition for access to mates constitutes a secondary force, and was stronger in the male compared to the female sex function, as predicted by classic theory. Importantly, experimentally induced variation in pollinator abundance modulated the balance between pre- and post-pollination sexual selection. Under reduced pollinator abundance, the opportunity for selection on mate acquisition increased. Crucially, we demonstrate that ignoring pollinator movements among plants leads to erroneous quantification of pre-pollination sexual selection. We argue that a unifying theory of sexual selection requires a more comprehensive quantification of pre- and post-pollination episodes of selection, taking into account the specificities of gamete transfer in plants. ### Competing Interest Statement The authors have declared no competing interest.

Introgression, the incorporation of foreign variants through hybridization and repeated backcross, is increasingly being studied for its potential evolutionary consequences, one of which is adaptive introgression (AI). In recent years, several statistical methods have been proposed for the detection of loci that have undergone adaptive introgression. Most of these methods have been tested and developed to infer the presence of Neanderthal or Denisovan AI in humans. Currently, the behaviour of these methods when faced with genomic datasets from evolutionary scenarios other than the human lineage remains unknown. This study therefore focuses on testing the performance of the methods using test data sets simulated under various evolutionary scenarios inspired by the evolutionary history of human, wall lizard (Podarcis) and bear (Ursus) lineages. These lineages were chosen to represent different combinations of divergence and migration times. We study the impact of these parameters, as well as migration rate, population size, selection coefficient and presence of recombination hotspots, on the performance of three methods (VolcanoFinder, Genomatnn and MaLAdapt) and a standalone summary statistic (Q95(w, y)). Furthermore, the hitchhiking effect of an adaptively introgressed mutation can have a strong impact on the flanking regions, and therefore on the discrimination between the genomic windows classes (i.e. AI/non-AI). For this reason, three different types of non-AI windows are taken into account in our analyses: independently simulated neutral introgression windows, windows adjacent to the window under AI, and windows coming from a second neutral chromosome unlinked to the chromosome under AI. Our results highlight the importance of taking into account adjacent windows in the training data in order to correctly identify the window with the mutation under AI. Finally, our tests show that methods based on Q95 seem to be the most efficient for an exploratory study of AI.

AbstractGenomic conflicts arise when different genes in a genome are selected for opposite phenotypic effects. One well-known conflict occurs in plants, between mitochondrial genes causing cytoplasmic male sterility (CMS) and their nuclear suppressors, called restorers of male fertility. The evolution of CMS-restorer polymorphisms has been modeled many times, but empirical validations remain indirect. Here we use a new biological model, a freshwater snail, to directly observe evolutionary trajectories. In this species, CMS-associated mitogenomes coexist with male-fertile ones in populations. Models predict such a coexistence when nuclear restorers make CMS mitogenomes less fit than male-fertile ones, thus preventing the fixation of CMS. During 11 generations of experimental evolution, we observed rapid decreases in the frequency of CMS mitogenomes in a restorer-rich nuclear background, with an estimated ∼20% fitness disadvantage, consistent with theoretical conditions for the maintenance of cytonuclear polymorphism. In parallel, in an ancillary experiment, eggs laid by isolated snails carrying CMS showed a reduced hatching rate. Although significant, this reduction did not reach 20%, suggesting that fitness differentials in populations are enhanced by competition or rely on unmeasured traits. Our study illustrates the speed at which evolution can proceed in the context of cytonuclear conflicts over sex allocation.

AbstractMaternal investment influences the survival and reproduction of both mothers and their progeny and plays a crucial role in understanding individuals’ life-history and population ecology. To reveal the complex mechanisms associated with reproduction and investment, it is necessary to examine variations in maternal investment across species. Comparisons across species call for a standardised method to quantify maternal investment, which remained to be developed. This paper addresses this limitation by introducing the maternal investment metric – MI – for mammalian species, established through the allometric scaling of the litter mass at weaning age by the adult mass and investment duration (i.e. gestation + lactation duration) of a species. Using a database encompassing hundreds of mammalian species, we show that the metric is not highly sensitive to the regression method used to fit the allometric relationship or to the proxy used for adult body mass. The comparison of the maternal investment metric between mammalian subclasses and orders reveals strong differences across taxa. For example, our metric confirms that Eutheria have a higher maternal investment than Metatheria. We discuss how further research could use the maternal investment metric as a valuable tool to understand variation in reproductive strategies.

Integrons are adaptive bacterial devices that rearrange promoter-less gene cassettes into variable ordered arrays under stress conditions, thereby sampling combinatorial phenotypic diversity. Chromosomal integrons often carry hundreds of silent gene cassettes, with integrase-mediated recombination leading to rampant DNA excision and integration, posing a potential threat to genome integrity. How this activity is regulated and controlled, particularly through selective pressures, to maintain such large cassette arrays is unknown. Here, we show a key role of promoter-containing toxin-antitoxin (TA) cassettes as systems that kill the cell when the overall cassette excision rate is too high. These results highlight the importance of TA cassettes regulating the cassette recombination dynamics and provide insight into the evolution and success of integrons in bacterial genomes.

We describe and evaluate a method of statistical inference of model parameters, which revisits the idea of inferring a likelihood surface using simulation when the likelihood function cannot be evaluated. The method aims in particular to provide confidence intervals with controlled coverage, and its performance is assessed accordingly. It is based on a combining the random forest machine-learning method, and multivariate Gaussian mixture (MGM) models, in an effective inference workflow, here used to fit models with up to 15 variable parameters. Masked autoregressive flows, a deep learning technique, is also tested as an alternative do MGM models. The method is compared to that of approximate Bayesian computation (ABC) with random forests, with which it shares some technical features, on scenarios of inference of historical demography from population genetic data. These comparisons highlight the importance of an iterative workflow for exploring the parameter space efficiently. For equivalent simulation effort of the data-generating process, the new summary-likelihood method provides better control of coverage than ABC with random forests, and than generally reported for ABC methods. ### Competing Interest Statement The authors have declared no competing interest.

To decarbonize the heating sector, the 4th and 5th generations of district heating networks have been identified as promising solutions. They offer superior energy efficiency, economic viability, and environmental advantages compared to decentralized, individual heating systems. However, they raise several challenges concerning their design and control optimization due to their size and the operational constraints of the production systems involved such as inertial heat generators, intermittent renewable energy sources and thermal storage. As a result, numerical simulations of these networks are computationally heavy which makes optimal control a complex and challenging task. A common strategy to address this limitation is to formulate reduced order models or to establish fast and yet accurate surrogate models. In this work, we present surrogate modeling framework to rapidly predict district heating networks transients. Our model is on a physics-guided spatio-temporal convolutional graph neural network. While similar work focused on the prediction of thermal loads, this paper tackles the challenge of simulating complex and non-linear behaviors of the distribution network of district heating systems. The results show that the simulation using our model is 99% less than a physical simulator while maintaining a high accuracy. In addition, we conducted an ablation study and a residual analysis to test the robustness of the proposed model. Furthermore, the generalization ability of our approach is assessed by evaluating it against different district heating network topologies.

During viral infection, cells can deploy immune strategies that deprive viruses of molecules essential for their replication. Here, we report a family of immune effectors in bacteria that, upon phage infection, degrade cellular adenosine triphosphate (ATP) and deoxyadenosine triphosphate (dATP) by cleaving the N-glycosidic bond between the adenine and sugar moieties. These ATP nucleosidase effectors are widely distributed within multiple bacterial defense systems, including cyclic oligonucleotide-based antiviral signaling systems (CBASS), prokaryotic argonautes, and nucleotide-binding leucine-rich repeat (NLR)-like proteins, and we show that ATP and dATP degradation during infection halts phage propagation. By analyzing homologs of the immune ATP nucleosidase domain, we discover and characterize Detocs, a family of bacterial defense systems with a two-component phosphotransfer-signaling architecture. The immune ATP nucleosidase domain is also encoded within diverse eukaryotic proteins with immune-like architectures, and we show biochemically that eukaryotic homologs preserve the ATP nucleosidase activity. Our findings suggest that ATP and dATP degradation is a cell-autonomous innate immune strategy conserved across the tree of life.

Pathogens have fueled the diversification of intracellular defense strategies that collectively define cell-autonomous innate immunity. In bacteria, innate immunity is manifested by a broad arsenal of defense systems that provide protection against bacterial viruses, called phages. The complexity of the bacterial immune repertoire has only been realized recently and is now suggesting that innate immunity has commonalities across the tree of life: many components of eukaryotic innate immunity are found in bacteria where they protect against phages, including the cGAS-STING pathway, gasdermins, and viperins. Here, I summarize recent findings on the conservation of innate immune pathways between prokaryotes and eukaryotes and hypothesize that bacterial defense mechanisms can catalyze the discovery of novel molecular players of eukaryotic innate immunity.

: District heating networks have proven their higher conversion efficiency, economic viability and environmental benefits when compared to decentralized and individual heating systems. These benefits are achieved through the ability to incorporate a wide variety of production means, including renewable intermittent sources but also via the use of short-term and/or inter-seasonal storage. Due to the numerous interactions between these components, their different dynamic aspects and operating constraints, physical simulations are computationally heavy so that running optimization tasks become pro-hibitively expensive and time consuming. Therefore, new control optimization schemes need to be drawn up to accelerate the predictive control and to facilitate the decision-making process. In the present work, we assess the application of geometric deep learning as a surrogate modeling framework for district heating simulations. Beyond processing non-Euclidian data, this deep learning approach aims to encode geometric and topological understandings of data as inductive biases in deep learning models. More precisely we trained Graph Neural Networks to emulate a thermo-hydraulic simulator of district heating network. This statistical inference method allows us to drastically reduce simulation time, hence unlocking further optimization loops and parametric space exploration. In addition, their permutation equivariance and stability to perturbations are assessed to discuss their scalability to more complex network topologies and control schemes.

Bacteria employ a complex arsenal of immune mechanisms to defend themselves against phages. Recent studies demonstrate that these immune mechanisms frequently involve regulated cell death in response to phage infection. By sacrificing infected cells, this strategy prevents the spread of phages within the surrounding population. In this review, we discuss the principles of regulated cell death in bacterial defense, and show that over 70% of sequenced prokaryotes employ this strategy as part of their defensive arsenals. We highlight the modularity of defense systems involving regulated cell death, explaining how shuffling between phage-sensing and cell-killing protein domains dominates their evolution. Some of these defense systems are the evolutionary ancestors of key components of eukaryotic immunity, highlighting their importance in shaping the evolutionary trajectory of immune systems across the tree of life.

The 2020 global spatial targets for protected areas set by the Convention on Biological Diversity have almost been achieved, but management effectiveness remains deficient. Personnel shortages are widely cited as major contributing factors but have not previously been quantified. Using data from 176 countries and territories, we estimate a current maximum of 555,000 terrestrial protected area personnel worldwide (one per 37 km 2 ), including 286,000 rangers (one per 72 km 2 ), far short of published guidance on required densities. Expansion by 2030 to 30% coverage of protected areas and other effective area-based conservation measures is widely agreed as a minimum for safeguarding biodiversity and ecosystem services. We project that effective management of this expanded system will require approximately 3 million personnel (one per 13 km 2 ), including more than 1.5 million rangers or equivalents (one per 26 km 2 ). Parallel improvements in resourcing, working conditions and capacity are required for effective, equitable and sustainable management.

Historically, mothers producing twins gave birth, on average, more often than non-twinners. This observation has been interpreted as twinners having higher intrinsic fertility - a tendency to conceive easily irrespective of age and other factors - which has shaped both hypotheses about why twinning persists and varies across populations, and the design of medical studies on female fertility. Here we show in >20k pre-industrial European mothers that this interpretation results from an ecological fallacy: twinners had more births not due to higher intrinsic fertility, but because mothers that gave birth more accumulated more opportunities to produce twins. Controlling for variation in the exposure to the risk of twinning reveals that mothers with higher twinning propensity - a physiological predisposition to producing twins - had fewer births, and when twin mortality was high, fewer offspring reaching adulthood. Twinning rates may thus be driven by variation in its mortality costs, rather than variation in intrinsic fertility.

Behavioral discrimination of kin is a key process structuring social relationships in animals. In this study, we provide a first example of discrimination towards non-kin by third-parties through a mechanism of phenotype matching. In mandrills, we recently demonstrated increased facial resemblance among paternally-related juvenile and adult females indicating adaptive opportunities for paternal kin recognition. Here, we hypothesize that mothers use offspring’s facial resemblance with other infants to guide offspring’s social opportunities towards similarly-looking ones. Using deep learning for face recognition in 80 wild mandrill infants, we first show that infants born to the same father or conceived during the tenure of the same alpha male resemble each other the most, independently of their age, sex or maternal origin, extending previous results to the youngest age class. Using long-term behavioral observations on association patterns and controlling for matrilineal origin, maternal relatedness and infant age and sex, we then demonstrate that, as hypothesized, mothers are spatially closer to infants that resemble their own offspring more, thereby facilitating associations among similar-looking infants. Using theoretical modeling, we describe a plausible evolutionary process whereby mothers gain fitness benefits by promoting nepotism among paternally related infants. This mechanism, that we call “second-order kin selection”, may extend beyond mother-infant interactions and has the potential to explain cooperative behaviors among non-kin in social species, including humans.

Behavioral discrimination of kin is a key process structuring social relationships in animals. In this study, we provide evidence for discrimination towards non-kin by third-parties through a mechanism of phenotype matching. In mandrills, we recently demonstrated increased facial resemblance among paternally related juvenile and adult females indicating adaptive opportunities for paternal kin recognition. Here, we hypothesize that mandrill mothers use offspring's facial resemblance with other infants to guide offspring's social opportunities towards similar-looking ones. Using deep learning for face recognition in 80 wild mandrill infants, we first show that infants sired by the same father resemble each other the most, independently of their age, sex or maternal origin, extending previous results to the youngest age class. Using long-term behavioral observations on association patterns, and controlling for matrilineal origin, maternal relatedness and infant age and sex, we then show, as predicted, that mothers are spatially closer to infants that resemble their own offspring more, and that this maternal behavior leads to similar-looking infants being spatially associated. We then discuss the different scenarios explaining this result, arguing that an adaptive maternal behavior is a likely explanation. In support of this mechanism and using theoretical modeling, we finally describe a plausible evolutionary process whereby mothers gain fitness benefits by promoting nepotism among paternally related infants. This mechanism, that we call 'second-order kin selection', may extend beyond mother-infant interactions and has the potential to explain cooperative behaviors among non-kin in other social species, including humans.

The black truffle Tuber melanosporum was disseminated all over the world, propelled by the development of a wide variety of empirical practices. A widespread practice, called 'truffle trap', consists of placing pieces of truffles into excavations dug under host trees, and of collecting truffle in these traps in the next years. This research aims at (1) evaluating the effect of this practice on fruitbody production based on the analysis of 9924 truffle traps installed in 11 orchards across T. melanosporum native area in France and (2) exploring the mechanisms involved in fruitbody emergence using traps where the genotypes of introduced truffles were compared with those of fruitbodies collected in the same traps. We confirmed that truffle traps provide a major and highly variable part of truffle ground production, representing up to 89% of the collected fruitbodies. We evidenced a genetic link between introduced spores and collected fruitbodies, and then demonstrated that truffle growers provide paternal partners for mating with local maternal mycelia. We also highlighted that soil disturbance stimulate the vegetative development of established maternal mycelia. This research supports that a widely used traditional practice enhances fruitbody production by shaping favorable conditions and providing sexual partners required for fruiting.