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Learning is a widespread ability among animals and, like physical traits, is subject to evolution. But how did learning first arise? What selection pressures and phenotypic preconditions fostered its evolution? Neither the fossil record nor phylogenetic comparative studies provide answers to these questions. Here, we take a novel approach by studying digital organisms in environments that promote the evolution of navigation and associative learning. Starting with a non-learning, sessile ancestor, we evolve multiple populations in four different environments, each consisting of nutrient trails with various layouts. Trail nutrients cue organisms on which direction to follow, provided they evolve to acquire and use those cues. Thus, each organism is tested on how well it navigates a randomly selected trail before reproducing. We find that behavior evolves modularly and in a predictable sequence, where simpler behaviors are necessary precursors for more complex ones. Associative learning is only one of many successful behaviors to evolve, and its origin depends on the environment possessing certain information patterns that organisms can exploit. Environmental patterns that are stable across generations foster the evolution of reflexive behavior, while environmental patterns that vary across generations, but remain consistent for periods within an organism’s lifetime, foster the evolution of learning behavior. Both types of environmental patterns are necessary, since the prior evolution of simple reflexive behaviors provides the building blocks for learning to arise. Finally, we observe that an intrinsic value system evolves alongside behavior and supports associative learning by providing reinforcement for behavior conditioning.
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Learning is a widespread ability among animals and, like physical traits, is subject to evolution. But how did learning first arise? What selection pressures and phenotypic preconditions fostered its evolution? Neither the fossil record nor phylogenetic comparative studies provide answers to these questions. Here, we take a novel approach by studying digital organisms in environments that promote the evolution of navigation and associative learning. Starting with a non-learning, sessile ancestor, we evolve multiple populations in four different environments, each consisting of nutrient trails with various layouts. Trail nutrients cue organisms on which direction to follow, provided they evolve to acquire and use those cues. Thus, each organism is tested on how well it navigates a randomly selected trail before reproducing. We find that behavior evolves modularly and in a predictable sequence, where simpler behaviors are necessary precursors for more complex ones. Associative learning is only one of many successful behaviors to evolve, and its origin depends on the environment possessing certain information patterns that organisms can exploit. Environmental patterns that are stable across generations foster the evolution of reflexive behavior, while environmental patterns that vary across generations, but remain consistent for periods within an organism’s lifetime, foster the evolution of learning behavior. Both types of environmental patterns are necessary, since the prior evolution of simple reflexive behaviors provides the building blocks for learning to arise. Finally, we observe that an intrinsic value system evolves alongside behavior and supports associative learning by providing reinforcement for behavior conditioning.
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In deterministic models of epidemics, there is a host abundance threshold, above which the introduction of a few infected individuals leads to a severe epidemic. Studies of weather-driven animal pathogens often assume that abundance thresholds will be overwhelmed by weather-driven stochasticity, but tests of this assumption are lacking. We collected observational and experimental data for a fungal pathogen, {\it Entomophaga maimaiga}, that infects the gypsy moth, {\it Lymantria dispar}. We used an advanced statistical-computing algorithm to fit mechanistic models to our data, such that different models made different assumptions about the effects of host density and weather on {\it E. maimaiga} epizootics (epidemics in animals). We then used AIC analysis to choose the best model. In the best model, epizootics are driven by a combination of weather and host density, and the model does an excellent job of explaining the data, whereas models that allow only for weather effects, or only density-dependence effects, do a poor job of explaining the data. Density-dependent transmission in our best model produces a host-density threshold, but this threshold is strongly blurred by the stochastic effects of weather. Our work shows that host-abundance thresholds may be important even if weather strongly affects transmission, suggesting that epidemiological models that allow for weather have an important role to play in understanding animal pathogens. The success of our model means that it could be useful for managing the gypsy moth, an important pest of hardwood forests in North America.
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Geophytes—plants typically with a bulb, corm, tuber or rhizome—are economically and evolutionarily important; however, the drivers of their morphological diversity remain unknown. Using a comprehensive phylogeny of monocots, we test for correlations between climate and growth form to better understand why we observe such a diversity of geophyte underground traits. Understanding the evolutionary factors promoting independent origins of these organs will lend insights into how plants adapt to environmental hardships. Using a phylogeny incorporated with global occurrence and climate data for the monocots, we investigated whether climatic patterns could explain differences between geophytes and non-geophytes, as well as differences among bulbous, cormous, tuberous, rhizomatous, and non-geophytic taxa. We used phylogenetically-informed ANOVAs, MANOVAs and PCAs to test differences in climatic variables between growth forms. Geophytes inhabit cooler, drier and thermally variable climates compared to non-geophytes. Although some underground traits (i.e., bulb, corm, and tuber) appear to inhabit particular niches, our data has limited evidence for an overall role of climate in the evolution of these traits. However, temperature may be a driving force in rhizome evolution, as well as the evolution of taxa considered here as non-geophytes. Our results suggest that temperature should be more strongly considered as a factor promoting the evolution of belowground bud placement, specifically as it relates to rhizomatous taxa. Bulbous, cormous and tuberous taxa need closer examination of other mechanisms, such as anatomical constraints or genetic controls, in order to begin to understand the causes behind the evolution of their underground morphology. In compliance with data protection regulations, you may request that we remove your personal registration details at any time. (Use the following URL: https://www.editorialmanager.com/ajb/login.asp?a=r) Please contact the publication office if you have any questions.
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Some neotropical amphibians, including a few species in Costa Rica, were presumed to be “extinct” after dramatic population declines in the late 1980s but have been rediscovered in isolated populations. Such populations seem to have evolved a resistance/tolerance to Batrachochytrium dendrobatidis (Bd), a fungal pathogen that causes a deadly skin disease and is considered one of the main drivers of worldwide amphibian declines. The skin microbiome is an important component of the host´s innate immune system and is associated with Bd-resistance. However, the way that the bacterial diversity of the skin microbiome confers protection against Bd in surviving species remains unclear. We studied variation in the skin microbiome and the prevalence of putatively anti-Bd bacterial taxa in four co-habiting species in the highlands of the Juan Castro Blanco National Park in Costa Rica using 16S rRNA amplicon sequencing. Lithobates vibicarius, Craugastor escoces, and Isthomohyla rivularis have recently been rediscovered, whereas Isthmohyla pseudopuma has suffered population fluctuations but has never disappeared. To investigate the life stage at which the protective skin microbiome is shaped and when shifts occur in the diversity of putatively anti-Bd bacteria, we studied the skin microbiome of tadpoles, juveniles and adults of L. vibicarius. We show that the skin bacterial composition of sympatric species and hosts with distinct Bd-infection statuses differs at the phyla, family, and genus level. We detected 94 amplicon sequence variants (ASVs) with putative anti-Bd activity pertaining to distinct bacterial taxa, e.g., Pseudomonas spp., Acinetobacter johnsonii, and Stenotrophomonas maltophilia. Bd-uninfected L. vibicarius harbored 79% more putatively anti-Bd ASVs than Bd-infected individuals. Although microbiome composition and structure differed across life stages, the diversity of putative anti-Bd bacteria was similar between pre- and post-metamorphic stages of L. vibicarius. Despite low sample size, our results support the idea that the skin microbiome is dynamic and protects against ongoing Bd presence in endangered species persisting after their presumed extinction. Our study serves as a baseline to understand the microbial patterns in species of high conservation value. Identification of microbial signatures linked to variation in disease susceptibility might, therefore, inform mitigation strategies for combating the global decline of amphibians.
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Antibodies are essential to functional immunity, yet the epitopes targeted by antibody repertoires remain largely uncharacterized. To aid in characterization, we developed a generalizable strategy to identify antibody-binding epitopes within individual proteins and entire proteomes. Specifically, we selected antibody-binding peptides for 273 distinct sera out of a random library and identified the peptides using next-generation sequencing. To identify antibody-binding epitopes and the antigens from which these epitopes were derived, we tiled the sequences of candidate antigens into short overlapping subsequences of length k (k-mers). We used the enrichment over background of these k-mers in the antibody-binding peptide dataset to identify antibody-binding epitopes. As a positive control, we used this approach, termed K-mer Tiling of Protein Epitopes (K-TOPE), to identify epitopes targeted by monoclonal and polyclonal antibodies of well-characterized specificity, accurately recovering their known epitopes. K-TOPE characterized a commonly targeted antigen from Rhinovirus A, identifying three epitopes recognized by antibodies present in 83% of sera (n = 250). An analysis of 2,908 proteins from 400 viral taxa that infect humans revealed seven enterovirus epitopes and five Epstein-Barr virus epitopes recognized by >30% of specimens. Analysis of Staphylococcus and Streptococcus proteomes similarly revealed six epitopes recognized by >40% of specimens. These common viral and bacterial epitopes exhibited excellent agreement with previously mapped epitopes. Additionally, we identified 30 HSV2-specific epitopes that were 100% specific against HSV1 in novel and previously reported antigens. The K-TOPE approach thus provides a powerful new tool to elucidate the organisms, antigens, and epitopes targeted by human antibody repertoires.
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Colonization at expanding range edges often involves few founders, reducing effective population size. This process can promote the evolution of self-fertilization, but implicating historical processes as drivers of trait evolution is often difficult and requires an explicit model of biogeographic history. In plants, contemporary limits to outcrossing are often invoked as evolutionary drivers of self-fertilization, but historical expansions may shape mating system diversity, with leading-edge populations evolving elevated selfing ability. In a widespread plant, Campanula americana, we identified a glacial refugium in the southern Appalachian Mountains from spatial patterns of genetic drift among 24 populations. Populations farther from this refugium have smaller effective sizes and fewer rare alleles. They also displayed elevated heterosis in among-population crosses, reflecting the accumulation of deleterious mutations during range expansion. While populations with elevated heterosis had reduced segregating mutation load, the magnitude of inbreeding depression lacked geographic pattern. The ability to self-fertilize was strongly positively correlated with the distance from the refugium and mutation accumulation—a pattern that contrasts sharply with contemporary mate and pollinator limitation. In this and other species, diversity in sexual systems may reflect the legacy of evolution in small, colonizing populations, with little or no relation to the ecology of modern populations.
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Head and neck squamous cell carcinoma (HNSCC) is a widely prevalent cancer globally with high mortality and morbidity. We report here changes in the genomic landscape in the development of these tumours from potentially premalignant lesions (PPOLS) to malignancy and lymph node metastases. Frequent likely pathological mutations are restricted to a relatively small set of genes including TP53, CDKN2A, FBXW7, FAT1, NOTCH1 and KMT2D; these arise early in tumour progression and are present in PPOLs with NOTCH1 mutations restricted to cell lines from lesions that subsequently progressed to HNSCC. The most frequent genetic changes are of consistent somatic copy number alterations (SCNA). The earliest SCNAs involved deletions of CSMD1 (8p23.2), FHIT (3p14.2) and CDKN2A (9p21.3) together with gains of chromosome 20. CSMD1 deletions or promoter hypermethylation were present in all of the immortal PPOLs and occurred at high frequency in the immortal HNSCC cell lines (promoter hypermethylation ~63%, hemizygous deletions ~75%, homozygous deletions ~18%). Forced expression of CSMD1 in the HNSCC cell line H103 showed significant suppression of proliferation (p=0.0053) and invasion in vitro (p=5.98X10-5) supporting a role for CSMD1 inactivation in early head and neck carcinogenesis. In addition, knockdown of CSMD1 in the CSMD1-expressing BICR16 cell line showed significant stimulation of invasion in vitro (p=1.82 x 10-5) but not cell proliferation (p=0.239). HNSCC with and without nodal metastases showed some clear differences including high copy number gains of CCND1, hsa-miR-548k and TP63 in the metastases group. GISTIC peak SCNA regions showed significant enrichment (adj P<0.01) of genes in multiple KEGG cancer pathways at all stages with disruption of an increasing number of these involved in the progression to lymph node metastases. Sixty-seven genes from regions with statistically significant differences in SCNA/LOH frequency between immortal PPOL and HNSCC cell lines showed correlation with expression including 5 known cancer drivers.
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1.Images are resourceful data for ecologists and can provide a more complete information than other methods to study biodiversity and the interactions between species. Automated image analysis however often relies on extensive datasets, not implementable by small research teams. We are here proposing an object detection method that allows the analysis of high‐resolution images containing many animals interacting in a small dataset. 2.We developed an image analysis pipeline named ‘CORIGAN' to extract the characteristics of animal communities. CORIGAN is based on the YOLOv3 model as the core of object detection. To illustrate potential applications, we use images collected during a sentinel prey experiment. 3.Our pipeline can be used to detect, count and study the physical interactions between various animals. On our example dataset, the model reaches 86.6% precision and 88.9% recall at the species level or even at the caste level for ants. The training set required fewer than 10 h of labelling. Based on the pipeline output it was possible to build the trophic and non‐trophic interactions network describing the studied community. 4.CORIGAN relies on generic properties of the detected animals and can be used for a wide range of studies and supports. Here, we study invertebrates on high‐resolution images, but the same processing can be transferred for the study of larger animals on satellite or aircraft images.
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Introduced species can impose profound impacts on the evolution of receiving communities with which they interact. If native and introduced taxa remain reproductively semi-isolated, human-mediated secondary contact may promote genetic exchange across newly created hybrid zones, potentially impacting native genetic diversity and invasive species spread. Here, we investigate the contributions of recent divergence histories and ongoing (post-introduction) gene flow between the invasive marine mussel, Mytilus galloprovincialis and a morphologically indistinguishable and taxonomically contentious native Australian taxon, Mytilus planulatus. Using transcriptome-wide markers, we demonstrate that two contemporary M. galloprovincialis introductions into southeastern Australia originate from genetically divergent lineages from its native range in the Mediterranean Sea and Atlantic Europe, where both introductions have led to repeated instances of admixture between introduced and endemic populations. Through increased genome-wide resolution of species relationships, combined with demographic modelling, we validate that mussels sampled in Tasmania are representative of the endemic Australian taxon (M. planulatus), but share strong genetic affinities to M. galloprovincialis. Demographic inferences indicate late-Pleistocene divergence times and historical gene flow between the Tasmanian endemic lineage and northern M. galloprovincialis, suggesting that native and introduced taxa have experienced a period of historical isolation of at least 100,000 years. Our results demonstrate that many genomic loci and sufficient sampling of closely related lineages in both sympatric (e.g., Australian populations) and allopatric (e.g., northern-hemisphere Mytilus taxa) ranges are necessary to accurately (i) interpret patterns of intraspecific differentiation and to (ii) distinguish contemporary invasive introgression from signatures left by recent divergence histories in high dispersal marine species. More broadly, our study fills a significant gap in systematic knowledge of native Australian biodiversity and sheds light on the intrinsic challenges for invasive species research when native and introduced species boundaries are not well-defined.
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