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The clownfish - sea anemone system is a great example of symbiotic mutualism where host «toxicity» does not impact its symbiont partner, although the underlying protection mechanism remains unclear. The regulation of nematocyst discharge in cnidarians involves N-acetylated sugars like sialic acid, that bind chemoreceptors on the tentacles of sea anemones, leading to the release of stings. It has been suggested that clownfish could be deprived of sialic acid on their skin surface, sparing them from being stung and facilitating mutualism with sea anemones. In this study, we sampled the skin mucus of two anemone symbionts, the clownfish Amphiprion akindynos and the juvenile damselfish Dascyllus trimaculatus, as well as two non-symbiotic adult damselfish Pomacentrus moluccensis and P. pavo. The free and total sialic acid content, including its conjugated form, and three other intermediates of this pathway were quantified using a stable isotope dilution mass spectrometry approach. We found significantly higher levels of sialic acid and its precursor in the non-symbiotic damselfishes. Concentrations of total sialic acid in anemone symbionts ranged between 13 µM and 16 µM, whereas the non-symbiotic damselfishes ranged between 21 µM and 30 µM. The presence of this metabolite and its precursors, as triggers of nematocyst discharge, in anemone symbionts, suggests that this is not the direct mechanism of protection or that the trigger is concentration dependent. This experiment demonstrates that anemone symbionts are not spared by nematocysts because of a lack of N-acetylated sugars, as previously thought, rather the biochemical mechanisms involving N-acetylated sugars are more complex than just a presence/absence of these molecules. [ABSTRACT FROM AUTHOR]

Mutations can be beneficial by bringing innovation to their bearer, allowing them to adapt to environmental change. These mutations are typically unpredictable since they respond to an unforeseen change in the environment. However, mutations can also be beneficial because they are simply restoring a state of higher fitness that was lost due to genetic drift in a stable environment. In contrast to adaptive mutations, these beneficial non-adaptive mutations can be predicted if the underlying fitness landscape is stable and known. The contribution of such non-adaptive mutations to molecular evolution has been widely neglected mainly because their detection is very challenging. We have here reconstructed protein-coding-gene fitness landscapes shared between mammals, using mutation-selection models and a multi-species alignments across 87 mammals. These fitness landscapes have allowed us to predict the fitness effect of polymorphisms found in 28 mammalian populations. Using methods that quantify selection at the population level, we have confirmed that beneficial non-adaptive mutations are indeed positively selected in extant populations. Our work confirms that deleterious substitutions are accumulating in mammals and are being reverted, generating a balance in which genomes are damaged and restored simultaneously at different loci. We observe that beneficial non-adaptive mutations represent between 15% and 45% of all beneficial mutations in 24 of 28 populations analyzed, suggesting that a substantial part of ongoing positive selection is not driven solely by adaptation to environmental change in mammals. Author summary: The extent to which adaptation to changing environments is shaping genomes is a central question in molecular evolution. To quantify the rate of adaptation, population geneticists have typically used signatures of positive selection. However, mutations restoring an ancestral state of higher fitness lost by genetic drift are also positively selected, but they do not respond to a change in the environment. In this study, we have managed to distinguish beneficial mutations that are due to changing environments and those that are restoring pre-existing functions in mammals. We show that a substantial proportion of beneficial mutations cannot be interpreted as adaptive. [ABSTRACT FROM AUTHOR]

Models have always been central to inferring molecular evolution and to reconstructing phylogenetic trees. Their use typically involves the development of a mechanistic framework reflecting our understanding of the underlying biological processes, such as nucleotide substitutions, and the estimation of model parameters by maximum likelihood or Bayesian inference. However, deriving and optimizing the likelihood of the data is not always possible under complex evolutionary scenarios or even tractable for large datasets, often leading to unrealistic simplifying assumptions in the fitted models. To overcome this issue, we coupled stochastic simulations of genome evolution with a new supervised deep-learning model to infer key parameters of molecular evolution. Our model is designed to directly analyze multiple sequence alignments and estimate per-site evolutionary rates and divergence without requiring a known phylogenetic tree. The accuracy of our predictions matched that of likelihood-based phylogenetic inference when rate heterogeneity followed a simple gamma distribution, but it strongly exceeded it under more complex patterns of rate variation, such as codon models. Our approach is highly scalable and can be efficiently applied to genomic data, as we showed on a dataset of 26 million nucleotides from the clownfish clade. Our simulations also showed that the integration of per-site rates obtained by deep learning within a Bayesian framework led to significantly more accurate phylogenetic inference, particularly with respect to the estimated branch lengths. We thus propose that future advancements in phylogenetic analysis will benefit from a semi-supervised learning approach that combines deep-learning estimation of substitution rates, which allows for more flexible models of rate variation, and probabilistic inference of the phylogenetic tree, which guarantees interpretability and a rigorous assessment of statistical support. [ABSTRACT FROM AUTHOR]

Even seemingly homogeneous on the surface, the oceans display high environmental heterogeneity across space and time. Indeed, different soft barriers structure the marine environment, which offers an appealing opportunity to study various evolutionary processes such as population differentiation and speciation. Here, we focus on Amphiprion clarkii (Actinopterygii; Perciformes), the most widespread of clownfishes that exhibits the highest colour polymorphism. Clownfishes can only disperse during a short pelagic larval phase before their sedentary adult lifestyle, which might limit connectivity among populations, thus facilitating speciation events. Consequently, the taxonomic status of A. clarkii has been under debate. We used whole‐genome resequencing data of 67 A. clarkii specimens spread across the Indian and Pacific Oceans to characterize the species' population structure, demographic history and colour polymorphism. We found that A. clarkii spread from the Indo‐Pacific Ocean to the Pacific and Indian Oceans following a stepping‐stone dispersal and that gene flow was pervasive throughout its demographic history. Interestingly, colour patterns differed noticeably among the Indonesian populations and the two populations at the extreme of the sampling distribution (i.e. Maldives and New Caledonia), which exhibited more comparable colour patterns despite their geographic and genetic distances. Our study emphasizes how whole‐genome studies can uncover the intricate evolutionary past of wide‐ranging species with diverse phenotypes, shedding light on the complex nature of the species concept paradigm. [ABSTRACT FROM AUTHOR]

Phenological events - defined points in the life cycle of a plant or animal - have been regarded as highly plastic traits, reflecting flexible responses to various environmental cues. The ability of a species to track, via shifts in phenological events, the abiotic environment through time might dictate its vulnerability to future climate change. Understanding the predictors and drivers of phenological change is therefore critical. Here, we evaluated evidence for phylogenetic conservatism - the tendency for closely related species to share similar ecological and biological attributes - in phenological traits across flowering plants. We aggregated published and unpublished data on timing of first flower and first leaf, encompassing ̃4000 species at 23 sites across the Northern Hemisphere. We reconstructed the phylogeny for the set of included species, first, using the software program Phylomatic, and second, from DNA data. We then quantified phylogenetic conservatism in plant phenology within and across sites. We show that more closely related species tend to flower and leaf at similar times. By contrasting mean flowering times within and across sites, however, we illustrate that it is not the time of year that is conserved, but rather the phenological responses to a common set of abiotic cues. Our findings suggest that species cannot be treated as statistically independent when modelling phenological responses. Synthesis. Closely related species tend to resemble each other in the timing of their life-history events, a likely product of evolutionarily conserved responses to environmental cues. The search for the underlying drivers of phenology must therefore account for species' shared evolutionary histories. Closely related species tend to resemble each other in the timing of their life-history events, a likely product of evolutionarily conserved responses to environmental cues. The search for the underlying drivers of phenology must therefore account for species' shared evolutionary histories. © 2013 British Ecological Society.