Sex and gametogenesis stage are strong drivers of gene expression in Mytilus edulis exposed to environmentally relevant plasticiser levels and pH 7.7.

Plastic pollution and changes in oceanic pH are both pressing environmental issues. Little emphasis, however, has been placed on the influence of sex and gametogenesis stage when investigating the effects of such stressors. Here, we examined histology and molecular biomarkers of blue mussels Mytilus edulis exposed for 7 days to a pH 7.7 scenario (- 0.4 units) in combination with environmentally relevant concentrations (0, 0.5 and 50 µg/L) of the endocrine disrupting plasticiser di-2-ethylhexyl phthalate (DEHP). Through a factorial design, we investigated the gametogenesis cycle and sex-related expression of genes involved in pH homeostasis, stress response and oestrogen receptor-like pathways after the exposure to the two environmental stressors. As expected, we found sex-related differences in the proportion of developing, mature and spawning gonads in histological sections. Male gonads also showed higher levels of the acid-base regulator CA2, but females had a higher expression of stress response-related genes (i.e. sod, cat, hsp70). We found a significant effect of DEHP on stress response-related gene expression that was dependent on the gametogenesis stage, but there was only a trend towards downregulation of CA2 in response to pH 7.7. In addition, differences in gene expression between males and females were most pronounced in experimental conditions containing DEHP and/or acidified pH but never the control, indicating that it is important to consider sex and gametogenesis stage when studying the response of mussels to diverse stressors.

Functional genomics of abiotic environmental adaptation in lacertid lizards and other vertebrates.

Understanding the genomic basis of adaptation to different abiotic environments is important in the context of climate change and resulting short-term environmental fluctuations. Using functional and comparative genomics approaches, we here investigated whether signatures of genomic adaptation to a set of environmental parameters are concentrated in specific subsets of genes and functions in lacertid lizards and other vertebrates. We first identify 200 genes with signatures of positive diversifying selection from transcriptomes of 24 species of lacertid lizards and demonstrate their involvement in physiological and morphological adaptations to climate. To understand how functionally similar these genes are to previously predicted candidate functions for climate adaptation and to compare them with other vertebrate species, we then performed a meta-analysis of 1,100 genes under selection obtained from -omics studies in vertebrate species adapted to different abiotic factors. We found that the vertebrate gene set formed a tightly connected interactome, which was to 23% enriched in previously predicted functions of adaptation to climate, and to a large part (18%) involved in organismal stress response. We found a much higher degree of identical genes being repeatedly selected among different animal groups (43.6%), and of functional similarity and post-translational modifications than expected by chance, and no clear functional division between genes used for ectotherm and endotherm physiological strategies. In total, 171 out of 200 genes of Lacertidae were part of this network. These results highlight an important role of a comparatively small set of genes and their functions in environmental adaptation and narrow the set of candidate pathways and markers to be used in future research on adaptation and stress response related to climate change.

Consequences of combined exposure to thermal stress and the plasticiser DEHP in Mytilus spp. differ by sex.

Little is known about the combined effect of environmental factors and contaminants on commercially important marine species, and whether this effect differs by sex. In this study, blue mussels were exposed for seven days to both single and combined stressors (i.e., +3 °C elevated temperature and two environmentally relevant concentrations of the plastic softener DEHP, 0.5 and 50 µg/l) in a factorial design. Males were observed to be more sensitive to high temperature, demonstrated by the significant increase in out-of-season spawning gonads and higher gene expression of the antioxidant catalase and the estrogen receptor genes. On the other hand, while the gametogenesis cycle in females was more resilient than in males, DEHP exposure altered the estrogen-related receptor gene expression. We show that the combined stressors DEHP and increased temperature, in environmentally relevant magnitudes, have different consequences in male and female mussels, with the potential to impact the timing and breeding season success in Mytilus spp.

Environmental temperatures shape thermal physiology as well as diversification and genome-wide substitution rates in lizards.

Climatic conditions changing over time and space shape the evolution of organisms at multiple levels, including temperate lizards in the family Lacertidae. Here we reconstruct a dated phylogenetic tree of 262 lacertid species based on a supermatrix relying on novel phylogenomic datasets and fossil calibrations. Diversification of lacertids was accompanied by an increasing disparity among occupied bioclimatic niches, especially in the last 10 Ma, during a period of progressive global cooling. Temperate species also underwent a genome-wide slowdown in molecular substitution rates compared to tropical and desert-adapted lacertids. Evaporative water loss and preferred temperature are correlated with bioclimatic parameters, indicating physiological adaptations to climate. Tropical, but also some populations of cool-adapted species experience maximum temperatures close to their preferred temperatures. We hypothesize these species-specific physiological preferences may constitute a handicap to prevail under rapid global warming, and contribute to explaining local lizard extinctions in cool and humid climates.

Artificial Epigenetic Networks: Automatic Decomposition of Dynamical Control Tasks Using Topological Self-Modification.

This paper describes the artificial epigenetic network, a recurrent connectionist architecture that is able to dynamically modify its topology in order to automatically decompose and solve dynamical problems. The approach is motivated by the behavior of gene regulatory networks, particularly the epigenetic process of chromatin remodeling that leads to topological change and which underlies the differentiation of cells within complex biological organisms. We expected this approach to be useful in situations where there is a need to switch between different dynamical behaviors, and do so in a sensitive and robust manner in the absence of a priori information about problem structure. This hypothesis was tested using a series of dynamical control tasks, each requiring solutions that could express different dynamical behaviors at different stages within the task. In each case, the addition of topological self-modification was shown to improve the performance and robustness of controllers. We believe this is due to the ability of topological changes to stabilize attractors, promoting stability within a dynamical regime while allowing rapid switching between different regimes. Post hoc analysis of the controllers also demonstrated how the partitioning of the networks could provide new insights into problem structure.

Using epigenetic networks for the analysis of movement associated with levodopa therapy for Parkinson's disease.

Levodopa is a drug that is commonly used to treat movement disorders associated with Parkinson's disease. Its dosage requires careful monitoring, since the required amount changes over time, and excess dosage can lead to muscle spasms known as levodopa-induced dyskinesia. In this work, we investigate the potential for using epiNet, a novel artificial gene regulatory network, as a classifier for monitoring accelerometry time series data collected from patients undergoing levodopa therapy. We also consider how dynamical analysis of epiNet classifiers and their transitions between different states can highlight clinically useful information which is not available through more conventional data mining techniques. The results show that epiNet is capable of discriminating between different movement patterns which are indicative of either insufficient or excessive levodopa.

The incorporation of epigenetics in artificial gene regulatory networks.

Artificial gene regulatory networks are computational models that draw inspiration from biological networks of gene regulation. Since their inception they have been used to infer knowledge about gene regulation and as methods of computation. These computational models have been shown to possess properties typically found in the biological world, such as robustness and self organisation. Recently, it has become apparent that epigenetic mechanisms play an important role in gene regulation. This paper describes a new model, the Artificial Epigenetic Regulatory Network (AERN) which builds upon existing models by adding an epigenetic control layer. Our results demonstrate that AERNs are more adept at controlling multiple opposing trajectories when applied to a chaos control task within a conservative dynamical system, suggesting that AERNs are an interesting area for further investigation.

Computational models of signalling networks for non-linear control.

Artificial signalling networks (ASNs) are a computational approach inspired by the signalling processes inside cells that decode outside environmental information. Using evolutionary algorithms to induce complex behaviours, we show how chaotic dynamics in a conservative dynamical system can be controlled. Such dynamics are of particular interest as they mimic the inherent complexity of non-linear physical systems in the real world. Considering the main biological interpretations of cellular signalling, in which complex behaviours and robust cellular responses emerge from the interaction of multiple pathways, we introduce two ASN representations: a stand-alone ASN and a coupled ASN. In particular we note how sophisticated cellular communication mechanisms can lead to effective controllers, where complicated problems can be divided into smaller and independent tasks.