Evolutionary genomics can improve prediction of species' responses to climate change

Global climate change (GCC) increasingly threatens biodiversity through the loss of species, and the transformation of entire ecosystems. Many species are challenged by the pace of GCC because they might not be able to respond fast enough to changing biotic and abiotic conditions. Species can respond either by shifting their range, or by persisting in their local habitat. If populations persist, they can tolerate climatic changes through phenotypic plasticity, or genetically adapt to changing conditions depending on their genetic variability and census population size to allow for de novo mutations. Otherwise, populations will experience demographic collapses and species may go extinct. Current approaches to predicting species responses to GCC begin to combine ecological and evolutionary information for species distribution modelling. Including an evolutionary dimension will substantially improve species distribution projections which have not accounted for key processes such as dispersal, adaptive genetic change, demography, or species interactions. However, eco-evolutionary models require new data and methods for the estimation of a species' adaptive potential, which have so far only been available for a small number of model species. To represent global biodiversity, we need to devise large-scale data collection strategies to define the ecology and evolutionary potential of a broad range of species, especially of keystone species of ecosystems. We also need standardized and replicable modelling approaches that integrate these new data to account for eco-evolutionary processes when predicting the impact of GCC on species' survival. Here, we discuss different genomic approaches that can be used to investigate and predict species responses to GCC. This can serve as guidance for researchers looking for the appropriate experimental setup for their particular system. We furthermore highlight future directions for moving forward in the field and allocating available resources more effectively, to implement mitigation measures before species go extinct and ecosystems lose important functions

Conserved genes underlie phenotypic plasticity in an incipiently social bee

Despite a strong history of theoretical work on the mechanisms of social evolution, relatively little is known of the molecular genetic changes that accompany transitions from solitary to eusocial forms. Here we provide the first genome of an incipiently social bee that shows both solitary and social colony organization in sympatry, the Australian carpenter bee Ceratina australensis. Through comparative analysis, we provide support for the role of conserved genes and cis-regulation of gene expression in the phenotypic plasticity observed in nest-sharing, a rudimentary form of sociality. Additionally, we find that these conserved genes are associated with caste differences in advanced eusocial species, suggesting these types of mechanisms could pave the molecular pathway from solitary to eusocial living. Genes associated with social nesting in this species show signatures of being deeply conserved, in contrast to previous studies in other bees showing novel and faster-evolving genes are associated with derived sociality. Our data provide support for the idea that the earliest social transitions are driven by changes in gene regulation of deeply conserved genes

Towards a Mathematical Theory of Cortical Micro-circuits

The theoretical setting of hierarchical Bayesian inference is gaining acceptance as a framework for understanding cortical computation. In this paper, we describe how Bayesian belief propagation in a spatio-temporal hierarchical model, called Hierarchical Temporal Memory (HTM), can lead to a mathematical model for cortical circuits. An HTM node is abstracted using a coincidence detector and a mixture of Markov chains. Bayesian belief propagation equations for such an HTM node define a set of functional constraints for a neuronal implementation. Anatomical data provide a contrasting set of organizational constraints. The combination of these two constraints suggests a theoretically derived interpretation for many anatomical and physiological features and predicts several others. We describe the pattern recognition capabilities of HTM networks and demonstrate the application of the derived circuits for modeling the subjective contour effect. We also discuss how the theory and the circuit can be extended to explain cortical features that are not explained by the current model and describe testable predictions that can be derived from the model

Electrotonic Signals along Intracellular Membranes May Interconnect Dendritic Spines and Nucleus

Synapses on dendritic spines of pyramidal neurons show a remarkable ability to induce phosphorylation of transcription factors at the nuclear level with a short latency, incompatible with a diffusion process from the dendritic spines to the nucleus. To account for these findings, we formulated a novel extension of the classical cable theory by considering the fact that the endoplasmic reticulum (ER) is an effective charge separator, forming an intrinsic compartment that extends from the spine to the nuclear membrane. We use realistic parameters to show that an electrotonic signal may be transmitted along the ER from the dendritic spines to the nucleus. We found that this type of signal transduction can additionally account for the remarkable ability of the cell nucleus to differentiate between depolarizing synaptic signals that originate from the dendritic spines and back-propagating action potentials. This study considers a novel computational role for dendritic spines, and sheds new light on how spines and ER may jointly create an additional level of processing within the single neuron

Mucous membrane pemphigoid and lichenoid reactions after immune checkpoint inhibitors: common pathomechanisms.

Immune checkpoint inhibitor (ICI) therapy has demonstrated impressive antitumor activity. However, it causes adverse effects, including lichenoid reactions. Cases of ICI-triggered bullous pemphigoid (BP) and anecdotally mucous membrane pemphigoid (MMP) have also been reported. We describe two new cases of pembrolizumab-triggered MMP, one of which was associated with cutaneous lichenoid lesions

Effects of adult temperature on gene expression in a butterfly: identifying pathways associated with thermal acclimation

Abstract Background Phenotypic plasticity is a pervasive property of all organisms and considered to be of key importance for dealing with environmental variation. Plastic responses to temperature, which is one of the most important ecological factors, have received much attention over recent decades. A recurrent pattern of temperature-induced adaptive plasticity includes increased heat tolerance after exposure to warmer temperatures and increased cold tolerance after exposure to cooler temperatures. However, the mechanisms underlying these plastic responses are hitherto not well understood. Therefore, we here investigate effects of adult acclimation on gene expression in the tropical butterfly Bicyclus anynana, using an RNAseq approach. Results We show that several antioxidant markers (e.g. peroxidase, cytochrome P450) were up-regulated at a higher temperature compared with a lower adult temperature, which might play an important role in the acclamatory responses subsequently providing increased heat tolerance. Furthermore, several metabolic pathways were up-regulated at the higher temperature, likely reflecting increased metabolic rates. In contrast, we found no evidence for a decisive role of the heat shock response. Conclusions Although the important role of antioxidant defence mechanisms in alleviating detrimental effects of oxidative stress is firmly established, we speculate that its potentially important role in mediating heat tolerance and survival under stress has been underestimated thus far and thus deserves more attention