Meeting review: Epigenetics in Development and Disease

The 2002 Keystone symposia held in Taos, New Mexico (21-26 February) saw the convergence of two related fields; Epigenetics in Development and Disease, and RNA Interference, Cosuppression and Related Phenomena. The meeting highlights presented here concentrate upon the sessions within the Epigenetics in Development and Disease meeting, although there were joint sessions which will also be discussed. Of course epigenetic regulation is not restricted to the vertebrates but I have chosen, rightly or wrongly, to limit the highlights to those concerning vertebrates.     

Spore Dispersal and Plant Disease Gradients; a Comparison between two Empirical Models

Power law and exponential models were fitted to 325 sets of observations which described decreases with distance in deposition of air-borne or splash-borne spores, or pollen, or in amounts of plant disease caused by fungi, bacteria or viruses. There, was generally little difference between the models in the goodness of fit to these data, although deposition gradients for spores borne in splash droplets were fitted better by exponential models and gradients for fungi with air-borne spores less than 10 μm in diameter were fitted better by power law models. The exponential model has the property that the observed variable decreases by half as the distance from the source increases by a constant increment (the half-distance); this provides a measureof the gradient that is more easy to visualize than the exponent in power law model. The half-distances of gradients for air-borne pathogens were greater than those for splash-borne or soil-borne pathogens. The exponential model is easier to incorporate into models of disease development than the power law model because the boundary condition at the source (the estimated number of spores or amount of disease at the source) is finite rather than infinite. However, both these empirical models have limitations and should not be extrapolated to distances outside the observed range.     

A new brand for Disease Models & Mechanisms and The Company of Biologists

Summary: The launch of a new brand and website for DMM.Regular readers of Disease Models & Mechanisms (DMM) during 2015 will have noticed some changes to the journal. This is part of the gradual implementation of a new Company brand and migration to a new, better, web platform. This culminated in October with the launch of a new website for The Company of Biologists (www.biologists.com), and a brand new look and feel for the DMM website (dmm.biologists.org) and the articles it publishes (see Fig. 1). The new DMM website (and those of its sister journals Development, Journal of Cell Science, Journal of Experimental Biology and Biology Open) is the result of a mammoth project to ensure that users have an enhanced experience when visiting our pages. The site is easier to navigate and uncluttered, making it even quicker to search and find the content you need. We hope it looks good too. Open in a separate windowFig. 1.The Company of Biologists and DMM: supporting biologists, inspiring biology.Although our five journals are well known, fewer people are aware of the other areas of support that The Company of Biologists brings to the biological community. Our new brand will help us to increase the awareness of our work, and strengthen the links between our journals and charitable activities.     

心脏发育和疾病的表观遗传调控机制

表观遗传调控机制是后基因组时代的重点研究领域,当前许多证据表明表观遗传学调控心脏发育进程,参与多种心脏疾病的调控。本文综述了DNA甲基化、组蛋白修饰、染色质重塑复合物和microRNAs在心脏发育中的作用,以及在动脉粥样硬化、心力衰竭、心肌缺血、心肌纤维化等心脏疾病中表观遗传调控的研究进展,同时概述了生物活性食品化合物在心脏保护中的作用,为心脏发育的分子机制研究和心脏疾病的预防与治疗方向提供新的视角。     

Finding Novel Molecular Connections between Developmental Processes and Disease

Identifying molecular connections between developmental processes and disease can lead to new hypotheses about health risks at all stages of life. Here we introduce a new approach to identifying significant connections between gene sets and disease genes, and apply it to several gene sets related to human development. To overcome the limits of incomplete and imperfect information linking genes to disease, we pool genes within disease subtrees in the MeSH taxonomy, and we demonstrate that such pooling improves the power and accuracy of our approach. Significance is assessed through permutation. We created a web-based visualization tool to facilitate multi-scale exploration of this large collection of significant connections (http://gda.cs.tufts.edu/development). High-level analysis of the results reveals expected connections between tissue-specific developmental processes and diseases linked to those tissues, and widespread connections to developmental disorders and cancers. Yet interesting new hypotheses may be derived from examining the unexpected connections. We highlight and discuss the implications of three such connections, linking dementia with bone development, polycystic ovary syndrome with cardiovascular development, and retinopathy of prematurity with lung development. Our results provide additional evidence that plays a key role in the early pathogenesis of polycystic ovary syndrome. Our evidence also suggests that the VEGF pathway and downstream NFKB signaling may explain the complex relationship between bronchopulmonary dysplasia and retinopathy of prematurity, and may form a bridge between two currently-competing hypotheses about the molecular origins of bronchopulmonary dysplasia. Further data exploration and similar queries about other gene sets may generate a variety of new information about the molecular relationships between additional diseases.     

Observing others give & take: A computational account of bystanders’ feelings and actions

Social interactions influence people’s feelings and behavior. Here, we propose that a person’s well-being is influenced not only by interactions they experience themselves, but also by those they observe. In particular, we test and quantify the influence of observed selfishness and observed inequality on a bystanders’ feelings and non-costly punishment decisions. We developed computational models that relate others’ (un)selfish acts to observers’ emotional reactions and punishment decisions. These characterize the rules by which others’ interactions are transformed into bystanders’ reactions, and successfully predict those reactions in out-of-sample participants. The models highlight the impact of two social values—‘selfishness aversion’ and ‘inequality aversion’. As for the latter we find that even small violations from perfect equality have a disproportionately large impact on feelings and punishment. In this age of internet and social media we constantly observe others’ online interactions, in addition to in-person interactions. Quantifying the consequences of such observations is important for predicting their impact on society.