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A major rationale for the advocacy of epigenetically mediated adaptive responses is that they facilitate faster adaptation to environmental challenges. This motivated us to develop a theoretical- experimental framework for disclosing the presence of such adaptation- speeding mechanisms in an experimental evolution setting circumventing the need for pursuing costly mutation-accumulation experiments. To this end, we exposed clonal populations of budding yeast to a whole range of stressors. By growth phenotyping, we found that almost complete adaptation to arsenic emerged after a few mitotic cell divisions without involving any phenotypic plasticity. Causative mutations were identified by deep sequencing of the arsenic-adapted populations and reconstructed for validation. Mutation effects on growth phenotypes, and the associated mutational target sizes were quantified and embedded in datadriven individual-based evolutionary population models. We found that the experimentally observed homogeneity of adaptation speed and heterogeneity of molecular solutions could only be accounted for if the mutation rate had been near estimates of the basal mutation rate. The ultrafast adaptation could be fully explained by extensive positive pleiotropy such that all beneficial mutations dramatically enhanced multiple fitness components in concert. As our approach can be exploited across a range of model organisms exposed to a variety of environmental challenges, it may be used for determining the importance of epigenetic adaptation- speeding mechanisms in general. [ABSTRACT FROM AUTHOR]

Computational models of many aspects of the mammalian cardiovascular circulation have been developed. Indeed, along with orthopaedics, this area of physiology is one that has attracted much interest from engineers, presumably because the equations governing blood flow in the vascular system are well understood and can be solved with well-established numerical techniques. Unfortunately, there have been only a few attempts to create a comprehensive public domain resource for cardiovascular researchers. In this paper we propose a roadmap for developing an open source cardiovascular circulation model. The model should be registered to the musculo-skeletal system. The computational infrastructure for the cardiovascular model should provide for near real-time computation of blood flow and pressure in all parts of the body. The model should deal with vascular beds in all tissues, and the computational infrastructure for the model should provide links into CellML models of cell function and tissue function. In this work we review the literature associated with 1D blood flow modelling in the cardiovascular system, discuss model encoding standards, software and a model repository. We then describe the coordinate systems used to define the vascular geometry, derive the equations and discuss the implementation of these coupled equations in the open source computational software OpenCMISS. Finally, some preliminary results are presented and plans outlined for the next steps in the development of the model, the computational software and the graphical user interface for accessing the model. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the editor discusses various reports within the issue on topics related to the integration of evolutionary biology and physiological science including the comparisons of chromatin marking and small RNA profiles in populations at initial stages of evolutionary divergence, Modern Synthesis, and the history and philosophy of the relevant concepts of the gene and their interpretations of the consequences.

The genotype-phenotype map (GP map) concept applies to any time point in the ontogeny of a living system. It is the outcome of very complex dynamics that include environmental effects, and bridging the genotype-phenotype gap is synonymous with understanding these dynamics. The context for this understanding is physiology, and the disciplinary goals of physiology do indeed demand the physiological community to seek this understanding. We claim that this task is beyond reach without use of mathematical models that bind together genetic and phenotypic data in a causally cohesive way. We provide illustrations of such causally cohesive genotype-phenotype models where the phenotypes span from gene expression profiles to development of whole organs. Bridging the genotype-phenotype gap also demands that large-scale biological ('omics') data and associated bioinformatics resources be more effectively integrated with computational physiology than is currently the case. A third major element is the need for developing a phenomics technology way beyond current state of the art, and we advocate the establishment of a Human Phenome Programme solidly grounded on biophysically based mathematical descriptions of human physiology. [ABSTRACT FROM AUTHOR]

. Purpose: Idiopathic intracranial hypertension (IIH) is a condition of increased intracranial pressure of unknown aetiology. Patients with IIH usually suffer from headache and visual disturbances. High intracranial pressure despite normal ventricle size and negative MRI indicate perturbed water flux across cellular membranes, which is provided by the brain water channel aquaporin-4 (AQP4). IIH could be associated with malfunctioning intracerebral water homeostasis and cerebrospinal fluid (CSF) reabsorption based on functional or regulatory alterations of AQP4. Methods: Clinical data, blood and CSF samples were collected from 28 patients with IIH. Clinical characteristics were assessed, and a genetic association study was performed by sequencing the AQP4 gene on chromosome 18. Genetic data were compared with 52 healthy controls and matched by age, sex and ethnicity. Chi-square test and linear discriminant analysis (LDA) were used in the search of a genotype-phenotype association. Results: While the majority of patients responded to medical treatment, four required shunt application. All, except one, had a good visual outcome. The 24 AQP4 gene SNPs showed no association with IIH. Full cross-validation of the LDA modelling resulted in only 55.1% correct classification of the cases and controls, with a corresponding estimated p-value 0.37. Conclusions: Our genetic case-control study did not indicate an association between AQP4 gene variants and IIH. However, the theory of an etiopathogenic link between IIH and AQP4 is tempting, and discussed in this article. Association studies with large sample size are difficult to perform owing is the rarity of the condition. [ABSTRACT FROM AUTHOR]

Phenotypic variation arising from populations adapting to different niches has a complex underlying genetic architecture. A major challenge in modern biology is to identify the causative variants driving phenotypic variation. Recently, the baker's yeast, Saccharomyces cerevisiae has emerged as a powerful model for dissecting complex traits. However, past studies using a laboratory strain were unable to reveal the complete architecture of polygenic traits. Here, we present a linkage study using 576 recombinant strains obtained from crosses of isolates representative of the major lineages. The meiotic recombinational landscape appears largely conserved between populations; however, strain-specific hotspots were also detected. Quantitative measurements of growth in 23 distinct ecologically relevant environments show that our recombinant population recapitulates most of the standing phenotypic variation described in the species. Linkage analysis detected an average of 6.3 distinct QTLs for each condition tested in all crosses, explaining on average 39% of the phenotypic variation. The QTLs detected are not constrained to a small number of loci, and the majority are specific to a single cross-combination and to a specific environment. Moreover, crosses between strains of similar phenotypes generate greater variation in the offspring, suggesting the presence of many antagonistic alleles and epistatic interactions. We found that subtelomeric regions play a key role in defining individual quantitative variation, emphasizing the importance of the adaptive nature of these regions in natural populations. This set of recombinant strains is a powerful tool for investigating the complex architecture of polygenic traits. [ABSTRACT FROM AUTHOR]

Abstract: Functionally sterile honey bee workers synthesize the yolk protein vitellogenin while performing nest tasks. The subsequent shift to foraging is linked to a reduced vitellogenin and an increased juvenile hormone (JH) titer. JH is a principal controller of vitellogenin expression and behavioral development. Yet, we show here that silencing of vitellogenin expression causes a significant increase in JH titer and its putative receptor. Mathematically, the increase corresponds to a dynamic dose–response. This role of vitellogenin in the tuning of the endocrine system is uncommon and may elucidate how an ancestral pathway of fertility regulation has been remodeled into a novel circuit controlling social behavior. [Copyright &y& Elsevier]