Rapid genetic divergence in response to 15 years of simulated climate change

Genetic diversity may play an important role in allowing individual species to resist climate change, by permitting evolutionary responses. Our understanding of the potential for such responses to climate change remains limited, and very few experimental tests have been carried out within intact ecosystems. Here, we use amplified fragment length polymorphism (AFLP) data to assess genetic divergence and test for signatures of evolutionary change driven by long-term simulated climate change applied to natural grassland at Buxton Climate Change Impacts Laboratory (BCCIL). Experimental climate treatments were applied to grassland plots for 15 years using a replicated and spatially blocked design and included warming, drought and precipitation treatments. We detected significant genetic differentiation between climate change treatments and control plots in two coexisting perennial plant study species (Festuca ovina and Plantago lanceolata). Outlier analyses revealed a consistent signature of selection associated with experimental climate treatments at individual AFLP loci in P. lanceolata, but not in F. ovina. Average background differentiation at putatively neutral AFLP loci was close to zero, and genomewide genetic structure was associated neither with species abundance changes (demography) nor with plant community-level responses to long-term climate treatments. Our results demonstrate genetic divergence in response to a suite of climatic environments in reproductively mature populations of two perennial plant species and are consistent with an evolutionary response to climatic selection in P. lanceolata. These genetic changes have occurred in parallel with impacts on plant community structure and may have contributed to the persistence of individual species through 15 years of simulated climate change at BCCIL

‘With whom shall I identify?’: Nineteenth-Century Representations of Parental Influences and Adolescent Identity Formation

This inter-disciplinary research considers cultural influences, such as religion and education, on adolescent identity formation and parental role-models in nineteenth-century texts. Definitions and representations of constructed identities are explored in relation to the influence of cultural factors using twentieth-century psychological, sociological and psychiatric theories surrounding adolescent and parental identity. Representations of adolescent experiences and parental influences within the home and society reflect changing attitudes towards shifting gender boundaries throughout the century. The conflict of changing family dynamics, in relation to parental roles and authority, are also considered with regards to how these influence the adolescent during this critical life-stage. The conflict and crisis involved in the process of adolescent identity formation is linked to the need for the adolescent to identify with a successful role-model. The analysis of representations of socially constructed role-models in the nineteenth-century suggests there are many factors that determine the success or failure of an adopted identity. This research supports the theory that the concept of a problematic adolescence is not borne out of the inability of adolescents to form an identity, rather the inability of nineteenth-century parents to provide a stable, positive and successful role-model, and the adolescent’s increasing awareness of this instability and their need for an individual identity. Representations support the argument that the growing pressure of individual responsibility for life-choices throughout the nineteenth century also increases the conflict and crisis of the adolescent experience and creates an adolescent desire for autonomy to realise their full potential

Natural organic matter in sedimentary basins and its relation to arsenic in anoxic ground water: the example of West Bengal and its worldwide implications

In order to investigate the mechanism of As release to anoxic ground water in alluvial aquifers, the authors sampled ground waters from 3 piezometer nests, 79 shallow (80 m) wells, in an area 750 m by 450 m, just north of Barasat, near Kolkata (Calcutta), in southern West Bengal. High concentrations of As (200-1180 mug L-1) are accompanied by high concentrations of Fe (3-13.7 mgL(-1)) and PO4 (1-6.5 mg L-1). Ground water that is rich in Mn (1-5.3 mg L-1) contains <50 mug L-1 of As. The composition of shallow ground water varies at the 100-m scale laterally and the metre-scale vertically, with vertical gradients in As concentration reaching 200 mug L-1 m(-1). The As is supplied by reductive dissolution of FeOOH and release of the sorbed As to solution. The process is driven by natural organic matter in peaty strata both within the aquifer sands and in the overlying confining unit. In well waters, thermotolerant coliforms, a proxy for faecal contamination, are not present in high numbers (<10 cfu/100 ml in 85% of wells) showing that faecally-derived organic matter does not enter the aquifer, does not drive reduction of FeOOH, and so does not release As to ground water.Arsenic concentrations are high (much greater than50 mug L-1) where reduction of FeOOH is complete and its entire load of sorbed As is released to solution, at which point the aquifer sediments become grey in colour as FeOOH vanishes. Where reduction is incomplete, the sediments are brown in colour and resorption of As to residual FeOOH keeps As concentrations below 10 mug L-1 in the presence of dissolved Fe. Sorbed As released by reduction of Mn oxides does not increase As in ground water because the As resorbs to FeOOH. High concentrations of As are common in alluvial aquifers of the Bengal Basin arise because Himalayan erosion supplies immature sediments, with low surface-loadings of FeOOH on mineral grains, to a depositional environment that is rich in organic mater so that complete reduction of FeOOH is common. (C) 2004 Published by Elsevier Ltd

Machine learning methods for automatic silent speech recognition using a wearable graphene strain gauge sensor

Silent speech recognition is the ability to recognise intended speech without audio information. Useful applications can be found in situations where sound waves are not produced or cannot be heard. Examples include speakers with physical voice impairments or environments in which audio transference is not reliable or secure. Developing a device which can detect non-auditory signals and map them to intended phonation could be used to develop a device to assist in such situations. In this work, we propose a graphene-based strain gauge sensor which can be worn on the throat and detect small muscle movements and vibrations. Machine learning algorithms then decode the non-audio signals and create a prediction on intended speech. The proposed strain gauge sensor is highly wearable, utilising graphene’s unique and beneficial properties including strength, flexibility and high conductivity. A highly flexible and wearable sensor able to pick up small throat movements is fabricated by screen printing graphene onto lycra fabric. A framework for interpreting this information is proposed which explores the use of several machine learning techniques to predict intended words from the signals. A dataset of 15 unique words and four movements, each with 20 repetitions, was developed and used for the training of the machine learning algorithms. The results demonstrate the ability for such sensors to be able to predict spoken words. We produced a word accuracy rate of 55% on the word dataset and 85% on the movements dataset. This work demonstrates a proof-of-concept for the viability of combining a highly wearable graphene strain gauge and machine leaning methods to automate silent speech recognition.EP/S023046/

A genome scale metabolic network for rice and accompanying analysis of tryptophan, auxin and serotonin biosynthesis regulation under biotic stress

Background Functional annotations of large plant genome projects mostly provide information on gene function and gene families based on the presence of protein domains and gene homology, but not necessarily in association with gene expression or metabolic and regulatory networks. These additional annotations are necessary to understand the physiology, development and adaptation of a plant and its interaction with the environment. Results RiceCyc is a metabolic pathway networks database for rice. It is a snapshot of the substrates, metabolites, enzymes, reactions and pathways of primary and intermediary metabolism in rice. RiceCyc version 3.3 features 316 pathways and 6,643 peptide-coding genes mapped to 2,103 enzyme-catalyzed and 87 protein-mediated transport reactions. The initial functional annotations of rice genes with InterPro, Gene Ontology, MetaCyc, and Enzyme Commission (EC) numbers were enriched with annotations provided by KEGG and Gramene databases. The pathway inferences and the network diagrams were first predicted based on MetaCyc reference networks and plant pathways from the Plant Metabolic Network, using the Pathologic module of Pathway Tools. This was enriched by manually adding metabolic pathways and gene functions specifically reported for rice. The RiceCyc database is hierarchically browsable from pathway diagrams to the associated genes, metabolites and chemical structures. Through the integrated tool OMICs Viewer, users can upload transcriptomic, proteomic and metabolomic data to visualize expression patterns in a virtual cell. RiceCyc, along with additional species-specific pathway databases hosted in the Gramene project, facilitates comparative pathway analysis. Conclusions Here we describe the RiceCyc network development and discuss its contribution to rice genome annotations. As a case study to demonstrate the use of RiceCyc network as a discovery environment we carried out an integrated bioinformatic analysis of rice metabolic genes that are differentially regulated under diurnal photoperiod and biotic stress treatments. The analysis of publicly available rice transcriptome datasets led to the hypothesis that the complete tryptophan biosynthesis and its dependent metabolic pathways including serotonin biosynthesis are induced by taxonomically diverse pathogens while also being under diurnal regulation. The RiceCyc database is available online for free access at http://www.gramene.org/pathway