Interaction between row-type genes in barley controls meristem determinacy and reveals novel routes to improved grain

Hordeum species develop a central spikelet flanked by two lateral spikelets at each inflorescence node. In 'two-rowed' spikes, the central spikelet alone is fertile and sets grain, while in 'six-rowed' spikes, lateral spikelets can also produce grain. Induced loss-of-function alleles of any of five Six-rowed spike (VRS) genes (VRS1-5) cause complete to intermediate gains of lateral spikelet fertility. Current six-row cultivars contain natural defective vrs1 and vrs5 alleles. Little information is known about VRS mechanism(s). We used comparative developmental, expression and genetic analyses on single and double vrs mutants to learn more about how VRS genes control development and assess their agronomic potential. We show that all VRS genes repress fertility at carpel and awn emergence in developing lateral spikelets. VRS4, VRS3 and VRS5 work through VRS1 to suppress fertility, probably by inducing VRS1 expression. Pairing vrs3, vrs4 or vrs5 alleles increased lateral spikelet fertility, despite the presence of a functional VRS1 allele. The vrs3 allele caused loss of spikelet identity and determinacy, improved grain homogeneity and increased tillering in a vrs4 background, while with vrs5, decreased tiller number and increased grain weight. Interactions amongst VRS genes control spikelet infertility, determinacy and outgrowth, and novel routes to improving six-row grain.Monika Zwirek, Robbie Waugh, Sarah M. McKi

Seasonal changes in patterns of gene expression in avian song control brain regions.

This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Photoperiod and hormonal cues drive dramatic seasonal changes in structure and function of the avian song control system. Little is known, however, about the patterns of gene expression associated with seasonal changes. Here we address this issue by altering the hormonal and photoperiodic conditions in seasonally-breeding Gambel's white-crowned sparrows and extracting RNA from the telencephalic song control nuclei HVC and RA across multiple time points that capture different stages of growth and regression. We chose HVC and RA because while both nuclei change in volume across seasons, the cellular mechanisms underlying these changes differ. We thus hypothesized that different genes would be expressed between HVC and RA. We tested this by using the extracted RNA to perform a cDNA microarray hybridization developed by the SoNG initiative. We then validated these results using qRT-PCR. We found that 363 genes varied by more than 1.5 fold (>log(2) 0.585) in expression in HVC and/or RA. Supporting our hypothesis, only 59 of these 363 genes were found to vary in both nuclei, while 132 gene expression changes were HVC specific and 172 were RA specific. We then assigned many of these genes to functional categories relevant to the different mechanisms underlying seasonal change in HVC and RA, including neurogenesis, apoptosis, cell growth, dendrite arborization and axonal growth, angiogenesis, endocrinology, growth factors, and electrophysiology. This revealed categorical differences in the kinds of genes regulated in HVC and RA. These results show that different molecular programs underlie seasonal changes in HVC and RA, and that gene expression is time specific across different reproductive conditions. Our results provide insights into the complex molecular pathways that underlie adult neural plasticity

IFNAR1-Signalling Obstructs ICOS-mediated Humoral Immunity during Non-lethal Blood-Stage Plasmodium Infection

Funding: This work was funded by a Career Development Fellowship (1028634) and a project grant (GRNT1028641) awarded to AHa by the Australian National Health & Medical Research Council (NHMRC). IS was supported by The University of Queensland Centennial and IPRS Scholarships. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Peer reviewedPublisher PD

Lymphocyte subsets and the role of Th1/Th2 balance in stressed chronic pain patients

Background: The complex regional pain syndrome (CRPS) and fibromyalgia (FM) are chronic pain syndromes occurring in highly stressed individuals. Despite the known connection between the nervous system and immune cells, information on distribution of lymphocyte subsets under stress and pain conditions is limited. Methods: We performed a comparative study in 15 patients with CRPS type I, 22 patients with FM and 37 age- and sex-matched healthy controls and investigated the influence of pain and stress on lymphocyte number, subpopulations and the Th1/Th2 cytokine ratio in T lymphocytes. Results: Lymphocyte numbers did not differ between groups. Quantitative analyses of lymphocyte subpopulations showed a significant reduction of cytotoxic CD8+ lymphocytes in both CRPS (p < 0.01) and FM (p < 0.05) patients as compared with healthy controls. Additionally, CRPS patients were characterized by a lower percentage of IL-2-producing T cell subpopulations reflecting a diminished Th1 response in contrast to no changes in the Th2 cytokine profile. Conclusions: Future studies are warranted to answer whether such immunological changes play a pathogenetic role in CRPS and FM or merely reflect the consequences of a pain-induced neurohumoral stress response, and whether they contribute to immunosuppression in stressed chronic pain patients. Copyright (c) 2008 S. Karger AG, Basel

Usefulness and engagement with a guided workbook intervention (WorkPlan) to support work related goals among cancer survivors

Background: Returning to work after cancer is associated with improved physical and psychological functioning, but managing this return can be a challenging process. A workbook based intervention (WorkPlan) was developed to support return-to-work among cancer survivors. The aim of this study was to explore how participants using the workbook engaged with the intervention and utilised the content of the intervention in their plan to return-to-work. Methods: As part of a feasibility randomised controlled trial, 23 participants from the intervention group were interviewed 4-weeks post intervention. Interviews focussed on intervention delivery and data was analysed using Framework analysis. Results: Participants revealed a sense of empowerment and changes in their outlook as they transitioned from patient to employee, citing the act of writing as a medium for creating their own return-to-work narrative. Participants found the generation of a return-to-work plan useful for identifying potential problems and solutions, which also served as a tool for aiding discussion with the employer on return-to-work. Additionally, participants reported feeling less uncertain and anxious about returning to work. Timing of the intervention in coordination with ongoing cancer treatments was crucial to perceived effectiveness; participants identified the sole or final treatment as the ideal time to receive the intervention. Conclusions: The self-guided workbook supports people diagnosed with cancer to build their communication and planning skills to successfully manage their return-to-work. Further research could examine how writing plays a role in this process

Global analysis of gene expression in NGF-deprived sympathetic neurons identifies molecular pathways associated with cell death

Developing sympathetic neurons depend on nerve growth factor (NGF) for survival and die by apoptosis after NGF withdrawal. This process requires de novo gene expression but only a small number of genes induced by NGF deprivation have been identified so far, either by a candidate gene approach or in mRNA differential display experiments. This is partly because it is difficult to obtain large numbers of sympathetic neurons for in vitro studies. Here, we describe for the first time, how advances in gene microarray technology have allowed us to investigate the expression of all known genes in sympathetic neurons cultured in the presence and absence of NGF

The great time series classification bake off: a review and experimental evaluation of recent algorithmic advances

In the last five years there have been a large number of new time series classification algorithms proposed in the literature. These algorithms have been evaluated on subsets of the 47 data sets in the University of California, Riverside time series classification archive. The archive has recently been expanded to 85 data sets, over half of which have been donated by researchers at the University of East Anglia. Aspects of previous evaluations have made comparisons between algorithms difficult. For example, several different programming languages have been used, experiments involved a single train/test split and some used normalised data whilst others did not. The relaunch of the archive provides a timely opportunity to thoroughly evaluate algorithms on a larger number of datasets. We have implemented 18 recently proposed algorithms in a common Java framework and compared them against two standard benchmark classifiers (and each other) by performing 100 resampling experiments on each of the 85 datasets. We use these results to test several hypotheses relating to whether the algorithms are significantly more accurate than the benchmarks and each other. Our results indicate that only 9 of these algorithms are significantly more accurate than both benchmarks and that one classifier, the Collective of Transformation Ensembles, is significantly more accurate than all of the others. All of our experiments and results are reproducible: we release all of our code, results and experimental details and we hope these experiments form the basis for more rigorous testing of new algorithms in the future

Nutritional correlates of koala persistence in a low-density population

It is widely postulated that nutritional factors drive bottom-up, resource-based patterns in herbivore ecology and distribution. There is, however, much controversy over the roles of different plant constituents and how these influence individual herbivores and herbivore populations. The density of koala (Phascolarctos cinereus) populations varies widely and many attribute population trends to variation in the nutritional quality of the eucalypt leaves of their diet, but there is little evidence to support this hypothesis. We used a nested design that involved sampling of trees at two spatial scales to investigate how leaf chemistry influences free-living koalas from a low-density population in south east New South Wales, Australia. Using koala faecal pellets as a proxy for koala visitation to trees, we found an interaction between toxins and nutrients in leaves at a small spatial scale, whereby koalas preferred trees with leaves of higher concentrations of available nitrogen but lower concentrations of sideroxylonals (secondary metabolites found exclusively in eucalypts) compared to neighbouring trees of the same species. We argue that taxonomic and phenotypic diversity is likely to be important when foraging in habitats of low nutritional quality in providing diet choice to tradeoff nutrients and toxins and minimise movement costs. Our findings suggest that immediate nutritional concerns are an important priority of folivores in low-quality habitats and imply that nutritional limitations play an important role in constraining folivore populations. We show that, with a careful experimental design, it is possible to make inferences about populations of herbivores that exist at extremely low densities and thus achieve a better understanding about how plant composition influences herbivore ecology and persistence.IW and WF received a grant from New South Wales (NSW) Department of Environment, Climate Change & Water

Predicting the Electron Requirement for Carbon Fixation in Seas and Oceans

Marine phytoplankton account for about 50% of all global net primary productivity (NPP). Active fluorometry, mainly Fast Repetition Rate fluorometry (FRRf), has been advocated as means of providing high resolution estimates of NPP. However, not measuring CO2-fixation directly, FRRf instead provides photosynthetic quantum efficiency estimates from which electron transfer rates (ETR) and ultimately CO2-fixation rates can be derived. Consequently, conversions of ETRs to CO2-fixation requires knowledge of the electron requirement for carbon fixation (Φe,C, ETR/CO2 uptake rate) and its dependence on environmental gradients. Such knowledge is critical for large scale implementation of active fluorescence to better characterise CO2-uptake. Here we examine the variability of experimentally determined Φe,C values in relation to key environmental variables with the aim of developing new working algorithms for the calculation of Φe,C from environmental variables. Coincident FRRf and 14C-uptake and environmental data from 14 studies covering 12 marine regions were analysed via a meta-analytical, non-parametric, multivariate approach. Combining all studies, Φe,C varied between 1.15 and 54.2 mol e- (mol C)-1 with a mean of 10.9±6.91 mol e- mol C)-1. Although variability of Φe,C was related to environmental gradients at global scales, region-specific analyses provided far improved predictive capability. However, use of regional Φe,C algorithms requires objective means of defining regions of interest, which remains challenging. Considering individual studies and specific small-scale regions, temperature, nutrient and light availability were correlated with Φe,C albeit to varying degrees and depending on the study/region and the composition of the extant phytoplankton community. At the level of large biogeographic regions and distinct water masses, Φe,C was related to nutrient availability, chlorophyll, as well as temperature and/or salinity in most regions, while light availability was also important in Baltic Sea and shelf waters. The novel Φe,C algorithms provide a major step forward for widespread fluorometry-based NPP estimates and highlight the need for further studying the natural variability of Φe,C to verify and develop algorithms with improved accuracy. © 2013 Lawrenz et al

Pervasive Sharing of Genetic Effects in Autoimmune Disease

Genome-wide association (GWA) studies have identified numerous, replicable, genetic associations between common single nucleotide polymorphisms (SNPs) and risk of common autoimmune and inflammatory (immune-mediated) diseases, some of which are shared between two diseases. Along with epidemiological and clinical evidence, this suggests that some genetic risk factors may be shared across diseases—as is the case with alleles in the Major Histocompatibility Locus. In this work we evaluate the extent of this sharing for 107 immune disease-risk SNPs in seven diseases: celiac disease, Crohn's disease, multiple sclerosis, psoriasis, rheumatoid arthritis, systemic lupus erythematosus, and type 1 diabetes. We have developed a novel statistic for Cross Phenotype Meta-Analysis (CPMA) which detects association of a SNP to multiple, but not necessarily all, phenotypes. With it, we find evidence that 47/107 (44%) immune-mediated disease risk SNPs are associated to multiple—but not all—immune-mediated diseases (SNP-wise PCPMA<0.01). We also show that distinct groups of interacting proteins are encoded near SNPs which predispose to the same subsets of diseases; we propose these as the mechanistic basis of shared disease risk. We are thus able to leverage genetic data across diseases to construct biological hypotheses about the underlying mechanism of pathogenesis