The effects of sorghum and cowpea genotype and sorghum sowing density in an intercrop system.

Five diverse sorghum genotypes were sown at sole crop density and at intercrop density with-out cowpea and with two contrasting cowpea genotypes, in the post-rainy season at Hyderabad, India. The interaction of sorghum genotype with sowing density was significant for sorghum dry fodder and grain yield, but the interaction of sorghum genotype with cowpea was not, because of compensation between yield components. The likely response of sorghum genotypes to intercropping can therefore be assessed initially from the performance of low density sole crops, followed by assessment in the presence of a single standard cowpea variety. The cowpea genotypes were affected by the presence of sorghum but not by the sorghum genotype. This suggests that the effect on the cowpea can be ignored when selecting a sorghum genotype for intercropping, and that a cowpea genotype for intercropping can be selected in the presence of a single sorghum genotype. However, these conclusions are unlikery to apply to rain season sowings, when sorghum dominates the intercrop more completely

Dehydration mechanism of a small molecular solid: 5-nitrouracil hydrate

Previous studies of the dehydration of 5-nitrouracil (5NU) have resulted in it being classified as a ‘‘channel hydrate’’ in which dehydration proceeds principally by the exit of the water molecules along channels in the structure. We have re-examined this proposal and found that in fact there are no continuous channels in the 5NU structure that would contribute to such a mechanism. Product water molecules would be immediately trapped in unlinked voids in the crystal structure and would require some additional mechanism to break loose from the crystal. Through a detailed structural analysis of the macro and micro structure of the 5NU as it dehydrates, we have developed a model for the dehydration process based on the observed development of structural defects in the 5NU crystal and the basic crystallography of the material. The model was tested against standard kinetic measurements and found to present a satisfactory account of kinetic observations, thus defining the mechanism. Overall, the study shows the necessity of complementing standard kinetic studies with a parallel macro and micro examination of the dehydrating material when evaluating the mechanisms of dehydration and decomposition processes

Genotypic variation in the response of sorghum to intercropping with cowpea, and in the effect on the associated legume.

Selection of sorghum genotypes for the sorghum-cowpea intercrop system would be simplified if it could be done in sole crop. In order to compare evaluation in sole crop and in the presence of the standard cowpea cultivar c 152, sorghum inbred lines, F2 hybrids and land races which differed in maturity date, height and canopy characters were grown in the two systems in two seasons at Hyderabad,India. Cowpea sole crop was included as an additional treatment. Sorghum canopy characters and yield components in intercrop were highly correlated with the same characters in sole crop. How-ever, multiple regression of sorghum grain yield in intercrop on characters measured in sole crop. Characters related to light interception were the most influential in determining sorghum yield, but some genetically determined variation in yield was unexplained by either multiple regression. Characters related to light interception had a negative influence on cowpea yield, though again some variation due to sorghum genotype was unexplained. Thus although the influence of sorghum plant characters on each component crop is predictable, compensation between the components makes the overall outcome more difficult to predict, and dependent upon which component isfavoured by the environment. The sorghum genotypes selected will therefore represent a compromise: they should not be dwarf types, but should be early maturing to escape drought, and have narrow canopies so as not to be too competitive on the cowpea. The final selection should be made in intercrop

Integrated analysis of dermal blister fluid proteomics and genome-wide skin gene expression in systemic sclerosis: an observational study

Background: Skin fibrosis is a hallmark feature of systemic sclerosis. Skin biopsy transcriptomics and blister fluid proteomics give insight into the local environment of the skin. We have integrated these modalities with the aim of developing a surrogate for the modified Rodnan skin score (mRSS), using candidate genes and proteins from the skin and blister fluid as anchors to identify key analytes in the plasma. Methods: In this single-centre, prospective observational study at the Royal Free Campus, University College London, London, UK, transcriptional and proteomic analyses of blood and skin were performed in a cohort of patients with systemic sclerosis (n=52) and healthy controls (n=16). Weighted gene co-expression network analysis was used to explore the association of skin transcriptomics data, clinical traits, and blister fluid proteomic results. Candidate hub analytes were identified as those present in both blister and skin gene sets (modules), and which correlated with plasma (module membership >0·7 and gene significance >0·6). Hub analytes were confirmed using RNA transcript data obtained from skin biopsy samples from patients with early diffuse cutaneous systemic sclerosis at 12 months. Findings: We identified three modules in the skin, and two in blister fluid, which correlated with a diagnosis of early diffuse cutaneous systemic sclerosis. From these modules, 11 key hub analytes were identified, present in both skin and blister fluid modules, whose transcript and protein levels correlated with plasma protein concentrations, mRSS, and showed statistically significant correlation on repeat transcriptomic samples taken at 12 months. Multivariate analysis identified four plasma analytes as correlates of mRSS (COL4A1, COMP, SPON1, and TNC), which can be used to differentiate disease subtype. Interpretation: This unbiased approach has identified potential biological candidates that might be drivers of local skin pathogenesis in systemic sclerosis. By focusing on measurable analytes in the plasma, we generated a promising composite plasma protein biomarker that could be used for assessment of skin severity, case stratification, and as a potential outcome measure for clinical trials and practice. Once fully validated, the biomarker score could replace a clinical score such as the mRSS, which carries substantial variability. Funding: GlaxoSmithKline and UK Medical Research Council

Molecular basis for clinical diversity between autoantibody subsets in diffuse cutaneous systemic sclerosis.

OBJECTIVES: Clinical heterogeneity is a cardinal feature of systemic sclerosis (SSc). Hallmark SSc autoantibodies are central to diagnosis and associate with distinct patterns of skin-based and organ-based complications. Understanding molecular differences between patients will benefit clinical practice and research and give insight into pathogenesis of the disease. We aimed to improve understanding of the molecular differences between key diffuse cutaneous SSc subgroups as defined by their SSc-specific autoantibodies METHODS: We have used high-dimensional transcriptional and proteomic analysis of blood and the skin in a well-characterised cohort of SSc (n=52) and healthy controls (n=16) to understand the molecular basis of clinical diversity in SSc and explore differences between the hallmark antinuclear autoantibody (ANA) reactivities. RESULTS: Our data define a molecular spectrum of SSc based on skin gene expression and serum protein analysis, reflecting recognised clinical subgroups. Moreover, we show that antitopoisomerase-1 antibodies and anti-RNA polymerase III antibodies specificities associate with remarkably different longitudinal change in serum protein markers of fibrosis and divergent gene expression profiles. Overlapping and distinct disease processes are defined using individual patient pathway analysis. CONCLUSIONS: Our findings provide insight into clinical diversity and imply pathogenetic differences between ANA-based subgroups. This supports stratification of SSc cases by ANA antibody subtype in clinical trials and may explain different outcomes across ANA subgroups in trials targeting specific pathogenic mechanisms

Integrating personality research and animal contest theory: aggressiveness in the green swordtail <i>Xiphophorus helleri</i>

&lt;p&gt;Aggression occurs when individuals compete over limiting resources. While theoretical studies have long placed a strong emphasis on context-specificity of aggression, there is increasing recognition that consistent behavioural differences exist among individuals, and that aggressiveness may be an important component of individual personality. Though empirical studies tend to focus on one aspect or the other, we suggest there is merit in modelling both within-and among-individual variation in agonistic behaviour simultaneously. Here, we demonstrate how this can be achieved using multivariate linear mixed effect models. Using data from repeated mirror trials and dyadic interactions of male green swordtails, &lt;i&gt;Xiphophorus helleri&lt;/i&gt;, we show repeatable components of (co)variation in a suite of agonistic behaviour that is broadly consistent with a major axis of variation in aggressiveness. We also show that observed focal behaviour is dependent on opponent effects, which can themselves be repeatable but were more generally found to be context specific. In particular, our models show that within-individual variation in agonistic behaviour is explained, at least in part, by the relative size of a live opponent as predicted by contest theory. Finally, we suggest several additional applications of the multivariate models demonstrated here. These include testing the recently queried functional equivalence of alternative experimental approaches, (e. g., mirror trials, dyadic interaction tests) for assaying individual aggressiveness.&lt;/p&gt

Quantifying possible bias in clinical and epidemiological studies with quantitative bias analysis: common approaches and limitations

Bias in epidemiological studies can adversely affect the validity of study findings. Sensitivity analyses, known as quantitative bias analyses, are available to quantify potential residual bias arising from measurement error, confounding, and selection into the study. Effective application of these methods benefits from the input of multiple parties including clinicians, epidemiologists, and statisticians. This article provides an overview of a few common methods to facilitate both the use of these methods and critical interpretation of applications in the published literature. Examples are given to describe and illustrate methods of quantitative bias analysis. This article also outlines considerations to be made when choosing between methods and discusses the limitations of quantitative bias analysis

An exploratory phenome wide association study linking asthma and liver disease genetic variants to electronic health records from the Estonian Biobank

<div><p>The Estonian Biobank, governed by the Institute of Genomics at the University of Tartu (Biobank), has stored genetic material/DNA and continuously collected data since 2002 on a total of 52,274 individuals representing ~5% of the Estonian adult population and is increasing. To explore the utility of data available in the Biobank, we conducted a phenome-wide association study (PheWAS) in two areas of interest to healthcare researchers; asthma and liver disease. We used 11 asthma and 13 liver disease-associated single nucleotide polymorphisms (SNPs), identified from published genome-wide association studies, to test our ability to detect established associations. We confirmed 2 asthma and 5 liver disease associated variants at nominal significance and directionally consistent with published results. We found 2 associations that were opposite to what was published before (rs4374383:AA increases risk of NASH/NAFLD, rs11597086 increases ALT level). Three SNP-diagnosis pairs passed the phenome-wide significance threshold: rs9273349 and E06 (thyroiditis, p = 5.50x10^-8); rs9273349 and E10 (type-1 diabetes, p = 2.60x10^-7); and rs2281135 and K76 (non-alcoholic liver diseases, including NAFLD, p = 4.10x10^-7). We have validated our approach and confirmed the quality of the data for these conditions. Importantly, we demonstrate that the extensive amount of genetic and medical information from the Estonian Biobank can be successfully utilized for scientific research.</p></div

Gene-Based Tests of Association

Genome-wide association studies (GWAS) are now used routinely to identify SNPs associated with complex human phenotypes. In several cases, multiple variants within a gene contribute independently to disease risk. Here we introduce a novel Gene-Wide Significance (GWiS) test that uses greedy Bayesian model selection to identify the independent effects within a gene, which are combined to generate a stronger statistical signal. Permutation tests provide p-values that correct for the number of independent tests genome-wide and within each genetic locus. When applied to a dataset comprising 2.5 million SNPs in up to 8,000 individuals measured for various electrocardiography (ECG) parameters, this method identifies more validated associations than conventional GWAS approaches. The method also provides, for the first time, systematic assessments of the number of independent effects within a gene and the fraction of disease-associated genes housing multiple independent effects, observed at 35%–50% of loci in our study. This method can be generalized to other study designs, retains power for low-frequency alleles, and provides gene-based p-values that are directly compatible for pathway-based meta-analysis