Comprehensive genotyping of the USA national maize inbred seed bank

Background

Genotyping by sequencing, a new low-cost, high-throughput sequencing technology was used to genotype 2,815 maize inbred accessions, preserved mostly at the National Plant Germplasm System in the USA. The collection includes inbred lines from breeding programs all over the world.

Results

The method produced 681,257 single-nucleotide polymorphism (SNP) markers distributed across the entire genome, with the ability to detect rare alleles at high confidence levels. More than half of the SNPs in the collection are rare. Although most rare alleles have been incorporated into public temperate breeding programs, only a modest amount of the available diversity is present in the commercial germplasm. Analysis of genetic distances shows population stratification, including a small number of large clusters centered on key lines. Nevertheless, an average fixation index of 0.06 indicates moderate differentiation between the three major maize subpopulations. Linkage disequilibrium (LD) decays very rapidly, but the extent of LD is highly dependent on the particular group of germplasm and region of the genome. The utility of these data for performing genome-wide association studies was tested with two simply inherited traits and one complex trait. We identified trait associations at SNPs very close to known candidate genes for kernel color, sweet corn, and flowering time; however, results suggest that more SNPs are needed to better explore the genetic architecture of complex traits.

Conclusions

The genotypic information described here allows this publicly available panel to be exploited by researchers facing the challenges of sustainable agriculture through better knowledge of the nature of genetic diversity.     

Signaling role of nitric oxide in the induction of plant defense by exogenous application of abiotic inducers

The objective of this work was to search out the probable molecule behind the activation of broad spectrum resistance during abiotic elicitors such as arachidonic acid, cupric chloride, chitosan, isonicotinic acid and salicylic acid mediated induced systemic resistance (ISR) in Raphanus sativus L. The elicitor compounds were sprayed on the radish leaves of healthy plant and after 24 h incubation a significant increase of β-1,3 glucanase, peroxidase, polyphenol oxidase and phenolics as well as a remarkable increase of nitric oxide (NO), a probable potent defense-signaling molecule in plant, was observed. Furthermore, treatment of the host with NO donor, sodium nitroprusside, also induced the same defense molecules. The results suggests that NO might be the signaling molecule during abiotic elicitor mediated ISR induction in the host system.     

Polysaccharide-rich fraction of Termitomyces eurhizus accelerate healing of indomethacin induced gastric ulcer in mice

The current study aims to determine the healing activity of water soluble polysaccharide-rich fraction of a wild mushroom, Termitomyces eurhizus (TEps) against the indomethacin induced gastric ulceration in mice model. Gastric tissue histology, myeloperoxidase (MPO) activity, cyclooxygenases (COX) 1 and 2 expression, prostaglandin E₂ (PGE₂) synthesis, and modulation of pro/anti inflammatory cytokines expression were studied for this purpose. Histological study shows that TEps (20 mg/kg) effectively healed the gastric ulceration. Based on biochemical results, the healing capacities of TEps could be attributed to reduction of MPO activity and protection of mucosal mucin content. Enhanced synthesis of PGE₂ by modulation of COX-1 and COX-2 expression and a prominent shift of cytokines expression from pro (TNF-α, IL-1ß) to anti inflammatory (IL-10) side are also held responsible for ulcer healing. The preliminary study highlights the anti-ulcerogenic property of polysaccharide-rich fraction of Termitomyces eurhizus and opens an alternative cure for NSAID induced gastroduodenal diseases.     

Elemental stoichiometry of basal resources and benthic macroinvertebrates along a land use gradient in a Great Basin watershed

The effects of land use on the elemental stoichiometry of aquatic organisms have rarely been studied in semi-arid watersheds. In eight semi-arid sub-watersheds differing in land use, we determined which predictor variable(s) best explains the elemental variability in two basal food resources and benthic macroinvertebrates (BMI). The elemental composition of periphyton and seston was best explained by percentage of urban and agricultural areas, forested land and associated differences in SRP, DOC, and stream water N:P ratios. In contrast, consumer elemental stoichiometry was related to taxonomic identity and feeding mode. Elemental imbalances were higher for collector-gatherer than for scraper and collector-filterer. However, high spatial and temporal variability in the elemental composition of basal food resources obscured clear spatial patterns of imbalances between nutrient-poor upstream and nutrient-rich downstream sites. Results from this study suggest that land use can affect BMI due to alteration in stoichiometry of their food resources. However, taxonomy and allometry must be taken into account to better understand spatial and temporal changes in the elemental composition of BMI. Our results indicate the importance of considering multiple effects to accurately assess land use effects on producer and consumer stoichiometry, particularly the in highly variable Great Basin watersheds.     

Structural Basis for Highly Effective HIV-1 Neutralization by CD4-Mimetic Miniproteins Revealed by 1.5 Å Cocrystal Structure of gp120 and M48U1

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Application of higher order statistics for atrial arrhythmia classification

Atrial fibrillation (AF) and atrial flutter (AFL) are the two common atrial arrhythmia encountered in the clinical practice. In order to diagnose these abnormalities the electrocardiogram (ECG) is widely used. The conventional linear time and frequency domain methods cannot decipher the hidden complexity present in these signals. The ECG is inherently a non-linear, non-stationary and non-Gaussian signal. The non-linear models can provide improved results and capture minute variations present in the time series. Higher order spectra (HOS) is a non-linear dynamical method which is highly rugged to noise. In the present study, the performances of two methods are compared: (i) 3rd order HOS cumulants and (ii) HOS bispectrum. The 3rd order cumulant and bispectrum coefficients are subjected to dimensionality reduction using independent component analysis (ICA) and classified using classification and regression tree (CART), random forest (RF), artificial neural network (ANN) and k-nearest neighbor (KNN) classifiers to select the best classifier. The ICA components of cumulant coefficients have provided the average accuracy, sensitivity, specificity and positive predictive value of 99.50%, 100%, 99.22% and 99.72% respectively using KNN classifier. Similarly, the ICA components of HOS bispectrum coefficients have yielded the average accuracy, sensitivity, specificity and PPV of 97.65%, 98.16%, 98.75% and 99.53% respectively using KNN. So, the ICA performed on the 3rd order HOS cumulants coupled with KNN classifier performed better than the HOS bispectrum method. The proposed methodology is robust and can be used in mass screening of cardiac patients.     

ECG beat classification using PCA,LDA, ICA and Discrete Wavelet Transform

Electrocardiogram (ECG) is the P-QRS-T wave, representing the cardiac function. The information concealed in the ECG signal is useful in detecting the disease afflicting the heart. It is very difficult to identify the subtle changes in the ECG in time and frequency domains. The Discrete Wavelet Transform (DWT) can provide good time and frequency resolutions and is able to decipher the hidden complexities in the ECG. In this study, five types of beat classes of arrhythmia as recommended by Association for Advancement of Medical Instrumentation (AAMI) were analyzed namely: non-ectopic beats, supra-ventricular ectopic beats, ventricular ectopic beats, fusion betas and unclassifiable and paced beats. Three dimensionality reduction algorithms; Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA) and Independent Component Analysis (ICA) were independently applied on DWT sub bands for dimensionality reduction. These dimensionality reduced features were fed to the Support Vector Machine (SVM), neural network (NN) and probabilistic neural network (PNN) classifiers for automated diagnosis. ICA features in combination with PNN with spread value (σ) of 0.03 performed better than the PCA and LDA. It has yielded an average sensitivity, specificity, positive predictive value (PPV) and accuracy of 99.97%, 99.83%, 99.21% and 99.28% respectively using ten-fold cross validation scheme.     

Functional significance of active site residues in the enzymatic component of the Clostridium difficile binary toxin

Clostridium difficile binary toxin (CDT) is an ADP-ribosyltransferase which is linked to enhanced pathogenesis of C. difficile strains. CDT has dual function: domain a (CDTa) catalyses the ADP-ribosylation of actin (enzymatic component), whereas domain b (CDTb) transports CDTa into the cytosol (transport component). Understanding the molecular mechanism of CDT is necessary to assess its role in C. difficile infection. Identifying amino acids that are essential to CDTa function may aid drug inhibitor design to control the severity of C. difficile infections. Here we report mutations of key catalytic residues within CDTa and their effect on CDT cytotoxicity. Rather than an all-or-nothing response, activity of CDTa mutants vary with the type of amino acid substitution; S345A retains cytotoxicity whereas S345Y was sufficient to render CDT non-cytotoxic. Thus CDTa cytotoxicity levels are directly linked to ADP-ribosyltransferase activity.