Sequence based polymorphic (SBP) marker technology for targeted genomic regions: its application in generating a molecular map of the Arabidopsis thaliana genome

<p>Abstract</p> <p>Background</p> <p>Molecular markers facilitate both genotype identification, essential for modern animal and plant breeding, and the isolation of genes based on their map positions. Advancements in sequencing technology have made possible the identification of single nucleotide polymorphisms (SNPs) for any genomic regions. Here a sequence based polymorphic (SBP) marker technology for generating molecular markers for targeted genomic regions in Arabidopsis is described.</p> <p>Results</p> <p>A ~3X genome coverage sequence of the <it>Arabidopsis thaliana </it>ecotype, Niederzenz (Nd-0) was obtained by applying Illumina's sequencing by synthesis (Solexa) technology. Comparison of the Nd-0 genome sequence with the assembled Columbia-0 (Col-0) genome sequence identified putative single nucleotide polymorphisms (SNPs) throughout the entire genome. Multiple 75 base pair Nd-0 sequence reads containing SNPs and originating from individual genomic DNA molecules were the basis for developing co-dominant SBP markers. SNPs containing Col-0 sequences, supported by transcript sequences or sequences from multiple BAC clones, were compared to the respective Nd-0 sequences to identify possible restriction endonuclease enzyme site variations. Small amplicons, PCR amplified from both ecotypes, were digested with suitable restriction enzymes and resolved on a gel to reveal the sequence based polymorphisms. By applying this technology, 21 SBP markers for the marker poor regions of the Arabidopsis map representing polymorphisms between Col-0 and Nd-0 ecotypes were generated.</p> <p>Conclusions</p> <p>The SBP marker technology described here allowed the development of molecular markers for targeted genomic regions of Arabidopsis. It should facilitate isolation of co-dominant molecular markers for targeted genomic regions of any animal or plant species, whose genomic sequences have been assembled. This technology will particularly facilitate the development of high density molecular marker maps, essential for cloning genes based on their genetic map positions and identifying tightly linked molecular markers for selecting desirable genotypes in animal and plant breeding experiments.</p

The Genome Sequence of the Fungal Pathogen Fusarium virguliforme That Causes Sudden Death Syndrome in Soybean

Fusarium virguliforme causes sudden death syndrome (SDS) of soybean, a disease of serious concern throughout most of the soybean producing regions of the world. Despite the global importance, little is known about the pathogenesis mechanisms of F. virguliforme. Thus, we applied Next-Generation DNA Sequencing to reveal the draft F. virguliforme genome sequence and identified putative pathogenicity genes to facilitate discovering the mechanisms used by the pathogen to cause this disease

Tanscriptomic Study of the Soybean-Fusarium virguliforme Interaction Revealed a Novel Ankyrin-Repeat Containing Defense Gene, Expression of Whose during Infection Led to Enhanced Resistance to the Fungal Pathogen in Transgenic Soybean Plants

Fusarium virguliforme causes the serious disease sudden death syndrome (SDS) in soybean. Host resistance to this pathogen is partial and is encoded by a large number of quantitative trait loci, each conditioning small effects. Breeding SDS resistance is therefore challenging and identification of single-gene encoded novel resistance mechanisms is becoming a priority to fight this devastating this fungal pathogen. In this transcriptomic study we identified a few putative soybean defense genes, expression of which is suppressed during F. virguliformeinfection. The F. virguliforme infection-suppressed genes were broadly classified into four major classes. The steady state transcript levels of many of these genes were suppressed to undetectable levels immediately following F. virguliforme infection. One of these classes contains two novel genes encoding ankyrin repeat-containing proteins. Expression of one of these genes, GmARP1, during F. virguliforme infection enhances SDS resistance among the transgenic soybean plants. Our data suggest that GmARP1 is a novel defense gene and the pathogen presumably suppress its expression to establish compatible interaction

On the Significance of Process Comprehension for Conducting Targeted ICS Attacks

The exploitation of Industrial Control Systems (ICSs) has been described as both easy and impossible, where is the truth? Post-Stuxnet works have included a plethora of ICS focused cyber secu- rity research activities, with topics covering device maturity, network protocols, and overall cyber security culture. We often hear the notion of ICSs being highly vulnerable due to a lack of inbuilt security mechanisms, considered a low hanging fruit to a variety of low skilled threat actors. While there is substantial evidence to support such a notion, when considering targeted attacks on ICS, it is hard to believe an attacker with limited resources, such as a script kiddie or hacktivist, using publicly accessible tools and exploits alone, would have adequate knowledge and resources to achieve targeted operational process manipulation, while simultaneously evade detection. Through use of a testbed environment, this paper provides two practical examples based on a Man-In-The-Middle scenario, demonstrating the types of information an attacker would need obtain, collate, and comprehend, in order to begin targeted process manipulation and detection avoidance. This allows for a clearer view of associated challenges, and illustrate why targeted ICS exploitation might not be possible for every malicious actor

Nitrogen Challenges and Opportunities for Agricultural and Environmental Science in India

In the last six decades, the consumption of reactive nitrogen (Nr) in the form of fertilizer in India has been growing rapidly, whilst the nitrogen use efficiency (NUE) of cropping systems has been decreasing. These trends have led to increasing environmental losses of Nr, threatening the quality of air, soils, and fresh waters, and thereby endangering climate-stability, ecosystems, and human-health. Since it has been suggested that the fertilizer consumption of India may double by 2050, there is an urgent need for scientific research to support better nitrogen management in Indian agriculture. In order to share knowledge and to develop a joint vision, experts from the UK and India came together for a conference and workshop on “Challenges and Opportunities for Agricultural Nitrogen Science in India.” The meeting concluded with three core messages: (1) Soil stewardship is essential and legumes need to be planted in rotation with cereals to increase nitrogen fixation in areas of limited Nr availability. Synthetic symbioses and plastidic nitrogen fixation are possibly disruptive technologies, but their potential and implications must be considered. (2) Genetic diversity of crops and new technologies need to be shared and exploited to reduce N losses and support productive, sustainable agriculture livelihoods. Móring et al. Nitrogen Challenges and Opportunities (3) The use of leaf color sensing shows great potential to reduce nitrogen fertilizer use (by 10–15%). This, together with the usage of urease inhibitors in neem-coated urea, and better management of manure, urine, and crop residues, could result in a 20–25% improvement in NUE of India by 2030

Pathobiological Implications of MUC16 Expression in Pancreatic Cancer

MUC16 (CA125) belongs to a family of high-molecular weight O-glycosylated proteins known as mucins. While MUC16 is well known as a biomarker in ovarian cancer, its expression pattern in pancreatic cancer (PC), the fourth leading cause of cancer related deaths in the United States, remains unknown. The aim of our study was to analyze the expression of MUC16 during the initiation, progression and metastasis of PC for possible implication in PC diagnosis, prognosis and therapy. In this study, a microarray containing tissues from healthy and PC patients was used to investigate the differential protein expression of MUC16 in PC. MUC16 mRNA levels were also measured by RT-PCR in the normal human pancreatic, pancreatitis, and PC tissues. To investigate its expression pattern during PC metastasis, tissue samples from the primary pancreatic tumor and metastases (from the same patient) in the lymph nodes, liver, lung and omentum from Stage IV PC patients were analyzed. To determine its association in the initiation of PC, tissues from PC patients containing pre-neoplastic lesions of varying grades were stained for MUC16. Finally, MUC16 expression was analyzed in 18 human PC cell lines. MUC16 is not expressed in the normal pancreatic ducts and is strongly upregulated in PC and detected in pancreatitis tissue. It is first detected in the high-grade pre-neoplastic lesions preceding invasive adenocarcinoma, suggesting that its upregulation is a late event during the initiation of this disease. MUC16 expression appears to be stronger in metastatic lesions when compared to the primary tumor, suggesting a role in PC metastasis. We have also identified PC cell lines that express MUC16, which can be used in future studies to elucidate its functional role in PC. Altogether, our results reveal that MUC16 expression is significantly increased in PC and could play a potential role in the progression of this disease

Nations within a nation: variations in epidemiological transition across the states of India, 1990–2016 in the Global Burden of Disease Study

18% of the world's population lives in India, and many states of India have populations similar to those of large countries. Action to effectively improve population health in India requires availability of reliable and comprehensive state-level estimates of disease burden and risk factors over time. Such comprehensive estimates have not been available so far for all major diseases and risk factors. Thus, we aimed to estimate the disease burden and risk factors in every state of India as part of the Global Burden of Disease (GBD) Study 2016

Preparation of InSe Thin Films by Thermal Evaporation Method and Their Characterization: Structural, Optical, and Thermoelectrical Properties

The indium selenium (InSe) bilayer thin films of various thickness ratios, InxSe(1-x) (x = 0.25, 0.50, 0.75), were deposited on a glass substrate keeping overall the same thickness of 2500 Ǻ using thermal evaporation method under high vacuum atmosphere. Electrical, optical, and structural properties of these bilayer thin films have been compared before and after thermal annealing at different temperatures. The structural and morphological characterization was done using XRD and SEM, respectively. The optical bandgap of these thin films has been calculated by Tauc’s relation that varies within the range of 1.99 to 2.05 eV. A simple low-cost thermoelectrical power measurement setup is designed which can measure the Seebeck coefficient “S” in the vacuum with temperature variation. The setup temperature variation is up to 70°C. This setup contains a Peltier device TEC1-12715 which is kept between two copper plates that act as a reference metal. Also, in the present work, the thermoelectric power of indium selenide (InSe) and aluminum selenide (AlSe) bilayer thin films prepared and annealed in the same way is calculated. The thermoelectric power has been measured by estimating the Seebeck coefficient for InSe and AlSe bilayer thin films. It was observed that the Seebeck coefficient is negative for InSe and AlSe thin films

Thermoelectric properties of InSe and AlSe bilayer thin films

101-105The indium selenide (InSe) and aluminum selenide (AlSe) bilayer thin films of different thickness ratio have been prepared using thermal evaporation at vacuum. Thermoelectric behaviour of each sample has been determined temperature regions of 300-310 K. The thermoelectric behaviour of prepared thin films has been found to improve when samples have been annealed in vacuum at 70 ºC and 100 ºC. Electrical studies have been carried out of each film before and after annealing

Empirical Analysis of Supervised and Unsupervised Filter based Feature Selection Methods for Breast Cancer Classification from Digital Mammograms

In the design and development of an automated CAD tool for breast cancer detection and diagnosis, the various steps include enhancement, segmentation, feature extraction, feature selection and classification. The feature selection plays an important role in the design of the said CAD tool as it aims towards the redundant feature elimination and relevant feature selection. The selected feature set also decides the efficacy of the chosen classifier for classification of mammograms. In literature, various filter based feature selection methods exists under unsupervised and supervised categories based on different basis criterion. The filter based feature selection methods ranks the extracted feature sets based on some criteria in descending order of their importance. The various methods produce different feature subsets which are associated with different performance measures. In this paper, an evaluation and comparative study of various unsupervised and supervised feature selection methods are presented for breast cancer classification from digital mammograms though various classifiers. The study aims towards finding out the better feature selection method and associated classifier which gives better performance