Transcriptome-Wide Association Supplements Genome-Wide Association in Zea mays.

Modern improvement of complex traits in agricultural species relies on successful associations of heritable molecular variation with observable phenotypes. Historically, this pursuit has primarily been based on easily measurable genetic markers. The recent advent of new technologies allows assaying and quantifying biological intermediates (hereafter endophenotypes) which are now readily measurable at a large scale across diverse individuals. The usefulness of endophenotypes for delineating the regulatory landscape of the genome and genetic dissection of complex trait variation remains underexplored in plants. The work presented here illustrated the utility of a large-scale (299-genotype and seven-tissue) gene expression resource to dissect traits across multiple levels of biological organization. Using single-tissue- and multi-tissue-based transcriptome-wide association studies (TWAS), we revealed that about half of the functional variation acts through altered transcript abundance for maize kernel traits, including 30 grain carotenoid abundance traits, 20 grain tocochromanol abundance traits, and 22 field-measured agronomic traits. Comparing the efficacy of TWAS with genome-wide association studies (GWAS) and an ensemble approach that combines both GWAS and TWAS, we demonstrated that results of TWAS in combination with GWAS increase the power to detect known genes and aid in prioritizing likely causal genes. Using a variance partitioning approach in the largely independent maize Nested Association Mapping (NAM) population, we also showed that the most strongly associated genes identified by combining GWAS and TWAS explain more heritable variance for a majority of traits than the heritability captured by the random genes and the genes identified by GWAS or TWAS alone. This not only improves the ability to link genes to phenotypes, but also highlights the phenotypic consequences of regulatory variation in plants

Direct esterification of poly (ethylene glycol) with amino acid hydrochlorides

Diesters of poly (ethylene glycol) with various a amino acid hydrochlorides were synthesized using dicyclohexyl carbodiimide as coupling agent. The use of hydrochloride as amino protecting group in dicyclohexyl carbodiimide mediated condensation reactions of amino acids was demonstrated for the first time

Reconstructing 3D x-ray CT images of polymer gel dosimeters using the zero-scan method

In this study x-ray CT has been used to produce a 3D image of an irradiated PAGAT gel sample, with noise-reduction achieved using the ‘zero-scan’ method. The gel was repeatedly CT scanned and a linear fit to the varying Hounsfield unit of each pixel in the 3D volume was evaluated across the repeated scans, allowing a zero-scan extrapolation of the image to be obtained. To minimise heating of the CT scanner’s x-ray tube, this study used a large slice thickness (1 cm), to provide image slices across the irradiated region of the gel, and a relatively small number of CT scans (63), to extrapolate the zero-scan image. The resulting set of transverse images shows reduced noise compared to images from the initial CT scan of the gel, without being degraded by the additional radiation dose delivered to the gel during the repeated scanning. The full, 3D image of the gel has a low spatial resolution in the longitudinal direction, due to the selected scan parameters. Nonetheless, important features of the dose distribution are apparent in the 3D x-ray CT scan of the gel. The results of this study demonstrate that the zero-scan extrapolation method can be applied to the reconstruction of multiple x-ray CT slices, to provide useful 2D and 3D images of irradiated dosimetry gels

Novel Bayesian Networks for Genomic Prediction of Developmental Traits in Biomass Sorghum.

The ability to connect genetic information between traits over time allow Bayesian networks to offer a powerful probabilistic framework to construct genomic prediction models. In this study, we phenotyped a diversity panel of 869 biomass sorghum (Sorghum bicolor (L.) Moench) lines, which had been genotyped with 100,435 SNP markers, for plant height (PH) with biweekly measurements from 30 to 120 days after planting (DAP) and for end-of-season dry biomass yield (DBY) in four environments. We evaluated five genomic prediction models: Bayesian network (BN), Pleiotropic Bayesian network (PBN), Dynamic Bayesian network (DBN), multi-trait GBLUP (MTr-GBLUP), and multi-time GBLUP (MTi-GBLUP) models. In fivefold cross-validation, prediction accuracies ranged from 0.46 (PBN) to 0.49 (MTr-GBLUP) for DBY and from 0.47 (DBN, DAP120) to 0.75 (MTi-GBLUP, DAP60) for PH. Forward-chaining cross-validation further improved prediction accuracies of the DBN, MTi-GBLUP and MTr-GBLUP models for PH (training slice: 30-45 DAP) by 36.4-52.4% relative to the BN and PBN models. Coincidence indices (target: biomass, secondary: PH) and a coincidence index based on lines (PH time series) showed that the ranking of lines by PH changed minimally after 45 DAP. These results suggest a two-level indirect selection method for PH at harvest (first-level target trait) and DBY (second-level target trait) could be conducted earlier in the season based on ranking of lines by PH at 45 DAP (secondary trait). With the advance of high-throughput phenotyping technologies, our proposed two-level indirect selection framework could be valuable for enhancing genetic gain per unit of time when selecting on developmental traits

Reproducibility of measurements of oestrogen-receptor concentration in breast cancer.

The reproducibility of measurements of oestrogen-receptor activity has been examined in multiple specimens from a rabbit uterus, a rat mammary tumour and human breast tumours. The relationship between receptor concentration and tumour histology has also been investigated in 11 large primary tumours. In the animal tissues, receptor measurements were relatively reproducible (coefficient of variance: wet wt. basis 16-17%, protein basis 16-21%) but in human breast tumours receptor activity varied considerably (c.v.: wet wt. basis, 22-125%; protein basis, 28-72%). In addition to these variations in receptor activity within tumours, there was a difference between tumours, as demonstrated by an analysis of variance (P less than 0.01). In the 11 primary breast cancers selected for study, the level of receptor activity was related to menopausal status and the tumour content of the specimen. We conclude that the receptor activity detected varies within a tumour and depends upon the tumour content of the biopsy specimen. Predictions based on precise quantitation of receptor concentrations may therefore necessitate replicate tumour sampling and correction for the fraction of non-tumour tissue in each sample

The moral technical imaginaries of internet convergence in an American television network

How emergent technologies are imagined, discussed, and implemented reveals social morality about how society, politics, and economics should be organized. For the television industry in the United States, for instance, the development of internet “convergence” provoked the rise of a new discourse about participatory democracy as well as the hopes for lucrative business opportunities. The simultaneity of technical, moral, and social ordering defines the “moral technical imaginary.” Populating this concept with ethnographic and historical detail, this article expands the theory of the moral technical imaginary with information from six years of participant observation, interviews, and employment with Current TV, an American-based television news network founded by Vice President Al Gore to democratize television production. This chapter explores the limits of political participation and morality when faced with neoliberal capitalism

Transition Metal Carbohydrazide Nitrates: Burn-rate Modifiers for Propellants

This paper discusses the synthesis and characterisation of cobalt (Co), nickel (Ni) andcopper (Cu) carbohydrazide nitrates. In differential scanning calorimetry (DSC), the complexesexhibited exothermic decomposition indicating their energetic nature. The commencement ofdecomposition was observed at 220 °C for Ni complex, and at 160 °C for Co complex whereasthat of Cu complex occurred at 75 °C. In view of the better thermal stability, Ni and Co complexeswere selected for further study. The activation energy of decomposition of Ni and Co complexeswere found to be 47 kcal/mol and 60 kcal/mol respectively. Impact and friction sensitivity testresults revealed relatively lower vulnerability of carbohydrazide cobalt nitrate. Its incorporationin an ammonium perchlorate (AP)-based composite propellant led to 9-19 per cent enhancementwhereas that of carbohydrazide nickel nitrate resulted in 28-74 per cent enhancement in burningrates in the pressure range 1.9 MPa to 8.8 MPa. Exothermic decomposition of the coordinationcomplexes on propellant surface and involvement of metal at molecular level formed ondecomposition of the complexes in combustion environment of composite propellant may beattributed to the catalytic effect of this class of compounds on the lines of reported literature

The Underpinnings of Workload in Unmanned Vehicle Systems

This paper identifies and characterizes factors that contribute to operator workload in unmanned vehicle systems. Our objective is to provide a basis for developing models of workload for use in design and operation of complex human-machine systems. In 1986, Hart developed a foundational conceptual model of workload, which formed the basis for arguably the most widely used workload measurement techniquethe NASA Task Load Index. Since that time, however, there have been many advances in models and factor identification as well as workload control measures. Additionally, there is a need to further inventory and describe factors that contribute to human workload in light of technological advances, including automation and autonomy. Thus, we propose a conceptual framework for the workload construct and present a taxonomy of factors that can contribute to operator workload. These factors, referred to as workload drivers, are associated with a variety of system elements including the environment, task, equipment and operator. In addition, we discuss how workload moderators, such as automation and interface design, can be manipulated in order to influence operator workload. We contend that workload drivers, workload moderators, and the interactions among drivers and moderators all need to be accounted for when building complex, human-machine systems