Accumulation of 5-hydroxynorvaline in maize (Zea mays) leaves is induced by insect feeding and abiotic stress.

Plants produce a wide variety of defensive metabolites to protect themselves against herbivores and pathogens. Non-protein amino acids, which are present in many plant species, can have a defensive function through their mis-incorporation during protein synthesis and/or inhibition of biosynthetic pathways in primary metabolism. 5-Hydroxynorvaline was identified in a targeted search for previously unknown non-protein amino acids in the leaves of maize (Zea mays) inbred line B73. Accumulation of this compound increases during herbivory by aphids (Rhopalosiphum maidis, corn leaf aphid) and caterpillars (Spodoptera exigua, beet armyworm), as well as in response to treatment with the plant signalling molecules methyl jasmonate, salicylic acid and abscisic acid. In contrast, ethylene signalling reduced 5-hydroxynorvaline abundance. Drought stress induced 5-hydroxynorvaline accumulation to a higher level than insect feeding or treatment with defence signalling molecules. In field-grown plants, the 5-hydroxynorvaline concentration was highest in above-ground vegetative tissue, but it was also detectable in roots and dry seeds. When 5-hydroxynorvaline was added to aphid artificial diet at concentrations similar to those found in maize leaves and stems, R. maidis reproduction was reduced, indicating that this maize metabolite may have a defensive function. Among 27 tested maize inbred lines there was a greater than 10-fold range in the accumulation of foliar 5-hydroxynorvaline. Genetic mapping populations derived from a subset of these inbred lines were used to map quantitative trait loci for 5-hydroxynorvaline accumulation to maize chromosomes 5 and 7

A Critical Appraisal and Evaluation of Modern PDFs

We review the present status of the determination of parton distribution functions (PDFs) in the light of the precision requirements for the LHC in Run 2 and other future hadron colliders. We provide brief reviews of all currently available PDF sets and use them to compute cross sections for a number of benchmark processes, including Higgs boson production in gluon-gluon fusion at the LHC. We show that the differences in the predictions obtained with the various PDFs are due to particular theory assumptions made in the fits of those PDFs. We discuss PDF uncertainties in the kinematic region covered by the LHC and on averaging procedures for PDFs, such as advocated by the PDF4LHC15 sets, and provide recommendations for the usage of PDF sets for theory predictions at the LHC.Comment: 70 pages pdflatex, 19 figures, 17 tables; final versio

A foundation for provitamin A biofortification of maize: genome-wide association and genomic prediction models of carotenoid levels.

Efforts are underway for development of crops with improved levels of provitamin A carotenoids to help combat dietary vitamin A deficiency. As a global staple crop with considerable variation in kernel carotenoid composition, maize (Zea mays L.) could have a widespread impact. We performed a genome-wide association study (GWAS) of quantified seed carotenoids across a panel of maize inbreds ranging from light yellow to dark orange in grain color to identify some of the key genes controlling maize grain carotenoid composition. Significant associations at the genome-wide level were detected within the coding regions of zep1 and lut1, carotenoid biosynthetic genes not previously shown to impact grain carotenoid composition in association studies, as well as within previously associated lcyE and crtRB1 genes. We leveraged existing biochemical and genomic information to identify 58 a priori candidate genes relevant to the biosynthesis and retention of carotenoids in maize to test in a pathway-level analysis. This revealed dxs2 and lut5, genes not previously associated with kernel carotenoids. In genomic prediction models, use of markers that targeted a small set of quantitative trait loci associated with carotenoid levels in prior linkage studies were as effective as genome-wide markers for predicting carotenoid traits. Based on GWAS, pathway-level analysis, and genomic prediction studies, we outline a flexible strategy involving use of a small number of genes that can be selected for rapid conversion of elite white grain germplasm, with minimal amounts of carotenoids, to orange grain versions containing high levels of provitamin A

Flavor decomposition of the sea quark helicity distributions in the nucleon from semi-inclusive deep-inelastic scattering

Double-spin asymmetries of semi-inclusive cross sections for the production of identified pions and kaons have been measured in deep-inelastic scattering of polarized positrons on a polarized deuterium target. Five helicity distributions including those for three sea quark flavors were extracted from these data together with re-analyzed previous data for identified pions from a hydrogen target. These distributions are consistent with zero for all three sea flavors. A recently predicted flavor asymmetry in the polarization of the light quark sea appears to be disfavored by the data.Comment: 5 pages, 3 figure

Nuclear Polarization of Molecular Hydrogen Recombined on a Non-metallic Surface

The nuclear polarization of $\mathrm{H}_2$ molecules formed by recombination of nuclear polarized H atoms on the surface of a storage cell initially coated with a silicon-based polymer has been measured by using the longitudinal double-spin asymmetry in deep-inelastic positron-proton scattering. The molecules are found to have a substantial nuclear polarization, which is evidence that initially polarized atoms retain their nuclear polarization when absorbed on this type of surfac

First Measurement of the Tensor Structure Function b1b_1 of the Deuteron

The \Hermes experiment has investigated the tensor spin structure of the deuteron using the 27.6 GeV/c positron beam of \Hera. The use of a tensor polarized deuteron gas target with only a negligible residual vector polarization enabled the first measurement of the tensor asymmetry \At and the tensor structure function \bd for average values of the Bj{\o}rken variable $0.01<0.45$ and of the squared four-momentum transfer $0.5 {\rm GeV^2} <5 {\rm GeV^2}$. The quantities \At and \bd are found to be non-zero. The rise of \bd for decreasing values of $x$ can be interpreted to originate from the same mechanism that leads to nuclear shadowing in unpolarized scattering

Computer vision and machine learning for robust phenotyping in genome-wide studies

Traditional evaluation of crop biotic and abiotic stresses are time-consuming and labor-intensive limiting the ability to dissect the genetic basis of quantitative traits. A machine learning (ML)-enabled image-phenotyping pipeline for the genetic studies of abiotic stress iron deficiency chlorosis (IDC) of soybean is reported. IDC classification and severity for an association panel of 461 diverse plant-introduction accessions was evaluated using an end-to-end phenotyping workflow. The workflow consisted of a multi-stage procedure including: (1) optimized protocols for consistent image capture across plant canopies, (2) canopy identification and registration from cluttered backgrounds, (3) extraction of domain expert informed features from the processed images to accurately represent IDC expression, and (4) supervised ML-based classifiers that linked the automatically extracted features with expert-rating equivalent IDC scores. ML-generated phenotypic data were subsequently utilized for the genome-wide association study and genomic prediction. The results illustrate the reliability and advantage of ML-enabled image-phenotyping pipeline by identifying previously reported locus and a novel locus harboring a gene homolog involved in iron acquisition. This study demonstrates a promising path for integrating the phenotyping pipeline into genomic prediction, and provides a systematic framework enabling robust and quicker phenotyping through ground-based systems