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We thank King Abdullah University of Science and Technology (KAUST) for funding this work, and Photon Systems Instruments (PSI) for their scientific and technical support. Special thanks to Dr. Xavier Sirault (CSIRO, Australia) for suggesting the use of the saturation method for salt imposition, Radka Mezulanikova and Jaromir Pytela (PSI, Czech Republic) for assisting with the phenotyping and Prof. Christa Testerink (UVA, Netherlands) for providing the HapMap seeds. We also thank the KAUST Greenhouse Core-lab personnel: Dr. Richard Soppe, Mr. Mupalla Reddy, Mr. Gomerito Sagun, Mr. John Rahmer, Mr. Thomas Hoover and Mr. Johnard Balangue for their help in propagating the plant material that was used in this study and for running the highthroughput phenotyping facility at KAUST.

Quinoa is a crop originating in the Andes but grown more widely and with the genetic potential for significant further expansion. Due to the phenotypic plasticity of quinoa, varieties need to be assessed across years and multiple locations. To improve comparability among field trials across the globe and to facilitate collaborations, components of the trials need to be kept consistent, including the type and methods of data collected. Here, an internationally open-access framework for phenotyping a wide range of quinoa features is proposed to facilitate the systematic agronomic, physiological and genetic characterization of quinoa for crop adaptation and improvement. Mature plant phenotyping is a central aspect of this paper, including detailed descriptions and the provision of phenotyping cards to facilitate consistency in data collection. High-throughput methods for multi-temporal phenotyping based on remote sensing technologies are described. Tools for higher-throughput post-harvest phenotyping of seeds are presented. A guideline for approaching quinoa field trials including the collection of environmental data and designing layouts with statistical robustness is suggested. To move towards developing resources for quinoa in line with major cereal crops, a database was created. The Quinoa Germinate Platform will serve as a central repository of data for quinoa researchers globally. EEA Famaillá Fil: Stanschewski, Clara S. King Abdullah University of Science and Technology. Center for Desert Agriculture, Biological and Environmental Sciences and Engineering Division; Arabia Saudita Fil: Rey, Elodie. King Abdullah University of Science and Technology. Center for Desert Agriculture, Biological and Environmental Sciences and Engineering Division; Arabia Saudita Fil: Fiene, Gabriele. King Abdullah University of Science and Technology. Center for Desert Agriculture, Biological and Environmental Sciences and Engineering Division; Arabia Saudita Fil: Craine, Evan B. Washington State University. Department of Crop and Soil Sciences; Estados Unidos Fil: Wellman, Gordon. King Abdullah University of Science and Technology. Center for Desert Agriculture, Biological and Environmental Sciences and Engineering Division; Arabia Saudita Fil: Melino, Vanessa J. King Abdullah University of Science and Technology. Center for Desert Agriculture, Biological and Environmental Sciences and Engineering Division; Arabia Saudita Fil: Patiranage, Dilan S.R. King Abdullah University of Science and Technology. Center for Desert Agriculture, Biological and Environmental Sciences and Engineering Division; Arabia Saudita Fil: Patiranage, Dilan S.R. Christian-Albrechts-University of Kiel. Plant Breeding Institute; Alemania Fil: Johansen, Kasper. King Abdullah University of Science and Technology. Water Desalination and Reuse Center; Arabia Saudita Fil: Schmöckel, Sandra M. University of Hohenheim. Institute of Crop Science. Department Physiology of Yield Stability; Alemania Fil: Erazzu, Luis Ernesto. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Famaillá; Argentina. Fil: Tester, Mark. King Abdullah University of Science and Technology. Center for Desert Agriculture, Biological and Environmental Sciences and Engineering Division; Arabia Saudita

Summary To optimize shoot growth and structure of cereals, we need to understand the genetic components controlling initiation and elongation. While measuring total shoot growth at high throughput using 2D imaging has progressed, recovering the 3D shoot structure of small grain cereals at a large scale is still challenging. Here, we present a method for measuring defined individual leaves of cereals, such as wheat and barley, using few images. Plant shoot modelling over time was used to measure the initiation and elongation of leaves in a bi‐parental barley mapping population under low and high soil salinity. We detected quantitative trait loci (QTL) related to shoot growth per se, using both simple 2D total shoot measurements and our approach of measuring individual leaves. In addition, we detected QTL specific to leaf elongation and not to total shoot size. Of particular importance was the detection of a QTL on chromosome 3H specific to the early responses of leaf elongation to salt stress, a locus that could not be detected without the computer vision tools developed in this study., Significance Statement To dissect overall shoot growth in small grain cereals, a computer vision‐based approach was developed for the measurement of individual leaves, which requires only few input images, making image acquisition fast and high throughput. The applicability of this approach is shown by mapping QTL for leaf elongation in a barley mapping population in response to salinity.

Genomic selection in crop breeding introduces modeling challenges not found in animal studies. These include the need to accommodate replicate plants for each line, consider spatial variation in field trials, address line by environment interactions, and capture nonadditive effects. Here, we propose a flexible single-stage genomic selection approach that resolves these issues. Our linear mixed model incorporates spatial variation through environment-specific terms, and also randomization-based design terms. It considers marker, and marker by environment interactions using ridge regression best linear unbiased prediction to extend genomic selection to multiple environments. Since the approach uses the raw data from line replicates, the line genetic variation is partitioned into marker and nonmarker residual genetic variation (i.e., additive and nonadditive effects). This results in a more precise estimate of marker genetic effects. Using barley height data from trials, in 2 different years, of up to 477 cultivars, we demonstrate that our new genomic selection model improves predictions compared to current models. Analyzing single trials revealed improvements in predictive ability of up to 5.7%. For the multiple environment trial (MET) model, combining both year trials improved predictive ability up to 11.4% compared to a single environment analysis. Benefits were significant even when fewer markers were used. Compared to a single-year standard model run with 3490 markers, our partitioned MET model achieved the same predictive ability using between 500 and 1000 markers depending on the trial. Our approach can be used to increase accuracy and confidence in the selection of the best lines for breeding and/or, to reduce costs by using fewer markers.

In many cereal crops, meiotic crossovers predominantly occur toward the ends of chromosomes and 30 to 50% of genes rarely recombine. This limits the exploitation of genetic variation by plant breeding. Previous reports demonstrate that chiasma frequency can be manipulated in plants by depletion of the synaptonemal complex protein ZIPPER1 (ZYP1) but conflict as to the direction of change, with fewer chiasmata reported in Arabidopsis thaliana and more crossovers reported for rice (Oryza sativa). Here, we use RNA interference (RNAi) to reduce the amount of ZYP1 in barley (Hordeum vulgare) to only 2 to 17% of normal zygotene levels. In the ZYP1(RNAi) lines, fewer than half of the chromosome pairs formed bivalents at metaphase and many univalents were observed, leading to chromosome nondisjunction and semisterility. The number of chiasmata per cell was reduced from 14 in control plants to three to four in the ZYP1-depleted lines, although the localization of residual chiasmata was not affected. DNA double-strand break formation appeared normal, but the recombination pathway was defective at later stages. A meiotic time course revealed a 12-h delay in prophase I progression to the first labeled tetrads. Barley ZYP1 appears to function similarly to ZIP1/ZYP1 in yeast and Arabidopsis, with an opposite effect on crossover number to ZEP1 in rice, another member of the Poaceae.

Phragmidium violaceum (Pv) isolate F15 was released for biological control of invasive European blackberry in Australia in 1991–1992. This study reports variation in the pathogenicity of isolate F15 and Pv isolates SA1, V1 and V2, collected in southeastern Australia in 1997 or 1998, on a broad sample of genetically variable European blackberry clones collected in 1996–2000. The use of whole shoots or detached leaflet discs led to the same conclusions about the relative susceptibility of a blackberry clone to a particular Pv isolate. Moderate to relatively high numbers of uredinia developed on all 25 blackberry clones inoculated with isolate V1, whereas no or few uredinia of isolates V2 and SA1 developed on Rubus erythrops clone EB20, three clones of Rubus leucostachys (EB9, EB19 and 960804) or Rubus sp. clone SR43. Pv isolate F15 differed from the three isolates collected in Australia in that no or few uredinia of F15 developed on Rubus polyanthemus clone 961107 or three clones of Rubus laciniatus (EB22, KE1, SR14). Isolate F15 also differed from isolates V1 and V2 for the density of uredinia as a function of leaf age in a clone of Rubus anglocandicans found widely in Australia. Isolates V1 and V2 ceased production of uredinia on leaves older than 16 days, whereas Pv isolate F15 continued production of uredinia beyond this leaf age. This study informed selection of additional Pv isolates from Europe for release in Australia in 2004.

Barley (Hordeum vulgare) is a crop of global significance. However, a third of the genes of barley are largely inaccessible to conventional breeding programmes as crossovers are localised to the ends of the chromosomes. This work examines whether crossovers can be shifted to more proximal regions simply by elevating growth temperature. We utilised a genome-wide marker set for linkage analysis combined with cytological mapping of crossover events to examine the recombination landscape of plants grown at different temperatures. We found that barley shows heterochiasmy, that is, differences between female and male recombination frequencies. In addition, we found that elevated temperature significantly changes patterns of recombination in male meiosis only, with a repositioning of Class I crossovers determined by cytological mapping of HvMLH3 foci. We show that the length of synaptonemal complexes in male meiocytes increases in response to temperature. The results demonstrate that the distribution of crossover events are malleable and can be shifted to proximal regions by altering the growth temperature. The shift in recombination is the result of altering the distribution of Class I crossovers, but the higher recombination at elevated temperatures is potentially not the result of an increase in Class I events.

A statistical approach is presented for selection of best performing lines for commercial release and best parents for future breeding programs from standard agronomic trials. The method involves the partitioning of the genetic effect of a line into additive and non-additive effects using pedigree based inter-line relationships, in a similar manner to that used in animal breeding. A difference is the ability to estimate non-additive effects. Line performance can be assessed by an overall genetic line effect with greater accuracy than when ignoring pedigree information and the additive effects are predicted breeding values. A generalized definition of heritability is developed to account for the complex models presented.

Background (1,3;1,4)-β-Glucan is an important component of the cell walls of barley grain as it affects processability during the production of alcoholic beverages and has significant human health benefits when consumed above recommended threshold levels. This leads to diametrically opposed quality requirements for different applications as low levels of (1,3;1,4)-β-glucan are required for brewing and distilling and high levels for positive impacts on human health. Results We quantified grain (1,3;1,4)-β-glucan content in a collection of 399 2-row Spring-type, and 204 2-row Winter-type elite barley cultivars originating mainly from north western Europe. We combined these data with genotypic information derived using a 9 K Illumina iSelect SNP platform and subsequently carried out a Genome Wide Association Scan (GWAS). Statistical analysis accounting for residual genetic structure within the germplasm collection allowed us to identify significant associations between molecular markers and the phenotypic data. By anchoring the regions that contain these associations to the barley genome assembly we catalogued genes underlying the associations. Based on gene annotations and transcript abundance data we identified candidate genes. Conclusions We show that a region of the genome on chromosome 2 containing a cluster of CELLULOSE SYNTHASE-LIKE (Csl) genes, including CslF3, CslF4, CslF8, CslF10, CslF12 and CslH, as well as a region on chromosome 1H containing CslF9, are associated with the phenotype in this germplasm. We also observed that several regions identified by GWAS contain glycoside hydrolases that are possibly involved in (1,3;1,4)-β-glucan breakdown, together with other genes that might participate in (1,3;1,4)-β-glucan synthesis, re-modelling or regulation. This analysis provides new opportunities for understanding the genes related to the regulation of (1,3;1,4)-β-glucan content in cereal grains. Electronic supplementary material The online version of this article (doi:10.1186/1471-2164-15-907) contains supplementary material, which is available to authorized users.

A statistical approach for the analysis of multi-environment trials (METs) is presented, in which selection of best performing lines, best parents, and best combination of parents can be determined. The genetic effect of a line is partitioned into additive, dominance and residual non-additive effects. The dominance effects are estimated through the incorporation of the dominance relationship matrix, which is presented under varying levels of inbreeding. A computationally efficient way of fitting dominance effects is presented which partitions dominance effects into between family dominance and within family dominance line effects. The overall approach is applicable to inbred lines, hybrid lines and other general population structures where pedigree information is available.

DiGeorge syndrome in humans is characterized by immunodeficiency, heart defects, mental retardation and facial dysmorphism; cytogenetic analysis has shown that deletions at 22q11 occur in approximately 25% of cases. To generate DNA markers from this region, we have microdissected and microcloned band q11 of human Chromosome (Chr) 22. Nineteen thousand clones were obtained from material dissected from 20 chromosome fragments. Seventeen of 61 clones analyzed (28%) were repetitive, 27 (44%) gave no signal, and 17 (28%) detected single copy sequences of which ten mapped to Chr 22. Two of these were found to be deleted in patients with DiGeorge syndrome and either monosomy for 22q11-pter or visible interstitial deletions of 22q11. These two markers are also hemizygous in patients with no visible chromosomal abnormality, demonstrating that submicroscopic deletions are common in DiGeorge syndrome patients.