An evaluation of genotyping by sequencing (GBS) to map the <em>Breviaristatum-e (ari-e)</em> locus in cultivated barley

ABSTRACT: We explored the use of genotyping by sequencing (GBS) on a recombinant inbred line population (GPMx) derived from a cross between the two-rowed barley cultivar ‘Golden Promise’ (ari-e.GP/Vrs1) and the six-rowed cultivar ‘Morex’ (Ari-e/vrs1) to map plant height. We identified three Quantitative Trait Loci (QTL), the first in a region encompassing the spike architecture gene Vrs1 on chromosome 2H, the second in an uncharacterised centromeric region on chromosome 3H, and the third in a region of chromosome 5H coinciding with the previously described dwarfing gene Breviaristatum-e (Ari-e). BACKGROUND: Barley cultivars in North-western Europe largely contain either of two dwarfing genes; Denso on chromosome 3H, a presumed ortholog of the rice green revolution gene OsSd1, or Breviaristatum-e (ari-e) on chromosome 5H. A recessive mutant allele of the latter gene, ari-e.GP, was introduced into cultivation via the cv. ‘Golden Promise’ that was a favourite of the Scottish malt whisky industry for many years and is still used in agriculture today. RESULTS: Using GBS mapping data and phenotypic measurements we show that ari-e.GP maps to a small genetic interval on chromosome 5H and that alternative alleles at a region encompassing Vrs1 on 2H along with a region on chromosome 3H also influence plant height. The location of Ari-e is supported by analysis of near-isogenic lines containing different ari-e alleles. We explored use of the GBS to populate the region with sequence contigs from the recently released physically and genetically integrated barley genome sequence assembly as a step towards Ari-e gene identification. CONCLUSIONS: GBS was an effective and relatively low-cost approach to rapidly construct a genetic map of the GPMx population that was suitable for genetic analysis of row type and height traits, allowing us to precisely position ari-e.GP on chromosome 5H. Mapping resolution was lower than we anticipated. We found the GBS data more complex to analyse than other data types but it did directly provide linked SNP markers for subsequent higher resolution genetic analysis

Spiked GBS: a unified, open platform for single marker genotyping and whole-genome profiling

Citation: Rife, T. W., Wu, S. Y., Bowden, R. L., & Poland, J. A. (2015). Spiked GBS: a unified, open platform for single marker genotyping and whole-genome profiling. Bmc Genomics, 16, 7. https://doi.org/10.1186/s12864-015-1404-9Background: In plant breeding, there are two primary applications for DNA markers in selection: 1) selection of known genes using a single marker assay (marker-assisted selection; MAS); and 2) whole-genome profiling and prediction (genomic selection; GS). Typically, marker platforms have addressed only one of these objectives. Results: We have developed spiked genotyping-by-sequencing (sGBS), which combines targeted amplicon sequencing with reduced representation genotyping-by-sequencing. To minimize the cost of targeted assays, we utilize a small percent of sequencing capacity available in runs of GBS libraries to "spike" amplified targets of a priori alleles tagged with a different set of unique barcodes. This open platform allows multiple, single-target loci to be assayed while simultaneously generating a whole-genome profile. This dual-genotyping approach allows different sets of samples to be evaluated for single markers or whole genome-profiling. Here, we report the application of sGBS on a winter wheat panel that was screened for converted KASP markers and newly-designed markers targeting known polymorphisms in the leaf rust resistance gene Lr34. Conclusions: The flexibility and low-cost of sGBS will enable a range of applications across genetics research. Specifically in breeding applications, the sGBS approach will allow breeders to obtain a whole-genome profile of important individuals while simultaneously targeting specific genes for a range of selection strategies across the breeding program

Genome mapping of quantitative trait loci (QTL) controlling domestication traits of intermediate wheatgrass (Thinopyrum intermedium).

Allohexaploid (2n = 6x = 42) intermediate wheatgrass (Thinopyrum intermedium), abbreviated IWG, is an outcrossing perennial grass belonging to the tertiary gene pool of wheat. Perenniality would be valuable option for grain production, but attempts to introgress this complex trait from wheat-Thinopyrum hybrids have not been commercially successful. Efforts to breed IWG itself as a dual-purpose forage and grain crop have demonstrated useful progress and applications, but grain yields are significantly less than wheat. Therefore, genetic and physical maps have been developed to accelerate domestication of IWG. Herein, these maps were used to identify quantitative trait loci (QTLs) and candidate genes associated with IWG grain production traits in a family of 266 full-sib progenies derived from two heterozygous parents, M26 and M35. Transgressive segregation was observed for 17 traits related to seed size, shattering, threshing, inflorescence capacity, fertility, stem size, and flowering time. A total of 111 QTLs were detected in 36 different regions using 3826 genotype-by-sequence markers in 21 linkage groups. The most prominent QTL had a LOD score of 15 with synergistic effects of 29% and 22% over the family means for seed retention and percentage of naked seeds, respectively. Many QTLs aligned with one or more IWG gene models corresponding to 42 possible domestication orthogenes including the wheat Q and RHT genes. A cluster of seed-size and fertility QTLs showed possible alignment to a putative Z self-incompatibility gene, which could have detrimental grain-yield effects when genetic variability is low. These findings elucidate pathways and possible hurdles in the domestication of IWG

Resistance to Gray Leaf Spot of Maize: Genetic Architecture and Mechanisms Elucidated through Nested Association Mapping and Near-Isogenic Line Analysis

Citation: Benson, J. M., Poland, J. A., Benson, B. M., Stromberg, E. L., & Nelson, R. J. (2015). Resistance to Gray Leaf Spot of Maize: Genetic Architecture and Mechanisms Elucidated through Nested Association Mapping and Near-Isogenic Line Analysis. Plos Genetics, 11(3), 23. https://doi.org/10.1371/journal.pgen.1005045Gray leaf spot (GLS), caused by Cercospora zeae-maydis and Cercospora zeina, is one of the most important diseases of maize worldwide. The pathogen has a necrotrophic lifestyle and no major genes are known for GLS. Quantitative resistance, although poorly understood, is important for GLS management. We used genetic mapping to refine understanding of the genetic architecture of GLS resistance and to develop hypotheses regarding the mechanisms underlying quantitative disease resistance (QDR) loci. Nested association mapping (NAM) was used to identify 16 quantitative trait loci (QTL) for QDR to GLS, including seven novel QTL, each of which demonstrated allelic series with significant effects above and below the magnitude of the B73 reference allele. Alleles at three QTL, qGLS1.04, qGLS2.09, and qGLS4.05, conferred disease reductions of greater than 10%. Interactions between loci were detected for three pairs of loci, including an interaction between iqGLS4.05 and qGLS7.03. Near-isogenic lines (NILs) were developed to confirm and fine-map three of the 16 QTL, and to develop hypotheses regarding mechanisms of resistance. qGLS1.04 was fine-mapped from an interval of 27.0 Mb to two intervals of 6.5 Mb and 5.2 Mb, consistent with the hypothesis that multiple genes underlie highly significant QTL identified by NAM. qGLS2.09, which was also associated with maturity (days to anthesis) and with resistance to southern leaf blight, was narrowed to a 4-Mb interval. The distance between major leaf veins was strongly associated with resistance to GLS at qGLS4.05. NILs for qGLS1.04 were treated with the C. zeae-maydis toxin cercosporin to test the role of host-specific toxin in QDR. Cercosporin exposure increased expression of a putative flavin-monooxygenase (FMO) gene, a candidate detoxification-related gene underlying qGLS1.04. This integrated approach to confirming QTL and characterizing the potential underlying mechanisms advances the understanding of QDR and will facilitate the development of resistant varieties

Kortsiktige aksjekurseffekter ved rapporterte innsidehandler på Oslo Børs : en empirisk studie av norske innsidehandler

Denne utredningen har ved hjelp av eventstudiemetoden studert de kortsiktige effektene av 467 rapporterte innsidehandler ved Oslo Børs i tidsperioden 01.09.2008 til 31.08.2010. Disse effektene er analysert med utgangspunkt i fem ulike faktorer i et forsøk på å avdekke trender og forskjeller mellom de ulike innsidehandlene. I samsvar med majoritetsandelen av tidligere forskning finner vi at innsidere oppnår akkumulert gjennomsnittlig anormal avkastning (CAR) signifikant forskjellig fra null. For kjøpstransaksjoner oppnår innsidere CAR på 2,02% i løpet av de første to dagene etter handelen, og tilsvarende -1,64% for salgstransaksjoner. Når det gjelder effektene av innsidekjøp, viser analysene flere faktorer som signifikant påvirker anormal avkastning. Vi finner at store kjøpssummer, handler i selskaper med markedsverdi mellom 1 og 3 milliarder og handler i selskaper som har falt mye 14 dager før handelen, genererer størst signifikant CAR for periode (0,2) på henholdsvis 3,96%, 3,41% og 3,16%. Studien viser også at innsiders stilling vil ha påvirking på den anormale avkastningen. Videre finner vi at innsidekjøp har signifikant høyere anormal avkastning i nedgangstider enn oppgangstider. For salgstransaksjoner gir salg i små selskaper signifikant CAR på -6,79%. Resultatene viser også at innsidesalg har signifikant høyere negativ anormal avkastning i oppgangstider enn nedgangstider. I tillegg er innsidere gode til å “time” markedet ved at de kjøper aksjer etter at verdien har falt mye og omvendt selger aksjer etter at verdien har steget mye. Tilslutt slår utredningen fast at utsidere kan replikere innsidere og oppnå anormal avkastning

Canopy Temperature and Vegetation Indices from High-Throughput Phenotyping Improve Accuracy of Pedigree and Genomic Selection for Grain Yield in Wheat

Citation: Rutkoski, J., . . . Singh, R. (2016). Canopy Temperature and Vegetation Indices from High-Throughput Phenotyping Improve Accuracy of Pedigree and Genomic Selection for Grain Yield in Wheat. G3-Genes Genomes Genetics, 6(9), 2799-2808. https://doi.org/10.1534/g3.116.032888Genomic selection can be applied prior to phenotyping, enabling shorter breeding cycles and greater rates of genetic gain relative to phenotypic selection. Traits measured using high-throughput phenotyping based on proximal or remote sensing could be useful for improving pedigree and genomic prediction model accuracies for traits not yet possible to phenotype directly. We tested if using aerial measurements of canopy temperature, and green and red normalized difference vegetation index as secondary traits in pedigree and genomic best linear unbiased prediction models could increase accuracy for grain yield in wheat, Triticum aestivum L., using 557 lines in five environments. Secondary traits on training and test sets, and grain yield on the training set were modeled as multivariate, and compared to univariate models with grain yield on the training set only. Cross validation accuracies were estimated within and across-environment, with and without replication, and with and without correcting for days to heading. We observed that, within environment, with unreplicated secondary trait data, and without correcting for days to heading, secondary traits increased accuracies for grain yield by 56% in pedigree, and 70% in genomic prediction models, on average. Secondary traits increased accuracy slightly more when replicated, and considerably less when models corrected for days to heading. In across-environment prediction, trends were similar but less consistent. These results show that secondary traits measured in high-throughput could be used in pedigree and genomic prediction to improve accuracy. This approach could improve selection in wheat during early stages if validated in early-generation breeding plots

Application of unmanned aerial systems for high throughput phenotyping of large wheat breeding nurseries

Citation: Haghighattalab, A., Perez, L. G., Mondal, S., Singh, D., Schinstock, D., Rutkoski, J., . . . Poland, J. (2016). Application of unmanned aerial systems for high throughput phenotyping of large wheat breeding nurseries. Plant Methods, 12, 15. https://doi.org/10.1186/s13007-016-0134-6Background: Low cost unmanned aerial systems (UAS) have great potential for rapid proximal measurements of plants in agriculture. In the context of plant breeding and genetics, current approaches for phenotyping a large number of breeding lines under field conditions require substantial investments in time, cost, and labor. For field-based high-throughput phenotyping (HTP), UAS platforms can provide high-resolution measurements for small plot research, while enabling the rapid assessment of tens-of-thousands of field plots. The objective of this study was to complete a baseline assessment of the utility of UAS in assessment field trials as commonly implemented in wheat breeding programs. We developed a semi-automated image-processing pipeline to extract plot level data from UAS imagery. The image dataset was processed using a photogrammetric pipeline based on image orientation and radiometric calibration to produce orthomosaic images. We also examined the relationships between vegetation indices (VIs) extracted from high spatial resolution multispectral imagery collected with two different UAS systems (eBee Ag carrying MultiSpec 4C camera, and IRIS+ quadcopter carrying modified NIR Canon S100) and ground truth spectral data from hand-held spectroradiometer. Results: We found good correlation between the VIs obtained from UAS platforms and ground-truth measurements and observed high broad-sense heritability for VIs. We determined radiometric calibration methods developed for satellite imagery significantly improved the precision of VIs from the UAS. We observed VIs extracted from calibrated images of Canon S100 had a significantly higher correlation to the spectroradiometer (r = 0.76) than VIs from the MultiSpec 4C camera (r = 0.64). Their correlation to spectroradiometer readings was as high as or higher than repeated measurements with the spectroradiometer per se. Conclusion: The approaches described here for UAS imaging and extraction of proximal sensing data enable collection of HTP measurements on the scale and with the precision needed for powerful selection tools in plant breeding. Low-cost UAS platforms have great potential for use as a selection tool in plant breeding programs. In the scope of tools development, the pipeline developed in this study can be effectively employed for other UAS and also other crops planted in breeding nurseries

Genomic Analysis and Prediction within a US Public Collaborative Winter Wheat Regional Testing Nursery

The development of inexpensive, whole-genome profiling enables a transition to allele-based breeding using genomic prediction models. These models consider alleles shared between lines to predict phenotypes and select new lines based on estimated breeding values. This approach can leverage highly unbalanced datasets that are common to breeding programs. The Southern Regional Performance Nursery (SRPN) is a public nursery established by the USDA–ARS in 1931 to characterize performance and quality of near-release wheat (Triticum aestivum L.) varieties from breeding programs in the US Central Plains. New entries are submitted annually and can be re-entered only once. The trial is grown at \u3e30 locations each year and lines are evaluated for grain yield, disease resistance, and agronomic traits. Overall genetic gain is measured across years by including common check cultivars for comparison. We have generated whole-genome profiles via genotyping-bysequencing (GBS) for 939 SPRN entries dating back to 1992 to explore the potential use of the nursery as a genomic selection (GS) training population (TP). The GS prediction models across years (average r = 0.33) outperformed year-to-year phenotypic correlation for yield (r = 0.27) for a majority of the years evaluated, suggesting that genomic selection has the potential to outperform low heritability selection on yield in these highly variable environments. We also examined the predictability of programs using both program-specific and whole-set TPs. Generally, the predictability of a program was similar with both approaches. These results suggest that wheat breeding programs can collaboratively leverage the immense datasets that are generated from regional testing networks

Establishment and optimization of genomic selection to accelerate the domestication and improvement of intermediate wheatgrass

Citation: Zhang, X., Sallam, A., Gao, L., Kantarski, T., Poland, J., DeHaan, L. R., . . . Anderson, J. A. (2016). Establishment and optimization of genomic selection to accelerate the domestication and improvement of intermediate wheatgrass. Plant Genome, 9(1). doi:10.3835/plantgenome2015.07.0059Intermediate wheatgrass (IWG) is a perennial species and has edible and nutritious grain and desirable agronomic traits, including large seed size, high grain yield, and biomass. It also has the potential to provide ecosystem services and an economic return to farmers. However, because of its allohexaploidy and self-incompatibility, developing molecular markers for genetic analysis and molecular breeding has been challenging. In the present study, using genotyping-by-sequencing (GBS) technology, 3436 genomewide markers discovered in a biparental population with 178 genets, were mapped to 21 linkage groups (LG) corresponding to 21 chromosomes of IWG. Genomic prediction models were developed using 3883 markers discovered in a breeding population containing 1126 representative genets from 58 half-sib families. High predictive ability was observed for seven agronomic traits using cross-validation, ranging from 0.46 for biomass to 0.67 for seed weight. Optimization results indicated that 8 to 10 genets from each half-sib family can form a good training population to predict the breeding value of their siblings, and 1600 genomewide markers are adequate to capture the genetic variation in the current breeding population for genomic selection. Thus, with the advances in sequencing-based marker technologies, it was practical to perform molecular genetic analysis and molecular breeding on a new and challenging species like IWG, and genomic selection could increase the efficiency of recurrent selection and accelerate the domestication and improvement of IWG.A. © Crop Science Society of America