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Dive into the research topics where Gina Brown-Guedira is active.

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Featured researches published by Gina Brown-Guedira.


Plant Biotechnology Journal | 2014

Characterization of polyploid wheat genomic diversity using a high-density 90 000 single nucleotide polymorphism array

Shichen Wang; Debbie Wong; Kerrie L. Forrest; Alexandra M. Allen; Shiaoman Chao; Bevan Emma Huang; Marco Maccaferri; Silvio Salvi; Sara Giulia Milner; Luigi Cattivelli; Anna M. Mastrangelo; Alex Whan; Stuart Stephen; Gary L. A. Barker; Ralf Wieseke; Joerg Plieske; Morten Lillemo; D. E. Mather; R. Appels; Rudy Dolferus; Gina Brown-Guedira; Abraham B. Korol; Alina Akhunova; Catherine Feuillet; Jérôme Salse; Michele Morgante; Curtis J. Pozniak; Ming-Cheng Luo; Jan Dvorak; Matthew K. Morell

High-density single nucleotide polymorphism (SNP) genotyping arrays are a powerful tool for studying genomic patterns of diversity, inferring ancestral relationships between individuals in populations and studying marker–trait associations in mapping experiments. We developed a genotyping array including about 90 000 gene-associated SNPs and used it to characterize genetic variation in allohexaploid and allotetraploid wheat populations. The array includes a significant fraction of common genome-wide distributed SNPs that are represented in populations of diverse geographical origin. We used density-based spatial clustering algorithms to enable high-throughput genotype calling in complex data sets obtained for polyploid wheat. We show that these model-free clustering algorithms provide accurate genotype calling in the presence of multiple clusters including clusters with low signal intensity resulting from significant sequence divergence at the target SNP site or gene deletions. Assays that detect low-intensity clusters can provide insight into the distribution of presence–absence variation (PAV) in wheat populations. A total of 46 977 SNPs from the wheat 90K array were genetically mapped using a combination of eight mapping populations. The developed array and cluster identification algorithms provide an opportunity to infer detailed haplotype structure in polyploid wheat and will serve as an invaluable resource for diversity studies and investigating the genetic basis of trait variation in wheat.


Proceedings of the National Academy of Sciences of the United States of America | 2013

Genome-wide comparative diversity uncovers multiple targets of selection for improvement in hexaploid wheat landraces and cultivars

Colin Cavanagh; Shiaoman Chao; Shichen Wang; Bevan Emma Huang; Stuart Stephen; Seifollah Kiani; Kerrie L. Forrest; Cyrille Saintenac; Gina Brown-Guedira; Alina Akhunova; Deven R. See; Guihua Bai; Michael O. Pumphrey; Luxmi Tomar; Debbie Wong; Stephan Kong; Matthew P. Reynolds; Marta Lopez da Silva; Harold E. Bockelman; L. E. Talbert; James A. Anderson; Susanne Dreisigacker; Arron H. Carter; Viktor Korzun; Peter L. Morrell; Jorge Dubcovsky; Matthew K. Morell; Mark E. Sorrells; Matthew J. Hayden; Eduard Akhunov

Domesticated crops experience strong human-mediated selection aimed at developing high-yielding varieties adapted to local conditions. To detect regions of the wheat genome subject to selection during improvement, we developed a high-throughput array to interrogate 9,000 gene-associated single-nucleotide polymorphisms (SNP) in a worldwide sample of 2,994 accessions of hexaploid wheat including landraces and modern cultivars. Using a SNP-based diversity map we characterized the impact of crop improvement on genomic and geographic patterns of genetic diversity. We found evidence of a small population bottleneck and extensive use of ancestral variation often traceable to founders of cultivars from diverse geographic regions. Analyzing genetic differentiation among populations and the extent of haplotype sharing, we identified allelic variants subjected to selection during improvement. Selective sweeps were found around genes involved in the regulation of flowering time and phenology. An introgression of a wild relative-derived gene conferring resistance to a fungal pathogen was detected by haplotype-based analysis. Comparing selective sweeps identified in different populations, we show that selection likely acts on distinct targets or multiple functionally equivalent alleles in different portions of the geographic range of wheat. The majority of the selected alleles were present at low frequency in local populations, suggesting either weak selection pressure or temporal variation in the targets of directional selection during breeding probably associated with changing agricultural practices or environmental conditions. The developed SNP chip and map of genetic variation provide a resource for advancing wheat breeding and supporting future population genomic and genome-wide association studies in wheat.


Theoretical and Applied Genetics | 2006

Advanced backcross QTL analysis of a hard winter wheat × synthetic wheat population

B. Narasimhamoorthy; Bikram S. Gill; Allan K. Fritz; James C. Nelson; Gina Brown-Guedira

Advanced backcross quantitative trait locus (AB-QTL) analysis was used to identify QTLs for yield and yield components in a backcross population developed from a cross between hard red winter wheat (Triticum aestivum L.) variety Karl 92 and the synthetic wheat line TA 4152-4. Phenotypic data were collected for agronomic traits including heading date, plant height, kernels per spike, kernel weight, tiller number, biomass, harvest index, test weight, grain yield, protein content, and kernel hardness on 190 BC2F2:4 lines grown in three replications in two Kansas environments. Severity of wheat soilborne mosaic virus (WSBMV) reaction was evaluated at one location. The population was genotyped using 151 microsatellite markers. Of the ten putative QTLs identified, seven were located on homoeologous group 2 and group 3 chromosomes. The favorable allele was contributed by cultivated parent Karl 92 at seven QTLs including a major one for WSBMV resistance, and by the synthetic parent at three QTLs: for grain hardness, kernels per spike, and tiller number.


Theoretical and Applied Genetics | 2011

An accurate DNA marker assay for stem rust resistance gene Sr2 in wheat

Rohit Mago; Gina Brown-Guedira; Susanne Dreisigacker; James Breen; Yue Jin; Ravi P. Singh; R. Appels; Evans S. Lagudah; Jeff Ellis; Wolfgang Spielmeyer

The stem rust resistance gene Sr2 has provided broad-spectrum protection against stem rust (Pucciniagraminis Pers. f. sp. tritici) since its wide spread deployment in wheat from the 1940s. Because Sr2 confers partial resistance which is difficult to select under field conditions, a DNA marker is desirable that accurately predicts Sr2 in diverse wheat germplasm. Using DNA sequence derived from the vicinity of the Sr2 locus, we developed a cleaved amplified polymorphic sequence (CAPS) marker that is associated with the presence or absence of the gene in 115 of 122 (95%) diverse wheat lines. The marker genotype predicted the absence of the gene in 100% of lines which were considered to lack Sr2. Discrepancies were observed in lines that were predicted to carry Sr2 but failed to show the CAPS marker. Given the high level of accuracy observed, the marker provides breeders with a selection tool for one of the most important disease resistance genes of wheat.


The Plant Genome | 2012

Evaluation of Genomic Prediction Methods for Fusarium Head Blight Resistance in Wheat

Jessica Rutkoski; Jared Benson; Yi Jia; Gina Brown-Guedira; Jean-Luc Jannink; Mark E. Sorrells

Fusarium head blight (FHB) resistance is quantitative and difficult to evaluate. Genomic selection (GS) could accelerate FHB resistance breeding. We used U.S. cooperative FHB wheat nursery data to evaluate GS models for several FHB resistance traits including deoxynivalenol (DON) levels. For all traits we compared the models: ridge regression (RR), Bayesian LASSO (BL), reproducing kernel Hilbert spaces (RKHS) regression, random forest (RF) regression, and multiple linear regression (MLR) (fixed effects). For DON, we evaluated additional prediction methods including bivariate RR models, phenotypes for correlated traits, and RF regression models combining markers and correlated phenotypes as predictors. Additionally, for all traits, we compared different marker sets including genomewide markers, FHB quantitative trait loci (QTL) targeted markers, and both sets combined. Genomic selection accuracies were always higher than MLR accuracies, RF and RKHS regression were often the most accurate methods, and for DON, marker plus trait RF regression was more accurate than all other methods. For all traits except DON, using QTL targeted markers alone led to lower accuracies than using genomewide markers. This study indicates that cooperative FHB nursery data can be useful for GS, and prior information about correlated traits and QTL could be used to improve accuracies in some cases.


Phytopathology | 2009

Post-anthesis moisture increased Fusarium head blight and deoxynivalenol levels in North Carolina winter wheat.

Christina Cowger; Jennifer Patton-Özkurt; Gina Brown-Guedira; Leandro Perugini

ABSTRACT Current models for forecasting Fusarium head blight (FHB) and deoxynivalenol (DON) levels in wheat are based on weather near anthesis, and breeding for resistance to FHB pathogens often relies on irrigation before and shortly after anthesis to encourage disease development. The effects of post-anthesis environmental conditions on FHB are poorly understood. We performed a field experiment at Kinston, NC, to explore the effects of increasing duration of post-anthesis moisture on disease incidence, disease severity, Fusarium-damaged kernels (FDK), percent infected kernels, and DON. The experiment had a split-plot design, and one trial was conducted in each of two successive years. Main plots consisted of post-anthesis mist durations of 0, 10, 20, or 30 days. Subplots were of eight cultivars in the first year and seven in the second year, two being susceptible to FHB and the remainder each with varying degrees of apparent type I and type II resistance. Plots were inoculated by spraying Fusarium graminearum macroconidia at mid-anthesis. Averaging across years and cultivars, 10 or 20 days of post-anthesis mist had the same effect (P > or = 0.198) and were associated with an approximately fourfold increase in mean disease incidence and eightfold increase in disease severity compared with 0 days of mist (P < or = 0.0002). In both years, mean FDK percentages at 0 and 10 days post-anthesis mist were the same and significantly lower than FDK percentages under 20 or 30 days of post-anthesis mist. Mist duration had a significant effect on percent kernels infected with Fusarium spp. as detected by a selective medium assay of 2007 samples. Averaging across all cultivars, in both years, DON levels increased significantly for 10 days compared with 0 days of mist, and increased again with 20 days of mist (P < or = 0.04). This is the first investigation to show that extended post-flowering moisture can have a significant enhancing effect on FHB, FDK, DON, and percent infected kernels of wheat. For all disease and toxin assays, cultivar rankings were significantly noncorrelated among mist durations in at least 1 year, suggesting that FHB screening programs might rank genotypes differently under extended post-anthesis moisture than without it. Our findings also imply that accurate forecasts of DON in small grains must take account of post-anthesis weather conditions.


Plant Disease | 2001

Success stories: breeding for wheat disease resistance in Kansas.

William W. Bockus; Jon A. Appel; Robert L. Bowden; Allan K. Fritz; Bikram S. Gill; T. Joe Martin; R. G. Sears; Dallas L. Seifers; Gina Brown-Guedira; Merle G. Eversmeyer

the development, release, and adoption of wheat cultivars with resistance to important wheat diseases. As a result of the annual disease survey and estimation of losses, the impact that resistant cultivars had on disease losses could be quantified. This paper describes the use of genetic resistance in wheat for control of diseases and related yield effects in Kansas during the past 25 to 30


PLOS ONE | 2014

Genome-Wide Association Study Reveals Novel Quantitative Trait Loci Associated with Resistance to Multiple Leaf Spot Diseases of Spring Wheat

Suraj Gurung; Sujan Mamidi; J. Michael Bonman; Mai Xiong; Gina Brown-Guedira; Tika B. Adhikari

Accelerated wheat development and deployment of high-yielding, climate resilient, and disease resistant cultivars can contribute to enhanced food security and sustainable intensification. To facilitate gene discovery, we assembled an association mapping panel of 528 spring wheat landraces of diverse geographic origin for a genome-wide association study (GWAS). All accessions were genotyped using an Illumina Infinium 9K wheat single nucleotide polymorphism (SNP) chip and 4781 polymorphic SNPs were used for analysis. To identify loci underlying resistance to the major leaf spot diseases and to better understand the genomic patterns, we quantified population structure, allelic diversity, and linkage disequilibrium. Our results showed 32 loci were significantly associated with resistance to the major leaf spot diseases. Further analysis identified QTL effective against major leaf spot diseases of wheat which appeared to be novel and others that were previously identified by association analysis using Diversity Arrays Technology (DArT) and bi-parental mapping. In addition, several identified SNPs co-localized with genes that have been implicated in plant disease resistance. Future work could aim to select the putative novel loci and pyramid them in locally adapted wheat cultivars to develop broad-spectrum resistance to multiple leaf spot diseases of wheat via marker-assisted selection (MAS).


Advances in Agronomy | 2006

Wheat Genetics Resource Center: The First 25 Years

Bikram S. Gill; Bernd Friebe; W. John Raupp; D. L. Wilson; T. Stan Cox; R. G. Sears; Gina Brown-Guedira; Allan K. Fritz

The Wheat Genetics Resource Center, a pioneering center without walls, has served the wheat genetics community for 25 years. The Wheat Genetics Resource Center (WGRC) assembled a working collection of over 11,000 wild wheat relatives and cytogenetic stocks for conservation and use in wheat genome analysis and crop improvement. Over 30,000 samples from the WGRC collection of wheat wild relatives, cytogenetic stocks, and improved germplasm have been distributed to scientists in 45 countries and 39 states in the United States. The WGRC and collaborators have developed standard karyotypes of 26 species of the Triticum / Aegilops complex, rye, and some perennial genera of the Triticeae. They have developed over 800 cytogenetic stocks including addition, substitution, and deletion lines. The anchor karyotypes, technical innovations, and associated cytogenetic stocks are a part of the basic tool kit of every wheat geneticist. They have cytogenetically characterized over six‐dozen wheat–alien introgression lines. The WGRC has released 47 improved germplasm lines incorporating over 50 novel genes against pathogens and pests; some genes have been deployed in agriculture. The WGRC hosted over three‐dozen scientists especially from developing countries for advanced training. The WGRC was engaged in international agriculture through several collaborating projects. Particularly noteworthy was the collaborative project with Centro Internacional de Mejoramiento de Maiz y Trigo (CIMMYT) on the production of synthetic wheats. It is estimated that “by the year 2003–2004, 26% of all new advanced lines made available through CIMMYT screening nurseries to cooperators for either irrigated or semi‐arid conditions were synthetic derivatives.” The WGRC is applying genomics tools to further expedite the use of exotic germplasm in wheat crop improvement.


Theoretical and Applied Genetics | 2015

Molecular characterization of a new powdery mildew resistance gene Pm54 in soft red winter wheat

Yuanfeng Hao; Ryan Parks; Christina Cowger; Zhenbang Chen; Yingying Wang; Dan Bland; J. Paul Murphy; Mohammed Guedira; Gina Brown-Guedira; Jerry W. Johnson

Key messageA new powdery mildew resistance genePm54was identified on chromosome 6BL in soft red winter wheat.AbstractPowdery mildew is causing increasing damage to wheat production in the southeastern USA. To combat the disease, a continuing need exists to discover new genes for powdery mildew resistance and to incorporate those genes into breeding programs. Pioneer® variety 26R61 (shortened as 26R61) and AGS 2000 have been used as checks in the Uniform Southern Soft Red Winter Wheat Nursery for a decade, and both have provided good resistance across regions during that time. In the present study, a genetic analysis of mildew resistance was conducted on a RIL population developed from a cross of 26R61 and AGS 2000. Phenotypic evaluation was conducted in the field at Plains, GA, and Raleigh, NC, in 2012 and 2013, a total of four environments. Three quantitative trait loci (QTL) with major effect were consistently detected on wheat chromosomes 2BL, 4A and 6BL. The 2BL QTL contributed by 26R61 was different from Pm6, a widely used gene in the southeastern USA. The other two QTL were identified from AGS 2000. The 6BL QTL was subsequently characterized as a simple Mendelian factor when the population was inoculated with a single Blumeria graminis f. sp. tritici (Bgt) isolate in controlled environments. Since there is no known powdery mildew resistance gene (Pm) on this particular location of common wheat, the gene was designated Pm54. The closely linked marker Xbarc134 was highly polymorphic in a set of mildew differentials, indicating that the marker should be useful for pyramiding Pm54 with other Pm genes by marker-assisted selection.

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David Marshall

North Carolina State University

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J. Paul Murphy

North Carolina State University

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E. Souza

Agricultural Research Service

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Christina Cowger

North Carolina State University

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Yue Jin

University of Minnesota

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Harold E. Bockelman

Agricultural Research Service

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J. A. Kolmer

Agricultural Research Service

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Yanhong Dong

University of Minnesota

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