dc.date.accessioned2019-02-22T14:54:30Z
dc.date.available2019-02-22T14:54:30Z
dc.date.created2019-02-22T14:54:30Z
dc.date.issued2014
dc.identifierhttps://hdl.handle.net/20.500.12866/5656
dc.identifierhttps://doi.org/10.1007/s00122-014-2448-y
dc.description.abstractDiseases represent a major constraint for barley (Hordeum vulgare L.) production in Latin America. Spot blotch (caused by Cochliobolus sativus), stripe rust (caused by Puccinia striiformis f.sp. hordei) and leaf rust (caused by Puccinia hordei) are three of the most important diseases that affect the crop in the region. Since fungicide application is not an economically or environmentally sound solution, the development of durably resistant varieties is a priority for breeding programs. Therefore, new resistance sources are needed. The objective of this work was to detect genomic regions associated with field level plant resistance to spot blotch, stripe rust, and leaf rust in Latin American germplasm. Disease severities measured in multi-environment trials across the Americas and 1,096 SNPs in a population of 360 genotypes were used to identify genomic regions associated with disease resistance. Optimized experimental design and spatial modeling were used in each trial to estimate genotypic means. Genome-Wide Association Mapping (GWAS) in each environment was used to detect Quantitative Trait Loci (QTL). All significant environment-specific QTL were subsequently included in a multi-environment-multi-QTL (MEMQ) model. Geographical origin and inflorescence type were the main determinants of population structure. Spot blotch severity was low to intermediate while leaf and stripe rust severity was high in all environments. Mega-environments were defined by locations for spot blotch and leaf rust. Significant marker-trait associations for spot blotch (9 QTL), leaf (6 QTL) and stripe rust (7 QTL) and both global and environment-specific QTL were detected that will be useful for future breeding efforts. Key message: Multi-environment multi-QTL mixed models were used in a GWAS context to identify QTL for disease resistance. The use of mega-environments aided the interpretation of environment-specific and general QTL.
dc.languageeng
dc.publisherSpringer
dc.relationTheoretical and Applied Genetics
dc.relation1432-2242
dc.rightshttps://creativecommons.org/licenses/by-nc-nd/4.0/deed.es
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.subjectPhenotype
dc.subjectGenotype
dc.subjectQuantitative Trait Loci
dc.subjectGenes
dc.subjectgenotype
dc.subjectphenotype
dc.subjectgenetics
dc.subjectquantitative trait locus
dc.subjectmicrobiology
dc.subjectstatistical model
dc.subjectModels, Statistical
dc.subjectGenetic Association Studies
dc.subjectgenetic association
dc.subjectAscomycetes
dc.subjectAscomycota
dc.subjectbreeding
dc.subjectPlants (botany)
dc.subjectaudiovisual equipment
dc.subjectApplication programs
dc.subjectBarley (hordeum vulgare l.)
dc.subjectBasidiomycetes
dc.subjectBasidiomycota
dc.subjectBreeding
dc.subjectChromosomes, Plant
dc.subjectCochliobolus sativus
dc.subjectDesign of experiments
dc.subjectdisease resistance
dc.subjectDisease Resistance
dc.subjectFungicide application
dc.subjectGenome-wide association
dc.subjectGeographical origins
dc.subjectHordeum
dc.subjectMapping
dc.subjectModels, Anatomic
dc.subjectplant chromosome
dc.subjectplant disease
dc.subjectPlant Diseases
dc.subjectPopulation structures
dc.subjectPuccinia striiformis
dc.subjectQuantitative trait locus
dc.titleMulti-environment multi-QTL association mapping identifies disease resistance QTL in barley germplasm from Latin America
dc.typeinfo:eu-repo/semantics/article


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