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Abstract
Background: Sclerotinia Head Rot (SHR) is one of the most damaging diseases of sunflower in Europe, Argentina, and USA, causing average yield reductions of 10 to 20 %, but leading to total production loss under favorable environmental conditions for the pathogen. Association Mapping (AM) is a promising choice for Quantitative Trait Locus (QTL) mapping, as it detects relationships between phenotypic variation and gene polymorphisms in existing germplasm [ver mas...]
dc.contributor.authorFusari, Corina Mariana
dc.contributor.authorDi Rienzo, Julio A.
dc.contributor.authorTroglia, Carolina Beatriz
dc.contributor.authorNishinakamasu, Veronica
dc.contributor.authorMoreno, Maria Valeria
dc.contributor.authorMaringolo, Carla Andrea
dc.contributor.authorQuiroz, Facundo Jose
dc.contributor.authorAlvarez, Daniel
dc.contributor.authorEscande, Alberto
dc.contributor.authorHopp, Horacio Esteban
dc.contributor.authorHeinz, Ruth Amelia
dc.contributor.authorLia, Veronica Viviana
dc.contributor.authorPaniego, Norma Beatriz
dc.date.accessioned2019-01-28T13:55:53Z
dc.date.available2019-01-28T13:55:53Z
dc.date.issued2012-06
dc.identifier.issn1471-2229
dc.identifier.otherhttps://doi.org/10.1186/1471-2229-12-93
dc.identifier.urihttps://bmcplantbiol.biomedcentral.com/articles/10.1186/1471-2229-12-93
dc.identifier.urihttp://hdl.handle.net/20.500.12123/4339
dc.description.abstractBackground: Sclerotinia Head Rot (SHR) is one of the most damaging diseases of sunflower in Europe, Argentina, and USA, causing average yield reductions of 10 to 20 %, but leading to total production loss under favorable environmental conditions for the pathogen. Association Mapping (AM) is a promising choice for Quantitative Trait Locus (QTL) mapping, as it detects relationships between phenotypic variation and gene polymorphisms in existing germplasm without development of mapping populations. This article reports the identification of QTL for resistance to SHR based on candidate gene AM. Results: A collection of 94 sunflower inbred lines were tested for SHR under field conditions using assisted inoculation with the fungal pathogen Sclerotinia sclerotiorum. Given that no biological mechanisms or biochemical pathways have been clearly identified for SHR, 43 candidate genes were selected based on previous transcript profiling studies in sunflower and Brassica napus infected with S. sclerotiorum. Associations among SHR incidence and haplotype polymorphisms in 16 candidate genes were tested using Mixed Linear Models (MLM) that account for population structure and kinship relationships. This approach allowed detection of a significant association between the candidate gene HaRIC_B and SHR incidence (P < 0.01), accounting for a SHR incidence reduction of about 20 %. Conclusions: These results suggest that AM will be useful in dissecting other complex traits in sunflower, thus providing a valuable tool to assist in crop breeding.eng
dc.formatapplication/pdfes_AR
dc.language.isoenges_AR
dc.publisherBMCes_AR
dc.rightsinfo:eu-repo/semantics/openAccesses_AR
dc.sourceBMC Plant Biology 12 : 93 (2012)es_AR
dc.subjectHelianthus Annuuses_AR
dc.subjectEnfermedades de las Plantases_AR
dc.subjectPlant Diseaseseng
dc.subjectSclerotiniaes_AR
dc.subjectResistencia a la Enfermedades_AR
dc.subjectDisease Resistanceeng
dc.subjectLoci de Rasgos Cuantitativoses_AR
dc.subjectQuantitative Trait Locieng
dc.subjectSclerotinia sclerotiorumes_AR
dc.subject.otherGirasoles_AR
dc.subject.otherQTLes_AR
dc.titleAssociation mapping in sunflower for sclerotinia head rot resistancees_AR
dc.typeinfo:ar-repo/semantics/artículoes_AR
dc.typeinfo:eu-repo/semantics/articlees_AR
dc.typeinfo:eu-repo/semantics/publishedVersiones_AR
dc.description.origenInstituto de Biotecnologíaes_AR
dc.description.filFil: Fusari, Corina Mariana. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentinaes_AR
dc.description.filFil: Di Rienzo, Julio A. Universidad Nacional de Córdoba. Facultad de Ciencias Agropecuarias; Argentinaes_AR
dc.description.filFil: Troglia, Carolina Beatriz. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; Argentinaes_AR
dc.description.filFil: Nishinakamasu, Veronica. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentinaes_AR
dc.description.filFil: Moreno, Maria Valeria. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Manfredi; Argentinaes_AR
dc.description.filFil: Maringolo, Carla Andrea. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; Argentinaes_AR
dc.description.filFil: Quiroz, Facundo Jose. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; Argentinaes_AR
dc.description.filFil: Alvarez, Daniel. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Manfredi; Argentinaes_AR
dc.description.filFil: Escande, Alberto. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; Argentina.es_AR
dc.description.filFil: Hopp, Horacio Esteban. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentinaes_AR
dc.description.filFil: Heinz, Ruth Amelia. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentinaes_AR
dc.description.filFil: Lia, Veronica Viviana. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentinaes_AR
dc.description.filFil: Paniego, Norma Beatriz. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentinaes_AR
dc.subtypecientifico


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