Association mapping in sunflower for sclerotinia head rot resistance

Autores
Fusari, Corina Mariana; Di Rienzo, Julio A.; Troglia, Carolina Beatriz; Nishinakamasu, Veronica; Moreno, Maria Valeria; Maringolo, Carla Andrea; Quiroz, Facundo Jose; Alvarez, Daniel; Escande, Alberto; Hopp, Horacio Esteban; Heinz, Ruth Amelia; Lia, Veronica Viviana; Paniego, Norma Beatriz
Año de publicación
2012
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
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 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.
Instituto de Biotecnología
Fil: Fusari, Corina Mariana. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentina
Fil: Di Rienzo, Julio A. Universidad Nacional de Córdoba. Facultad de Ciencias Agropecuarias; Argentina
Fil: Troglia, Carolina Beatriz. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; Argentina
Fil: Nishinakamasu, Veronica. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentina
Fil: Moreno, Maria Valeria. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Manfredi; Argentina
Fil: Maringolo, Carla Andrea. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; Argentina
Fil: Quiroz, Facundo Jose. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; Argentina
Fil: Alvarez, Daniel. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Manfredi; Argentina
Fil: Escande, Alberto. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; Argentina.
Fil: Hopp, Horacio Esteban. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina
Fil: Heinz, Ruth Amelia. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina
Fil: Lia, Veronica Viviana. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina
Fil: Paniego, Norma Beatriz. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentina
Fuente
BMC Plant Biology 12 : 93 (2012)
Materia
Helianthus Annuus
Enfermedades de las Plantas
Sclerotinia
Resistencia a la Enfermedad
Loci de Rasgos Cuantitativos
Sclerotinia sclerotiorum
Plant Diseases
Disease Resistance
Quantitative Trait Loci
Girasol
QTL
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
INTA Digital (INTA)
Institución
Instituto Nacional de Tecnología Agropecuaria
OAI Identificador
oai:localhost:20.500.12123/4339
Acceder
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oai_identifier_str oai:localhost:20.500.12123/4339
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network_name_str INTA Digital (INTA)
spelling Association mapping in sunflower for sclerotinia head rot resistanceFusari, Corina MarianaDi Rienzo, Julio A.Troglia, Carolina BeatrizNishinakamasu, VeronicaMoreno, Maria ValeriaMaringolo, Carla AndreaQuiroz, Facundo JoseAlvarez, DanielEscande, AlbertoHopp, Horacio EstebanHeinz, Ruth AmeliaLia, Veronica VivianaPaniego, Norma BeatrizHelianthus AnnuusEnfermedades de las PlantasSclerotiniaResistencia a la EnfermedadLoci de Rasgos CuantitativosSclerotinia sclerotiorumPlant DiseasesDisease ResistanceQuantitative Trait LociGirasolQTLBackground: 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.Instituto de BiotecnologíaFil: Fusari, Corina Mariana. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; ArgentinaFil: Di Rienzo, Julio A. Universidad Nacional de Córdoba. Facultad de Ciencias Agropecuarias; ArgentinaFil: Troglia, Carolina Beatriz. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; ArgentinaFil: Nishinakamasu, Veronica. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; ArgentinaFil: Moreno, Maria Valeria. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Manfredi; ArgentinaFil: Maringolo, Carla Andrea. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; ArgentinaFil: Quiroz, Facundo Jose. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; ArgentinaFil: Alvarez, Daniel. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Manfredi; ArgentinaFil: Escande, Alberto. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; Argentina.Fil: Hopp, Horacio Esteban. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; ArgentinaFil: Heinz, Ruth Amelia. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; ArgentinaFil: Lia, Veronica Viviana. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; ArgentinaFil: Paniego, Norma Beatriz. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; ArgentinaBMC2019-01-28T13:55:53Z2019-01-28T13:55:53Z2012-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttps://bmcplantbiol.biomedcentral.com/articles/10.1186/1471-2229-12-93http://hdl.handle.net/20.500.12123/43391471-2229https://doi.org/10.1186/1471-2229-12-93BMC Plant Biology 12 : 93 (2012)reponame:INTA Digital (INTA)instname:Instituto Nacional de Tecnología Agropecuariaenginfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)2025-10-16T09:29:25Zoai:localhost:20.500.12123/4339instacron:INTAInstitucionalhttp://repositorio.inta.gob.ar/Organismo científico-tecnológicoNo correspondehttp://repositorio.inta.gob.ar/oai/requesttripaldi.nicolas@inta.gob.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:l2025-10-16 09:29:26.25INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuariafalse
dc.title.none.fl_str_mv Association mapping in sunflower for sclerotinia head rot resistance
title Association mapping in sunflower for sclerotinia head rot resistance
spellingShingle Association mapping in sunflower for sclerotinia head rot resistance
Fusari, Corina Mariana
Helianthus Annuus
Enfermedades de las Plantas
Sclerotinia
Resistencia a la Enfermedad
Loci de Rasgos Cuantitativos
Sclerotinia sclerotiorum
Plant Diseases
Disease Resistance
Quantitative Trait Loci
Girasol
QTL
title_short Association mapping in sunflower for sclerotinia head rot resistance
title_full Association mapping in sunflower for sclerotinia head rot resistance
title_fullStr Association mapping in sunflower for sclerotinia head rot resistance
title_full_unstemmed Association mapping in sunflower for sclerotinia head rot resistance
title_sort Association mapping in sunflower for sclerotinia head rot resistance
dc.creator.none.fl_str_mv Fusari, Corina Mariana
Di Rienzo, Julio A.
Troglia, Carolina Beatriz
Nishinakamasu, Veronica
Moreno, Maria Valeria
Maringolo, Carla Andrea
Quiroz, Facundo Jose
Alvarez, Daniel
Escande, Alberto
Hopp, Horacio Esteban
Heinz, Ruth Amelia
Lia, Veronica Viviana
Paniego, Norma Beatriz
author Fusari, Corina Mariana
author_facet Fusari, Corina Mariana
Di Rienzo, Julio A.
Troglia, Carolina Beatriz
Nishinakamasu, Veronica
Moreno, Maria Valeria
Maringolo, Carla Andrea
Quiroz, Facundo Jose
Alvarez, Daniel
Escande, Alberto
Hopp, Horacio Esteban
Heinz, Ruth Amelia
Lia, Veronica Viviana
Paniego, Norma Beatriz
author_role author
author2 Di Rienzo, Julio A.
Troglia, Carolina Beatriz
Nishinakamasu, Veronica
Moreno, Maria Valeria
Maringolo, Carla Andrea
Quiroz, Facundo Jose
Alvarez, Daniel
Escande, Alberto
Hopp, Horacio Esteban
Heinz, Ruth Amelia
Lia, Veronica Viviana
Paniego, Norma Beatriz
author2_role author
author
author
author
author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Helianthus Annuus
Enfermedades de las Plantas
Sclerotinia
Resistencia a la Enfermedad
Loci de Rasgos Cuantitativos
Sclerotinia sclerotiorum
Plant Diseases
Disease Resistance
Quantitative Trait Loci
Girasol
QTL
topic Helianthus Annuus
Enfermedades de las Plantas
Sclerotinia
Resistencia a la Enfermedad
Loci de Rasgos Cuantitativos
Sclerotinia sclerotiorum
Plant Diseases
Disease Resistance
Quantitative Trait Loci
Girasol
QTL
dc.description.none.fl_txt_mv 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 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.
Instituto de Biotecnología
Fil: Fusari, Corina Mariana. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentina
Fil: Di Rienzo, Julio A. Universidad Nacional de Córdoba. Facultad de Ciencias Agropecuarias; Argentina
Fil: Troglia, Carolina Beatriz. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; Argentina
Fil: Nishinakamasu, Veronica. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentina
Fil: Moreno, Maria Valeria. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Manfredi; Argentina
Fil: Maringolo, Carla Andrea. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; Argentina
Fil: Quiroz, Facundo Jose. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; Argentina
Fil: Alvarez, Daniel. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Manfredi; Argentina
Fil: Escande, Alberto. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; Argentina.
Fil: Hopp, Horacio Esteban. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina
Fil: Heinz, Ruth Amelia. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina
Fil: Lia, Veronica Viviana. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina
Fil: Paniego, Norma Beatriz. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentina
description 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 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.
publishDate 2012
dc.date.none.fl_str_mv 2012-06
2019-01-28T13:55:53Z
2019-01-28T13:55:53Z
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://bmcplantbiol.biomedcentral.com/articles/10.1186/1471-2229-12-93
http://hdl.handle.net/20.500.12123/4339
1471-2229
https://doi.org/10.1186/1471-2229-12-93
url https://bmcplantbiol.biomedcentral.com/articles/10.1186/1471-2229-12-93
http://hdl.handle.net/20.500.12123/4339
https://doi.org/10.1186/1471-2229-12-93
identifier_str_mv 1471-2229
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv BMC
publisher.none.fl_str_mv BMC
dc.source.none.fl_str_mv BMC Plant Biology 12 : 93 (2012)
reponame:INTA Digital (INTA)
instname:Instituto Nacional de Tecnología Agropecuaria
reponame_str INTA Digital (INTA)
collection INTA Digital (INTA)
instname_str Instituto Nacional de Tecnología Agropecuaria
repository.name.fl_str_mv INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuaria
repository.mail.fl_str_mv tripaldi.nicolas@inta.gob.ar
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