Unveiling the genetic basis of Sclerotinia head rot resistance in sunflower
- Autores
- Filippi, Carla Valeria; Zubrzycki, Jeremias Enrique; Di Rienzo, Julio Alejandro; Quiroz, Facundo Jose; Puebla, Andrea Fabiana; Alvarez, Daniel; Maringolo, Carla Andrea; Escande, Alberto; Hopp, Horacio Esteban; Heinz, Ruth Amelia; Paniego, Norma Beatriz; Lia, Veronica Viviana
- Año de publicación
- 2020
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- Background: Sclerotinia sclerotiorum is a necrotrophic fungus that causes Sclerotinia head rot (SHR) in sunflower, with epidemics leading to severe yield losses. In this work, we present an association mapping (AM) approach to investigate the genetic basis of natural resistance to SHR in cultivated sunflower, the fourth most widely grown oilseed crop in the world. Results: Our association mapping population (AMP), which comprises 135 inbred breeding lines (ILs), was genotyped using 27 candidate genes, a panel of 9 Simple Sequence Repeat (SSR) markers previously associated with SHR resistance via bi-parental mapping, and a set of 384 SNPs located in genes with molecular functions related to stress responses. Moreover, given the complexity of the trait, we evaluated four disease descriptors (i.e, disease incidence, disease severity, area under the disease progress curve for disease incidence, and incubation period). As a result, this work constitutes the most exhaustive AM study of disease resistance in sunflower performed to date. Mixed linear models accounting for population structure and kinship relatedness were used for the statistical analysis of phenotype-genotype associations, allowing the identification of 13 markers associated with disease reduction. The number of favourable alleles was negatively correlated to disease incidence, disease severity and area under the disease progress curve for disease incidence, whereas it was positevily correlated to the incubation period. Conclusions: Four of the markers identified here as associated with SHR resistance (HA1848, HaCOI_1, G33 and G34) validate previous research, while other four novel markers (SNP117, SNP136, SNP44, SNP128) were consistently associated with SHR resistance, emerging as promising candidates for marker-assisted breeding. From the germplasm point of view, the five ILs carrying the largest combination of resistance alleles provide a valuable resource for sunflower breeding programs worldwide.
Instituto de Biotecnología
Fil: Filippi, Carla Valeria. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Zubrzycki, Jeremias Enrique. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentina. Biocódices; Argentina
Fil: Di Rienzo, Julio Alejandro. Universidad Nacional de Córdoba. Facultad de Ciencias Agropecuarias. Cátedra de Estadística y Biometría; Argentina
Fil: Quiroz, Facundo Jose. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce. Laboratorio de Patología Vegetal; Argentina
Fil: Puebla, Andrea Fabiana. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentina
Fil: Alvarez, Daniel. 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. Laboratorio de Patología Vegetal; Argentina
Fil: Escande, Alberto. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce. Laboratorio de Patología Vegetal; 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. Consejo Nacional de Investigaciones Científicas y Técnicas; 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. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Lia, Veronica Viviana. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina - Fuente
- BMC Plant Biology 20 : article number: 322 (2020)
- Materia
-
Helianthus annuus
Enfermedades de las Plantas
Sclerotinia
Genética
Resistencia a la Enfermedad
Plant Diseases
Genetics
Disease Resistance
Rots
Podredumbres
Girasol
Sunflower - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by-nc-sa/4.0/
- Repositorio
- Institución
- Instituto Nacional de Tecnología Agropecuaria
- OAI Identificador
- oai:localhost:20.500.12123/7559
Ver los metadatos del registro completo
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Unveiling the genetic basis of Sclerotinia head rot resistance in sunflowerFilippi, Carla ValeriaZubrzycki, Jeremias EnriqueDi Rienzo, Julio AlejandroQuiroz, Facundo JosePuebla, Andrea FabianaAlvarez, DanielMaringolo, Carla AndreaEscande, AlbertoHopp, Horacio EstebanHeinz, Ruth AmeliaPaniego, Norma BeatrizLia, Veronica VivianaHelianthus annuusEnfermedades de las PlantasSclerotiniaGenéticaResistencia a la EnfermedadPlant DiseasesGeneticsDisease ResistanceRotsPodredumbresGirasolSunflowerBackground: Sclerotinia sclerotiorum is a necrotrophic fungus that causes Sclerotinia head rot (SHR) in sunflower, with epidemics leading to severe yield losses. In this work, we present an association mapping (AM) approach to investigate the genetic basis of natural resistance to SHR in cultivated sunflower, the fourth most widely grown oilseed crop in the world. Results: Our association mapping population (AMP), which comprises 135 inbred breeding lines (ILs), was genotyped using 27 candidate genes, a panel of 9 Simple Sequence Repeat (SSR) markers previously associated with SHR resistance via bi-parental mapping, and a set of 384 SNPs located in genes with molecular functions related to stress responses. Moreover, given the complexity of the trait, we evaluated four disease descriptors (i.e, disease incidence, disease severity, area under the disease progress curve for disease incidence, and incubation period). As a result, this work constitutes the most exhaustive AM study of disease resistance in sunflower performed to date. Mixed linear models accounting for population structure and kinship relatedness were used for the statistical analysis of phenotype-genotype associations, allowing the identification of 13 markers associated with disease reduction. The number of favourable alleles was negatively correlated to disease incidence, disease severity and area under the disease progress curve for disease incidence, whereas it was positevily correlated to the incubation period. Conclusions: Four of the markers identified here as associated with SHR resistance (HA1848, HaCOI_1, G33 and G34) validate previous research, while other four novel markers (SNP117, SNP136, SNP44, SNP128) were consistently associated with SHR resistance, emerging as promising candidates for marker-assisted breeding. From the germplasm point of view, the five ILs carrying the largest combination of resistance alleles provide a valuable resource for sunflower breeding programs worldwide.Instituto de BiotecnologíaFil: Filippi, Carla Valeria. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Zubrzycki, Jeremias Enrique. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentina. Biocódices; ArgentinaFil: Di Rienzo, Julio Alejandro. Universidad Nacional de Córdoba. Facultad de Ciencias Agropecuarias. Cátedra de Estadística y Biometría; ArgentinaFil: Quiroz, Facundo Jose. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce. Laboratorio de Patología Vegetal; ArgentinaFil: Puebla, Andrea Fabiana. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; ArgentinaFil: Alvarez, Daniel. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Manfredi; ArgentinaFil: Maringolo, Carla Andrea. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce. Laboratorio de Patología Vegetal; ArgentinaFil: Escande, Alberto. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce. Laboratorio de Patología Vegetal; ArgentinaFil: 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. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; ArgentinaFil: Paniego, Norma Beatriz. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Lia, Veronica Viviana. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; ArgentinaBMC2020-07-15T17:34:53Z2020-07-15T17:34:53Z2020-07info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://hdl.handle.net/20.500.12123/7559https://bmcplantbiol.biomedcentral.com/articles/10.1186/s12870-020-02529-71471-2229https://doi.org/10.1186/s12870-020-02529-7BMC Plant Biology 20 : article number: 322 (2020)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)2025-09-29T13:44:58Zoai:localhost:20.500.12123/7559instacron:INTAInstitucionalhttp://repositorio.inta.gob.ar/Organismo científico-tecnológicoNo correspondehttp://repositorio.inta.gob.ar/oai/requesttripaldi.nicolas@inta.gob.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:l2025-09-29 13:44:59.271INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuariafalse |
dc.title.none.fl_str_mv |
Unveiling the genetic basis of Sclerotinia head rot resistance in sunflower |
title |
Unveiling the genetic basis of Sclerotinia head rot resistance in sunflower |
spellingShingle |
Unveiling the genetic basis of Sclerotinia head rot resistance in sunflower Filippi, Carla Valeria Helianthus annuus Enfermedades de las Plantas Sclerotinia Genética Resistencia a la Enfermedad Plant Diseases Genetics Disease Resistance Rots Podredumbres Girasol Sunflower |
title_short |
Unveiling the genetic basis of Sclerotinia head rot resistance in sunflower |
title_full |
Unveiling the genetic basis of Sclerotinia head rot resistance in sunflower |
title_fullStr |
Unveiling the genetic basis of Sclerotinia head rot resistance in sunflower |
title_full_unstemmed |
Unveiling the genetic basis of Sclerotinia head rot resistance in sunflower |
title_sort |
Unveiling the genetic basis of Sclerotinia head rot resistance in sunflower |
dc.creator.none.fl_str_mv |
Filippi, Carla Valeria Zubrzycki, Jeremias Enrique Di Rienzo, Julio Alejandro Quiroz, Facundo Jose Puebla, Andrea Fabiana Alvarez, Daniel Maringolo, Carla Andrea Escande, Alberto Hopp, Horacio Esteban Heinz, Ruth Amelia Paniego, Norma Beatriz Lia, Veronica Viviana |
author |
Filippi, Carla Valeria |
author_facet |
Filippi, Carla Valeria Zubrzycki, Jeremias Enrique Di Rienzo, Julio Alejandro Quiroz, Facundo Jose Puebla, Andrea Fabiana Alvarez, Daniel Maringolo, Carla Andrea Escande, Alberto Hopp, Horacio Esteban Heinz, Ruth Amelia Paniego, Norma Beatriz Lia, Veronica Viviana |
author_role |
author |
author2 |
Zubrzycki, Jeremias Enrique Di Rienzo, Julio Alejandro Quiroz, Facundo Jose Puebla, Andrea Fabiana Alvarez, Daniel Maringolo, Carla Andrea Escande, Alberto Hopp, Horacio Esteban Heinz, Ruth Amelia Paniego, Norma Beatriz Lia, Veronica Viviana |
author2_role |
author author author author author author author author author author author |
dc.subject.none.fl_str_mv |
Helianthus annuus Enfermedades de las Plantas Sclerotinia Genética Resistencia a la Enfermedad Plant Diseases Genetics Disease Resistance Rots Podredumbres Girasol Sunflower |
topic |
Helianthus annuus Enfermedades de las Plantas Sclerotinia Genética Resistencia a la Enfermedad Plant Diseases Genetics Disease Resistance Rots Podredumbres Girasol Sunflower |
dc.description.none.fl_txt_mv |
Background: Sclerotinia sclerotiorum is a necrotrophic fungus that causes Sclerotinia head rot (SHR) in sunflower, with epidemics leading to severe yield losses. In this work, we present an association mapping (AM) approach to investigate the genetic basis of natural resistance to SHR in cultivated sunflower, the fourth most widely grown oilseed crop in the world. Results: Our association mapping population (AMP), which comprises 135 inbred breeding lines (ILs), was genotyped using 27 candidate genes, a panel of 9 Simple Sequence Repeat (SSR) markers previously associated with SHR resistance via bi-parental mapping, and a set of 384 SNPs located in genes with molecular functions related to stress responses. Moreover, given the complexity of the trait, we evaluated four disease descriptors (i.e, disease incidence, disease severity, area under the disease progress curve for disease incidence, and incubation period). As a result, this work constitutes the most exhaustive AM study of disease resistance in sunflower performed to date. Mixed linear models accounting for population structure and kinship relatedness were used for the statistical analysis of phenotype-genotype associations, allowing the identification of 13 markers associated with disease reduction. The number of favourable alleles was negatively correlated to disease incidence, disease severity and area under the disease progress curve for disease incidence, whereas it was positevily correlated to the incubation period. Conclusions: Four of the markers identified here as associated with SHR resistance (HA1848, HaCOI_1, G33 and G34) validate previous research, while other four novel markers (SNP117, SNP136, SNP44, SNP128) were consistently associated with SHR resistance, emerging as promising candidates for marker-assisted breeding. From the germplasm point of view, the five ILs carrying the largest combination of resistance alleles provide a valuable resource for sunflower breeding programs worldwide. Instituto de Biotecnología Fil: Filippi, Carla Valeria. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Zubrzycki, Jeremias Enrique. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentina. Biocódices; Argentina Fil: Di Rienzo, Julio Alejandro. Universidad Nacional de Córdoba. Facultad de Ciencias Agropecuarias. Cátedra de Estadística y Biometría; Argentina Fil: Quiroz, Facundo Jose. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce. Laboratorio de Patología Vegetal; Argentina Fil: Puebla, Andrea Fabiana. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentina Fil: Alvarez, Daniel. 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. Laboratorio de Patología Vegetal; Argentina Fil: Escande, Alberto. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce. Laboratorio de Patología Vegetal; 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. Consejo Nacional de Investigaciones Científicas y Técnicas; 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. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Lia, Veronica Viviana. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina |
description |
Background: Sclerotinia sclerotiorum is a necrotrophic fungus that causes Sclerotinia head rot (SHR) in sunflower, with epidemics leading to severe yield losses. In this work, we present an association mapping (AM) approach to investigate the genetic basis of natural resistance to SHR in cultivated sunflower, the fourth most widely grown oilseed crop in the world. Results: Our association mapping population (AMP), which comprises 135 inbred breeding lines (ILs), was genotyped using 27 candidate genes, a panel of 9 Simple Sequence Repeat (SSR) markers previously associated with SHR resistance via bi-parental mapping, and a set of 384 SNPs located in genes with molecular functions related to stress responses. Moreover, given the complexity of the trait, we evaluated four disease descriptors (i.e, disease incidence, disease severity, area under the disease progress curve for disease incidence, and incubation period). As a result, this work constitutes the most exhaustive AM study of disease resistance in sunflower performed to date. Mixed linear models accounting for population structure and kinship relatedness were used for the statistical analysis of phenotype-genotype associations, allowing the identification of 13 markers associated with disease reduction. The number of favourable alleles was negatively correlated to disease incidence, disease severity and area under the disease progress curve for disease incidence, whereas it was positevily correlated to the incubation period. Conclusions: Four of the markers identified here as associated with SHR resistance (HA1848, HaCOI_1, G33 and G34) validate previous research, while other four novel markers (SNP117, SNP136, SNP44, SNP128) were consistently associated with SHR resistance, emerging as promising candidates for marker-assisted breeding. From the germplasm point of view, the five ILs carrying the largest combination of resistance alleles provide a valuable resource for sunflower breeding programs worldwide. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-07-15T17:34:53Z 2020-07-15T17:34:53Z 2020-07 |
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 |
http://hdl.handle.net/20.500.12123/7559 https://bmcplantbiol.biomedcentral.com/articles/10.1186/s12870-020-02529-7 1471-2229 https://doi.org/10.1186/s12870-020-02529-7 |
url |
http://hdl.handle.net/20.500.12123/7559 https://bmcplantbiol.biomedcentral.com/articles/10.1186/s12870-020-02529-7 https://doi.org/10.1186/s12870-020-02529-7 |
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 20 : article number: 322 (2020) 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 |
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tripaldi.nicolas@inta.gob.ar |
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