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
INTA Digital (INTA)
Institución
Instituto Nacional de Tecnología Agropecuaria
OAI Identificador
oai:localhost:20.500.12123/7559
Acceder
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oai_identifier_str oai:localhost:20.500.12123/7559
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network_name_str INTA Digital (INTA)
spelling 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)2025-10-16T09:29:51Zoai: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:l2025-10-16 09:29:51.364INTA 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
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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
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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)
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reponame_str INTA Digital (INTA)
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