Unveiling the genetic basis of Sclerotinia head rot resistance in sunflower

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 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; Argentin

Genome-wide association studies in sunflower : towards sclerotinia sclerotiorum and diaporthe/phomopsis resistance breeding

Diseases caused by necrotrophic fungi, such as the cosmopolitan Sclerotinia sclerotiorum and the Diaporthe/Phomopsis complex, are among the most destructive diseases of sunflower worldwide. The lack of complete resistance combined with the inefficiency of chemical control makes assisted breeding the best strategy for disease control. In this work, we present an integrated genome-wide association (GWA) study investigating the response of a diverse panel of sunflower inbred lines to both pathogens. Phenotypic data for Sclerotinia head rot (SHR) consisted of five disease descriptors (disease incidence, DI; disease severity, DS; area under the disease progress curve for DI, AUDPCI, and DS, AUDPCS; and incubation period, IP). Two disease descriptors (DI and DS) were evaluated for two manifestations of Diaporthe/Phomopsis: Phomopsis stem canker (PSC) and Phomopsis head rot (PHR). In addition, a principal component (PC) analysis was used to derive transformed phenotypes as inputs to a univariateGWA (PC-GWA). Genotypic data comprised a panel of 4269 single nucleotide polymorphisms (SNP), generated via genotyping-by-sequencing. The GWA analysis revealed 24 unique marker–trait associations for SHR, 19 unique marker–trait associations for Diaporthe/Phomopsis diseases, and 7 markers associated with PC1 and PC2. No common markers were found for the response to the two pathogens. Nevertheless, epistatic interactions were identified between markers significantly associated with the response to S. sclerotiorum and Diaporthe/Phomopsis. This suggests that, while the main determinants of resistance may differ for the two pathogens, there could be an underlying common genetic basis. The exploration of regions physically close to the associated markers yielded 364 genes, of which 19 were predicted as putative disease resistance genes. This work presents the first simultaneous evaluation of two manifestations of Diaporthe/Phomopsis in sunflower, and undertakes a comprehensive GWA study by integrating PSC, PHR, and SHR data. The multiple regions identified, and their exploration to identify candidate genes, contribute not only to the understanding of the genetic basis of resistance, but also to the development of tools for assisted breeding.Instituto de BiotecnologíaFil: Filippi, Carla Valeria. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Agrobiotecnología y Biología Molecular; ArgentinaFil: Filippi, Carla Valeria. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Corro Molas, Andres. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Anguil. Agencia de Extensión Rural General Pico; ArgentinaFil: Dominguez, Matías. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Pergamino; ArgentinaFil: Colombo, Denis Nahuel. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Anguil; ArgentinaFil: Heinz, N. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Manfredi; ArgentinaFil: Troglia, Carolina Beatriz. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; 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: Lia, Veronica Viviana. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Agrobiotecnología y Biología Molecular; ArgentinaFil: Lia, Veronica Viviana. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Lia, Veronica Viviana. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; ArgentinaFil: Paniego, Norma Beatriz. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Agrobiotecnología y Biología Molecular; ArgentinaFil: Paniego, Norma Beatriz. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

Main and epistatic QTL analyses for Sclerotinia Head Rot resistance in sunflower

Sclerotinia Head Rot (SHR), a disease caused by Sclerotinia sclerotiorum, is one of the most limiting factors in sunflower production. In this study, we identified genomic loci associated with resistance to SHR to support the development of assisted breeding strategies. We genotyped 114 Recombinant Inbred Lines (RILs) along with their parental lines (PAC2 –partially resistant–and RHA266 –susceptible–) by using a 384 single nucleotide polymorphism (SNP) Illumina Oligo Pool Assay to saturate a sunflower genetic map. Subsequently, we tested these lines for SHR resistance using assisted inoculations with S. sclerotiorum ascospores. We also conducted a randomized complete-block assays with three replicates to visually score disease incidence (DI), disease severity (DS), disease intensity (DInt) and incubation period (IP) through four field trials (2010–2014). We finally assessed main effect quantitative trait loci (M-QTLs) and epistatic QTLs (E-QTLs) by composite interval mapping (CIM) and mixed-model-based composite interval mapping (MCIM), respectively. As a result of this study, the improved map incorporates 61 new SNPs over candidate genes. We detected a broad range of narrow sense heritability (h2) values (1.86–59.9%) as well as 36 M-QTLs and 13 E-QTLs along 14 linkage groups (LGs). On LG1, LG10, and LG15, we repeatedly detected QTLs across field trials; which emphasizes their putative effectiveness against SHR. In all selected variables, most of the identified QTLs showed high determination coefficients, associated with moderate to high heritability values. Using markers shared with previous Sclerotinia resistance studies, we compared the QTL locations in LG1, LG2, LG8, LG10, LG11, LG15 and LG16. This study constitutes the largest report of QTLs for SHR resistance in sunflower. Further studies focusing on the regions in LG1, LG10, and LG15 harboring the detected QTLs are necessary to identify causal alleles and contribute to unraveling the complex genetic basis governing the resistance.Instituto de BiotecnologíaFil: Zubrzycki, Jeremias Enrique. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; ArgentinaFil: Maringolo, Carla Andrea. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce. Laboratorio de Patología Vegetal; ArgentinaFil: Filippi, Carla Valeria. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Quiroz, Facundo Jose. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce. Laboratorio de Patología Vegetal; ArgentinaFil: Nishinakamasu, Veronica. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; ArgentinaFil: Puebla, Andrea Fabiana. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; ArgentinaFil: Di Rienzo, Julio Alejandro. Universidad Nacional de Córdoba. Facultad de Ciencias Agropecuarias. Cátedra de Estadística y Biometría; ArgentinaFil: Escande, Alberto. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce. Laboratorio de Patología Vegetal; 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; 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: Hopp, Horacio Esteban. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; ArgentinaFil: Cervigni, Gerardo Domingo Lucio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro de Estudios Fotosintéticos y Bioquímicos. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Centro de Estudios Fotosintéticos y Bioquímicos; ArgentinaFil: Paniego, Norma Beatriz. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

On-field phenotypic evaluation of sunflower populations for broad-spectrum resistance to Verticillium leaf mottle and wilt

Sunflower Verticillium Wilt and Leaf Mottle (SVW), caused by Verticillium dahliae (Kleb.; Vd), is a soil-borne disease affecting sunflower worldwide. A single dominant locus, known as V1, was formerly effective in controlling North-American Vd races, whereas races from Argentina, Europe and an emerging race from USA overcome its resistance. This emphasizes the need for identifying broad-spectrum genetic resistance (BSR) sources. Here we characterize two sunflower mapping populations (MPs) for SVW resistance: a biparental MP and the association MP from the National Institute of Agricultural Technology (INTA), under field growing conditions. Nine field-trials (FTs) were conducted in highly infested fields in the most SVW-affected region of Argentina. Several disease descriptors (DDs), including incidence and severity, were scored across four phenological stages. Generalized linear models were fitted according to the nature of each variable, adjusting mean phenotypes for inbred lines across and within FTs. Comparison of these responses allowed the identification of novel BSR sources. Furthermore, we present the first report of SVW resistance heritability, with estimates ranging from 35 to 45% for DDs related to disease incidence and severity, respectively. This study constitutes the largest SVW resistance characterization reported to date in sunflower, identifying valuable genetic resources for BSR-breeding to cope with a pathogen of increasing importance worldwide.EEA PergaminoFil: Montecchia, Juan Francisco. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Agrobiotecnología y Biología Molecular (IABIMO); ArgentinaFil: Fass, Mónica I. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología. Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET). Instituto de Agrobiotecnología y Biología Molecular (IABIMO); ArgentinaFil: Cerrudo, Ignacio. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; ArgentinaFil: Quiroz, Facundo José. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; ArgentinaFil: Nicosia, Salvador Maria. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnologoía. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Agrobiotecnología y Biología Molecular (IABIMO); ArgentinaFil: Maringolo, Carla Andrea. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; ArgentinaFil: Di Rienzo, Julio. Universidad Nacional de Córdoba. Facultad de Ciencias Agropecuarias; ArgentinaFil: Troglia, Carolina Beatriz. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; ArgentinaFil: Hopp, Horacio Esteban. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnologoía. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Agrobiotecnología y Biología Molecular (IABIMO); ArgentinaFil: Hopp, Horacio Esteban. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; ArgentinaFil: Escande, Alberto. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; ArgentinaFil: Gonzalez, Julio Horacio. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Pergamino. Sección Girasol; ArgentinaFil: Alvarez, Daniel. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Manfredi; ArgentinaFil: Heinz, Ruth Amelia. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnologoía. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Agrobiotecnología y Biología Molecular (IABIMO); ArgentinaFil: Lia, Veronica Viviana. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnologoía. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Agrobiotecnología y Biología Molecular (IABIMO); ArgentinaFil: Lia, Veronica Viviana. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; ArgentinaFil: Paniego, Norma Beatriz. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnologoía. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Agrobiotecnología y Biología Molecular (IABIMO); Argentin

Phenotyping sunflower genetic resources for Sclerotinia head rot response: assessing variability for disease resistance breeding

Sclerotinia head rot (SHR) is one of the most serious constraints to sunflower (Helianthus annuus L. var. macrocarpus) production worldwide. Here, we evaluated the response to SHR in a sunflower inbred panel from a large INTA germplasm collection, consisting of 137 inbred lines (ILs). Field trials were performed over five consecutive seasons using a twice-replicated randomized complete-block design. Disease incidence, disease severity, incubation period and area under disease progress curve for disease incidence and severity were determined after controlled inoculation with the pathogen. Statistical analysis using mixed-effect models detected significant differences among ILs for all variables (P<0.001). In addition, Principal Component Analysis (PCA) and distance based methods were used to classify the ILs according to their response to SHR, with ILs ALB2/5261 and 5383 emerging as the most resistant. Broad-sense heritability estimates ranged from 20.64% for disease severity to 10.58% for incubation period. The ample phenotypic variability of our collection, along with the moderate heritability estimates, highlight the importance of molecular breeding approaches to gain new insights into the genetic basis of sunflower resistance to SHR. The exhaustive phenotypic characterization presented here provides a reliable set of variables to comprehensively evaluate the disease and identifies two new sources of resistance to SHR.Instituto de BiotecnologíaFil: Filippi, Carla Valeria. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; ArgentinaFil: Zubrzycki, Jeremias Enrique. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; ArgentinaFil: Di Rienzo, Julio A. Universidad Nacional de Córdoba. Facultad de Ciencias Agropecuarias; ArgentinaFil: Quiroz, Facundo Jose. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; ArgentinaFil: Fusari, Corina Mariana. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentina. Max Planck Institute of Molecular Plant Physiology; AlemaniaFil: 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; ArgentinaFil: Cordes, Diego Darío. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Manfredi; ArgentinaFil: Escande, Alberto. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; 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: 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; ArgentinaFil: Paniego, Norma Beatriz. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

Genetic linkage map of BMP showing locations on LG14-17 of different types of QTLs and interactions detected through single- and two-locus QTL analyses for resistance traits.

<p>Mapped markers are listed on the left. Underlined markers correspond to the 61 SNPs mapped in this work. Lengths of confidence Interval (CI) for the M-QTL and the Ep-QTL are denoted by full lines and dashed lines, respectively. Epistatic interaction between QTLs is represented with arrows. SHR QTLs coincident with previous reported QTLs are in bold. * QTLs detected using QTL Cartographer. ** QTLs detected using QTLNetwork. *** QTLs detected using both programs.</p

Parameters associated with main-effect QTLs and those involved in interaction with the trial (environment) detected in BMP by two-locus analysis using QTLNetwork.

<p>Parameters associated with main-effect QTLs and those involved in interaction with the trial (environment) detected in BMP by two-locus analysis using QTLNetwork.</p

Marker density and marker distribution on sunflower linkage groups (LGs).

<p>Marker density and marker distribution on sunflower linkage groups (LGs).</p

Statistical analysis for four disease resistant traits of RIL population and parents in multiple environments.

<p>Statistical analysis for four disease resistant traits of RIL population and parents in multiple environments.</p

Genetic linkage map of BMP showing locations on LG6-9 of different types of QTLs and interactions detected through single- and two-locus QTL analyses for resistance traits.

<p>Mapped markers are listed on the left. Underlined markers correspond to the 61 SNPs mapped in this work. Lengths of confidence Interval (CI) for the M-QTL and the Ep-QTL are denoted by full lines and dashed lines, respectively. Epistatic interaction between QTLs is represented with arrows. SHR QTLs coincident with previous reported QTLs are in bold. * QTLs detected using QTL Cartographer. ** QTLs detected using QTLNetwork. *** QTLs detected using both programs.</p