Exploring sunflower responses to Sclerotinia head rot at early stages of infection using RNA-seq analysis

Sclerotinia head rot (SHR), caused by the necrotrophic fungus Sclerotinia sclerotiorum, is one of the most devastating sunflower crop diseases. Despite its worldwide occurrence, the genetic determinants of plant resistance are still largely unknown. Here, we investigated the Sclerotinia-sunflower pathosystem by analysing temporal changes in gene expression in one susceptible and two tolerant inbred lines (IL) inoculated with the pathogen under field conditions. Differential expression analysis showed little overlapping among ILs, suggesting genotype-specific control of cell defense responses possibly related to differences in disease resistance strategies. Functional enrichment assessments yielded a similar pattern. However, all three ILs altered the expression of genes involved in the cellular redox state and cell wall remodeling, in agreement with current knowledge about the initiation of plant immune responses. Remarkably, the over-representation of long non-coding RNAs (lncRNA) was another common feature among ILs. Our findings highlight the diversity of transcriptional responses to SHR within sunflower breeding lines and provide evidence of lncRNAs playing a significant role at early stages of defense.Fil: Fass, Mónica Irina. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Agrobiotecnología y Biología Molecular. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Agrobiotecnología y Biología Molecular; ArgentinaFil: Rivarola, Maximo Lisandro. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Agrobiotecnología y Biología Molecular. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Agrobiotecnología y Biología Molecular; ArgentinaFil: Ehrenbolger, Guillermo Federico. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Agrobiotecnología y Biología Molecular. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Agrobiotecnología y Biología Molecular; ArgentinaFil: Maringolo, Carla A.. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Buenos Aires Sur. Estación Experimental Agropecuaria Balcarce; ArgentinaFil: Montecchia, Juan Francisco. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Agrobiotecnología y Biología Molecular. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Agrobiotecnología y Biología Molecular; ArgentinaFil: Quiroz, Facundo José. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Buenos Aires Sur. Estación Experimental Agropecuaria Balcarce; ArgentinaFil: García García, Francisco. Centro de Investigaciones Príncipe Felipe; EspañaFil: Dopazo Blázquez, Joaquín. Hospital Virgen del Rocio; EspañaFil: Hopp, Horacio Esteban. Universidad de Buenos Aires; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Agrobiotecnología y Biología Molecular. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Agrobiotecnología y Biología Molecular; ArgentinaFil: Heinz, Ruth Amelia. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Agrobiotecnología y Biología Molecular. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Agrobiotecnología y Biología Molecular; ArgentinaFil: Paniego, Norma Beatriz. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Agrobiotecnología y Biología Molecular. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Agrobiotecnología y Biología Molecular; ArgentinaFil: Lia, Verónica Viviana. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Agrobiotecnología y Biología Molecular. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Agrobiotecnología y Biología Molecular; 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

Association mapping in sunflower for sclerotinia head rot resistance

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 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  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.</p

Association mapping in sunflower for sclerotinia head rot resistance

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 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; 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

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