Literature DB >> 19853265

Metabolic profiles of sunflower genotypes with contrasting response to Sclerotinia sclerotiorum infection.

Lucila Peluffo1, Verónica Lia, Carolina Troglia, Carla Maringolo, Paniego Norma, Alberto Escande, H Esteban Hopp, Anna Lytovchenko, Alisdair R Fernie, Ruth Heinz, Fernando Carrari.   

Abstract

We report a comprehensive primary metabolite profiling of sunflower (Helianthus annuus) genotypes displaying contrasting behavior to Sclerotinia sclerotiorum infection. Applying a GC-MS-based metabolite profiling approach, we were able to identify differential patterns involving a total of 63 metabolites including major and minor sugars and sugar alcohols, organic acids, amino acids, fatty acids and few soluble secondary metabolites in the sunflower capitulum, the main target organ of pathogen attack. Metabolic changes and disease incidence of the two contrasting genotypes were determined throughout the main infection period (R5.2-R6). Both point-by-point and non-parametric statistical analyses showed metabolic differences between genotypes as well as interaction effects between genotype and time after inoculation. Network correlation analyses suggested that these metabolic changes were synchronized in a time-dependent manner in response to the pathogen. Concerted differential metabolic changes were detected to a higher extent in the susceptible, rather than the resistant genotype, thereby allowing differentiation of modules composed by intermediates of the same pathway which are highly interconnected in the susceptible line but not in the resistant one. Evaluation of these data also demonstrated a genotype specific regulation of distinct metabolic pathways, suggesting the importance of detection of metabolic patterns rather than specific metabolite changes when looking for metabolic markers differentially responding to pathogen infection. In summary, the GC-MS strategy developed in this study was suitable for detection of differences in carbon primary metabolism in sunflower capitulum, a tissue which is the main entry point for this and other pathogens which cause great detrimental impact on crop yield. 2009 Elsevier Ltd. All rights reserved.

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Year:  2009        PMID: 19853265     DOI: 10.1016/j.phytochem.2009.09.018

Source DB:  PubMed          Journal:  Phytochemistry        ISSN: 0031-9422            Impact factor:   4.072


  13 in total

1.  Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize.

Authors:  Christian Riedelsheimer; Jan Lisec; Angelika Czedik-Eysenberg; Ronan Sulpice; Anna Flis; Christoph Grieder; Thomas Altmann; Mark Stitt; Lothar Willmitzer; Albrecht E Melchinger
Journal:  Proc Natl Acad Sci U S A       Date:  2012-05-21       Impact factor: 11.205

2.  Identification of candidate genes associated with leaf senescence in cultivated sunflower (Helianthus annuus L.).

Authors:  Sebastian Moschen; Sofia Bengoa Luoni; Norma B Paniego; H Esteban Hopp; Guillermo A A Dosio; Paula Fernandez; Ruth A Heinz
Journal:  PLoS One       Date:  2014-08-11       Impact factor: 3.240

3.  Integration of transcriptomic and metabolic data reveals hub transcription factors involved in drought stress response in sunflower (Helianthus annuus L.).

Authors:  Sebastián Moschen; Julio A Di Rienzo; Janet Higgins; Takayuki Tohge; Mutsumi Watanabe; Sergio González; Máximo Rivarola; Francisco García-García; Joaquin Dopazo; H Esteban Hopp; Rainer Hoefgen; Alisdair R Fernie; Norma Paniego; Paula Fernández; Ruth A Heinz
Journal:  Plant Mol Biol       Date:  2017-06-21       Impact factor: 4.076

Review 4.  ROS and Oxidative Response Systems in Plants Under Biotic and Abiotic Stresses: Revisiting the Crucial Role of Phosphite Triggered Plants Defense Response.

Authors:  Mohammad Aqa Mohammadi; Yan Cheng; Mohammad Aslam; Bello Hassan Jakada; Myat Hnin Wai; Kangzhuo Ye; Xiaoxue He; Tiantian Luo; Li Ye; Chunxing Dong; Bin Hu; S V G N Priyadarshani; Gefu Wang-Pruski; Yuan Qin
Journal:  Front Microbiol       Date:  2021-07-01       Impact factor: 5.640

Review 5.  Genetic Improvement in Sunflower Breeding-Integrated Omics Approach.

Authors:  Milan Jocković; Siniša Jocić; Sandra Cvejić; Ana Marjanović-Jeromela; Jelena Jocković; Aleksandra Radanović; Dragana Miladinović
Journal:  Plants (Basel)       Date:  2021-06-04

6.  Perturbations in the Primary Metabolism of Tomato and Arabidopsis thaliana Plants Infected with the Soil-Borne Fungus Verticillium dahliae.

Authors:  Anja Buhtz; Katja Witzel; Nadine Strehmel; Jörg Ziegler; Steffen Abel; Rita Grosch
Journal:  PLoS One       Date:  2015-09-18       Impact factor: 3.240

7.  Metabolomic-based study of the leafy gall, the ecological niche of the phytopathogen Rhodococcus fascians, as a potential source of bioactive compounds.

Authors:  Aminata P Nacoulma; Olivier M Vandeputte; Manuella De Lorenzi; Mondher El Jaziri; Pierre Duez
Journal:  Int J Mol Sci       Date:  2013-06-14       Impact factor: 5.923

Review 8.  Evaluating plant immunity using mass spectrometry-based metabolomics workflows.

Authors:  Adam L Heuberger; Faith M Robison; Sarah Marie A Lyons; Corey D Broeckling; Jessica E Prenni
Journal:  Front Plant Sci       Date:  2014-06-24       Impact factor: 5.753

9.  Network and biosignature analysis for the integration of transcriptomic and metabolomic data to characterize leaf senescence process in sunflower.

Authors:  Sebastián Moschen; Janet Higgins; Julio A Di Rienzo; Ruth A Heinz; Norma Paniego; Paula Fernandez
Journal:  BMC Bioinformatics       Date:  2016-06-06       Impact factor: 3.169

Review 10.  Sunflower Hybrid Breeding: From Markers to Genomic Selection.

Authors:  Aleksandra Dimitrijevic; Renate Horn
Journal:  Front Plant Sci       Date:  2018-01-17       Impact factor: 5.753

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