Adriano Nunes-Nesi, Saleh Alseekh, Franklin Magnum de Oliveira Silva, Nooshin Omranian, Gabriel Lichtenstein, Mohammad Mirnezhad, Roman R. Romero Gonzalez, Julia Sabio y Garcia, Mariana Conte, Kirsten A. Leiss, Peter Gerardus Leonardus Klinkhamer, Zoran Nikoloski, Fernando Carrari, Alisdair Fernie
- IntroductionTo date, most studies of natural variation and metabolite quantitative trait loci (mQTL) in tomato have focused on fruit metabolism, leaving aside the identification of genomic regions involved in the regulation of leaf metabolism.ObjectiveThis study was conducted to identify leaf mQTL in tomato and to assess the association of leaf metabolites and physiological traits with the metabolite levels from other tissues.MethodsThe analysis of components of leaf metabolism was performed by phenotypying 76 tomato ILs with chromosome segments of the wild species Solanum pennellii in the genetic background of a cultivated tomato (S. lycopersicum) variety M82. The plants were cultivated in two different environments in independent years and samples were harvested from mature leaves of non-flowering plants at the middle of the light period. The non-targeted metabolite profiling was obtained by gas chromatography time-of-flight mass spectrometry (GC-TOF-MS). With the data set obtained in this study and already published metabolomicsIntroductionTo date, most studies of natural variation and metabolite quantitative trait loci (mQTL) in tomato have focused on fruit metabolism, leaving aside the identification of genomic regions involved in the regulation of leaf metabolism.ObjectiveThis study was conducted to identify leaf mQTL in tomato and to assess the association of leaf metabolites and physiological traits with the metabolite levels from other tissues.MethodsThe analysis of components of leaf metabolism was performed by phenotypying 76 tomato ILs with chromosome segments of the wild species Solanum pennellii in the genetic background of a cultivated tomato (S. lycopersicum) variety M82. The plants were cultivated in two different environments in independent years and samples were harvested from mature leaves of non-flowering plants at the middle of the light period. The non-targeted metabolite profiling was obtained by gas chromatography time-of-flight mass spectrometry (GC-TOF-MS). With the data set obtained in this study and already published metabolomics data from seed and fruit, we performed QTL mapping, heritability and correlation analyses.ResultsChanges in metabolite contents were evident in the ILs that are potentially important with respect to stress responses and plant physiology. By analyzing the obtained data, we identified 42 positive and 76 negative mQTL involved in carbon and nitrogen metabolism.ConclusionsOverall, these findings allowed the identification of S. lycopersicum genome regions involved in the regulation of leaf primary carbon and nitrogen metabolism, as well as the association of leaf metabolites with metabolites from seeds and fruits.…
MetadatenAuthor details: | Adriano Nunes-Nesi, Saleh AlseekhORCiDGND, Franklin Magnum de Oliveira Silva, Nooshin OmranianORCiDGND, Gabriel LichtensteinORCiD, Mohammad Mirnezhad, Roman R. Romero Gonzalez, Julia Sabio y Garcia, Mariana Conte, Kirsten A. Leiss, Peter Gerardus Leonardus KlinkhamerGND, Zoran NikoloskiORCiDGND, Fernando Carrari, Alisdair FernieORCiDGND |
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DOI: | https://doi.org/10.1007/s11306-019-1503-8 |
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ISSN: | 1573-3882 |
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ISSN: | 1573-3890 |
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Pubmed ID: | https://pubmed.ncbi.nlm.nih.gov/30874962 |
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Title of parent work (English): | Metabolomics |
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Publisher: | Springer |
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Place of publishing: | New York |
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Publication type: | Article |
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Language: | English |
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Date of first publication: | 2019/03/15 |
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Publication year: | 2019 |
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Release date: | 2021/03/11 |
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Tag: | Leaf metabolism; Metabolite QTL; Metabolite network; Tomato |
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Volume: | 15 |
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Issue: | 46 |
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Number of pages: | 13 |
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Funding institution: | Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq)National Council for Scientific and Technological Development (CNPq) [484675/2013-3]; Fundacao de Amparo a Pesquisa do Estado de Minas Gerais (FAPEMIG)Minas Gerais State Research Foundation (FAPEMIG) [APQ-00688-12, APQ-02548-13]; Max Planck SocietyMax Planck Society; CNPqNational Council for Scientific and Technological Development and innovation programme (SGA-CSA) [664621, 739582, 664620]; TOMRES grant (H2020) [727929]; CONICETConsejo Nacional de Investigaciones Cientificas y Tecnicas (CONICET); European Union Horizon 2020 Research and Innovation Programme [679796]; ANPCYTANPCyT; UBA (Argentina)University of Buenos Aires |
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Organizational units: | Mathematisch-Naturwissenschaftliche Fakultät / Institut für Biochemie und Biologie |
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DDC classification: | 5 Naturwissenschaften und Mathematik / 57 Biowissenschaften; Biologie / 570 Biowissenschaften; Biologie |
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License (German): | CC-BY - Namensnennung 4.0 International |
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