Identification and characterization of metabolite quantitative trait loci in tomato leaves and comparison with those reported for fruits and seeds

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Introduction To 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. Objective This study was conducted to identify leaf mQT...

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Detalles Bibliográficos
Otros Autores: Nunes Nesi, Adriano, Alseekh, Saleh, Oliveira Silva, Franklin Magnum de, Omranian, Nooshin, Lichtenstein, Gabriel, Mirnezhad, Mohammad, Romero González, Roman R., Carrari, Fernando
Formato: Artículo
Lenguaje:Inglés
Materias:
METABOLITE QTL
TOMATO
LEAF METABOLISM
METABOLITE NETWORK
Acceso en línea:http://ri.agro.uba.ar/files/download/articulo/2019nunesnesi.pdf
LINK AL EDITOR
Aporte de:Registro referencial: Solicitar el recurso aquí
Biblioteca Central (FAUBA) de Universidad de Buenos Aires
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245 1 0 |a Identification and characterization of metabolite quantitative trait loci in tomato leaves and comparison with those reported for fruits and seeds 
520 |a Introduction To 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. Objective This 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. Methods The 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. Results Changes 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. Conclusions Overall, 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. 
653 |a METABOLITE QTL 
653 |a TOMATO 
653 |a LEAF METABOLISM 
653 |a METABOLITE NETWORK 
700 1 |a Nunes Nesi, Adriano  |u Universidade Federal de Viçosa. Departamento de Biologia Vegetal. Viçosa, Minas Gerais, Brazil.  |u Max - Planck- Institute of Molecular Plant Physiology. Potsdam, Germany.  |9 68745 
700 1 |a Alseekh, Saleh  |u Max - Planck- Institute of Molecular Plant Physiology. Potsdam, Germany.  |u Center of Plant System Biology and Biotechnology (CPSBB). Plovdiv, Bulgaria.  |9 68267 
700 1 |a Oliveira Silva, Franklin Magnum de  |u Universidade Federal de Viçosa. Departamento de Biologia Vegetal. Viçosa, Minas Gerais, Brazil.  |9 68746 
700 1 |a Omranian, Nooshin  |u Max - Planck- Institute of Molecular Plant Physiology. Potsdam, Germany.  |u Center of Plant System Biology and Biotechnology (CPSBB). Plovdiv, Bulgaria.  |9 68747 
700 1 |a Lichtenstein, Gabriel  |u Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología. Castelar, Buenos Aires, Argentina.  |u CONICET. Buenos Aires, Argentina.  |9 68748 
700 1 |a Mirnezhad, Mohammad  |u Leiden University. Plant Ecology, Institute of Biology. The Netherlands.  |9 68749 
700 1 |a Romero González, Roman R.  |u Leiden University. Plant Ecology. Institute of Biology. The Netherlands.  |9 68751 
700 1 |9 11158  |a Carrari, Fernando  |u Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología. Castelar, Buenos Aires, Argentina.  |u CONICET. Buenos Aires, Argentina.  |u Universidad de Buenos Aires. Instituto de Fisiología. Biología Molecular y Neurociencias (IFIBYNE‑UBA‑CONICET). Buenos Aires, Argentina.  |u Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Biología Aplicada y Alimentos. Cátedra de Genética. Buenos Aires, Argentina. 
773 0 |t Metabolomics  |g vol.15, no.46 (2019), p.1-13, grafs., tbls. 
856 |f 2019nunesnesi  |i en internet  |q application/pdf  |u http://ri.agro.uba.ar/files/download/articulo/2019nunesnesi.pdf  |x ARTI201904 
856 |z LINK AL EDITOR  |u https://link.springer.com 
942 |c ARTICULO 
942 |c ENLINEA 
976 |a AAG 

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