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

dc.contributor.authorNunes‐Nesi, Adriano
dc.contributor.authorAlseekh, Saleh
dc.contributor.authorSilva, Franklin Magnum de Oliveira
dc.contributor.authorOmranian, Nooshin
dc.contributor.authorLichtenstein, Gabriel
dc.contributor.authorMirnezhad, Mohammad
dc.contributor.authorGonzález, Roman R. Romero
dc.contributor.authorGarcia, Julia Sabio y
dc.contributor.authorConte, Mariana
dc.contributor.authorLeiss, Kirsten A.
dc.contributor.authorKlinkhamer, Peter G. L.
dc.contributor.authorNikoloski, Zoran
dc.contributor.authorCarrari, Fernando
dc.contributor.authorFernie, Alisdair R.
dc.date.accessioned2019-03-29T12:04:35Z
dc.date.available2019-03-29T12:04:35Z
dc.date.issued2019-04
dc.description.abstractTo 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.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.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.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.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.en
dc.formatpdfpt-BR
dc.identifier.issn15733890
dc.identifier.urihttps://doi.org/10.1007/s11306-019-1503-8
dc.identifier.urihttp://www.locus.ufv.br/handle/123456789/24202
dc.language.isoengpt-BR
dc.publisherMetabolomicspt-BR
dc.relation.ispartofseriesVolume 15, Issue 04, Article 46, Pages 01- 13, April 2019pt-BR
dc.rightsOpen Accesspt-BR
dc.subjectMetabolite QTLpt-BR
dc.subjectTomatopt-BR
dc.subjectLeaf metabolismpt-BR
dc.subjectMetabolite networkpt-BR
dc.titleIdentification and characterization of metabolite quantitative trait loci in tomato leaves and comparison with those reported for fruits and seedsen
dc.typeArtigopt-BR

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