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Plant Cell. 2017 May;29(5):919-943. doi: 10.1105/tpc.16.00613. Epub 2017 Apr 10.

Exploiting the Genetic Diversity of Maize Using a Combined Metabolomic, Enzyme Activity Profiling, and Metabolic Modeling Approach to Link Leaf Physiology to Kernel Yield.

Author information

1
Institut Jean-Pierre Bourgin, Institut National de la Recherche Agronomique (INRA), Centre de Versailles-Grignon, Unité Mixte de Recherche 1318, INRA-Agro-ParisTech, Equipe de Recherche Labellisée, Centre National de la Recherche Scientifique (CNRS) 3559, F-78026 Versailles cedex, France.
2
Departamento de Biología Molecular y Bioquímica, Facultad de Ciencias, Universidad de Málaga, 29071 Málaga, Spain.
3
Department of Chemical Engineering, The Pennsylvania State University, University Park, Pennsylvania 16802.
4
University of Angers, Institut de Recherche en Horticulture et Semences, INRA, Structure Fédérative de Recherche 4207, Qualité et Santé du Végétal, F-49045 Angers, France.
5
Unité Mixte Recherche 1332, Biologie du Fruit et Pathologie, Bordeaux Métabolome Platform, INRA de Bordeaux-Aquitaine, F-33883 Villenave d'Ornon cedex, France.
6
Station de Génétique Végétale, INRA-UPS-INAPG-CNRS, Ferme du Moulon, F-91190 Gif/Yvette, France.
7
Lancaster Environment Centre, Lancaster University, Lancaster LA1 4YQ, United Kingdom.
8
Institut Jean-Pierre Bourgin, Institut National de la Recherche Agronomique (INRA), Centre de Versailles-Grignon, Unité Mixte de Recherche 1318, INRA-Agro-ParisTech, Equipe de Recherche Labellisée, Centre National de la Recherche Scientifique (CNRS) 3559, F-78026 Versailles cedex, France hirel@versailles.inra.fr.

Erratum in

Abstract

A combined metabolomic, biochemical, fluxomic, and metabolic modeling approach was developed using 19 genetically distant maize (Zea mays) lines from Europe and America. Considerable differences were detected between the lines when leaf metabolic profiles and activities of the main enzymes involved in primary metabolism were compared. During grain filling, the leaf metabolic composition appeared to be a reliable marker, allowing a classification matching the genetic diversity of the lines. During the same period, there was a significant correlation between the genetic distance of the lines and the activities of enzymes involved in carbon metabolism, notably glycolysis. Although large differences were observed in terms of leaf metabolic fluxes, these variations were not tightly linked to the genome structure of the lines. Both correlation studies and metabolic network analyses allowed the description of a maize ideotype with a high grain yield potential. Such an ideotype is characterized by low accumulation of soluble amino acids and carbohydrates in the leaves and high activity of enzymes involved in the C4 photosynthetic pathway and in the biosynthesis of amino acids derived from glutamate. Chlorogenates appear to be important markers that can be used to select for maize lines that produce larger kernels.

PMID:
28396554
PMCID:
PMC5466022
DOI:
10.1105/tpc.16.00613
[Indexed for MEDLINE]
Free PMC Article

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