A quantitative genetic study for elucidating the contribution of glutamine synthetase, glutamate dehydrogenase and other nitrogen-related physiological traits to the agronomic performance of common wheat
2009
Fontaine, Jean-Xavier | Ravel, Catherine | Pageau, Karine | Heumez, Emmanuel | Dubois, Frédéric | Hirel, Bertrand | Le Gouis, Jacques
To better understand the genetic variability for nitrogen use efficiency in winter wheat is a necessity in the frame of the present economic and ecological context. The objective of this work was to investigate the role of the enzymes glutamine synthetase (GS) and glutamate dehydrogenase (GDH), and other nitrogen (N)-related physiological traits in the control of agronomic performance in wheat. A quantitative genetics approach was developed using the Arche x Récital population of doubled haploid lines grown for 3 years in the field. GS and GDH activities, ammonium, amino acid and protein contents were measured at different stages of plant development in different organs after flowering. Significant genotypic effects were observed for all measured physiological and agronomical traits. Heading date was negatively correlated with ammonium, amino acid, protein contents and GS activity in the flag leaf lamina. Grain protein content was positively correlated with both ammonium and amino acid content, and to a lesser extent with soluble protein content and GS activity. A total of 148 quantitative trait loci (QTLs) were detected, 104 QTLs for physiological traits and 44 QTLs for agronomic traits. Twenty-six QTLs were detected for GDH activity spread over 13 chromosomes and 25 QTLs for GS activity spread over 12 chromosomes. We found only a co-localization between a QTL for GS activity and GSe, a structural gene encoding cytosolic GS on chromosome 4B. A coincidence between a QTL for GDH activity and a gene encoding GDH was also found on chromosome 2B. QTL regions combining both physiological and agronomical QTLs were mainly identified on linkage groups 2A, 2B, 2D, 5A, 5B and 5D. This approach allowed us to propose possible functions of physiological traits to explain the variation observed for agronomic traits including yield and its components.
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