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Fine Quantitative Trait Loci Mapping of Carbon and Nitrogen Metabolism Enzyme Activities and Seedling Biomass in the Maize IBM Mapping Population

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons97167

Gibon,  Y.
System Regulation, Department Stitt, Max Planck Institute of Molecular Plant Physiology, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons97199

Hoehne,  M.
System Regulation, Department Stitt, Max Planck Institute of Molecular Plant Physiology, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons98180

Tschoep,  H.
System Regulation, Department Stitt, Max Planck Institute of Molecular Plant Physiology, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons97427

Stitt,  M.
System Regulation, Department Stitt, Max Planck Institute of Molecular Plant Physiology, Max Planck Society;

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Zhang-2010-Fine Quantitative Tr.pdf
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Zitation

Zhang, N., Gibon, Y., Gur, A., Chen, C., Lepak, N., Hoehne, M., et al. (2010). Fine Quantitative Trait Loci Mapping of Carbon and Nitrogen Metabolism Enzyme Activities and Seedling Biomass in the Maize IBM Mapping Population. Plant Physiology, 154(4), 1753-1765. doi:10.1104/pp.110.165787.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0014-22A0-8
Zusammenfassung
Understanding the genetic basis of nitrogen and carbon metabolism will accelerate the development of plant varieties with high yield and improved nitrogen use efficiency. A robotized platform was used to measure the activities of 10 enzymes from carbon and nitrogen metabolism in the maize (Zea mays) intermated B73 x Mo17 mapping population, which provides almost a 4-fold increase in genetic map distance compared with conventional mapping populations. Seedling/juvenile biomass was included to identify its genetic factors and relationships with enzyme activities. All 10 enzymes showed heritable variation in activity. There were strong positive correlations between activities of different enzymes, indicating that they are coregulated. Negative correlations were detected between biomass and the activity of six enzymes. In total, 73 significant quantitative trait loci (QTL) were found that influence the activity of these 10 enzymes and eight QTL that influence biomass. While some QTL were shared by different enzymes or biomass, we critically evaluated the probability that this may be fortuitous. All enzyme activity QTL were in trans to the known genomic locations of structural genes, except for single cis-QTL for nitrate reductase, Glu dehydrogenase, and shikimate dehydrogenase; the low frequency and low additive magnitude compared with trans-QTL indicate that cis-regulation is relatively unimportant versus trans-regulation. Two-gene epistatic interactions were identified for eight enzymes and for biomass, with three epistatic QTL being shared by two other traits; however, epistasis explained on average only 2.8% of the genetic variance. Overall, this study identifies more QTL at a higher resolution than previous studies of genetic variation in metabolism.