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Biochemical and genetic analyses of N metabolism in maize testcross seedlings: 2. Roots

Author:
Silva, IgnacioTrucillo, Abbaraju, HariKishan R., Fallis, LynneP., Liu, Hongjun, Lee, Michael, Dhugga, KanwarpalS.
Source:
Theoretical and applied genetics 2018 v.131 no.6 pp. 1191-1205
ISSN:
0040-5752
Subject:
Zea mays, alanine transaminase, aspartate transaminase, aspartate-ammonia ligase, biomass production, chromosomes, confidence interval, corn, crops, enzyme activity, epistasis, farmers, genetic analysis, genomics, glutamate-ammonia ligase, hydroponics, leaves, metabolism, metabolites, models, nitrogen content, plant growth, pollution, profitability, quantitative trait loci, roots, seedlings, structural genes, testcrosses, variance
Abstract:
KEY MESSAGE: Intracellular factors differentially affected enzyme activities of N assimilation in the roots of maize testcrosses where alanine aminotransferase and glutamate synthase were the main enzymes regulating the levels of glutamate. N is a key macronutrient for plant growth and development. Breeding maize with improved efficiency in N use could help reduce environmental contamination as well as increase profitability for the farmers. Quantitative trait loci (QTL) mapping of traits related to N metabolism in the root tissue was undertaken in a maize testcross mapping population grown in hydroponic cultures. N concentration was negatively correlated with root and total dry mass. Neither the enzyme activities nor metabolites were appreciably correlated between the root and leaf tissues. Repeatability measures for most of the enzymes were lower than for dry mass. Weak negative correlations between most of the enzymes and dry mass resulted likely from dilution and suggested the presence of excess of enzyme activities for maximal biomass production. Glutamate synthase and alanine aminotransferase each explained more variation in glutamate concentration than either aspartate aminotransferase or asparagine synthetase whereas glutamine synthetase was inconsequential. Twenty-six QTL were identified across all traits. QTL models explained 7–43% of the variance with no significant epistasis between the QTL. Thirteen candidate genes were identified underlying QTL within 1-LOD confidence intervals. All the candidate genes were located in trans configuration, unlinked or even on different chromosomes, relative to the known genomic positions of the corresponding structural genes. Our results have implications in improving NUE in maize and other crop plants.
Agid:
5964175