Genome-Wide Association Mapping Reveals That Specific and Pleiotropic Regulatory Mechanisms Fine-Tune Central Metabolism and Growth in Arabidopsis.

Central metabolism is a coordinated network that is regulated at multiple levels by resource availability and by environmental and developmental cues. Its genetic architecture has been investigated by mapping metabolite quantitative trait loci (QTL). A more direct approach is to identify enzyme activity QTL, which distinguishes between cis-QTL in structural genes encoding enzymes and regulatory trans-QTL. Using genome-wide association studies, we mapped QTL for 24 enzyme activities, nine metabolites, three structural components, and biomass in Arabidopsis thaliana We detected strong cis-QTL for five enzyme activities. A cis-QTL for UDP-glucose pyrophosphorylase activity in the UGP1 promoter is maintained through balancing selection. Variation in acid invertase activity reflects multiple evolutionary events in the promoter and coding region of VAC-INVcis-QTL were also detected for ADP-glucose pyrophosphorylase, fumarase, and phosphoglucose isomerase activity. We detected many trans-QTL, including transcription factors, E3 ligases, protein targeting components, and protein kinases, and validated some by knockout analysis. trans-QTL are more frequent but tend to have smaller individual effects than cis-QTL. We detected many colocalized QTL, including a multitrait QTL on chromosome 4 that affects six enzyme activities, three metabolites, protein, and biomass. These traits are coordinately modified by different ACCELERATED CELL DEATH6 alleles, revealing a trade-off between metabolism and defense against biotic stress.

Metabolite pools and carbon flow during C4 photosynthesis in maize: 13CO2 labeling kinetics and cell type fractionation.

Worldwide efforts to engineer C4 photosynthesis into C3 crops require a deep understanding of how this complex pathway operates. CO2 is incorporated into four-carbon metabolites in the mesophyll, which move to the bundle sheath where they are decarboxylated to concentrate CO2 around RuBisCO. We performed dynamic 13CO2 labeling in maize to analyze C flow in C4 photosynthesis. The overall labeling kinetics reflected the topology of C4 photosynthesis. Analyses of cell-specific labeling patterns after fractionation to enrich bundle sheath and mesophyll cells revealed concentration gradients to drive intercellular diffusion of malate, but not pyruvate, in the major CO2-concentrating shuttle. They also revealed intercellular concentration gradients of aspartate, alanine, and phosphenolpyruvate to drive a second phosphoenolpyruvate carboxykinase (PEPCK)-type shuttle, which carries 10-14% of the carbon into the bundle sheath. Gradients also exist to drive intercellular exchange of 3-phosphoglycerate and triose-phosphate. There is rapid carbon exchange between the Calvin-Benson cycle and the CO2-concentrating shuttle, equivalent to ~10% of carbon gain. In contrast, very little C leaks from the large pools of metabolites in the C concentration shuttle into respiratory metabolism. We postulate that the presence of multiple shuttles, alongside carbon transfer between them and the Calvin-Benson cycle, confers great flexibility in C4 photosynthesis.

Network analysis of enzyme activities and metabolite levels and their relationship to biomass in a large panel of Arabidopsis accessions.

Natural genetic diversity provides a powerful resource to investigate how networks respond to multiple simultaneous changes. In this work, we profile maximum catalytic activities of 37 enzymes from central metabolism and generate a matrix to investigate species-wide connectivity between metabolites, enzymes, and biomass. Most enzyme activities change in a highly coordinated manner, especially those in the Calvin-Benson cycle. Metabolites show coordinated changes in defined sectors of metabolism. Little connectivity was observed between maximum enzyme activities and metabolites, even after applying multivariate analysis methods. Measurements of posttranscriptional regulation will be required to relate these two functional levels. Individual enzyme activities correlate only weakly with biomass. However, when they are used to estimate protein abundances, and the latter are summed and expressed as a fraction of total protein, a significant positive correlation to biomass is observed. The correlation is additive to that obtained between starch and biomass. Thus, biomass is predicted by two independent integrative metabolic biomarkers: preferential investment in photosynthetic machinery and optimization of carbon use.

Starch as a major integrator in the regulation of plant growth.

Rising demand for food and bioenergy makes it imperative to breed for increased crop yield. Vegetative plant growth could be driven by resource acquisition or developmental programs. Metabolite profiling in 94 Arabidopsis accessions revealed that biomass correlates negatively with many metabolites, especially starch. Starch accumulates in the light and is degraded at night to provide a sustained supply of carbon for growth. Multivariate analysis revealed that starch is an integrator of the overall metabolic response. We hypothesized that this reflects variation in a regulatory network that balances growth with the carbon supply. Transcript profiling in 21 accessions revealed coordinated changes of transcripts of more than 70 carbon-regulated genes and identified 2 genes (myo-inositol-1-phosphate synthase, a Kelch-domain protein) whose transcripts correlate with biomass. The impact of allelic variation at these 2 loci was shown by association mapping, identifying them as candidate lead genes with the potential to increase biomass production.

Integration of metabolite with transcript and enzyme activity profiling during diurnal cycles in Arabidopsis rosettes.

BACKGROUND: Genome-wide transcript profiling and analyses of enzyme activities from central carbon and nitrogen metabolism show that transcript levels undergo marked and rapid changes during diurnal cycles and after transfer to darkness, whereas changes in activities are smaller and delayed. In the starchless pgm mutant, where sugars are depleted every night, there are accentuated diurnal changes in transcript levels. Enzyme activities in this mutant do not show larger diurnal changes; instead, they shift towards the levels found in the wild type after several days of darkness. This indicates that enzyme activities change slowly, integrating the changes in transcript levels over several diurnal cycles. RESULTS: To generalize this conclusion, 137 metabolites were profiled using gas and liquid chromatography coupled to mass spectroscopy. The amplitudes of the diurnal changes in metabolite levels in pgm were (with the exception of sugars) similar or smaller than in the wild type. The average levels shifted towards those found after several days of darkness in the wild type. Examples include increased levels of amino acids due to protein degradation, decreased levels of fatty acids, increased tocopherol and decreased myo-inositol. Many metabolite-transcript correlations were found and the proportion of transcripts correlated with sugars increased dramatically in the starchless mutant. CONCLUSION: Rapid diurnal changes in transcript levels are integrated over time to generate quasi-stable changes across large sectors of metabolism. This implies that correlations between metabolites and transcripts are due to regulation of gene expression by metabolites, rather than metabolites being changed as a consequence of a change in gene expression.