Gene transcripts with invariant abundance during development and in the face of environmental stimuli are essential reference points for accurate gene expression analyses, such as RNA gel-blot analysis or quantitative reverse transcription-polymerase chain reaction (PCR). An exceptionally large set of data from Affymetrix ATH1 whole-genome GeneChip studies provided the means to identify a new generation of reference genes with very stable expression levels in the model plant species Arabidopsis (Arabidopsis thaliana). Hundreds of Arabidopsis genes were found that outperform traditional reference genes in terms of expression stability throughout development and under a range of environmental conditions. Most of these were expressed at much lower levels than traditional reference genes, making them very suitable for normalization of gene expression over a wide range of transcript levels. Specific and efficient primers were developed for 22 genes and tested on a diverse set of 20 cDNA samples. Quantitative reverse transcription-PCR confirmed superior expression stability and lower absolute expression levels for many of these genes, including genes encoding a protein phosphatase 2A subunit, a coatomer subunit, and an ubiquitin-conjugating enzyme. The developed PCR primers or hybridization probes for the novel reference genes will enable better normalization and quantification of transcript levels in Arabidopsis in the future.

Multiparallel analyses of mRNA and proteins are central to today's functional genomics initiatives. We describe here the use of metabolite profiling as a new tool for a comparative display of gene function. It has the potential not only to provide deeper insight into complex regulatory processes but also to determine phenotype directly. Using gas chromatography/mass spectrometry (GC/MS), we automatically quantified 326 distinct compounds from Arabidopsis thaliana leaf extracts. It was possible to assign a chemical structure to approximately half of these compounds. Comparison of four Arabidopsis genotypes (two homozygous ecotypes and a mutant of each ecotype) showed that each genotype possesses a distinct metabolic profile. Data mining tools such as principal component analysis enabled the assignment of "metabolic phenotypes" using these large data sets. The metabolic phenotypes of the two ecotypes were more divergent than were the metabolic phenotypes of the single-loci mutant and their parental ecotypes. These results demonstrate the use of metabolite profiling as a tool to significantly extend and enhance the power of existing functional genomics approaches.

The cpd mutation localized by T-DNA tagging on Arabidopsis chromosome 5-14.3 inhibits cell elongation controlled by the ecdysone-like brassinosteroid hormone brassinolide. The cpd mutant displays de-etiolation and derepression of light-induced genes in the dark, as well as dwarfism, male sterility, and activation of stress-regulated genes in the light. The CPD gene encodes a cytochrome P450 (CYP90) sharing homologous domains with steroid hydroxylases. The phenotype of the cpd mutant is restored to wild type both by feeding with C23-hydroxylated brassinolide precursors and by ectopic overexpression of the CPD cDNA. Brassinosteroids also compensate for different cell elongation defects of Arabidopsis det, cop, fus, and axr2 mutants, indicating that these steroids play an essential role in the regulation of plant development.

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.Arabidopsis ͉ association mapping ͉ biomass ͉ metabolites ͉ predictive P lants use light energy to convert CO 2 into carbohydrates.Although we might expect plant growth to be driven by the availability of carbohydrates and other central metabolites, recent studies point to a more complex interaction. Numerous free air CO 2 elevation studies show that higher rates of photosynthesis do not lead to a commensurate increase in biomass and yield (1). Studies of natural genetic diversity reveal a negative correlation between the levels of metabolites and biomass or yield (2-4). Although biomass was only very weakly correlated with individual metabolites in an Arabidopsis recombinant inbred line (RIL) population, a highly significant prediction was obtained when multivariate analysis was used on the entire metabolite profile (3). These results indicate that much of the genetic variation for biomass production affects the balance between resource availability and developmental programs, which determine how rapidly these resources are used for growth.Plants are exposed to a changeable environment and need to cope with continual changes in carbon (C) availability. One striking example is the daily alternation between a positive C balance in the light and a negative C balance in the dark. Growth nevertheless continues at night (5). This continued growth is possible because some newly fixed C accumulates as starch in the light and is remobilized at night to support respiration and growth. Starch is almost completely exhausted by the end of the night. If a change in the conditions (e.g., longer nights) leads to a temporary period of C starvation, the C budget is rebalanced (6-11) by increasing the rate of starch synthesis, decreasing the rate of starch breakdown, and decreasing the rate of growth (10,11). Starchless mutants illustrate the importance of this buffer; they cannot grow in a light/dark cycle because they become C-starved every night, leading to an inhibition of growth that is no...