The decline of available fossil fuel reserves has triggered world-wide efforts to develop alternative energy sources based on plant biomass. Detailed knowledge of the relations of metabolism and biomass accumulation can be expected to yield powerful novel tools to accelerate and enhance energy plant breeding programs. We used metabolic profiling in the model Arabidopsis to study the relation between biomass and metabolic composition using a recombinant inbred line (RIL) population. A highly significant canonical correlation (0.73) was observed, revealing a close link between biomass and a specific combination of metabolites. Dividing the entire data set into training and test sets resulted in a median correlation between predicted and true biomass of 0.58. The demonstrated high predictive power of metabolic composition for biomass features this composite measure as an excellent biomarker and opens new opportunities to enhance plant breeding specifically in the context of renewable resources.

Summary: The zinc hyperaccumulator plant Arabidopsis halleri is able to naturally accumulate 100‐fold higher leaf zinc concentrations when compared with non‐accumulator species such as the closely related A. lyrata and A. thaliana, without showing toxicity symptoms. A novel member of the cation diffusion facilitator (CDF) protein family, an A. halleri metal tolerance protein 1 (MTP1), and the homologous A. thaliana Zn transporter (ZAT)/AtMTP1 metal‐specifically complement the zinc hypersensitivity of a Saccharomyces cerevisiae zrc1 cot1 mutant strain. A fusion of the AhMTP1 protein to green fluorescent protein (GFP) localizes to the vacuolar membrane of A. thaliana protoplasts. When compared with A. lyrata and A. thaliana, the total MTP1 transcript levels are substantially higher in the leaves and upregulated upon exposure to high zinc concentrations in the roots of A. halleri. The high MTP1 transcript levels in A. halleri can be primarily attributed to two genetically unlinked genomic AhMTP1 gene copies. The two corresponding loci co‐segregate with zinc tolerance in the back‐cross 1 generation of a cross between the zinc‐tolerant species A. halleri and the zinc‐sensitive species A. lyrata. In contrast, a third MTP1 gene in the genome of A. halleri generates only minor amounts of MTP1 transcripts and does not co‐segregate with zinc tolerance. Our data suggests that zinc tolerance in A. halleri involves an expanded copy number of an ancestral MTP1 gene, encoding functional proteins that mediate the detoxification of zinc in the cell vacuole. At the transcript level, MTP1 gene copies of A. halleri are regulated differentially and in response to changes in zinc supply.

There has been much excitement about the possibility that exposure to specific environments can induce an ecological memory in the form of whole-sale, genome-wide epigenetic changes that are maintained over many generations. In the model plant Arabidopsis thaliana, numerous heritable DNA methylation differences have been identified in greenhouse-grown isogenic lines, but it remains unknown how natural, highly variable environments affect the rate and spectrum of such changes. Here we present detailed methylome analyses in a geographically dispersed A. thaliana population that constitutes a collection of near-isogenic lines, diverged for at least a century from a common ancestor. Methylome variation largely reflected genetic distance, and was in many aspects similar to that of lines raised in uniform conditions. Thus, even when plants are grown in varying and diverse natural sites, genome-wide epigenetic variation accumulates mostly in a clock-like manner, and epigenetic divergence thus parallels the pattern of genome-wide DNA sequence divergence. It continues to be hotly debated to what extent environmentally induced epigenetic change is stably inherited and thereby contributes to short-term adaptation. It has been shown before that natural Arabidopsis thaliana lines differ substantially in their methylation profiles. How much of this is independent of genetic changes remains, however, unclear, especially given that there is very little conservation of methylation between species, simply because the methylated sequences themselves, mostly repeats, are not conserved over millions of years. On the other hand, there is no doubt that artificially induced epialleles can contribute to phenotypic variation. To investigate whether epigenetic differentiation, at least in the short term, proceeds very differently from genetic variation, and whether genome-wide epigenetic fingerprints can be used to uncover local adaptation, we have taken advantage of a near-clonal North American A. thaliana population that has diverged under natural conditions for at least a century. We found that both patterns and rates of methylome variation were in many aspects similar to those of lines grown in stable environments, which suggests that environment-induced changes are only minor contributors to durable genome-wide heritable epigenetic variation.

Summary: Plant growth and development are tightly linked to primary metabolism and are subject to natural variation. In order to obtain an insight into the genetic factors controlling biomass and primary metabolism and to determine their relationships, two Arabidopsis thaliana populations [429 recombinant inbred lines (RIL) and 97 introgression lines (IL), derived from accessions Col‐0 and C24] were analyzed with respect to biomass and metabolic composition using a mass spectrometry‐based metabolic profiling approach. Six and 157 quantitative trait loci (QTL) were identified for biomass and metabolic content, respectively. Two biomass QTL coincide with significantly more metabolic QTL (mQTL) than statistically expected, supporting the notion that the metabolic profile and biomass accumulation of a plant are linked. On the same basis, three out the six biomass QTL can be simulated purely on the basis of metabolic composition. QTL based on analysis of the introgression lines were in substantial agreement with the RIL‐based results: five of six biomass QTL and 55% of the mQTL found in the RIL population were also found in the IL population at a significance level of P ≤ 0.05, with >80% agreement on the allele effects. Some of the differences could be attributed to epistatic interactions. Depending on the search conditions, metabolic pathway‐derived candidate genes were found for 24–67% of all tested mQTL in the database AraCyc 3.5. This dataset thus provides a comprehensive basis for the detection of functionally relevant variation in known genes with metabolic function and for identification of genes with hitherto unknown roles in the control of metabolism.