Acclimation and adaptation of metabolism to a changing environment are key processes for plant survival and reproductive success. In the present study, 241 natural accessions of Arabidopsis (Arabidopsis thaliana) were grown under two different temperature regimes, 16 °C and 6 °C, and growth parameters were recorded, together with metabolite profiles, to investigate the natural genome × environment effects on metabolome variation. The plasticity of metabolism, which was captured by metabolic distance measures, varied considerably between accessions. Both relative growth rates and metabolic distances were predictable by the underlying natural genetic variation of accessions. Applying machine learning methods, climatic variables of the original growth habitats were tested for their predictive power of natural metabolic variation among accessions. We found specifically habitat temperature during the first quarter of the year to be the best predictor of the plasticity of primary metabolism, indicating habitat temperature as the causal driver of evolutionary cold adaptation processes. Analyses of epigenome- and genome-wide associations revealed accession-specific differential DNA-methylation levels as potentially linked to the metabolome and identified FUMARASE2 as strongly associated with cold adaptation in Arabidopsis accessions. These findings were supported by calculations of the biochemical Jacobian matrix based on variance and covariance of metabolomics data, which revealed that growth under low temperatures most substantially affects the accession-specific plasticity of fumarate and sugar metabolism. Our findings indicate that the plasticity of metabolic regulation is predictable from the genome and epigenome and driven evolutionarily by Arabidopsis growth habitats.

Austrian Academy of Sciences Gregor Mendel Institute 1030 Vienna Austria

Bioinformatics Max Planck Institute of Molecular Plant Physiology 14476 Potsdam Germany

Brno University of Technology Faculty of Electrical Engineering and Communication Department of Biomedical Engineering Technická 12 616 00 Brno Czech Republic

Genome Engineering Facility Max Planck Institute of Molecular Cell Biology and Genetics 01307 Dresden Germany

LMU Munich Faculty of Biology Plant Evolutionary Cell Biology 82152 Planegg Germany

Molecular Systems Biology Department of Functional and Evolutionary Ecology Faculty of Life Sciences University of Vienna 1030 Vienna Austria

Plant Sciences Facility Vienna BioCenter Core Facilities GmbH 1030 Vienna Austria

Vienna Metabolomics Center University of Vienna 1030 Vienna Austria

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A perspective on genetic and polygenic risk scores-advances and limitations and overview of associated tools