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. 2018 Nov 6;9:1556. doi: 10.3389/fpls.2018.01556

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Copyright © 2018 Nagler, Nägele, Gilli, Fragner, Korte, Platzer, Farlow, Nordborg and Weckwerth.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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By the application of metabolomics, multivariate statistics and mathematical modeling based on genome-derived biochemical pathway information, biochemical and physiological signatures of in situ Arabidopsis populations can be identified. Different metabolic steady states on a population level and general patterns common to all populations can be distinguished by this metabolic modeling approach in combination with eco-metabolomics. This finally allows for the prediction of characteristic processes of in situ metabolic adaptation. For details see text and Materials and Methods.