Metabolomics: the chemistry between ecology and genetics
Mirka Macel1, Nicole M Van Dam, Joost J B Keurentjes
1Department of Terrestrial Ecology, Netherlands Institute of Ecology (NIOO-KNAW), Boterhoeksestraat 48, NL-6666 GA Heteren, The Netherlands Laboratory of Plant Physiology, Wageningen University, Droevendaalsesteeg 1, NL-6708 PB Wageningen, The Netherlands Laboratory of Genetics, Wageningen University, Droevendaalsesteeg 1, NL-6708 PB Wageningen, The Netherlands Centre for Biosystems Genomics, Droevendaalsesteeg 1, NL-6708 PB Wageningen, The Netherlands.
Metabolomics offers comprehensive chemical analysis for any organism, aiding functional genomics and systems biology. This review focuses on its applications in plant ecology and genetics, linking phenotypes to genotypes.
Area of Science:
- Metabolomics
- Functional Genomics
- Systems Biology
- Plant Ecology
- Environmental Science
Background:
- Metabolomics provides a comprehensive analysis of an organism's chemical compounds.
- Its utility depends on species-specific metabolome databases.
- It operates downstream of transcriptomics and proteomics.
Purpose of the Study:
- To review the applications of metabolomics in plant ecology and genetics.
- To discuss analytical platforms and their limitations.
- To highlight metabolomics as a tool for linking phenotypes to genotypes.
Main Methods:
- Comprehensive untargeted chemical analyses.
- Application across diverse organisms, irrespective of prior genomic or metabolomic knowledge.
- Review of commonly used analytical metabolomic platforms.
Main Results:
- Metabolomics successfully links phenotypes to genotypes in model plants like Arabidopsis thaliana.
- It provides novel insights into plant resistance mechanisms against herbivores in ecological studies.
- Increasing use in ecological and environmental metabolomics.
Conclusions:
- Metabolomics is a powerful tool for functional genomics and systems biology.
- Its application in plant ecology reveals mechanisms of herbivore resistance.
- Development of species-specific databases is crucial for maximizing metabolomic data utility.
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