ArticlePloS one2021
Genome-wide association study on metabolite accumulation in a wild barley NAM population reveals natural variation in sugar metabolism.
Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 10 citations in OpenAlex.
- Provenance effect on the fine-root metabolome and structure of mature Scots pine revealed in a long-term common garden experiment.Tree physiology · 2026Article
- Coumarin metabolites in Ocimum: chemical diversity, biosynthetic pathways, and network pharmacology-based prediction of multi-target anticancer potential.Plant molecular biology · 2026Article
- Deciphering barley's stress response: metabolomic strategies and phenotypic implications under multiple abiotic stresses.Metabolomics : Official journal of the Metabolomic Society · 2026Article
- UPLC-ESI-TOF-MS Profiling of Metabolome Alterations in Barley (Journal of agricultural and food chemistry · 2025Article
- Approach strategies and application of metabolomics to biotechnology in plants.Frontiers in plant science · 2023Review
- Review
- Recent applications of metabolomics in plant breeding.Breeding science · 2022Article
- The Application of Metabolomics in Recent Colorectal Cancer Studies: A State-of-the-Art Review.Cancers · 2022Review
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Metabolites play a key role in plants as they are routing plant developmental processes and are involved in biotic and abiotic stress responses. Their analysis can offer important information on the underlying processes. Regarding plant breeding, metabolite concentrations can be used as biomarkers instead of or in addition to genetic markers to predict important phenotypic traits (metabolic prediction). In this study, we applied a genome-wide association study (GWAS) in a wild barley nested association mapping (NAM) population to identify metabolic quantitative trait loci (mQTL). A set of approximately 130 metabolites, measured at early and late sampling dates, was analysed. For four metabolites from the early and six metabolites from the late sampling date significant mQTL (grouped as 19 mQTL for the early and 25 mQTL for the late sampling date) were found. Interestingly, all of those metabolites could be classified as sugars. Sugars are known to be involved in signalling, plant growth and plant development. Sugar-related genes, encoding mainly sugar transporters, have been identified as candidate genes for most of the mQTL. Moreover, several of them co-localized with known flowering time genes like Ppd-H1, HvELF3, Vrn-H1, Vrn-H2 and Vrn-H3, hinting on the known role of sugars in flowering. Furthermore, numerous disease resistance-related genes were detected, pointing to the signalling function of sugars in plant resistance. An mQTL on chromosome 1H in the region of 13 Mbp to 20 Mbp stood out, that alone explained up to 65% of the phenotypic variation of a single metabolite. Analysis of family-specific effects within the diverse NAM population showed the available natural genetic variation regarding sugar metabolites due to different wild alleles. The study represents a step towards a better understanding of the genetic components of metabolite accumulation, especially sugars, thereby linking them to biological functions in barley.
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