ArticleThe Plant cell2024
Chemical-tag-based semi-annotated metabolomics facilitates gene identification and specialized metabolic pathway elucidation in wheat.
Article in The Plant cell, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 13 citations in OpenAlex.
- Integrating Metabolomics and Proteomics to Reveal the Regulatory Network Governing the Natural Variation in Rice Seed Germination Rate.Plants (Basel, Switzerland) · 2026Article
- Unraveling the regulatory network of barley grain metabolism through the integrative analysis of multiomics and mQTL.Nature communications · 2025Article
- Review
- Metabolomic Analysis Reveals the Diversity of Defense Metabolites in Nine Cereal Crops.Plants (Basel, Switzerland) · 2025Article
- Review
- Evolution of plant metabolism: the state-of-the-art.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024Review
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Authors and funding
17 authors at 2 institutions in 2 countries.
Funding
Abstract
The importance of metabolite modification and species-specific metabolic pathways has long been recognized. However, linking the chemical structure of metabolites to gene function in order to explore the genetic and biochemical basis of metabolism has not yet been reported in wheat (Triticum aestivum). Here, we profiled metabolic fragment enrichment in wheat leaves and consequently applied chemical-tag-based semi-annotated metabolomics in a genome-wide association study in accessions of wheat. The studies revealed that all 1,483 quantified metabolites have at least one known functional group whose modification is tailored in an enzyme-catalyzed manner and eventually allows efficient candidate gene mining. A Triticeae crop-specific flavonoid pathway and its underlying metabolic gene cluster were elucidated in further functional studies. Additionally, upon overexpressing the major effect gene of the cluster TraesCS2B01G460000 (TaOMT24), the pathway was reconstructed in rice (Oryza sativa), which lacks this pathway. The reported workflow represents an efficient and unbiased approach for gene mining using forward genetics in hexaploid wheat. The resultant candidate gene list contains vast molecular resources for decoding the genetic architecture of complex traits and identifying valuable breeding targets and will ultimately aid in achieving wheat crop improvement.
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Registered trials
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