ArticleMetabolites2024
Data-Driven Characterization of Metabolome Reprogramming during Early Development of Sorghum Seedlings.
Article in Metabolites, 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, 5 citations in OpenAlex.
- Germination Time and Temperature Modulate Bioactive Compound Accumulation in Black Rice (Plants (Basel, Switzerland) · 2026Article
- The Metabolic Awakening of Barley Seedlings: A Time-Resolved View of How Germination and Light Shape Tissue-Specific Metabolic Networks.Plant direct · 2026Article
- Comparative analysis of primary and secondary metabolites in wheat seedlings (Triticum aestivum L.) cultivated under varying photosynthetic photon flux densities and growth periods.Journal of the science of food and agriculture · 2025Article
- Sustainable Management of Major Fungal Phytopathogens in Sorghum (Journal of fungi (Basel, Switzerland) · 2025Review
- Chemical Biology Meets Metabolomics: The Response of Barley Seedlings to 3,5-Dichloroanthranilic Acid, a Resistance Inducer.Molecules (Basel, Switzerland) · 2025Article
- Metabolomics analysis of five cultivars of Sorghum bicolor reveals the contribution of flavonoid pathway to tannin content.PloS one · 2025Article
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Specialized metabolites are produced via discrete metabolic pathways. These small molecules play significant roles in plant growth and development, as well as defense against environmental stresses. These include damping off or seedling blight at a post-emergence stage. Targeted metabolomics was followed to gain insights into metabolome changes characteristic of different developmental stages of sorghum seedlings. Metabolites were extracted from leaves at seven time points post-germination and analyzed using ultra-high performance liquid chromatography coupled to mass spectrometry. Multivariate statistical analysis combined with chemometric tools, such as principal component analysis, hierarchical clustering analysis, and orthogonal partial least squares-discriminant analysis, were applied for data exploration and to reduce data dimensionality as well as for the selection of potential discriminant biomarkers. Changes in metabolome patterns of the seedlings were analyzed in the early, middle, and late stages of growth (7, 14, and 29 days post-germination). The metabolite classes were amino acids, organic acids, lipids, cyanogenic glycosides, hormones, hydroxycinnamic acid derivatives, and flavonoids, with the latter representing the largest class of metabolites. In general, the metabolite content showed an increase with the progression of the plant growth stages. Most of the differential metabolites were derived from tryptophan and phenylalanine, which contribute to innate immune defenses as well as growth. Quantitative analysis identified a correlation of apigenin flavone derivatives with growth stage. Data-driven investigations of these metabolomes provided new insights into the developmental dynamics that occur in seedlings to limit post-germination mortality.
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