Analysis of Metabolic Differences Between Marselan and Cabernet Sauvignon Grape Berries from the Manas Wine-Producing Region of Xinjiang Based on Untargeted Metabolomics
Year: 2026
Type: article
Abstract: To characterize cultivar-specific metabolic differences between Marselan and Cabernet Sauvignon grapes cultivated in the Manas subregion on the northern foothills of the Tianshan Mountains in Xinjiang, China, mature berries from the two cultivars grown in adjacent plots within the same vineyard were analyzed, with three independent biological replicates per cultivar (n = 3). Untargeted metabolomics based on UHPLC–Q Exactive MS was used to compare the overall metabolic profiles of the two cultivars. PCA revealed clear separation between their global metabolic profiles in both positive- and negative-ion modes. A total of 236 candidate differential metabolites were identified using VIP > 1 and unadjusted p < 0.05, of which 34 further met FDR ≤ 0.05 and |log2FC| ≥ 1. After reviewing metabolite annotation evidence and grape berry metabolic context, 13 biologically interpretable features were selected for hierarchical clustering in the main text. KEGG analysis showed that flavonoid biosynthesis remained significantly enriched after multiple-testing correction, whereas phenylalanine metabolism and flavone and flavonol biosynthesis also showed distinct differential metabolite mapping patterns. Overall, Marselan and Cabernet Sauvignon exhibited distinct cultivar-associated metabolic phenotypes in mature berries, mainly involving phenylalanine and its downstream phenolic and flavonoid-related metabolic processes. Given the limited sample size and the risk of overfitting in supervised models, the conclusions were interpreted mainly on the basis of PCA, multiple-testing-corrected univariate statistics, and metabolite annotation evidence.
Source: Foods
Institution: Xinjiang Agricultural University
Language: English
Subfield: Plant Science
Domain: Life Sciences
SDG: Zero hunger
Open Access status: gold
Estimated APC paid: $3,499
Awards: G1982990472, G9000923337
OpenAlex ID: W7220382794
