A Multi-Variety Co-Expression Network Identifies Candidate Genes Associated with Tuber Color, Starch Composition and Texture in Greater Yam
Year: 2026
Type: article
Abstract: Greater yam (Dioscorea alata L.) is a globally distributed yam species with high agronomic potential but variable culinary quality. The molecular basis of key tuber quality attributes, including flesh pigmentation, starch and sugar composition, texture after cooking, and moldability, remain poorly understood. To address this knowledge gap, we performed an integrative transcriptome analysis of six contrasting D. alata varieties representing diverse tuber quality profiles. RNA-seq data were integrated with biochemical, morphological, textural, and flesh-color phenotypes to identify genes associated with quality variation. Differential expression and pathway enrichment analyses revealed major changes in phenylpropanoid, flavonoid, carotenoid, galactose, zeatin, and photosynthesis-related pathways. Weighted gene co-expression network analysis identified 26 expression modules, five of which were associated with specific varieties and quality traits. Candidate genes were prioritized by integrating co-expression modules, differential expression patterns, and functional annotation. Anthocyanin- and flavonoid-related genes and regulators (including CCoAOMT, C3H, F3′H, F3′5′H, DFR, AP2, MYB, WD40) were associated with purple flesh, whereas carotenoid biosynthetic genes (PSY and NCED) were linked to yellow flesh. Modules associated with starch, sugar and moldability highlighted genes involved in carbohydrate metabolism and cell wall modification, including beta-glucosidase, glycosyl hydrolases, pectinesterase, and galacturonidase. By simultaneously analyzing six genetically diverse varieties, this study extends previous pairwise transcriptomic comparisons and provides a comprehensive candidate-gene resource for improving tuber quality in D. alata.
Source: Horticulturae
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
SDG: Zero hunger
Open Access status: gold
Estimated APC paid: $2,654
OpenAlex ID: W7215893167
