Integrative Transcriptomic Analysis and Co-Expression Network Characterization of Soybean Developmental Tissues

Document Type

Article

Publication Date

2026

Abstract

Soybean (Glycine max (L.) Merr.) is a globally important legume crop valued as a major source of plant-based protein and edible oil. Understanding the transcriptional programs underlying tissue-specific development is essential for improving seed quality and agronomic performance. Here, we present an integrative transcriptomic analysis of soybean based on 12 samples representing key seed developmental stages—including globular, heart, cotyledon, embryo, dry seed, mid-mature, and late-mature—and vegetative and reproductive tissues, including leaf, root, stem, flower bud, and seedling at 6 days after imbibition (6 DAI). Following data preprocessing and filtering, 54,880 genes were retained for downstream analysis. Principal component analysis revealed clear separation between seed and non-seed tissues, indicating that tissue identity is the dominant driver of transcriptomic variation. Analysis of the top 100 most variable genes further highlighted distinct expression modules associated with seed maturation and vegetative growth. Differential expression analysis identified 9785 genes exhibiting significant expression differences between seed and non-seed tissues, including 1139 upregulated and 8646 downregulated genes under relaxed statistical thresholds. Functional characterization of seed-upregulated genes revealed enrichment of biological processes related to storage metabolism, embryo development, and stress protection mechanisms associated with desiccation tolerance. In addition, co-expression network and correlation analyses demonstrated strong transcriptional coherence among seed tissues and distinct clustering of vegetative organs. Together, these results provide a comprehensive systems-level overview of transcriptional organization across soybean tissues and identify candidate gene sets relevant to seed biology, functional genomics, and crop improvement. © 2026 by the authors.

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