Spanning from the heart-stage embryo to seed germination, the study charts dynamic gene expression patterns in the embryo axis and cotyledon, revealing key regulatory networks. This work uncovers how transcription factors, hormone signals, and metabolic genes cooperate throughout development—and even shows that dehydration-resistance genes were positively selected during domestication.
Soybean is a globally important legume crop, supplying over 45% of plant-derived oil and 67% of animal feed in China alone. Its seeds develop from embryos, meaning that embryo growth directly determines seed size, weight, and quality. While transcriptome atlases have been constructed for crops like maize, wheat, and Arabidopsis, a high-resolution map covering the full embryo development process in soybeans—and other legumes—has been lacking. Soybean also differs from these models in cotyledon development, metabolite accumulation, and environmental sensitivity. A complete transcriptome atlas would thus not only clarify key developmental processes but also support advanced crop breeding strategies in soybean and related species.
A study (DOI: 10.48130/seedbio-0024-0021) published in Seed Biology on 13 December 2024 by Yingxiang Wang's & Yalin Liu's team, South China Agricultural University, serves as a powerful resource for functional genomics and opens doors for smarter breeding of high-yield, stress-resilient soybean varieties.
The study collected 18 tissue samples representing major stages of soybean embryo development, including the embryo axis and cotyledon, dry seeds, and germination phases. Each sample underwent RNA sequencing, generating high-coverage data with consistent replicates. Analysis revealed dynamic transcriptional activity: the number of expressed genes peaked during early maturation (over 25,000) and declined significantly in dry seeds, before rising again post-imbibition. EA typically exhibited more moderately expressed genes, while CT showed higher expression of select genes. Transcription patterns clustered according to developmental stages, with EA and CT from the same stage more similar than the same tissue across stages. Differential gene expression analysis revealed massive transcriptional reprogramming, especially during transitions into and out of maturation. For instance, nearly 5,000 genes were downregulated during late maturation, coinciding with seed desiccation. Gene ontology enrichment indicated key biological processes such as circadian rhythm regulation, hormone signaling, and flavonoid biosynthesis were stage-specific. Researchers also identified 1,922 active transcription factors (TFs), including well-known embryogenesis regulators such as BBM, STM, WOX11, and YABBY, which displayed tissue- and stage-specific expression. Moreover, genes involved in oil, protein, flavonoid, folate, and steroid biosynthesis revealed coordinated expression peaks, supporting the metabolic transitions during seed development. Notably, gibberellin-related genes peaked early, while abscisic acid-related genes dominated later stages. Surprisingly, dry seeds contained stored transcripts related to spliceosome and ribosome assembly, likely supporting rapid germination. Finally, genes associated with dehydration tolerance (LEA, HSP, oleosin, dehydrin) were found to be positively selected through domestication, showing increased expression from wild soybeans to modern cultivars. Altogether, this transcriptome landscape provides vital resources for crop improvement and evolutionary biology.
This transcriptome atlas offers a foundational resource for soybean functional genomics and seed trait improvement. The identified transcription factors and metabolic genes provide precise targets for breeding programs aimed at enhancing oil or protein content, improving stress resilience, or optimizing seed size. The discovery of stored transcripts in dry seeds may lead to strategies for boosting seed vigor and longevity. Moreover, the demonstrated selection of dehydration-related genes informs our understanding of how soybean adapted to changing climates over millennia. These insights can help accelerate the development of next-generation soybean varieties tailored for specific climates and agricultural needs.
