PlantRegMoD: An integrative and AI-driven multi-omics database for plant regeneration research

Li, Y.-M.; Ma, Y.-B.; Gui, L.-Y.; Tang, Y.; Meng, C.; Li, Y.; Yao, L.; Zhang, J.; Xia, S.; Peng, Y.; Song, S.; Zeng, Z.; He, J.-B.; Zhang, N.; Xiao, P.-X.; Xu, Y.; Tan, L.; Iwase, A.; Chen, C.; Jiao, W.-B.

doi:10.64898/2026.09.15.751352

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bioRxiv · 10.64898/2026.09.15.751352

PlantRegMoD: An integrative and AI-driven multi-omics database for plant regeneration research

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Abstract

Plant regeneration underpins plant developmental plasticity, tissue culture, genetic transformation and crop improvement. Although numerous related omics datasets have been generated, specialized multi-omics databases for this field are still scarce. Here, we constructed PlantRegMoD, an AI-powered integrated database dedicated to plant regeneration. This platform hosts 20.54 TB standardized multi-omics data from 147 projects across 32 plant species and 2,593 samples. We established a unified hierarchical classification system covering five major categories and nine regeneration models, and curated 236 regeneration genes as well as their 28,190 homologs across 58 representative plant species. It contains extensive transcriptomic resources across all regeneration models, together with 196,423 single cells and over 8.81 million epigenetic peaks to dissect cellular heterogeneity and multi-layered epigenetic regulation. Equipped with nine online omics-related tools and a RAG-based intelligent Q&A system, PlantRegMoD greatly reduces bioinformatic barriers and serves as a robust resource for mechanistic, functional and evolutionary studies of plant regeneration.

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Li, Y.-M., Ma, Y.-B., Gui, L.-Y., Tang, Y., Meng, C., Li, Y., Yao, L., Zhang, J., Xia, S., Peng, Y., Song, S., Zeng, Z., He, J.-B., Zhang, N., Xiao, P.-X., Xu, Y., Tan, L., Iwase, A., Chen, C., Jiao, W.-B.. 2026-09-17. PlantRegMoD: An integrative and AI-driven multi-omics database for plant regeneration research. https://doi.org/10.64898/2026.09.15.751352

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