ArticleBMC genomics2025
ASAPv2: an improved platform for exploring gene function in Angelica sinensis.
Article in BMC genomics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Angelica sinensis (Danggui) is a long-valued herb in traditional Chinese medicine for treating gynecological and other health issues. Modern research has identified numerous bioactive compounds in A. sinensis roots, but the genetic and biosynthetic pathways underlying these constituents remain partially understood. The recent availability of high-quality A. sinensis genomes and extensive omic data has opened new opportunities for gene function analysis. Integrating these resources can significantly aid in uncovering gene functions in A. sinensis’s secondary metabolic pathways. We created ASAPv2, an improved platform for analyzing A. sinensis gene functions. It combines two reference genomes, 97 transcriptome datasets from diverse tissues and treatment conditions, and metabolomic profiles from existing studies. All genes in the database are annotated with functional information by sequence similarity to public databases and domain analyses. Key gene families have been identified including 5,594 transcription factors, 2,665 protein kinases, 1,746 Carbohydrate-Active enZymes, 1,727 transporters, and 2,770 ubiquitin-related enzymes. Furthermore, ASAPv2 identified 1,055,573 positive co-expression relationships and 86,486 protein–protein interaction networks predicted by orthology to Arabidopsis. The platform, built on a LAMP architecture, offers a web interface with browsing, search, and visualization tools. Users can query genes, perform BLAST searches, view genomic regions in JBrowse, examine gene expression heatmaps, explore network relationships, and retrieve sequences. In addition, by mining transcriptome data through the data platform, we identified a candidate gene, SOC1, involved in flowering regulation. Multiple lines of functional evidence obtained via the platform support this finding, indicating that the platform can play an auxiliary role in acquiring and mining gene function information. We hope ASAPv2 (accessible at www.gzybioinformatics.cn/ASAPv2 ) will enhance A. sinensis research and enable new discoveries.
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