Chloroplast genome comparison and taxonomy assessment in Polygonatum sensu lato
Source: CNGBdb Project (ID CNP0007294)
CC BY 4

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Description: The Polygonati Rhizoma have generated significant market interest for their medicinal and culinary applications. However, morphological similarities and shifting species boundaries complicate genera and species identification, hindering product development and utilization of Polygonatum sensu lato. Despite the widespread application of the chloroplast genome for taxonomic boundary revisions for Polygonatum s.l., a critical gap remains in the evaluations of genomic applicability and standardized pipelines for developing species-specific molecular markers to enable rapid species discrimination. This study aims to assess the support of chloroplast genomes in clarifying the current classification status of the genera and species of Polygonatum s.l., and develop a process for rapid identification of designated species from other species. 21 chloroplast genomes were sequenced and assembled. Phylogeny, multiple molecular species assessment methods, and an automated screening framework were employed for subsequent analysis. Comparative analysis revealed relatively conserved chloroplast genomes, with only notable variation in the length of IR and LSC regions. Integrating multiple methods, the chloroplast genome can validate 82.46% of the current classification status of Polygonatum s.l., and demonstrate stronger support (90.63%) for species represented by multiple sequences but only moderate support (70%) for those with single-sequence representation. This study established and validated a scalable framework for molecular marker development, spanning from the identification of species-specific SNPs/InDels to the design of high-resolution molecular markers, using Heteropolygonatum and three medicinal Polygonatum species as cases.
Data type: Genome sequencing and assembly
Sample scope: Multispecies
Relevance: Industrial
Submitter: 胡迎峰(Huyingfeng); 安徽师范大学
Release date: 2025-05-03
Last updated: 2025-05-03
Data size: 932.01KB