Differences in morphological characteristics, photosynthetic capacity and Chloroplast genomes reveal molecular markers to distinguish Angelica sinensis, A. acutiloba and A. gigas.

Background: The dried roots of Angelica sinensis, A. acutiloba, and A. gigas in the Angelica L. have been used as the same traditional medicines for nourishing the blood, regulating female menstrual disorders, relieving pains, and relaxing bowels for thousands of years. Although significant differences in geographical distribution, morphological characteristics, chemical components, and gene sizes have been observed in previous studies, they were limited to distinguishing the three species through an efficient, unique, and accurate approach.

Results: In this study, morphological characteristics, photosynthetic capacity, and chloroplast (CP) genomes of the three species were performed. There were obvious differences in morphological characteristics, such as leaf margin irregularly coarse-cuspidate-serrate of A. sinensis, leaf margin irregularly acute-serrate of A. acutiloba, and leaf margin irregularly coarse-toothed apex acute of A. gigas. There was a higher photosynthetic capacity of A. gigas and A. acutiloba than A. sinensis, which was consistent with root biomass. The length of CP genomes of A. sinensis, A. acutiloba and A. gigas were 141,869, 147,057 and 147,050 bp with encoding 124,128 and 128 genes, respectively. There were 3 genes (i.e., psbA, ndhB, and ycf15) affecting the expansion and contraction of inverted repeat (IR), and 7 genes (i.e., matK, psbN, ccsA, rps8, ndhF, ycf1, and ycf2) in the gene regions presenting notably high nucleotide diversity.

Conclusion: The distinct phenotypes of leaf shape and stem color can be used for species delimitation of the three species. The 3 genes (i.e., psbA, ndhB, and ycf15) can be used to distinguish A. sinensis from A. acutiloba and A. gigas using the agarose gel electrophoresis and the base sequence. The 7 genes (i.e., matK, psbN, ccsA, rps8, ndhF, ycf1, and ycf2) can accurately distinguish the three species using the base sequence. We establish a rapid and reliable multi-level identification system for the three Angelica species. This approach addresses critical challenges in medicinal plant taxonomy and supports quality control in herbal product industries.