Exploration of transcriptome SSR markers and its application in genetic diversity assessment of Asarum sieboldii.
10.19540/j.cnki.cjcmm.20230623.101
- Author:
Meng-Ying CHEN
1
;
Rui-Xian DAI
2
;
Yu-Ling FAN
3
;
Zhong LIU
1
Author Information
1. School of Pharmacy, Shanghai Jiao Tong University Shanghai 200240, China.
2. School of Pharmacy, Shanghai Jiao Tong University Shanghai 200240, China School of Pharmacy, Fujian University of Traditional Chinese Medicine Fuzhou 350122, China.
3. School of Pharmacy, Shanghai Jiao Tong University Shanghai 200240, China School of Life Sciences, Beijing University of Chinese Medicine Beijing 102488, China.
- Publication Type:Journal Article
- Keywords:
Asarum sieboldii;
SSR markers;
genetic diversity;
population genetic structure;
transcriptome
- MeSH:
Humans;
Genetic Variation;
Asarum;
Transcriptome/genetics*;
Microsatellite Repeats/genetics*;
Phylogeny
- From:
China Journal of Chinese Materia Medica
2023;48(20):5519-5530
- CountryChina
- Language:Chinese
-
Abstract:
To explore the genetic diversity of Asarum sieboldii this study developed SSR markers based on transcriptome sequencing results and five populations of A.sieboldii from different regions were used as samples for genetic diversity assessment using software such as GenALEx 6.5, NTSYS 2.1, and Structure 2.3.4. The results showed that 16 SSR markers with high polymorphism and good repeatability were selected from the A.sieboldii transcriptome. Primers designed based on the flanking sequences of these markers successfully amplified 56 polymorphic fragments from 150 individual samples of the five A.sieboldii populations. On average, each primer amplified 3.5 polymorphic fragments, ranging from 2 to 8. The mean values of expected heterozygosity(H_e), Shannon's diversity index(I), Nei's gene diversity index(H), and the polymorphic information content(PIC) were 0.172, 0.281, 0.429, and 0.382, respectively. The mean population differentiation coefficient(F_(ST)) was 0.588, consistent with the analysis of molecular variance(AMOVA) results, which indicated greater genetic variation among A.sieboldii populations(69%) than that within populations(31%). The percentage of polymorphic loci(PPL) ranged from highest to lowest as SNJ>LN>SY>SZ>TB. Principal coordinate analysis(PCoA) and UPGMA clustering analysis further revealed genetic clustering of A.sieboldii individuals based on their geographical distribution, consistent with the results of the structure clustering analysis. In summary, the SSR markers developed from the transcriptome effectively assessed the genetic differentiation and population structure of natural A.sieboldii populations, revealing a relatively low genetic diversity in A.sieboldii, with genetic variation primarily observed at the population level and a correlation between population differentiation and geographic distance.
