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Assessment of the genetic diversity and population structure of Sophora tonkinensisin South China by AFLP markers

Authors :
Qiao, Zhu
Xiao, Dong
Keovongkod, Chanthaphoone
Wei, Kun-Hua
He, Long-Fei
Source :
Biotechnology & Biotechnological Equipment; January 2020, Vol. 34 Issue: 1 p975-985, 11p
Publication Year :
2020

Abstract

AbstractSophora tonkinensisis an important source of herbal medicine for treatment of swelling and pain in the throat. Its chemical composition has been extensively studied; however, there are still gaps in the research on genetic diversity of S. tonkinensiswhich can provide insights for better utilization and conservation of genetic resources. In this study, 23 populations of diverse locations from southern China were evaluated using AFLP markers. The average number of alleles (Naand Ne) from all populations was 0.608 (Na) and 1.153 (Ne), average Shannon’s information index was 0.137, which indicated that the genetic diversity of the whole populations was low. Unweighted pair-group method with arithmetic mean (UPGMA) clustering and principal coordinates analysis (PCoA) showed that the populations could be divided into three clades. The analysis of molecular variance (AMOVA) indicated that 20% of the molecular variance was due to differences among wild populations and 80% of the molecular variance was due to divergence within wild populations. There was a significant positive correlation between genetic distance and geographical distance, as well as ecological factors including altitude and temperature. It is necessary to closely monitor the status of the wild populations and consider expanding their genetic diversity. Establishment of the conservation basis in different areas is more conducive to the protection of S. tonkinensis.

Details

Language :
English
ISSN :
13102818 and 13143530
Volume :
34
Issue :
1
Database :
Supplemental Index
Journal :
Biotechnology & Biotechnological Equipment
Publication Type :
Periodical
Accession number :
ejs54757232
Full Text :
https://doi.org/10.1080/13102818.2020.1812430