Genetic and phytochemical investigations for understanding population variability of the medicinally important tree Saraca asoca to help develop conservation strategies
| Title | Genetic and phytochemical investigations for understanding population variability of the medicinally important tree Saraca asoca to help develop conservation strategies |
| Publication Type | Journal Article |
| Year of Publication | 2018 |
| Authors | Hegde, S, Pai, SRamchandra, Bhagwat, RM, Saini, A, Rathore, PKanwar, Jalalpure, SSatyappa, Hegde, HVasudev, Sugunan, APurushotta, Gupta, VS, Kholkute, SD, Roy, S |
| Journal | Phytochemistry |
| Volume | 156 |
| Pagination | 43-54 |
| Date Published | DEC |
| Type of Article | Article |
| ISSN | 0031-9422 |
| Abstract | Saraca asoca (Roxb.) De Wilde (Caesalpiniaceae) is a highly traded IUCN red listed tree species used in Ayurvedic medicines for the treatment of various disorders, especially gynaecological problems. However, information about the genetic variations between populations and corresponding variation in specialized metabolites of S. asoca remains unclear. To address this issue, we analysed 11 populations of S. asoca with 106 accessions collected from Western Ghats of India using ISSR markers along with selected phytocompounds using RP-HPLC. Twenty primers were screened, out of which seven were selected for further analysis based on generation of clear polymorphic banding patterns. These seven ISSR primers produced 74 polymorphic loci. AMOVA showed 43% genetic variation within populations and 57% among the populations of S. asoca. To estimate the genetic relationships among S. asoca populations, UPGMA and Bayesian Models were constructed, which revealed two clusters of similar grouping patterns. However, excluding minor deviations, UPGMA and dissimilarity analysis showed close association of genotypes according to their geographical locations. Catechin (CAT), epicatechin (EPI) and gallic acid (GA) were quantified from bark and leaf samples of corresponding genotypes collected from 106 accessions. ROC plots depicted the sensitivity and specificity of the concentrations of tested phytocompounds at various cut-off points. Although, multiple logistic regression analysis predicted some association between few loci with GA, EPI and CAT, but PCA for phytochemical data failed to distinguish the populations. Overall, there were no significant trends observed to distinguish the populations based on these phytocompounds. Furthermore, the study advocates the delineate provenance regions of S. asoca genotypes/chemotype snapshots for in-situ conservation and ex-situ cultivation. |
| DOI | 10.1016/j.phytochem.2018.08.016 |
| Type of Journal (Indian or Foreign) | Foreign |
| Impact Factor (IF) | 3.875 |
Divison category:
Biochemical Sciences
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