AUTHOR=Alekseeva Marina , Zagorcheva Tzvetelina , Rusanova Mila , Rusanov Krasimir , Atanassov Ivan 

TITLE=Genetic and Flower Volatile Diversity in Natural Populations of Origanum vulgare subsp. hirtum (Link) Ietsw. in Bulgaria: Toward the Development of a Core Collection

JOURNAL=Frontiers in Plant Science

VOLUME=Volume 12 - 2021

YEAR=2021

URL=https://www.frontiersin.org/journals/plant-science/articles/10.3389/fpls.2021.679063

DOI=10.3389/fpls.2021.679063

ISSN=1664-462X

ABSTRACT=We studied the genetic and flower volatile diversity in Origanum vulgare subsp. hirtum (Link) Ietsw. natural populations in Bulgaria using SSR and SRAP markers and GC/MS analysis of flower volatiles from individual plants. Two typical for the species regions including the Kresna Gorge and Eastern Rhodopes comprising eight populations and 239 individual plants were included in the study. Analysis with 11 SSR markers and eight SRAP primer combinations showed that SRAP markers were substantially more informative than the SSR markers and were further used for analysis of the genetic diversity. The results showed low to midrange genetic differentiation between the populations with pairwise Fst values ranging between 0.0047 and 0.11. A total of 10 genetic clusters were identified. Analysis of the flower volatile diversity identified a total of 63 compounds with the vast majority of plants belonging to the carvacrol chemotype and just a single plant to the thymol chemotype. Large deviations were observed for individual compounds within each region as well as within the populations. Hierarchical clustering showed clear sample grouping based on the two different regions. Further in-depth analysis identified 6 major and 23 minor metabolite clusters. The overall data set and cluster analysis were further used for development and testing of a simple and straightforward strategy for selection of individual plants for development of a core collection representing the sampled natural populations for this species in Bulgaria. The proposed strategy involves precise genetic clustering of the tested plants followed by selection of a minimal set from each genetic cluster representing the different metabolite clusters. The selected core set was further compared with a core set extracted by the PowerCore software. Comparison of the genetic and metabolic affiliation of the members of both sets showed that the reported approach selected representatives from each genetic and minor metabolic clusters, whereas some metabolic clusters were unrepresented in the PowerCore set.  The feasibility and efficiency for the application of the pointed strategy for development of a core collection representing both the genetic and metabolite diversity of aromatic and medicinal plants natural populations towards subsequent steps of selection and breeding is discussed.