Abstract

In the present research, inter and intra genetic variability of 77 accessions belonging to 11 Thymus species were assessed using eight SRAP primer combinations. High polymorphism (98.3%) was observed in the studied species. The cluster analysis classified Thymus species into five main groups. According to molecular variance (AMOVA) analysis, 63.14% of total genetic variation was obtained within the species, while 36.86% of variation was observed among species. STRUCTURE analysis was also performed to estimate the admixture of species. For instance, T. carmanicus and T. transcaspicus revealed high admixtures. HPLC analysis also demonstrated the presence of rosmarinic acid (32.3–150.7 mg/100 g DW), salvianolic acid (8–90 mg/100 g DW), and cinnamic acid (1.7–32.3 mg/100 g DW) as major phenolic acids, as well as apigenin, epicatechin, and naringenin as the major flavonoids. The highest phenolic and flavonoid contents were detected in T. transcaspicus (37.62 mg gallic acid equivalents (GAE) g−1 DW) and T. vulgaris (8.72 mg quercetin equivalents (QE) g−1 DW), respectively. The antioxidant properties and total phenolic of Thymus species were examined using DPPH and β-carotene-linoleic acid model systems and consequently T. vulgaris and T. pubescens were detected with the highest and the lowest antioxidant activities respectively. Cluster and principal Components Analysis (PCA) of the components classified the species in to three groups. Finally, similarity within some species was observed comparing molecular and phytochemical markers. For instance, T. vulgaris separated from other species according to major polyphenolic profiles and molecular analyses, as well as T. transcaspicus, T. carmanicus, and T. fedtschenkoi that were clustered in the same groups.

Highlights

  • Phenolic and flavonoid compounds have been known as natural products with high antioxidant activity

  • Mey., T. serpyllum L., T. trautvetteri Klokov & Desj. -Shost., T. transcaspicus Klokov, T. carmanicus Jalas, T. fedtschenkoi Ronneger, T. daenensis Celak subsp. daenensis, T. pubescens Boiss. & Kotschy ex Celak, T. kotschyanus Boiss. & Hohen., and T. vulgaris L, (2) to determine the polyphenolic profiles of studied species based on HPLC analysis, (3) to determine the inter- and intra-genic relationships of the species based on SRAP molecular marker, and (4) to classify the species based on molecular and phytochemical markers using multivariate analyses

  • Rosmarinic acid has been reported as the major phenolic acid in most of the previous studies in several ­species[9,10,30], while different classes of flavonoids have been reported in Thymus species

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Summary

Introduction

Phenolic and flavonoid compounds have been known as natural products with high antioxidant activity Nowadays, such components are frequently used and emphasized in food and some industrial products because of their health ­properties[1]. Most of the previous researches have focused on polyphenolic profiles of one or few limited species and there are no comprehensive and comparative study focusing on phenolics, flavonoids and their derivatives in Thymus species. As the previous studies mostly reported one species and the extraction methods were different, so another importance of this research was the comparison of 11 Thymus species in one experiment using a similar extraction method that increase the validity of comparison This is the first report to introduce and compare the phenolic and flavonoid compounds of several Thymus species based on HPLC analysis. Mey., T. serpyllum L., T. trautvetteri Klokov & Desj. -Shost., T. transcaspicus Klokov, T. carmanicus Jalas, T. fedtschenkoi Ronneger, T. daenensis Celak subsp. daenensis, T. pubescens Boiss. & Kotschy ex Celak, T. kotschyanus Boiss. & Hohen., and T. vulgaris L, (2) to determine the polyphenolic profiles of studied species based on HPLC analysis, (3) to determine the inter- and intra-genic relationships of the species based on SRAP molecular marker, and (4) to classify the species based on molecular and phytochemical markers using multivariate analyses

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