4.5 Article

Genetic Diversity of Ancient Camellia sinensis (L.) O.Kuntze in Sandu County of Guizhou Province in China

Journal

DIVERSITY-BASEL
Volume 13, Issue 6, Pages -

Publisher

MDPI
DOI: 10.3390/d13060276

Keywords

ancient tea plant; phenotypic characters; genetic diversity; SSR markers

Funding

  1. Key Laboratory of Mountain Plant Resources Protection and Planting Innovation, Ministry of Education (Guizhou University)
  2. independent Project Survey, Identification and Utilization of Ancient tea plant germplasm Resources in Sandu
  3. Science and Technology Support Program (Agriculture) of Guizhou, China [[2020]1Y001]
  4. Cultivation of high-level innovative talents in Guizhou Province [(2016)4003]

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The study aimed to evaluate the genetic and phenotypic diversity of 145 ancient tea plant germplasm resources from five populations in Sandu County of Guizhou province in China. The results showed relatively high genetic and phenotypic diversity, providing valuable baseline data for developing more efficient management and breeding plans.
The ancient tea plant germplasm is an important resource for breeding new tea plant varieties and has great economic value. However, due to man-made and natural disturbances, it has become endangered. In order to have a better management of the conserved tea plant germplasm, it is a requirement to understand the genetic and phenotypic diversity. The aim of this study was to evaluate the genetic and phenotypic diversity of 145 ancient tea plant germplasm resources from five populations in Sandu County of Guizhou province in China. To explore the population genetics of tea plant, we successfully identified 15 simple sequence repeat (SSR) markers, which were highly polymorphic. Additionally, we applied traditional phenotypic methods to evaluate the tea plant diversity. The results suggested that the genetic and phenotypic diversity were relatively high. A total of 96 alleles were identified, and the mean polymorphic information content (PIC) value was found to be 0.66. The analysis of molecular variance (AMOVA) showed that genetic variation within the populations was greater than among the populations. Overall, our results are the valuable baseline data in developing more efficient management and breeding plans for one of the most popular non-alcoholic beverage crops, the tea plant species.

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