Kejian Wang
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Kejian Wang has a total of 15 co-authors. Here are the top co-authors by number of shared publications:
- Danjuan Huang
Key Laboratory of Tea Resources Comprehensive Utilization, Ministry of Agriculture and Rural Affairs, Wuhan 430064, China
1 shared publication - Hong Peng
Linzhi Agricultural and Animal Husbandry Technology Extension Center, Nyingchi 860013, China
1 shared publication - Hongjuan Wang
Key Laboratory of Tea Resources Comprehensive Utilization, Ministry of Agriculture and Rural Affairs, Wuhan 430064, China
1 shared publication - Juan Mao
Institute of Vegetables, Xizang Academy of Agricultural and Animal Husbandry Sciences, Lhasa 850032, China
1 shared publication - Liang Chen
State Key Laboratory of Animal Nutrition and Feeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
1 shared publication - Long Jiao
Key Laboratory of Tea Resources Comprehensive Utilization, Ministry of Agriculture and Rural Affairs, Institute of Fruit and Tea, Hubei Academy of Agricultural Sciences, Wuhan 430064, China
1 shared publication
Latest Publications
- Open Access
- 31 December 2025
- Published by MDPI AG in Horticulturae
- Vol. 12 (1) , 50
Genetic Diversity and Population Structure of Tea (Camellia sinensis) Germplasm from the Xizang Plateau
From the 1950s to the 1970s, approximately 80,000 kg of tea seeds were introduced from mainland China to the Xizang Autonomous Region for experimental cultivation. To assess the genetic diversity patterns of these tea accessions following more than half a century of acclimatization to plateau environments, we analyzed genetic variation, population structure, and genetic distinctiveness among fifty tea germplasm using nine phenotypic traits and 30 SSR markers. Phenotypic analysis revealed a moderately high level of genetic diversity, as indicated by the mean Shannon diversity index (H′ = 1.29). Principal component analysis (PCA) indicated that phenotypic variation was not geographically structured across the collection sites. The SSR markers exhibited a high degree of polymorphism, with an average polymorphic information content (PIC) of 0.610 and a genetic diversity index (I) of 1.437, indicating substantial genetic variation. Analysis of molecular variance (AMOVA) revealed that genetic differentiation occurred predominantly within populations, accounting for 91.49% of the total genetic variation. Similarly, 97.86% of the variation was attributed to differences within elevational gradients. Discriminant analysis of principal components (DAPC) and Bayesian population structure modeling (STRUCTURE) both identified two genetic clusters among the studied genotypes. Our results have practical implications for tea breeding programs by providing guidance for parental selection, informing germplasm collection management, and supporting the conservation of genetic resources.
- 31 December 2025
- Published by MDPI AG in Horticulturae
- Vol. 12 (1) , 50
Open AccessGenetic Diversity and Population Structure of Tea (Camellia sinensis) Germplasm from the Xizang Plateau
From the 1950s to the 1970s, approximately 80,000 kg of tea seeds were introduced from mainland China to the Xizang Autonomous Region for experimental cultivation. To assess the genetic diversity patterns of these tea accessions following more than half a century of acclimatization to plateau environments, we analyzed genetic variation, population structure, and genetic distinctiveness among fifty tea germplasm using nine phenotypic traits and 30 SSR markers. Phenotypic analysis revealed a moderately high level of genetic diversity, as indicated by the mean Shannon diversity index (H′ = 1.29). Principal component analysis (PCA) indicated that phenotypic variation was not geographically structured across the collection sites. The SSR markers exhibited a high degree of polymorphism, with an average polymorphic information content (PIC) of 0.610 and a genetic diversity index (I) of 1.437, indicating substantial genetic variation. Analysis of molecular variance (AMOVA) revealed that genetic differentiation occurred predominantly within populations, accounting for 91.49% of the total genetic variation. Similarly, 97.86% of the variation was attributed to differences within elevational gradients. Discriminant analysis of principal components (DAPC) and Bayesian population structure modeling (STRUCTURE) both identified two genetic clusters among the studied genotypes. Our results have practical implications for tea breeding programs by providing guidance for parental selection, informing germplasm collection management, and supporting the conservation of genetic resources.