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Genome-wide association study of leaf-related traits in tea plant in Guizhou based on genotyping-by-sequencing.
Chen, Yanjun; Niu, Suzhen; Deng, Xinyue; Song, Qinfei; He, Limin; Bai, Dingchen; He, Yingqin.
Affiliation
  • Chen Y; College of Tea Science / Tea Engineering Technology Research Center, Guizhou University, Guiyang, 550025, Guizhou Province, People's Republic of China.
  • Niu S; College of Tea Science / Tea Engineering Technology Research Center, Guizhou University, Guiyang, 550025, Guizhou Province, People's Republic of China. niusuzhen@163.com.
  • Deng X; Key Laboratory of Plant Resources Conservation and Germplasm Innovation in Mountainous Region, Ministry of Education, Institute of Agro-Bioengineering, Guizhou University, Guiyang, 550025, Guizhou Province, People's Republic of China. niusuzhen@163.com.
  • Song Q; School of Architecture, Guizhou University, Guiyang, 550025, Guizhou Province, People's Republic of China.
  • He L; College of Tea Science / Tea Engineering Technology Research Center, Guizhou University, Guiyang, 550025, Guizhou Province, People's Republic of China.
  • Bai D; College of Tea Science / Tea Engineering Technology Research Center, Guizhou University, Guiyang, 550025, Guizhou Province, People's Republic of China.
  • He Y; College of Tea Science / Tea Engineering Technology Research Center, Guizhou University, Guiyang, 550025, Guizhou Province, People's Republic of China.
BMC Plant Biol ; 23(1): 196, 2023 Apr 12.
Article in En | MEDLINE | ID: mdl-37046207
ABSTRACT

BACKGROUND:

Studying the genetic characteristics of tea plant (Camellia spp.) leaf traits is essential for improving yield and quality through breeding and selection. Guizhou Plateau, an important part of the original center of tea plants, has rich genetic resources. However, few studies have explored the associations between tea plant leaf traits and single nucleotide polymorphism (SNP) markers in Guizhou.

RESULTS:

In this study, we used the genotyping-by-sequencing (GBS) method to identify 100,829 SNP markers from 338 accessions of tea germplasm in Guizhou Plateau, a region with rich genetic resources. We assessed population structure based on high-quality SNPs, constructed phylogenetic relationships, and performed genome-wide association studies (GWASs). Four inferred pure groups (G-I, G-II, G-III, and G-IV) and one inferred admixture group (G-V), were identified by a population structure analysis, and verified by principal component analyses and phylogenetic analyses. Through GWAS, we identified six candidate genes associated with four leaf traits, including mature leaf size, texture, color and shape. Specifically, two candidate genes, located on chromosomes 1 and 9, were significantly associated with mature leaf size, while two genes, located on chromosomes 8 and 11, were significantly associated with mature leaf texture. Additionally, two candidate genes, located on chromosomes 1 and 2 were identified as being associated with mature leaf color and mature leaf shape, respectively. We verified the expression level of two candidate genes was verified using reverse transcription quantitative polymerase chain reaction (RT-qPCR) and designed a derived cleaved amplified polymorphism (dCAPS) marker that co-segregated with mature leaf size, which could be used for marker-assisted selection (MAS) breeding in Camellia sinensis.

CONCLUSIONS:

In the present study, by using GWAS approaches with the 338 tea accessions population in Guizhou, we revealed a list of SNPs markers and candidate genes that were significantly associated with four leaf traits. This work provides theoretical and practical basis for the genetic breeding of related traits in tea plant leaves.
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Full text: 1 Database: MEDLINE Main subject: Camellia sinensis / Genome-Wide Association Study Type of study: Prognostic_studies / Risk_factors_studies Language: En Journal: BMC Plant Biol Year: 2023 Type: Article

Full text: 1 Database: MEDLINE Main subject: Camellia sinensis / Genome-Wide Association Study Type of study: Prognostic_studies / Risk_factors_studies Language: En Journal: BMC Plant Biol Year: 2023 Type: Article