Construction of fingerprinting for tea plant accessions using new genomic SSR markers
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Construction of fingerprinting for tea plant (Camellia sinensis) accessions using new genomic SSR markers


Shengrui Liu, Hongwei Liu, Ailin Wu, Yan Hou, Yanlin An, ChaoLing Wei*


Mol Breeding (2017) 37:93


As one of the most popular non-alcoholic beverage crops, the tea plant (
Camellia sinensis)
plays an important role in human health and lifestyle. Genetic fingerprinting based on genomic-derived markers in tea, however, is still in the initial stages, which has limited tea germplasm resource utilization and cultivar protection. In the current study, we identified whole genome-based simple sequence repeat (SSR) loci and successfully developed 36 new genomic SSR markers, which are highly polymorphic with average allele number and polymorphic information content (PIC) of 14.9 and 0.862, respectively. A phylogenetic tree for 80 tea plant accessions was subsequently constructed based on their genotypic scores for these 36 markers. The phylogenetic relationships among the 80 accessions are highly consistent with their genetic backgrounds or original places. Noteworthy, robust fingerprinting power was performed, and the overall probability of finding two random individuals sharing identical genotypes across the 36 loci was estimated to be 1.5×10-56. We subsequently identified five SSR markers as a recommended core marker set for fingerprinting the tea plant cultivars or accessions. The combined PI and PIsibs of the marker set were 1.49×10-9 and 2.57×10-3, respectively, which allowed us to fully discriminate all 80 tea plant accessions from one another. The SSR markers developed here will provide a valuable resource for tea plant genetics and genomic studies, as well as breeding programs. The fingerprinting profiles can serve as a database that is essential for the tea industry and commercial breeding, and for tea plant cultivar identification, utilization, and protection.

  • construction of fingerprinting for tea plant(刘升锐,韦朝领, 2017).pdf
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