›› 2020, Vol. 32 ›› Issue (5): 824-830.DOI: 10.3969/j.issn.1004-1524.2020.05.10

• Horticultural Science • Previous Articles     Next Articles

Analysis on genetic relationship of mango (Mangifera indica L.) germplasms by CDDP markers

ZHANG Yu, ZHANG Ji, RONG Tao, OU Kewei*, HUANG Guodi, SONG Hongxia   

  1. Guangxi Subtropical Crops Research Institute, Nanning 530001, China
  • Received:2019-10-29 Online:2020-05-25 Published:2020-05-29

Abstract: To analyze the genetic diversity of 31 mango varieties and provide theoretical basis for the identification of mango germplasm resources and molecular assisted breeding, the genetic diversity of 31 mango varieties preserved in Guangxi Subtropical Crops Research Institute was analyzed by conserved DNA-derived polymorphism(CDDP) molecular marker technique. Eight CDDP primers were selected for PCR amplification of mango species tested, electrophoresis, cluster analysis and principal component analysis. There were 107 clear bands amplified from 31 mango varieties, with number of polymorphic bands (NPB) of 100 and polymorphism rate (PPB) of 93.57%. On average, 13 bands and 12 polymorphism bands were amplified from each primer. The average allele number (Na), effective allele number (Ne), Nei's gene diversity (H) and Shannon information index (I) of each locus were 1.847 1, 1.636 8, 0.410 8 and 0.84, respectively, indicating that there was rich genetic diversity among mango species. The range of similarity coefficients between mango species was 0.620 6-0.920 8. UPGMA clustering results showed that mango could be divided into 7 categories at the genetic similarity coefficient of 0.690 6. The results of principal component analysis were basically consistent with the results of cluster analysis, and the classification results were not closely related to the mango origin. The CDDP primer obtained by screening had a high polymorphism detection rate on mango germplasm resources, which was suitable for resource identification and relationship analysis.

Key words: mango, CDDP, clustering analysis, principal component analysis

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