Use of morpho-agronomic traits and DNA profiling for classification of genetic diversity in papaya

Abstract

We examined the genetic diversity of papaya (Carica papaya) based on morpho-agronomic and molecular data. Twenty-seven genotypes grown in Brazil were analyzed with 11 AFLP primer combinations, 23 ISSR markers, 22 qualitative, and 30 quantitative descriptors. For the joint analyses, we used the Gower algorithm (Joint Gower) and the average value of the individual dissimilarity matrix for each type of data (Average-Joint Gower); 359 AFLP and 52 ISSR polymorphic bands were found. Approximately 29.2 and 7.7% of the AFLP and ISSR bands, respectively, were genotype-specific and may therefore be used for papaya variety protection. Although there was a significant correlation between the qualitative and quantitative descriptor dissimilarity matrices (r = 0.43), the morpho-agronomic data were not highly correlated with the molecular data. Moreover, correlation between AFLP and ISSR dissimilarity matrices was nearly null (r = -0.01). Joint Gower analysis of all data showed high correlations, especially for AFLP markers, most likely due to the larger number of bands, generating a strong bias in the diversity estimates. The Average-Joint Gower analysis allowed a better balance between the correlations for the continuous and the discrete variables. The results generated by clustering analysis distinguished 5 genetically distinct groups. While we found that papaya genotypes are significantly variable for many traits, we observed that Average-Joint Gower analysis allowed for genotype clustering based on the most widely used criterion for classifying papaya genotypes, which is fruit type ('Formosa' or 'Solo'). This information helps provide an accurate estimate of the genetic diversity and structure of papaya germplasm, which will be used for further breeding strategies.