Identification of Genetic Diversity Using Morphological Properties and Self-Incompatibility Alleles in Selected Prunus dulcisMiller (D.A. Webb) Genotypes

Autor: Pınar, Hasan, Yıldız, Ercan, Bircan, Mustafa, Uzun, Aydın
Zdroj: Erwerbs-Obstbau; 20230101, Issue: Preprints p1-8, 8p
Abstrakt: In this study, 48 almond (Prunus dulcisMiller [D.A. Webb]) genotypes were analyzed in terms of detailed morphological parameters. On the other hand, the incompatibility S genotypes in these genotypes were determined using a polymerase chain reaction (PCR) approach with allele-specific primers. High morphological diversity among the genotypes was observed. Most of the total variation (71.94%) in the seven phenological and five morphological traits consisted of the first three main principal components (PCs). The all-important traits ensured a positive value, but leaf colour had a negative value for the first three PCs. On the other hand, foliation time and petiole length showed low variation among the studied genotypes. According to the results of PCR using the AS1II- and AmyC5R-specific primers in a single reaction, the amplification was successful. The results showed amplification of nine different self-incompatibility alleles (S1, S2, S3, S5, S6, S10, S11, S12 and S13) and of the self-compatibility allele Sf. The PCR-amplified fragments ranged from 600 to 1600 bp. The self-compatibility allele Sf and S3 allele had the same band size at 1200 bp. The number of self-compatible genotypes was 12, including ‘Marta’, ‘F. Barese’, ‘Tuono’ and ‘Super Nova’ cultivars. S1, S2, S5 and S6 were the most common alleles, as each was found in almond genotypes assayed here. The least common alleles were S10, S11, S12 and S13 alleles, and especially S10 was determined only in ‘Dokuzoguz’ cultivar. The PCR approach is an easy, low-cost tool for early identification of self-compatible progeny seedlings. From these results, it could be concluded that these local genotypes might be considered as potential candidates to be used in breeding programs.
Databáze: Supplemental Index