Genetic Diversity and Population Structure of 72 Turkish Ficus carica (L.) Genotypes Assessed Using SCoT Markers.

Authors

Meliha Feryal Sarıkaya, Muhammad Azhar Nadeem, Sarmad Ali Qureshi, Mehmet Bedir, Muhammed Tatar, Amjad Ali, Muhammad Tanveer Altaf, Viyan Acar Uçer, Kağan Kökten, Erdal Aglar, Faheem Shehzad Baloch

Published in

Biochemical genetics. Jun 25, 2026. Epub Jun 25, 2026.

Abstract

Ficus carica L. is an economically important fruit crop widely cultivated in the Mediterranean region. In this study, genetic diversity and population structure were investigated in 72 F. carica genotypes collected from the Derecik and Çukurca regions of Hakkâri province, Türkiye, using 15 highly polymorphic Start Codon Targeted (SCoT) markers. A total of 481 amplification bands were obtained, of which 475 were polymorphic, resulting in a high average polymorphism rate of 98.60%. Genetic diversity indices indicated substantial variation among the genotypes, with a mean effective number of alleles of 1.53, gene diversity of 0.31, and Shannon information index of 0.47. The average genetic distance among genotypes was 0.37, with the highest pairwise distance (0.721) observed between genotypes HC4 and HD7. Analysis of molecular variance (AMOVA) revealed that most genetic variation was distributed within populations (93%), whereas only 7% was among populations. Bayesian STRUCTURE analysis identified two distinct genetic clusters corresponding largely to geographic origin, with 22 genotypes (30.56%) classified as admixed based on a membership coefficient threshold of < 0.70. Principal coordinate analysis (PcoA) clearly separated genotypes according to their sampling locations, where Axis 1 and Axis 2 explained 24.31% and 15.07% of the total genetic variation, respectively. Overall, these findings demonstrate the effectiveness of SCoT markers in assessing genetic diversity and population structure in F. carica germplasm from southeastern Türkiye. Future studies should use codominant markers (SSRs and SNPs) expand geographic sampling, and adopt open data repositories to enhance conservation and breeding strategies.

PMID:
42348125
Bibliographic data and abstract were imported from PubMed on 25 Jun 2026.

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