Investigating the genetic variation of selected genotypes of Rosa damascena grown in rain-fed conditions using molecular markers

Background and Objectives: Genetic and environmental factors continuously shape the genetic structure of plant populations, generating valuable diversity that can be exploited in plant breeding programs. Accurate assessment of genetic diversity is essential for the efficient selection of parental genotypes and the development of improved varieties. Although morphological traits have traditionally been used to evaluate genetic variation, their application has become increasingly limited because they are strongly influenced by environmental conditions and developmental stages. Consequently, molecular markers are now widely employed alongside morphological traits to provide a more reliable assessment of genetic diversity. Rosa damascena Mill. is one of the most economically important aromatic and medicinal plants, extensively utilized in the food, pharmaceutical, perfumery, and cosmetic industries. Therefore, the development of cultivars adapted to diverse climatic conditions is of considerable importance. The present study was conducted to investigate the genetic diversity of selected R. damascena genotypes using Start Codon Targeted (SCoT) molecular markers and to compare the molecular classification with grouping based on agronomic performance under rain-fed conditions.
Materials and Methods: The genetic diversity of 12 R. damascena genotypes was evaluated using SCoT molecular markers. The plant materials consisted of seven elite genotypes previously selected based on plant height, flower yield, and flower essential oil content under rain-fed conditions, together with five additional genotypes collected from East and West Azerbaijan provinces of Iran. Young leaf samples were collected, and genomic DNA was extracted using a modified CTAB protocol. Polymerase chain reaction (PCR) amplification was performed using 29 SCoT primers, and the amplified DNA fragments were separated by electrophoresis on 5% polyacrylamide gels. Banding patterns were scored as presence (1) or absence (0). Polymorphic information content (PIC), effective multiplex ratio (EMR), and marker index (MI) were calculated using Microsoft Excel. Genetic diversity parameters, including the number of effective alleles (Ne), Shannon’s information index (I), expected heterozygosity (He), and unbiased expected heterozygosity (uHe), together with principal coordinate analysis (PCoA), were estimated using GenAlEx software. Jaccard’s similarity coefficients and cluster analysis were calculated using NTSYS software. In addition, hierarchical clustering based on agronomic traits measured under rain-fed conditions was performed and compared with the clustering obtained from molecular marker data.
Results: Among the 29 SCoT primers evaluated, 13 generated clear and reproducible amplification products. A total of 88 polymorphic alleles were detected across the 12 R. damascena genotypes. Primer SCoT12 produced the highest number of polymorphic alleles (17), whereas primers SCoT46 and SCoT61 each generated only two polymorphic alleles. On average, 6.76 polymorphic alleles were detected per informative primer. Cluster analysis based on Jaccard’s similarity coefficient and the UPGMA algorithm grouped the 12 genotypes into four major clusters at a similarity coefficient of 0.71. Cluster I included genotypes G40, G28, G8, G35, G29, and G6; Cluster II contained genotype G21; Cluster III comprised genotypes GA1 and GA2; and Cluster IV consisted of genotypes GA3, GA4, and GA5. Principal coordinate analysis supported the clustering pattern obtained from the similarity matrix. Based on agronomic traits, including plant height, flower yield, and flower essential oil content, the seven elite rain-fed genotypes were classified into three major groups. Cluster I contained genotypes G6, G8, and G35; Cluster II included genotypes G21, G28, and G29; whereas Cluster III consisted solely of genotype G40.
Conclusion: The results demonstrated substantial genetic divergence between the genotypes maintained at the Research Institute of Forests and Rangelands and those collected from East and West Azerbaijan provinces, suggesting that these materials do not share a recent common genetic origin. Comparison of the clustering patterns derived from SCoT molecular markers and agronomic traits revealed a moderate level of agreement between the two approaches. These findings indicate that combining molecular markers with phenotypic evaluation provides a more comprehensive assessment of genetic diversity and can facilitate the identification of suitable parental genotypes for future Rosa damascena breeding programs under rain-fed conditions.