Background
Genetic analysis of gladiolus germplasm using simple sequence repeat (SSR) markers is largely missing due to scarce genomic information. Hence, microsatellites identified for related genera or species may be utilized to understand the genetic diversity and assess genetic relationships among cultivated gladiolus varieties.
Conclusion
SSR markers from the present study can be utilized for cultivar identification, conservation and sustainable utilization of gladiolus genotypes for crop improvement. Genetic relationships assessed among the genotypes of respective clusters may assist the breeders in selecting desirable parents for crossing.
Methods
In the present investigation, we screened 26 genomic SSRs (Gladiolus palustris, Crocus sativus, Herbertia zebrina, Sysirinchium micranthum), 14 chloroplast SSRs (Gladiolus spp., chloroplast DNA regions) and 25 Iris Expressed Sequence Tags (ESTs) derived SSRs across the 84 gladiolus (Gladiolus × grandiflorus L.) genotypes. Polymorphic markers detected from amplified SSRs were used to calculate genetic diversity estimates, analyze population structure, cluster analysis and principal coordinate analysis (PCoA).
Results
A total of 41 SSRs showed reproducible amplification pattern among the selected gladiolus cultivars. Among these, 17 highly polymorphic SSRs revealed a total of 58 polymorphic alleles ranging from two to six with an average of 3.41 alleles per marker. Polymorphic information content (PIC) values ranged from 0.11 to 0.71 with an average value of 0.48. A total of 4 SSRs were selectively neutral based on the Ewens-Watterson test. Hence, 66.66% of Gladiolus palustris, 48% of Iris spp. EST, 71.42% of Crocus sativus SSRs showed cross-transferability among the gladiolus genotypes. Analysis of genetic structure of 84 gladiolus genotypes revealed two subpopulations; 35 genotypes were assigned to subpopulation 1, 37 to subpopulation 2 and the remaining 12 genotypes could not be attributed to either subpopulation. Analysis of molecular variance indicated maximum variance (53.59%) among individuals within subpopulations, whereas 36.55% of variation among individuals within the total population. The least variation (9.86%) was noticed between two subpopulations. Moderate (FST = 0.10) genetic differentiation between two subpopulations was observed. The grouping pattern of population structure was consistent with the unweighted pair group method with arithmetic mean (UPGMA) dendrogram based on simple matching dissimilarity coefficient and PCoA.