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    Applicability of SCoT markers in unraveling genetic variation and population structure among sugar beet (Beta vulgaris L.) germplasm
    (Springer Science and Business Media B.V., 2024) Yalınkılıç, Nazlı Aybar; Başbağ, Sema; Altaf, Muhammad Tanveer; Ali, Amjad; Nadeem, Muhammad Azhar; Baloch, Faheem Shahzad
    Background Sugar beet (Beta vulgaris L.) holds significant importance as a crop globally cultivated for sugar production. The genetic diversity present in sugar beet accessions plays a crucial role in crop improvement programs. Methods and results During the present study, we collected 96 sugar beet accessions from different regions and extracted DNA from their leaves. Genomic DNA was amplified using SCoT primers, and the resulting fragments were separated by gel electrophoresis. The data were analyzed using various genetic diversity indices, and constructed a population STRUCTURE, applied the unweighted pair-group method with arithmetic mean (UPGMA), and conducted Principle Coordinate Analysis (PCoA). The results revealed a high level of genetic diversity among the sugar beet accessions, with 265 bands produced by the 10 SCoT primers used. The percentage of polymorphic bands was 97.60%, indicating substantial genetic variation. The study uncovered significant genetic variation, leading to higher values for overall gene diversity (0.21), genetic distance (0.517), number of effective alleles (1.36), Shannon’s information index (0.33), and polymorphism information contents (0.239). The analysis of molecular variance suggested a considerable amount of genetic variation, with 89% existing within the population. Using STRUCTURE and UPGMA analysis, the sugar beet germplasm was divided into two major populations. Structure analysis partitioned the germplasm based on the origin and domestication history of sugar beet, resulting in neighboring countries clustering together. Conclusion The utilization of SCoT markers unveiled a noteworthy degree of genetic variation within the sugar beet germplasm in this study. These findings can be used in future breeding programs with the objective of enhancing both sugar beet yield and quality.
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    Exploring the genetic diversity and population structure of upland cotton germplasm by iPBS-retrotransposons markers
    (Springer Science and Business Media, 2023) Baran, Nurettin; Shimira, Flavien; Nadeem, Muhammad Azhar; Altaf, Muhammad Tanveer; Andırman, Mehtap; Baloch, Faheem Shehzad; Temiz, Mefhar Gültekin
    Background: Upland cotton is one of the utmost significant strategic fiber crops, and play a vital role in the global textile industry. Methods and results: A total of 128 genotypes comprised Gossypium hirsutum L, Gossypium barbadense L., and pure lines were used to examine genetic diversity using iPBS-retrotransposon markers system. Eleven highly polymorphic primers yielded 287 bands and 99.65% polymorphism was recorded. The mean polymorphism information content was estimated at 0.297 and the average diversity indices for the effective number of alleles, Shannon’s information index, and overall gene diversity were 1.481, 0.443, and 0.265, respectively. The analysis of molecular variance (AMOVA) revealed that 69% of the genetic variation was within the population. A model-based STRUCTURE algorithm divided the entire germplasm into four populations and one un-classified population, the genotypes G42 (originating in Egypt) and G128 (originating in the United States), showed the highest genetic distance (0.996) so these genotypes could be suggested for breeding programs as parental lines. Conclusions: This is the first investigation using an iPBS-retrotransposon marker system to examine the genetic diversity and population structure of upland cotton germplasm. The rich diversity found in upland cotton germplasm could be exploited as a genetic resource when developing breeding programs and could also help with efforts to breed cotton around the world. These findings also show the applicability and effectiveness of iPBS-retrotransposons for the molecular characterization of cotton germplasm.