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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., (© 2024. The Author(s), under exclusive licence to Springer Nature B.V.)

Background: Rosewood (Aniba rosaeodora Ducke), which has a great demand due to its essential oil globally, is an evergreen tree of the Amazon forests. Rosewood natural stands have been depleted through deforestation and the destruction of habitat. Currently, rosewood is included in the ICUN red list of endangered species., Methods and Results: The 11 highly polymorphic primers amplified total 305 bands of which 301 (98.69%) were polymorphic. The number of effective alleles (Ne), Shannon's information index (I), overall gene diversity (Ht), gene diversity (h), and polymorphism information content (PIC) were (1.562), (0.505), (0.330), (0.337) and (0.343), respectively. These diversity indices explored high genetic diversity in rosewood germplasm. Among studied germplasm, the Santa Marta population was found most diverse by reflecting higher values of diversity indices while the Zungarococha population was found least diverse. The analysis of molecular variance (AMOVA) revealed that 79% of the genetic variation was within the populations. The STRUCTURE algorithm, unweighted pair group with arithmetic mean (UPGMA), and principal coordinate's analysis (PCoA) separated all germplasms into different population groups according to their geographic locations. Santa Marta population was found more diverse by reflecting higher values of diversity indices. The maximum genetic distance (0.868) was found between the Huajoya-10 and Nanay-3. In this investigation, iPBS- retrotransposon marker system was used to explore the genetic diversity of Peruvian rosewood germplasm., Conclusions: The results in this study such as higher genetic diversity indices, AMOVA (79%) within population and PIC value (0.343) showed the utility and reproducibility of iPBS-retrotransposons in this species successfully. The STRUCTURE algorithm separated the germplasms into six population groups according to their geographic locations. These results have valuable information for the conservation, management strategies and future breeding activities of rosewood., (© 2021. The Author(s), under exclusive licence to Springer Nature B.V.)

Cotton (Gossypium hirsutum L.) is a significant global crop and a vital raw material for industries. Studying existing cotton germplasm is crucial for discovering new genetic resources for future breeding. In this study, the effectiveness of EST-SSRs and ISSRs markers were compared for assessing genetic variation among 45 Pakistani Bt and non-Bt cotton varieties. ISSR and EST-SSR primers yielded 108 and 28 loci, respectively. The polymorphism was found 32.40% for ISSR, while 89.28% was recorded for SSR primers. Cluster analysis revealed a high level of genetic similarity for ISSR (average 0.92) and EST-SSR (average 0.85) among cotton genotypes. The mean polymorphic information content (PIC) value was 0.25 for ISSR, whereas it was recorded 0.48 for EST-SSRs. Confusion probability (Cj) exhibited a negative association with discriminating power (Dj), while Dj displayed a positive association with PIC. Marker discriminating statistics showed that EST-SSRs have a high expected heterozygosity of polymorphic loci (Hep) as compared to ISSR, along with a higher marker index value (MI). The effective multiplex ratio for ISSRs (1.40) was greater than EST-SSRs (1.12). The structural analysis revealed 6 sub-clusters for EST-SSRs and 4 sub-clusters for ISSRs. This phylogenetic study is crucial for identifying promising genotypes for breeding programs, especially given the limited genetic diversity in cotton breeding. The study showed that Bt cotton genotypes share a high genetic similarity, emphasizing the need for introducing diverse or exotic genotypes into breeding programs to enrich genetic diversity. Additionally, marker-discriminating indices can aid in selecting effective markers to assess genetic variation, facilitating the development of improved cotton varieties with desired traits. [ABSTRACT FROM AUTHOR]

Spring durum wheat occupies over 0.5 M ha in Kazakhstan and represents an important domestic and export commodity. This study aimed to characterize 151 durum wheat cultivars and advanced lines originating from eight breeding programs of the Kazakhstan–Siberia Spring Wheat Improvement Network (KASIB) between 2003 and 2018. The phenotypic characterization was performed in two contracting evaluation sites more than 1000 km apart (Almaty in the Southeast and Shortandy in the North) for two years and a total of 11 agronomic traits were recorded. Field trials at both locations followed regional agronomy practices, including sowing, harvesting, and genotype evaluation using a randomized complete block design (RCBD). The growing season was longer in Almaty, resulting in a higher number of grains per spike. Though grains are smaller in size with an overall higher yield, 243 g/m2 versus 170 g/m2, there was no correlation between germplasm performance at the two sites. Molecular characterization was performed with 10 iPBS-retrotransposons primers that resulted in a total of 345 bands and showed a mean polymorphism of 91.9%. Mean values of gene diversity (0.251), Shannon's information index (0.388), and expected heterozygosity (0.233) revealed a relatively high level of genetic diversity in the KASIB set. AMOVA revealed higher genetic variations due to differences within the populations. Marker-based cluster analysis, including STRUCTURE and neighbor-joining algorithms, divided the material into two populations with clear differences in geographic origin. Superiors and diverse germplasm identified in the study are recommended for marker assisted selection and breeding. [ABSTRACT FROM AUTHOR]