Browsing by Author "Cavagnaro, Pablo Federico"

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Application of Ipbs-Retrotransposons Markers for the Assessment of Genetic Diversity and Population Structure Among Sugar Beet (Beta Vulgaris) Germplasm From Different Regions of the World
(Springer, 2025) Sadik, Gokhan; Yildiz, Mehtap; Taskin, Bilgin; Kocak, Metin; Cavagnaro, Pablo Federico; Baloch, Faheem Shehzad
Sugar beet is an important agricultural crop product that has been produced and consumed worldwide since the eighteenth century and can adapt to various climatic and soil conditions. The two fundamental building blocks of any crop improvement program are germplasm resources, which contain genetic diversity and phenotypic expression of desired traits. In this study, a total of 58 sugar beet genotypes including 12 from Turkey, 4 from India, 12 from the United States of America, 16 from Iran, 12 from England and Beta vulgaris L. subsp. maritima L. Arcang. as wild species were characterized using 15 inter-primer binding site (iPBS) markers that produced intense and polymorphic bands in the germplasm library. Using these 15 iPBS markers, 102 polymorphic bands were produced and the average number of polymorphic bands was determined as 6.8. Polymorphism information content (PIC) values ranged between 0.58 and 0.83, and the average PIC value was found to be 0.70. It was determined that the most genetically different genotypes were PI 590697-US11 and PI 171508-TR8, with a distance of 0.73. Clustering algorithms Unweighted Pair Group Method Algorithm (UPGMA) and Principal Coordinate Algorithm (PCoA) confirmed that genotypes are an important factor in clustering, and STRUCTURE analysis divided sugar beet gene resources into six populations. Also, the analysis of molecular variance (AMOVA) showed that there was 8% variance among populations and 92% variance within populations. This is the first study to investigate the genetic diversity and population structure of sugar beet germplasm using the iPBS-retrotransposon marker system. The results of this research emphasized that iPBS markers are very successful and effective in examining the genetic diversity of sugar beet germplasm. The results obtained in this study provide a theoretical basis for future selection and breeding of superior sugar beet germplasm sources.
Characterization of a Diverse Okra (Abelmoschus Esculentus L. Moench) Germplasm Collection Based on Fruit Quality Traits
(Mdpi, 2025) Yildiz, Mehtap; Sirke, Sibel Turan; Kocak, Metin; Mancak, Ibrahim; Ozkaya, Aslihan Agar; Abak, Kazim; Cavagnaro, Pablo Federico
Okra is an important dietary component of many Asian countries, providing high levels of dietary fiber, phytonutrients (e.g., antioxidant vitamins and pigments), and essential minerals. Evaluation of okra germplasm collections can improve the curation of genebanks and help identify superior materials for breeding. In this study, 66 okra accessions from diverse geographical origins were characterized based on fruit quality traits, including fruit fresh (FFW) and dry weights (FDW), dry matter (DM), diameter, length, and diameter of the fruit peduncle; concentration of vitamin C, chlorophyll a and b, and total chlorophyll; and color-chroma values. Significant (p < 0.05) and substantial variation was found among the accessions for all traits. Mean FFW and FDW varied nearly three-fold, with ranges of 3.76-9.99 g and 0.43-1.34 g, respectively, with a range in DM content of 10.5-19.4%. Vitamin C and total chlorophyll content varied 6.4- and 8.3-fold, with ranges of 12.8-82.8 and 1.07-8.91 mg/100 g fw, respectively, with substantial variation also observed in chlorophyll composition. Significant positive correlations were found between vitamin C and total and subtypes of chlorophyll levels (r = 0.29-0.32), whereas the strongest correlations were between FFW and FDW (r = 0.88) and between total chlorophyll and chlorophyll subtypes a and b (r = 0.90-0.95). Additionally, a dendrogram constructed based on these phenotypic data grouped the accessions in general agreement with their geographical origins and fruit traits. Overall, our results revealed broad phenotypic diversity in the evaluated germplasm, which is exploitable in okra breeding programs aimed at increasing fruit quality and nutraceutical value.
Correction: Population Structure, Genetic Diversity, and GWAS Analyses with GBS-Derived SNPs and Silicodart Markers Unveil Genetic Potential for Breeding and Candidate Genes for Agronomic and Root Quality Traits in an International Sugar Beet Germplasm Collection
(BMC, 2025) Bahjat, Noor Maiwan; Yildiz, Mehtap; Nadeem, Muhammad Azhar; Morales, Andres; Wohlfeiler, Josefina; Baloch, Faheem Shahzad; Cavagnaro, Pablo Federico
Population Structure, Genetic Diversity, and GWAS Analyses With GBS-Derived SNPs and Silicodart Markers Unveil Genetic Potential for Breeding and Candidate Genes for Agronomic and Root Quality Traits in an International Sugar Beet Germplasm Collection
(Bmc, 2025) Bahjat, Noor Maiwan; Yildiz, Mehtap; Nadeem, Muhammad Azhar; Morales, Andres; Wohlfeiler, Josefina; Baloch, Faheem Shahzad; Cavagnaro, Pablo Federico
BackgroundKnowledge about the degree of genetic diversity and population structure is crucial as it facilitates novel variations that can be used in breeding programs. Similarly, genome-wide association studies (GWAS) can reveal candidate genes controlling traits of interest. Sugar beet is a major industrial crops worldwide, generating 20% of the world's total sugar production. In this work, using genotyping by sequencing (GBS)-derived SNP and silicoDArT markers, we present new insights into the genetic structure and level of genetic diversity in an international sugar beet germplasm (94 accessions from 16 countries). We also performed GWAS to identify candidate genes for agriculturally-relevant traits.ResultsAfter applying various filtering criteria, a total of 4,609 high-quality non-redundant SNPs and 6,950 silicoDArT markers were used for genetic analyses. Calculation of various diversity indices using the SNP (e.g., mean gene diversity: 0.31, MAF: 0.22) and silicoDArT (mean gene diversity: 0.21, MAF: 0.12) data sets revealed the existence of a good level of conserved genetic diversity. Cluster analysis by UPGMA revealed three and two distinct clusters for SNP and DArT data, respectively, with accessions being grouped in general agreement with their geographical origins and their tap root color. Coincidently, structure analysis indicated three (K = 3) and two (K = 2) subpopulations for SNP and DArT data, respectively, with accessions in each subpopulation sharing similar geographic origins and root color; and comparable clustering patterns were also found by principal component analysis. GWAS on 13 root and leaf phenotypic traits allowed the identification of 35 significant marker-trait associations for nine traits and, based on predicted functions of the genes in the genomic regions surrounding the significant markers, 25 candidate genes were identified for four root (fresh weight, width, length, and color) and three leaf traits (shape, blade color, and veins color).ConclusionsThe present work unveiled conserved genetic diversity-evidenced both genetically (by SNP and silicoDArT markers) and phenotypically- exploitable in breeding programs and germplasm curation of sugar beet. Results from GWAS and candidate gene analyses provide a frame work for future studies aiming at deciphering the genetic basis underlying relevant traits for sugar beet and related crop types within Beta vulgaris subsp. vulgaris.