Determination of Markers Associated with Important Agronomic Traits of Watermelon (Citrullus lanatus L.)
Journal of Agricultural Science and Technology, vol.26, no.6, pp.1359-1371, 2024 (SCI-Expanded, Scopus)
- Publication Type: Article / Article
- Volume: 26 Issue: 6
- Publication Date: 2024
- Doi Number: 10.22034/jast.26.6.1359
- Journal Name: Journal of Agricultural Science and Technology
- Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, CAB Abstracts, Food Science & Technology Abstracts, Veterinary Science Database
- Page Numbers: pp.1359-1371
- Keywords: Association mapping, ISSR, iPBS, SSR, Sugar parameters
- Erciyes University Affiliated: Yes
Abstract
Association analysis using phenotypic information and molecular markers may provide valuable information for molecular breeding and marker-assisted selection. The objectives of this study were to determine markers associated with sugar parameters and important agronomic traits of watermelon and to estimate the level of genetic diversity. Ninety-six watermelon lines were genotyped by combining SSR (Simple Sequence Repeat), ISSR (Inter-Simple Sequence Repeat) and iPBS (Inter-Priming Binding Sites) marker data. These genotypes were also assessed for population structure, Linkage Disequilibrium (LD), and Association Mapping (AM) of sugar parameters and other important agronomic traits. In the analysis, 583 markers had LD values to a certain degree. A general linear model was developed using only the Q matrix showing the population structure in association mapping, a complex linear model using a kinship matrix, and a complex linear model using both the Q and K matrix linear models. The regression model explanation rates for the 26 characters varied from 11.3 to 81.3%. The highest rates of regression model explanation were measured for fruit firmness (81.3%) and fruit height (78.2%). It might be possible to determine the genes associated with these studied characteristics, to contribute to future genetic and breeding studies, and to be used in Marker-Assisted Selection (MAS) studies.