Association Mapping Study of Various Desirable Traits of Rice
Abstract
Background: This study was performed to evaluate the diversity of various morphological characters and their relationship with yield in rice. The goal of this work was to find quantitative trait loci (QTL) for yield, yield components, and other agronomic variables in 100 different rice germplasm samples, as well as to assess the genetic structure and degree of linkage disequilibrium in the rice germplasm diversity panel. To establish Linkage Disequilibrium (LD) between markers and causative mutations, marker density is essential. Linkage disequilibrium (LD) patterns of various SNP markers on all chromosomes. If markers are sufficiently dense to have good coverage of LD, the LD decay with distance can be compared to the marker density.
Methods: Different traits were measured and recorded under Randomized Complete Block Design (RCBD) experiment. DNA extraction and PCR analysis was done to measure the genotypic characteristics of rice. Genotypic and phenotypic variability was measured by using ANOVA and GWAS.
Results: For pair-wise markers, linkage disequilibrium is calculated as R square and plotted versus the distance between the markers. In this study, the overall phenotypic variability among the examined traits was represented by R2 and ranged from 11.47% to 25.44%. The genetic architecture of these traits may be implied by the recently identified genomic regions (loci). An influential replacement for bi-parental gene maps, genome-wide association studies (GWAS) use data from genome-wide markers in large amounts of easily obtained germplasm.
Conclusion: The linkage disequilibrium, which is the non-random link between an allele at two or more loci, is used in this mapping method to infer the innate relationships between phenotypic variations and marker polymorphisms. Genome Wide Association Study (GWAS) of genotypes provides the information about for the selection of genotypes and determination of new marker trait association.
Keywords: Oryza sativa L; Rice; DNA; Association mapping; Traits
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DOI: http://dx.doi.org/10.62940/als.v10i2.1708
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