Bambang Supriyanta


Simulation study was done to evaluate QTL mapping and selection efficiency of molecular markers utilisation in the F2 population. The simulation study started with formulating genetic configuration which consists of chromosome maps and genetic models. Genetic model for diploid individuals is a model which consists two alleles for each locus. Genetic model that used is a mathematical model consists additive, dominance, and interactions with different effects at each locus, with maximum interaction occurs between two loci (digenic). QTL mapping was constructed by using single locus model, two loci model and multiple loci model. the effect of sample size, heritability, and marker density was observed. Three model was used to analyse QTL position, i.e. marker regression, interval mapping (IM) and composite interval mapping (CIM). Several parameters were specified in this study: genetic variability coefficient (GVC=15%), population mean (μ=10), epistasis and genetic variance ratio (f=0.1), dominance and additive variance ratio (r=0.25), the ratio of AA:AD:DD is 3:2:1 with additive and dominance gene action, and its interaction. The first and last marker were located at each edge of 150 cM chromosome for each chromosome. The interval distance between markers were equal. Haldane’s map function was used in this simulation. The simulation was performed by using the QTL Package on “R” software.  With a heritability 0.2, the required sample size to indicate the interval markers associated with QTL were 50 for single locus model. The level of selection efficiency using molecular markers was higher than the phenotypic screening on. Efficiency level of selection based on molecular markers (Em) is a function of the distance between the markers to QTL (d) which follows “reciprocal quadratic” function. Efficiency level of selection based on phenotype (Ef) is a function of heritability favourable traits which follows “reciprocal quadratic” function.

Keywords: efficiency, markers, QTL, simulation


efficiency, markers, QTL, simulation

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DOI: https://doi.org/10.31315/agrivet.v24i1.4661

DOI (PDF): https://doi.org/10.31315/agrivet.v24i1.4661.g3384


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