Effect of the Accuracy of Estimated QTL Effect on Marker Assisted Selection Response Considering the Dominance Deviation

Document Type : Genetics & breeding

Authors

• Mojtaba Tahmoorespur ¹
• nasiredin moghadar ²

¹ Department of Animal Sciences, Faculty of Agriculture, Ferdowsi University of Mashhad, Mashhad, Iran

² University of New England, Armidale, Australia

10.22067/ijasr.v9i3.36829

Abstract

Introduction During years genetic improvement of economically important traits, which are amongst polygenic traits, has been based on the estimation of breeding values i.e. the total heritable effects of genes, based on pedigree and phenotypic records. This approach had limitations such as being time consuming and demanding massive phenotypic information. Nowadays, high throughput genomic technologies are available that provide genotypes of dense markers across genome towards estimating breeding values more accurately. Accurate estimation of allelic and genotypic effects of markers in linkage with QTLs needs a lot of phenotypic observations which is not always available in practice. Therefore, the amount of error of estimated QTL effect could be high. Further, the distribution of the effects of genes controlling traits might be non-non-normal. In case of overlooking these facts, the predicted genetic progress can be erroneous. The objective of this study was to find the influence of the accuracy of QTL effect estimation, considering the dominance deviation, on marker assisted selection response.
Materials and Methods A base population of 1000 unrelated, non-inbred individuals was simulated according to a trait with heritability of 0.1 and 0.3. The trait was affected by residual polygenic and QTL with additive effect associated with 0.0, 0.1 and 0.2 standard errors and complete or incomplete dominance effect. The genotypic effects of the three QTL genotypes were a, d and –a, respectively for dominant homozygotes, heterozygotes and recessive homozygotes. The QTL had two alleles and the dominance deviation was considered either equal to or half of the genotypic effect a. The population was in Hardy-Weinberg equilibrium. The polygenic variance was calculated as the difference between total additive genetic variance and QTL variance. Residual variance was equal to the difference between phenotypic variance and total additive genetic variance. Two selection was employed; one with polygenes and marker information, and the other one with polygenic variance without marker information. The difference between mean of selected group and the population mean was considered as response to selection. The selection response calculated by truncation selection based on the performance of top 20% with and without using QTL information over 500 repetitions.
Results and Discussion The results showed higher response for marker assisted selection compared to conventional selection without marker information, but it also showed the presence of dominance effect for QTL effect associated with estimation errors leads to decrease in marker assisted selection response. The superiority of genetic progress with marker assisted selection is proportional to the QTL variance contributing to the total genetic variance. Increasing standard error of QTL effect to 10 and 20 percent, led to lower genetic response to selection. When the contribution of QTL variance in total genetic variance is higher, with high levels of standard error of QTL effect, the response to selection was even lower than response to selection without marker information. Complete dominance further decreased the genetic response compared to incomplete dominance. This is because the genetic variance is more influenced by the dominance variance in case of complete dominance.
Conclusion This study showed that QTL information may be used in practical selection programs when estimated parameters are of high accuracy to be used in practical selection programs. Estimating QTL effects with error causes that selection response would be even lower than polygenic selection if the associated error rate is high. Estimated effects of genes controlling quantitative traits should have less error rate in order to be used in breeding programs.

Keywords

• Dominance deviation
• Marker assisted selection
• QTL

20.1001.1.20083106.1396.9.3.4.4

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