The effect of genomic accuracy on interaction between genotype and environment

Today, thanks to availability of genomic markers and pedigree data, it is possible to investigate (G × E) interaction more than last decades. Therefore, the aim of this study was to evaluate different animal models and genomic scenarios in order to estimate breeding value and genotype × environment (G × E) interaction. Genomic data were simulated to survey variation in QTL number (۲۰۰ and ۴۰۰) and linkage disequilibrium (low and high) using ۲۰K SNP panel for ۵۰ chromosomes. The QMSim software was used for simulation and creation of population. Three levels of heritability (۰.۰۵, ۰.۲۵ and ۰.۴۵) were used respectively as low, medium and high levels. Then, low (۰.۲۵) and high (۰.۷۵) genetic correlations were created between third environments. Results showed that the accuracy of genomic prediction increased with heightening the amount of heritability, linkage disequilibrium and the genetic correlation between the traits. Compared with single trait animal model, multi trait animal model resulted in higher accuracy of genomic prediction. Surprisingly, the highest accuracy (۰.۴۴) obtained from the scenario with high linkage disequilibrium and low QTL. Simultaneously, accuracies of genomic prediction increased with higher percentage of animals from ۱۵ to ۸۵. On the other hand, LD level, type of animals in training set, number of phenotypic records in validation set and genetic correlation among different environments were important factors if there was an interaction G × E. In conclusion, G × E interaction can be used for identifying variation of quantitative traits and more accurate genomic selection.

کلیدواژه ها:

accuracy ، heritability ، linkage ، prediction ، simulation