Effect of Selection on the Accuracy of Genomic Selection and Genome-Wide Association Analysis

Subject Areas :

A.A. Shadparvar ¹ , N. Ghavi Hossein-Zadeh ² , Z. Lotfi ³ , Z. Lotfi ^{4 *}

1 - Department of Animal Science, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran
2 - Department of Animal Science, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran
3 - Department of Animal Science, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran
4 - Department of Animal Science, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran

Received: 2024-11-01 Accepted : 2025-06-11 Published : 2025-06-30

Keywords: accuracy, genome-wide association, genomic selection, quantitative trait locus, reference population, simulation, validation population,

Abstract :

Several factors, such as trait heritability, marker density, distance between individuals in the reference population and selection candidates, as well as the number of phenotypic records in the reference popula-tion dataset, significantly affect the accuracy of genomic evaluation. The objective of the present study was to evaluate the effect of selection on the accuracy of genomic selection and genome-wide association analy-sis. Four selection schemes were considered: 1) no selection in both reference and validation populations. 2) selection in the reference population based on the estimated accuracy of estimated breeding values of 0.7, while no selection was applied in the validation population. 3) selection in both the reference and validation populations, comparable to scheme 2. 4) selection in both populations similar to that of scheme 3, however, the selection was done in the validation population with an accuracy of 0.5. In each scenario, a reference population and a validation population were randomly simulated using QMSim. The results indicated that the comparison of accuracy levels between the reference and validation populations showed higher accu-racy in the reference population for all schemes, heritabilities, numbers of markers, and QTL numbers. The highest genomic evaluation accuracy for both populations was achieved in scheme 1. Results suggested that the correlation coefficient between genomic evaluation accuracy in the reference and validation populations was related to the number of common single nucleotide polymorphisms (SNPs) between the reference and validation populations. Selection in the reference population led to a significant reduction in the number of markers.

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