Marker genotyping error effects on genomic predictions under different genetic architectures

Area of Science:

• Quantitative Genetics
• Animal Breeding
• Genomics

Background:

• Genomic prediction utilizes marker information to estimate breeding values.
• Marker genotyping errors can potentially impact the accuracy of these predictions.
• Understanding the extent of this impact is vital for effective genomic selection.

Purpose of the Study:

• To investigate the influence of varying marker genotyping error rates on genomic prediction accuracy.
• To assess the effect of marker density, quantitative trait loci (QTL) density, and heritability on this relationship.
• To evaluate the bias introduced by genotyping errors in genomic evaluation.

Main Methods:

• A stochastic simulation approach was employed.
• Reference and validation populations were simulated with phenotypic and genotypic data.
• Genomic breeding values were predicted, and accuracy was assessed via correlation and bias via regression coefficients.

Main Results:

• Genomic evaluation accuracy was highest with no marker genotyping error (0.731–0.934).
• Accuracy decreased substantially with 20% marker genotyping error (0.517–0.762).
• Unbiased estimates were obtained only when marker genotyping error was zero.

Conclusions:

• Marker genotyping errors demonstrably reduce genomic prediction accuracy.
• These errors can lead to biased estimates of genomic breeding values.
• Minimizing marker genotyping errors to zero is essential for accurate genomic evaluation programs.