QTL detection in multi-breed cattle populations including crossbred animals: a simulation study

Area of Science:

• Animal Genetics
• Quantitative Genetics
• Genomic Prediction

Background:

• Identifying causal variants and quantitative trait loci (QTL) is crucial for animal breeding.
• Existing methods often struggle with multi-breed and crossbred populations due to linkage disequilibrium phase variations.

Purpose of the Study:

• To introduce a novel method, breed origin of alleles (BOA), for analyzing purebred (PB) and crossbred (XB) animal data together.
• To assess BOA's performance against conventional methods in identifying QTL across diverse breed compositions.

Main Methods:

• Developed the breed origin of alleles (BOA) method, allowing correlated QTL effects across breeds.
• Compared BOA (PB+XB_BOA) with individual purebred analysis (PB_SINGLE) and joint analysis without BOA (PB+XB_JOINT) using simulations.
• Evaluated methods based on true positives, power of detection, false positive rate, and positive predictive value.

Main Results:

• PB_SINGLE analysis showed the lowest QTL detection ability, particularly in smaller breeds.
• Joint analysis (PB+XB_JOINT) improved QTL detection compared to PB_SINGLE.
• The proposed BOA method (PB+XB_BOA) outperformed both PB_SINGLE and PB+XB_JOINT, yielding more QTL, higher detection power, and better positive predictive value with narrower peaks.

Conclusions:

• The BOA methodology is superior for identifying genomic regions of interest in mixed purebred and crossbred populations.
• BOA effectively handles variations in linkage disequilibrium phase across breeds.
• This approach enhances the accuracy and power of genomic selection in complex multi-breed scenarios.