Accurate imputation of African cattle genomes using a diverse reference panel

Area of Science:

• Genomics
• Animal Science
• Bioinformatics

Background:

• Genotyping arrays are suboptimal for African cattle genetic diversity.
• Low-coverage whole-genome sequencing (LCWGS) with imputation offers a cost-effective alternative.
• Genomic variation in African cattle is complex and underrepresented.

Purpose of the Study:

• To develop a high-quality imputation panel for African cattle.
• To enable accurate genotyping using LCWGS in diverse cattle populations.
• To support genetic improvement and conservation of African cattle.

Main Methods:

• Generated 116 high-coverage African cattle genomes.
• Combined data with public genomes to create a 3,300+ genome reference panel.
• Applied stringent filtering to retain 1,882 high-quality genomes for imputation.

Main Results:

• The imputation panel accurately genotypes common (>99%) and rare (>98%) variants.
• High accuracy is achieved even with low genome coverage (0.5×).
• The developed pipeline is effective for diverse cattle populations.

Conclusions:

• The reference panel is a valuable resource for African cattle genomics.
• Facilitates genetic improvement and conservation strategies.
• Enhances the utility of LCWGS for global cattle populations.