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Background <p>In cattle, most commercial single-nucleotide polymorphism (SNP) genotyping arrays have been shown to be suboptimal for capturing genomic variation in non-European populations, particularly in African cattle. Low-coverage whole-genome sequencing (LCWGS) followed by imputation provides a cost-effective method for genotyping that is more adaptable and can outperform genotyping arrays.</p> Results <p>Here, we generate a high-quality reference imputation panel representative of the complex ancestries of cattle populations in Africa to enable the deployment of LCWGS. To do so, we generated 116 high-coverage (between 20‒24×) new African cattle genomes, representing most cattle breeds across the continent. We combined this data with publicly available genomes from other regions to build a reference panel that comprised over 3,300 cattle genomes from 133 cattle populations, thus capturing the genetic diversity of domestic cattle across the world. After applying a high filtering step to remove poor genome sequences with very low sequence coverage, we retained 1,882 with an average coverage of 7×. We show that the imputation pipeline implemented, based on this reference panel, provides highly accurate genotypes of common (&gt; 99% accuracy) and rare (&gt; 98% accuracy) variants in genome coverage as low as 0.5×.</p> Conclusion <p>This panel provides an important new resource for genetic improvement and conservation of African cattle populations.</p>

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Accurate imputation of African cattle genomes using a diverse reference panel

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月6日

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  • Said I. Ng’ang’a,
  • James A. Ward,
  • Stephen J. Rossiter,
  • Chris G. Faulkes,
  • Katia Bougiouri,
  • Gillian P. McHugo,
  • Fenton P. D. Cotterill,
  • Atunga Nyachieo,
  • Olaf Thalmann,
  • Ivica Medugorac,
  • Stefan Krebs,
  • Tad S. Sonstegard,
  • Olivier Hanotte,
  • Daniel G. Bradley,
  • Gary Vaughan-Smith,
  • David E. MacHugh,
  • Laurent A.F. Frantz

摘要

Background

In cattle, most commercial single-nucleotide polymorphism (SNP) genotyping arrays have been shown to be suboptimal for capturing genomic variation in non-European populations, particularly in African cattle. Low-coverage whole-genome sequencing (LCWGS) followed by imputation provides a cost-effective method for genotyping that is more adaptable and can outperform genotyping arrays.

Results

Here, we generate a high-quality reference imputation panel representative of the complex ancestries of cattle populations in Africa to enable the deployment of LCWGS. To do so, we generated 116 high-coverage (between 20‒24×) new African cattle genomes, representing most cattle breeds across the continent. We combined this data with publicly available genomes from other regions to build a reference panel that comprised over 3,300 cattle genomes from 133 cattle populations, thus capturing the genetic diversity of domestic cattle across the world. After applying a high filtering step to remove poor genome sequences with very low sequence coverage, we retained 1,882 with an average coverage of 7×. We show that the imputation pipeline implemented, based on this reference panel, provides highly accurate genotypes of common (> 99% accuracy) and rare (> 98% accuracy) variants in genome coverage as low as 0.5×.

Conclusion

This panel provides an important new resource for genetic improvement and conservation of African cattle populations.