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February 2, 2026Nature Communications0 citationsOpen Access

Phased-assembly-driven pangenome graphs for structural variant genotyping and complex trait mapping in dairy cattle

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LYLiu YangYGYahui GaoKKKristen L. Kuhn

Key Points

  • The study aims to utilize a Holstein-specific pangenome graph for improved genotyping of structural variants and mapping of complex traits.
  • Developed a breed-specific pangenome graph (H20D) using phased haploid assemblies from 20 Holstein cows.
  • Compared performance of H20D to existing assembly- and read-based methods.
  • Genotyped structural variants in 173 cattle using H20D.
  • Conducted a genome-wide association study (GWAS) to identify significant variants.
  • H20D identified over 10,000 additional structural variants per sample compared to previous methods.
  • Significant improvement in structural variant detection relative to other graphs.
  • A larger fraction of structural variants than SNPs reached genome-wide significance in GWAS, indicating potential causality.

Abstract

Abstract Structural variants are an underexplored source of genetic diversity. As part of the FarmGTEx Project, here we report a Holstein breed-specific pangenome graph (H20D) using Minigraph-Cactus and 40 phased haploid assemblies from 20 cows. H20D outperforms both assembly- and read-based long-read callers, and far exceeds short-read approaches, identifying over 10,000 additional structural variants per sample. It also significantly improves structural variant detection and genotyping relative to graphs built across breeds or from fewer/unphased assemblies, with particular advantages in complex regions. Using H20D, we genotype variants in 173 cattle and performed a GWAS, where a larger fraction of structural variants than SNPs reach genome-wide significance, implicating them as potential causal variants. Together, these results demonstrate the power of phased, within-breed pangenome graphs for accurate SV genotyping and trait mapping in dairy cattle.

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Cite This Study

Yang et al. (2026) studied this question.

synapsesocial.com/papers/6980ff19c1c9540dea811da8https://doi.org/10.1038/s41467-026-68807-4
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