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Pangenome Graph Reveals the Structural Variation Landscape in 2929 Cattle Samples and Its Impact on Gene Regulation
Pengju Zhao1,2, Chen Peng1,2, Yahui Gao3,4
1Hainan Institute, Zhejiang University, Yongyou Industry Park, Yazhou Bay Sci-Tech City, Sanya 572000, China.
Genomics, Proteomics & Bioinformatics
|July 16, 2026
Summary
This study reveals the extensive structural variation (SV) landscape in cattle, identifying thousands of high-quality SVs and their regulatory impact on gene expression. These findings enhance our understanding of cattle genomics and trait heritability.
Area of Science:
- Genomics
- Animal Genetics
- Bioinformatics
Background:
- Structural variations (SVs) are key drivers of genomic diversity in livestock, influencing gene expression and traits.
- A comprehensive understanding of the cattle SV landscape and its regulatory impact is lacking.
Purpose of the Study:
- To construct high-fidelity pangenome graphs for cattle by integrating assembly and whole-genome sequencing (WGS) data.
- To comprehensively characterize the SV landscape and its role in gene regulation.
Main Methods:
- Integrated assembly-based and WGS-derived SV catalogs to build pangenome graphs.
- Genotyped 80,328 high-quality SVs across 2929 cattle samples.
- Analyzed SV-expression quantitative trait loci (SV-eQTL) using WGS and RNA-seq data from 170 Simmental cattle.
Main Results:
- Identified 80,328 high-quality SVs and characterized their linkage disequilibrium, functional annotations, and genomic distributions.
- Discovered 637 SV-eQTLs, explaining 10.81% of target gene expression heritability, with many linked to regulatory regions.
- Replicated 46 SV-eQTLs using CattleGTEx data and identified GHSR gene insertions associated with expression and heat tolerance adaptation.
Conclusions:
- Pangenome graphs are effective for SV genotyping and characterizing the SV landscape in cattle.
- SVs significantly contribute to gene regulation and expression heritability in cattle.
- This study provides crucial insights into the functional impact of SVs in cattle genetics and adaptation.
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