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Pangenome-genotyped structural variation improves molecular phenotype mapping in cattle.

Alexander S Leonard1, Xena M Mapel2, Hubert Pausch1

  • 1Animal Genomics, ETH Zurich, 8092 Zurich, Switzerland alleonard@ethz.ch hubert.pausch@usys.ethz.ch.

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|February 14, 2024
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This study integrates pangenomics with short-read data to identify millions of genetic variants, including structural variations, in cattle. These variants help uncover novel expression and splicing quantitative trait loci (e/sQTL), revealing transposable elements as key regulators.

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Area of Science:

  • Genomics
  • Quantitative Trait Loci (QTL) analysis
  • Population genetics

Background:

  • Expression and splicing quantitative trait loci (e/sQTL) significantly contribute to phenotypic variation.
  • Accurate e/sQTL mapping necessitates large cohorts with genotypes and molecular phenotypes.
  • Short-read sequencing struggles to comprehensively resolve complex structural variations.

Purpose of the Study:

  • To build a cattle pangenome using HiFi haplotype-resolved assemblies.
  • To identify and genotype small and structural variations in a large cattle cohort.
  • To perform e/sQTL mapping using a comprehensive variant set and identify novel associations.

Main Methods:

  • Construction of a pangenome from 16 HiFi haplotype-resolved cattle assemblies.
  • Genotyping of 307 short-read samples using the PanGenie tool.
  • Validation of structural variants using short-read and medium-coverage HiFi data.
  • e/sQTL mapping in 117 cattle with testis transcriptome data.

Main Results:

  • High concordance (>90%) between PanGenie-genotyped and DeepVariant-called small variations.
  • Identification and genotyping of approximately 21 million small and 43,000 structural variants.
  • Validation of 85% of structural variants (MAF > 0.1).
  • Discovery of 92 structural variants as causal candidates for eQTL and 73 for sQTL.
  • Approximately half of the top associated structural variants are transposable elements.
  • Identification of 28 additional eQTL and 17 sQTL by including structural variants.

Conclusions:

  • Pangenome-based genotyping enables comprehensive identification of small and structural variations in cattle.
  • Structural variants, particularly transposable elements, play a significant role in regulating gene expression and splicing.
  • Integrating structural variation into e/sQTL analysis provides deeper insights into genetic architecture and phenotypic variability.