Gene function & annotation

Leveraging a genome-wide structural variant catalogue to fine-map QTL in Braunvieh cattle

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Abstract

The routine microarray-based genotyping of cattle has produced large cohorts of animals with both genotypes and phenotypes. By leveraging whole-genome sequenced reference panels, the microarray-derived genotypes can be imputed to the sequence level. These datasets have facilitated the identification of numerous genomic regions associated with complex traits. Despite utilising an extensive catalogue of SNPs, pinpointing causal variants remains challenging. Long-read sequencing enables the identification of small and structural variants (SVs). SVs can exert substantial effects on trait variation that remain undetected. Here, we leverage a large dataset of Braunvieh cattle with own performance records and array-derived genotypes, and a population-level long-read sequenced cohort to identify SVs that are associated with complex traits. SNP array genotypes from Braunvieh cattle were imputed to the sequence-level using a two-step procedure with Beagle (version 5.4). We considered four complex traits, stature (KBHM), front udder attachment (AVO), udder central ligament (ZBA), and front teat position (ZVV), with observations available for up to 23,143 Brown Swiss (BSW) and 4,262 Original Braunvieh (OB) cows. The association between traits and imputed sequence variants was tested using a mixed model-based approach implemented in GCTA (version 1.94.1). We detected significant SNPs surpassing the significance threshold (p 0.2, moderate > 0.5, and high > 0.8) with all significant SNPs within ±100 Kb. In total, 87 SVs were in high LD with at least one significant variant across the four traits. A highly significantly associated mammary gland morphology QTL on BTA17 was in high LD (r2 = 0.95) with a 325-bp insertion (17:61623975). BSW and OB shared 2 SVs that were in high LD with variants associated with stature; a 355 bp insertion (25:685173) and a 51 bp deletion (25:608456), which was within an intron of a gene previously associated with height (METRN-201). These results reveal several SVs that are candidate causal variants for QTL as they are in high LD with top SNPs. Building on this, future work will focus on extending SV genotyping through imputation to enable population-based analyses of SVs across a multitude of traits.

Keywords: 2026

How to Cite:

Watson, N., He, Q., Kadri, N., Leonard, A., Mapel, X., Seefried, F. & Pausch, H., (2026) “Leveraging a genome-wide structural variant catalogue to fine-map QTL in Braunvieh cattle”, World Congress on Genetics Applied to Livestock Production Digital Archive 2026(1): 2283128. doi: https://doi.org/10.31274/wcgalp.23485

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