bioRxivGenomicsPreprint
Genome-Wide Association Testing for Haemorrhagic Bowel Syndrome in a Swiss Large White Pig Population
Arnav MehrotraiD, Alexander S. LeonardiD, Cord DrögemülleriD, Alexander GrahoferiD, Negar KhayatzadehiD, Andreas Hofer AiD, Stefan NeuenschwanderiD, Hubert PauschiD
Abstract
BackgroundThe porcine haemorrhagic bowel syndrome (HBS) is a multifactorial disease causing fatal gastrointestinal disturbances and sudden death in fattening pigs. HBS is the leading cause of deaths during fattening in Swiss pigs, with unclear etiology. Environmental and management factors are associated with HBS incidence, but recent findings also suggest a potential genetic predisposition. Pigs sired by a Swiss Large White (SLW) line appear more prone to HBS. Here we conduct genome-wide association studies (GWAS) for HBS between cases and controls to investigate potential genetic factors for the disease in Swiss fattening pigs. ResultsOur study included 1,036 HBS cases and 4,080 controls with available microarray genotypes or whole-genome sequencing data. Variant positions were determined according to the current porcine reference assembly (Sscrofa11.1) or a HiFi-based SLW haplotype assembly which we constructed using trio-binning. GWAS for HBS were conducted using 12.49 to 15.46 million biallelic variants in three mapping cohorts consisting of purebred animals from SLW sire and dam lines, or crosses between these two parental lines. The statistical model applied for the GWAS accounted for animal relatedness, population structure, and an imbalanced case/control ratio. No sequence variants significantly associated with HBS were identified, regardless of the cohort analysed and the reference sequence considered. ConclusionsThe lack of genetic associations despite a relatively large sample size suggests that susceptibility to HBS in the studied SLW population is not due to large effect variants but may be influenced by numerous small effect genetic variants, in addition to environmental and management factors.
- organism: plant (other)
- assay: whole-genome sequencing
- research focus: GWAS / association mapping
- approach: statistical model
- Citations
- 0
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