Single- and Bayesian Multi-Marker Genome-Wide Association for Haematological Parameters in Pigs

Abstract

Haematological traits are important traits that show associations with immune and metabolic status, as well as diseases in humans and animals. Mapping genome regions that affect the blood cell traits can contribute to the identification of genomic features useable as biomarkers for immune, disease and metabolic status. A genome-wide association study (GWAS) was conducted using PorcineSNP60 BeadChips. Single-marker and Bayesian multi-marker approaches were integrated to identify genomic regions and corresponding genes overlapping for both methods. GWAS was performed for haematological traits of 591 German Landrace pig. Heritability estimates for haematological traits were medium to high. In total 252 single SNPs associated with 12 haematological traits were identified (NegLog10 of p-value > 5). The Bayesian multi-marker approach revealed 102 QTL regions across the genome, indicated by 1-Mb windows with contribution to additive genetic variance above 0.5%. The integration of both methods resulted in 24 overlapping QTL regions. This study identified overlapping QTL regions from single- and multi-marker approaches for haematological traits. Identifying candidate genes that affect blood cell traits provides the first step towards the understanding of the molecular basis of haematological phenotypes.

Fig 1. Manhattan plots displaying the genome-wide association based on single-markers analysis with haematological traits in German Landrace.

Black lines indicate the significance threshold corresponding to negative log10 (NegLog10)>5.

Fig 2. Manhattan plots displaying the genome-wide association based on the Bayesian multi-marker approach (Bayes B) for haematological traits in German Landrace.

Horizontal line represents the threshold of 0.05% of additive genetic variance explained by 1-Mb marker windows.