Genome-wide association study of Mycobacterium avium subspecies Paratuberculosis infection in Chinese Holstein.

Background: Paratuberculosis is a contagious, chronic and enteric disease in ruminants, which is caused by Mycobacterium avium subspecies paratuberculosis (MAP) infection, resulting in enormous economic losses worldwide. There is currently no effective cure for MAP infection or a vaccine, it is thus important to explore the genetic variants that contribute to host susceptibility to infection by MAP, which may provide a better understanding of the mechanisms of paratuberculosis and benefit animal genetic improvement. Herein we performed a genome-wide association study (GWAS) to identify genomic regions and candidate genes associated with susceptibility to MAP infection in dairy cattle.

Results: Using Illumina Bovine 50 K (54,609 SNPs) and GeneSeek HD (138,893 SNPs) chips, two analytical approaches were performed, GRAMMAR-GC and ROADTRIPS in 937 Chinese Holstein cows, among which individuals genotyped by the 50 K chip were imputed to HD SNPs with Beagle software. Consequently, 15 and 11 significant SNPs (P < 5 × 10) were identified with GRAMMAR-GC and ROADTDRIPS, respectively. A total of 10 functional genes were in proximity to (i.e., within 1 Mb) these SNPs, including IL4, IL5, IL13, IRF1, MyD88, PACSIN1, DEF6, TDP2, ZAP70 and CSF2. Functional enrichment analysis showed that these genes were involved in immune related pathways, such as interleukin, T cell receptor signaling pathways and inflammatory bowel disease (IBD), implying their potential associations with susceptibility to MAP infection. In addition, by examining the publicly available cattle QTLdb, a previous QTL for MAP was found to be overlapped with one of regions detected currently at 32.5 Mb on BTA23, where the TDP2 gene was anchored.

Conclusions: In conclusion, we identified 26 SNPs located on 15 chromosomes in the Chinese Holstein population using two GWAS strategies with high density SNPs. Integrated analysis of GWAS, biological functions and the reported QTL information helps to detect positional candidate genes and the identification of regions associated with susceptibility to MAP traits in dairy cattle.