| Literature DB >> 29862454 |
Lydia Siebert1, Margaret E Staton2, Susan Headrick1, Mark Lewis1, Barbara Gillespie1, Charles Young3, Raul A Almeida1, Stephen P Oliver1,4, Gina M Pighetti5.
Abstract
Mastitis is a detrimental disease in the dairy industry that decreases milk quality and costs upwards of $2 billion annually. Often, mastitis results from bacteria entering the gland through the teat opening. Streptococcus uberis is responsible for a high percentage of subclinical and clinical mastitis. Following an intramammary experimental challenge with S. uberis on Holstein cows (n = 40), milk samples were collected and somatic cell counts (SCC) were determined by the Dairy Herd Improvement Association Laboratory. Traditional genome-wide association studies (GWAS) have utilized test day SCC or SCC lactation averages to identify loci of interest. Our approach utilizes SCC collected following a S. uberis experimental challenge to generate three novel phenotypes: (1) area under the curve (AUC) of SCC for 0-7 days and (2) 0-28 days post-challenge; and (3) when SCC returned to below 200,000 cells/mL post-challenge (< 21 days, 21-28 days, or > 28 days). Polymorphisms were identified using Illumina's BovineSNP50 v2 DNA BeadChip. Associations were tested using Plink software and identified 16 significant (p < 1.0 × 10-4) single-nucleotide polymorphisms (SNPs) across the phenotypes. Most significant SNPs were in genes linked to cell signaling, migration, and apoptosis. Several have been recognized in relation to infectious processes (ATF7, SGK1, and PACRG), but others less so (TRIO, GLRA1, CELSR2, TIAM2, CPE). Further investigation of these genes and their roles in inflammation (e.g., SCC) can provide potential targets that influence resolution of mammary gland infection. Likewise, further investigation of the identified SNP with mastitis and other disease phenotypes can provide greater insight to the potential of these SNP as genetic markers.Entities:
Keywords: Candidate genes; GWAS; Genetics; Mastitis; Post-partum; S. uberis
Mesh:
Year: 2018 PMID: 29862454 DOI: 10.1007/s00251-018-1065-3
Source DB: PubMed Journal: Immunogenetics ISSN: 0093-7711 Impact factor: 2.846