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Identification of genomic regions and genes associated with subclinical ketosis in periparturient dairy cows

Authors :
Jihwan Lee
KwangHyeon Cho
Kent A. Weigel
Heather M. White
ChangHee Do
Inchul Choi
Source :
Journal of Animal Science and Technology, Vol 66, Iss 3, Pp 567-576 (2024)
Publication Year :
2024
Publisher :
Korean Society of Animal Sciences and Technology, 2024.

Abstract

Subclinical ketosis (SCK) is a prevalent metabolic disorder that occurs during the transition to lactation period. It is defined as a high blood concentration of ketone bodies (beta-hydroxybutyric acid f ≥ 1.2 mmol/L) within the first few weeks of lactation, and often presents without clinical signs. SCK is mainly caused by negative energy balance (NEB). The objective of this study is to identify single nucleotide polymorphisms (SNPs) associated with SCK using genome-wide association studies (GWAS), and to predict the biological functions of proximal genes using gene-set enrichment analysis (GSEA). Blood samples were collected from 112 Holstein cows between 5 and 18 days postpartum to determine the incidence of SCK. Genomic DNA extracted from both SCK and healthy cows was examined using the Illumina Bovine SNP50K BeadChip for genotyping. GWAS revealed 194 putative SNPs and 163 genes associated with those SNPs. Additionally, GSEA showed that the genes retrieved by Database for Annotation, Visualization, and Integrated Discovery (DAVID) belonged to calcium signaling, starch and sucrose, immune network, and metabolic pathways. Furthermore, the proximal genes were found to be related to germ cell and early embryo development. In summary, this study proposes several feasible SNPs and genes associated with SCK through GWAS and GSEA. These candidates can be utilized in selective breeding programs to reduce the genetic risk for SCK and subfertility in high-performance dairy cows.

Details

Language :
English
ISSN :
26720191 and 20550391
Volume :
66
Issue :
3
Database :
Directory of Open Access Journals
Journal :
Journal of Animal Science and Technology
Publication Type :
Academic Journal
Accession number :
edsdoj.2ebad3544b8a4056b575216a507fc96e
Document Type :
article
Full Text :
https://doi.org/10.5187/jast.2023.e97