Genome-wide association analysis for \u03b2-hydroxybutyrate concentration in Milk in Holstein dairy cattle

S Nayeri,A Cánovas,V Kroezen,M Sargolzaei,F Miglior,J Squires,C Baes,A Fleming,F Schenkel

doi:10.1186/s12863-019-0761-9

Abstract

BackgroundKetosis in dairy cattle has been shown to cause a high morbidity in the farm and substantial financial losses to dairy farmers. Ketosis symptoms, however, are difficult to identify, therefore, the amount of ketone bodies (mainly β-hydroxybutyric acid, BHB) is used as an indicator of subclinical ketosis in cows. It has also been shown that milk BHB concentrations have a strong correlation with ketosis in dairy cattle. Mid-infrared spectroscopy (MIR) has recently became a fast, cheap and high-throughput method for analyzing milk components. The aim of this study was to perform a genome-wide association study (GWAS) on the MIR-predicted milk BHB to identify genomic regions, genes and pathways potentially affecting subclinical ketosis in North American Holstein dairy cattle.ResultsSeveral significant regions were identified associated with MIR-predicted milk BHB concentrations (indicator of subclinical ketosis) in the first lactation (SCK1) and second and later lactations (SCK2) in Holstein dairy cows. The strongest association was located on BTA6 for SCK1 and BTA14 on SCK2. Several SNPs on BTA6 were identified in regions and variants reported previously to be associated with susceptibility to ketosis and clinical mastitis in Jersey and Holstein dairy cattle, respectively. One highly significant SNP on BTA14 was found within the DGAT1 gene with known functions on fat metabolism and inflammatory response in dairy cattle. A region on BTA6 and three SNPs on BTA20 were found to overlap between SCK1 and SCK2. However, a novel region on BTA20 (55–63 Mb) for SCK2 was also identified, which was not reported in previous association studies. Enrichment analysis of the list of candidate genes within the identified regions for MIR-predicted milk BHB concentrations yielded molecular functions and biological processes that may be involved in the inflammatory response and lipid metabolism in dairy cattle.ConclusionsThe results of this study confirmed several SNPs and genes identified in previous studies as associated with ketosis susceptibility and immune response, and also found a novel region that can be used for further analysis to identify causal variations and key regulatory genes that affect clinical/ subclinical ketosis.

Highlights

Ketosis in dairy cattle has been shown to cause a high morbidity in the farm and substantial financial losses to dairy farmers
The objective of this study was 1) to identify genome-wide regions associated with Mid-infrared spectroscopy (MIR) predicted β-hydroxybutyric acid (BHB) concentrations in milk, as an indicator of sub-clinical ketosis in North American Holstein dairy cattle, and 2) to perform enrichment analysis to identify biologically significant genes and pathways associated with MIR predicted BHB concentrations in milk, as an indicator of subclinical ketosis, and their possible associations with other metabolic correlated traits
The genome-wide association analysis on MIR predicted BHB milk in this study identified several significant regions associated with subclinical ketosis in first (SCK1) and later (SCK2) lactations in North American Holstein dairy cattle

Summary

Introduction

Ketosis in dairy cattle has been shown to cause a high morbidity in the farm and substantial financial losses to dairy farmers. Ketosis leads to hypoglycemia and hyperketonemia, and has the highest rate of prevalence after calving that extends to the lactation peak [12, 13] This metabolic disease can be diagnosed through clinical signs in dairy cattle, including decrease in appetite, weight loss and decrease in milk production [14]. These symptoms are usually difficult to detect; the amount of ketone bodies (acetone, β-hydroxybutyric acid (BHB), and acetoacetate) present in blood, milk, urine and lymph is used as good indicators of subclinical cases in cows [11, 15]. The prediction accuracy of milk BHB concentrations using fourier transform mid-infrared (FTMIR) was reported to be 71% [26]

Objectives

Methods

Results

Discussion

Conclusion