Genome-Wide Associations for Microscopic Differential Somatic Cell Count and Specific Mastitis Pathogens in Holstein Cows in Compost-Bedded Pack and Cubicle Farming Systems.

Patricia Wagner,Christina Weimann,Petra Engel,Tong Yin,Kerstin Brügemann,Sven König,Karen Schlez

doi:10.3390/ani11061839

Abstract

Simple SummaryNew free walk housing systems such as compost-bedded pack barns might positively influence animal welfare. However, udder health can be negatively affected due to the microbial environment in the pack. Udder health depends on many factors, such as the environment, the feed, the pathogen species, and the genetic mechanisms of the cow’s immune system. For a more precise evaluation of udder health, we examined novel traits including specific mastitis pathogens and differential somatic cell fractions in milk. In order to identify possible candidate genes for udder health, a genome-wide association study, including single-nucleotide polymorphisms (SNP) by housing system interactions (compost-bedded pack barn and conventional cubicle barn), was performed. We identified two potential candidate genes for the interaction effect in relation to udder health. The identified potential candidate gene HEMK1 (HemK methyltransferase family member 1) is involved in immune system development, and CHL1 (cell adhesion molecule L1 like) has an immunosuppressive effect during stress conditions. The results suggest housing system-specific breeding strategies in order to improve udder health in compost-bedded pack and conventional cubicle barns.The aim of the present study was to detect significant SNP (single-nucleotide polymorphism) effects and to annotate potential candidate genes for novel udder health traits in two different farming systems. We focused on specific mastitis pathogens and differential somatic cell fractions from 2198 udder quarters of 537 genotyped Holstein Friesian cows. The farming systems comprised compost-bedded pack and conventional cubicle barns. We developed a computer algorithm for genome-wide association studies allowing the estimation of main SNP effects plus consideration of SNPs by farming system interactions. With regard to the main effect, 35 significant SNPs were detected on 14 different chromosomes for the cell fractions and the pathogens. Six SNPs were significant for the interaction effect with the farming system for most of the udder health traits. We inferred two possible candidate genes based on significant SNP interactions. HEMK1 plays a role in the development of the immune system, depending on environmental stressors. CHL1 is regulated in relation to stress level and influences immune system mechanisms. The significant interactions indicate that gene activity can fluctuate depending on environmental stressors. Phenotypically, the prevalence of mastitis indicators differed between systems, with a notably lower prevalence of minor bacterial indicators in compost systems.

Highlights

Genotype by environment interactions (GxE) in dairy cows have been reported widely [1,2,3,4]
A total of 35 significant single-nucleotide polymorphism (SNP) for the main effect were detected on 14 different chromosomes for the traits polymorphonuclear leucocytes (PMN), segmented neutrophils (sN), banded neutrophils (bN), major pathogens (MAJOR), minor pathogens (MINOR), cultural negative, Aerobic bacilli (AER), and Coagulasenegative staphylococci (CNS) (Tables 1 and 2)
Based on a novel modelling approach allowing genomewide association studies (GWAS) with SNP by farming system interaction effects, we identified significant main and interaction effects for specific pathogens and cell fractions in milk

Summary

Introduction

Genotype by environment interactions (GxE) in dairy cows have been reported widely [1,2,3,4]. There are many different approaches to prove GxE, such as creating a cross-classified research design for, e.g., climate or feeding groups [2], or calculating correlations between the same trait recorded in different environments [3,4,5]. Another approach focusses on continuous environmental descriptors such as temperature, herd production level, or herd size and the application of random regression or reaction norm methodology [3]. In a two-step approach, they estimated intercept and slope effects for each single-nucleotide polymorphism (SNP). Streit et al [1]

Objectives

Results

Discussion

Conclusion