Unraveling the genomic background of resilience based on variability in milk yield and milk production levels in North American Holstein cattle through genome-wide association study and Mendelian randomization analyses.

Breeding more resilient animals will benefit the dairy cattle industry in the long term, especially as global climate changes become more severe. Previous studies have reported genetic parameters for various milk yield-based resilience indicators, but the underlying genomic background of these traits remain unknown. In this study, we conducted GWAS of 62,029 SNPs with 4 milk yield-based resilience indicators, including the weighted occurrence frequency (wfPert) and accumulated milk losses (dPert) of milk yield perturbations, and log-transformed variance (LnVar) and lag-1 autocorrelation (rauto) of daily yield residuals. These variables were previously derived from 5.6 million daily milk yield records from 21,350 lactations (parities 1-3) of 11,787 North American Holstein cows. The average daily milk yield (ADMY) throughout lactation was also included to compare the shared genetic background of resilience indicators with milk yield. The differential genetic background of these indicators was first revealed by the significant genomic regions identified and significantly enriched biological pathways of positional candidate genes, which confirmed the genetic difference among resilience indicators. Interestingly, the functional analyses of candidate genes suggested that the regulation of intestinal homeostasis is most likely affecting resilience derived based on variability in milk yield. Based on Mendelian randomization analyses of multiple instrumental SNPs, we further found an unfavorable causal association of ADMY with LnVar. In conclusion, the resilience indicators evaluated are genetically different traits, and there are causal associations of milk yield with some of the resilience indicators evaluated. In addition to providing biological insights into the molecular regulation mechanisms of resilience derived based on variability in milk yield, this study also indicates the need for developing selection indexes combining multiple indicator traits and taking into account their genetic relationship for breeding more resilient dairy cattle.

Types of milk consumed and risk of essential hypertension: A 2-sample Mendelian randomization analysis.

Observational associations between milk consumption and essential hypertension have been reported. However, their causal inferences have not been proven, and the effects of different types of milk consumption on hypertension risk remain poorly characterized. The Mendelian randomization (MR) analysis was performed using public summary-level statistics from genome-wide association studies to determine whether the different types of milk consumption affect essential hypertension differently. Six different milk consumption types were defined as exposure conditions, whereas essential hypertension identified by the ninth and tenth revisions of the International Classification of Diseases was considered the outcome of interest. Genetic variants, which were genome-wide associated with the types of milk consumed, were used as an instrumental variable for MR analysis. In primary MR analysis, the inverse-variance weighted method was adopted followed by several sensitivity analyses. Our findings suggested that of the 6 common types of milk consumed, semi-skimmed and soya milk products were protective against essential hypertension, whereas skim milk had the opposite effect. Consistent results were also observed in sensitivity analyses that followed. The present study provided genetic evidence that a causal link between milk consumption and the risk of essential hypertension and a new reference for the diet antihypertensive treatment plan for patients with hypertension.