Exploitation Of The Difference Of Milk Protein Yield In Holstein Dairy Cows Based On Blood-omics Analysis

Milk yield(MY)and milk protein content(MP)are important traits to evaluate the milk performance of dairy cows,which directly affect the profits of dairy industry.Milk protein yield(MPY)is an integrated variable to reflect above two traits.From the perspective of dairy cows physiology,this study was performed to explore the physiological factors towards the MPY by the analysis of physiology stage,serum biochemical parameters and hormone profiles.Furthermore,serum metabolome and whole blood transcriptome were performed to deeply elucidate the modulating mechanisms of MPY differences.Some potential biomarkers reflecting the MPY was digged out,which has important practical signicifance.1 Preliminarily exploration to the physiological factors influencing milk protein yield of dairy cowsUnder the same diet and management conditions,a total of 287 multiparous mid-lactation dairy cows were selected to perform this part of study.Milk yield was recorded and milk composition was analyzed;and blood samples were taken from the jugular vein to analyze the serum biochemical parameters and hormones.All of the experimental cows were grouped based on the parity or days-in-milk(DIM)to explore the effects of physiological stage on above milk and serum parameters firstly.Then,in combination with the whole-group correlation analysis,a comparsion analysis of serum biochemical parameters and hormones between the cows with the high and low MPY,was performed to investigate the physiological factors influencing MPY preliminarily.1.1 The effects of parity and DIM on milk protein yield,serum biochemical parameters and hormone profilesAll of the 287 experimental cows were separated into 5 groups based on the parity range(parity:2-6),or 4 groups based on the DIM(DIM = 90-119,120-149,150-179 and 180-219).The changes of milk performance traits,serum biochemical parameters and hormone profiles under different parity or DIM were analyzed to dig out the contributions of parity and DIM on milk performance traits and above serum parameters.The MY and MP were all affected by the parity and DIM(P<0.05),while the MPY was only affected by the parity,keeping stable in cows with parity 2-4 but lower in cows with parity 6(P = 0.020).Among the 14 serum biochemical parameter relating to the protein metabolism,energy supply,liver and kidney function and oxidative stress,serum total protein,P-hydrobutyric acid and creatinine concentrations were affected by both parity and DIM.Total cholesterol(P = 0.001)and superoxide dismutase(P = 0.034)were only influenced by the parity.Blood urea nitrogen(BUN,P<0.001),glucose(P<0.001),non-esterified fatty acids(P<0.001),total bilirubin(P<0.001),malonaldehyde(P<0.001),glutathione peroxidase(P = 0.038)and total antioxidant capability(P =0.001)were only affected by the DIM.Parity had no effect on the hormone concerntrations(P>0.05),while glucagon(P = 0.012),insulin-like growth factor-1(IGF-1,P = 0.001)and the revised insulin sensitive check index(RQUICKI,P<0.001)were influenced by the DIM.An interaction of DIM and parity effect was detected for glucagon concentration(P = 0.015).1.2 The comparsion analysis of serum biochemical parameters and serum hormone profiles in dairy cows with high and low milk protein yieldTo deeply explore the self-metabolic factors affecting the MPY,20 cows with high MY and high MP(MY>34.5 kg/d,MP>3.20%)were selected from above 287 experimental cows and defined as the HH(MPY>1.11 kg/d);and 20 dairy cows with low MY and low MP(MY<31.0 kg/d,MP<2.90%)were selected and defined as the LL(MPY<0.87 kg/d).Based on the previous study,DIM and parity were controlled to be consistent between HH and LL cows,and were regarded as fixed effects to be introduced into the model to identify the differences of serum biochemical parameters and hormones.Furthermore,a whole-group correlation analysis among the MPY and serum biochemical parameters,hormones were conducted to dig out the physiological factors influencing MPY.It was found that only total cholesterol and malonaldehyde were significantly different between the two groups,which were significantly higher in HH group than in LL group(P<0.05).A significantly higher trend of insulin was found in HH group than that in LL group(P = 0.055).Whole-group association analysis showed that total cholesterol(r = 0.341,P<0.01)and superoxide dismutase(r = 0.190,P<0.05)were positively correlated with MPY,while blood glucose(r =-0.141,P<0.05),malonaldehyde(r =-0.134,P<0.05),IGF-1(r =-0.189,P<0.05)were negatively correlated with MPY.2 Metabolic pathways and potential biomarkers relating to the milk protein yield based on the serum metabolome profilingSimilarly,HH and LL cows in Part 1.2 were used as experimental cows in this part.The gas chromatography-time of flight/mass spectrometry(GC-TOF/MS)and the ultra high performance liquid chromatography-mass spectrometry/mass spectrometry(UHPLC-MS/MS)platforms were utilized to identify metabolites and quantify key metabolites,respectively.This study identified 178 metabolites,with 36 were identified as the significantly different metabolites(VIP>1,P<0.05),which mainly involved in valine,leucine and isoleucine biosynthesis(P = 0.021,Impact value = 0.333)and glycine,serine and threonine metabolism(P = 0.027,Impact value = 0.243).With biomarker analysis and quantified validation,hippuric acid,nicotinamide,and pelargonic acid were chosen to serve as the potential biomarkers associated with MPY(AUC = 0.943).3 The transcriptomic modulating mechanisms of the milk protein yield based on the whole blood transcriptome profilesA total of 12 Holstein cows were chosen from the 287 experimental cows.Among them,6 cows with high MY and high MP(MY>36.0 kg/d,MP>3.14%)were defined as the high MPY(HH:MPY>1.14 kg/d),and 6 dairy cows with low MY and low MP(MY<33.0 kg/d,MP<2.95%)were defined as the low MPY group(MPY<0.95 kg/d).The Novaseq 6000 was used to detect the whole blood transcriptome.This study identified a total of 11003 core genes,among which.10157 genes were function-known genes,relating to the binding(>25%)and catalytic activity(>25%),with their main biological process as the metabolic process(>25%)and biological regulation(>20%).A total of 326 genes were identified as the significantly differenent genes(DEGs:P<0.05,FC>1.5 or FC<-1.5).Among them,225 genes were up-regulated and 101 genes were down-regulated in the high MPY group.Main gene ontology of the DEGs were defense response,immune response and inflammatory response,etc(P<0.001).The ingenuity pathway analysis(IPA)results showed that the ingenuity canonical pathways were GP6 signaling pathway,ILK signaling,and leukocyte extravasation signaling pathways,etc(P<0.05,z-score?1 or z-score?-1).Six DEGs with relatively most variances were selected to do the qPCR validation.Excep the expression of H2AFY2 was too low to be accurately quanfied,5 genes were significantly different between the 2 groups.Besides,the trend of qPCR result was consistent with RNA-seq results.The weighted gene co-expression network analysis(WGCNA)showed that 3 modules showed significantly positive correlation with the MPY(P<0.05),with a positive correlation or positive tendency with the MY and MP at the same time;one module was negatively correlated with the MPY(P<0.05),with a negative correlation or negative tendency with the MY and MP at the same time.Furthermore,the functional analysis by DAVID showed that the positively correlated gene modules were mainly involved in the regulation of signaling,regulation of response to external stimulus stimulus response and positively regulation of protein metabolism,while the negatively correlated gene module was focused on the negative regulation of metabolic process and regulation of nitrogen compound metabolic process.With biomarker analysis and quantified validation,COL18A1 were chosen to serve as the potential biomarkers associated with MPY(AUC = 1).In summary,under the same diet and management condition,physiological factors(physiological stage,serum biochemical parameters,hormones)served to preliminarily reflect the difference reasons of MPY.Combined with the the serum metabolome and whole blood transcriptome approaches,this study deeply explored the influencing pathways and modulating mechanisms towards MPY,which provided basis for improving the MPY from the physiological perspective.Furthermore,this study identified biomarkers relating to the MPY,which possessed important practical significance.