Single nucleotide polymorphisms and metabolic biochemical profile of productive markers characterize three European breeds of dairy cattle

The objective of this study was to investigate polymorphisms of DGAT1, FABP, OLR1 and ATP1A1 genes using PCR-DNA sequencing, and to associate these genetic structures to changes in metabolic biochemical markers and milk composition indicators in a total of 90 dairy cows of the Holstein, Simmental, and Brown Swiss breeds (30 cows each). PCR was carried out for amplification of 411-bp of DGAT1, 525-bp of FABP, 582-bp of OLR1, and 300-bp of ATP1A1 genes. Three breeds’ nucleotide sequence variations in the form of single nucleotide polymorphisms (SNPs) were detailed by DNA sequencing analysis. Chisquare analysis showed that the distribution of all discovered SNPs varied significantly (P < 0.001). Biochemical indices in cow’s serum revealed no significant difference in serum total protein, albumin, and total cholesterol among the three breeds. However, triglyceride showed a significant increase in Simmental compared to either Holsteins or Brown Swiss, while the highest mean value of triiodothyronine (T3) and tetraiodothyronine (T4) was detected in Holstein dairy cows The milk composition indicators analysis revealed that milk protein, sugar, and density were significantly higher in Holsteins than both Simmental and Brown Swiss. Meanwhile, milk fat and total solids revealed a significantly higher increase in Simmental than both brown Swiss and Holstein. As a result, the metabolic biochemical markers profile along with the identified SNPs could be used as a candidate and a reference guide for effective characterization of the Holstein, Simmental, and Brown Swiss breeds, leading to the creation of a marker-assisted selection system for production traits in dairy cattle breeds.

Variation of Detailed Protein Composition of Cow Milk Predicted from a Large Database of Mid-Infrared Spectra

Simple Summary

Milk proteins are one of the most valuable milk components. The objective of the present study was to assess sources of variation of detailed protein composition predicted from infrared spectra in milk of dairy and dual-purpose cattle breeds. Results showed that protein fractions were primarily influenced by days in milk, and the relative proportion of each fraction through lactation was not constant. Protein fractions correlated with crude protein, total casein, fat and milk urea nitrogen. In perspective, mid-infrared predictions of milk fractions could be useful for the dairy sector to improve nutritional and technological properties of milk.

Abstract

This study aimed to investigate factors affecting protein fractions, namely α-casein (α-CN), β-casein (β-CN), κ-casein (κ-CN), β-lactoglobulin (β-LG) and α-lactalbumin (α-LA) predicted from milk infrared spectra in milk of dairy and dual-purpose cattle breeds. The dataset comprised 735,328 observations from 49,049 cows in 1782 herds. Results highlighted significant differences of protein fractions in milk of the studied breeds. Significant variations of protein fractions were found also through parities and lactation, with the latter thoroughly influencing protein fractions percentage. Interesting correlations (r) were estimated between β-CN, κ-CN and β-LG, expressed as percentage of crude protein, and milk urea nitrogen (r = 0.31, −0.20 and −0.26, respectively) and between α-LA and fat percentage (r = 0.41). The present study paves the way for future studies on the associations between protein fractions and milk technological properties, and for the estimation of genetic parameters of predicted protein composition.