Milk composition always serves as an indicator for the cow’s health status and body condition. Some non-genetic factors such as parity, days in milk (DIM), and calving season, which obviously affect milk performance, therefore, need to be considered in dairy farm management. However, only a few milk compositions are used in the current animal selection programs. The mid-infrared (MIR) spectroscopy can reflect the global composition of milk, but this information is currently underused. The objectives of this study were to detect the effect of some non-genetic factors on milk production traits as well as 1060 individual spectral points covering from 925.92 cm−1 to 5011.54 cm−1, estimate heritabilities of milk production traits and MIR spectral wavenumbers, and explore the genetic correlations between milk production traits and 1060 individual spectral points in a Chinese Holstein population. The mixed models procedure of SAS software was used to test the non-genetic factors. Single-trait animal models were used to estimate heritabilities and bivariate animal models were used to estimate genetic correlations using the package of ASReml in R software. The results showed that herd, parity, calving season, and lactation stage had significant effects on the percentages of protein and lactose, whereas herd and lactation stage had significant effects on fat percentage. Moreover, the herd showed a significant effect on all of the 1060 individual wavenumbers, whereas lactation stage, parity, and calving season had significant effect on most of the wavenumbers of the lactose-region (925 cm−1 to 1200 cm−1), protein-region (1240 cm−1 to 1600 cm−1), and fat-regions (1680 cm−1 to 1770 cm−1 and 2800 cm−1 to 3015 cm−1). The estimated heritabilities for protein percentage (PP), fat percentage (FP), and lactose percentage (LP) were 0.08, 0.05, and 0.09, respectively. Further, the milk spectrum was heritable but low for most individual points. Heritabilities of 1060 individual spectral points were 0.04 on average, ranging from 0 to 0.11. In particular, heritabilities for wavenumbers of spectral regions related to water absorption were very low and even null, and heritabilities for wavenumbers of specific MIR regions associated with fat-I, fat-II, protein, and lactose were 0.04, 0.06, 0.05, and 0.06 on average, respectively. The genetic correlations between PP and FP, PP and LP, FP, and LP were 0.78, −0.29, and −0.14, respectively. In addition, PP, FP, and LP shared the similar patterns of genetic correlations with the spectral wavenumbers. The genetic correlations between milk production traits and spectral regions related to important milk components varied from weak to very strong (0.01 to 0.94, and −0.01 to −0.96). The current study could be used as a management tool for dairy farms and also provides a further understanding of the genetic background of milk MIR spectra.

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Milk produced by dairy cows is a complex combination of many components. However, at present, changes in only a few milk components (e.g., fat, protein, and lactose) during the estrus cycle in dairy cows have been documented. Mid-infrared (MIR) spectroscopy is a worldwide method routinely used for milk analysis, as MIR spectra reflect the global composition of milk. Therefore, this study aimed to investigate the changes in milk MIR spectra and milk production traits (fat, protein, lactose, urea, total solids (TS), and solid not fat (SnF)) due to estrus. Cows that were successfully inseminated, leading to conception, were included. Cows confirmed to be pregnant were considered to be in estrus at the day of insemination (day 0). A general linear mixed model, which included the random effect of cows, the fixed classification effects of parity number, days in relation to estrus, as well as the interaction between parity number and days in relation to estrus, was applied to investigate the changes in milk production traits and 1060 milk infrared wavenumbers, ranging from 925 to 5011 cm−1, of 371 records from 162 Holstein cows on the days before (day −3, day −2, and day −1) and on the day of estrus (day 0). The days in relation to estrus had a significant effect on fat, protein, urea, TS, and SnF, whose contents increased from day −3 to day 0. Lactose did not seem to be significantly influenced by the occurrence of estrus. The days in relation to estrus had significant effects on the majority of the wavenumbers. Besides, we found that some of the wavenumbers in the water absorption regions were significantly changed on the days before and on the day of estrus. This suggests that these wavenumbers may contain useful information. In conclusion, the changes in the milk composition due to estrus can be observed through the analysis of the milk MIR spectrum. Further analyses are warranted to more deeply explore the potential use of milk MIR spectra in the detection of estrus.

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Estrus is crucial for cow fertility in modern dairy farms, but almost 50% of cows do not show the behavioral signs of estrus due to silent estrus and lack of suitable and high-accuracy methods to detect estrus. MiRNA and exosomes play essential roles in reproductive function and may be developed as novel biomarkers in estrus detection. Thus, we analyzed the miRNA expression patterns in milk exosomes during estrus and the effect of milk exosomes on hormone secretion in cultured bovine granulosa cells in vitro. We found that the number of exosomes and the exosome protein concentration in estrous cow milk were significantly lower than in non-estrous cow milk. Moreover, 133 differentially expressed exosomal miRNAs were identified in estrous cow milk vs. non-estrous cow milk. Functional enrichment analyses indicated that exosomal miRNAs were involved in reproduction and hormone-synthesis-related pathways, such as cholesterol metabolism, FoxO signaling pathway, Hippo signaling pathway, mTOR signaling pathway, steroid hormone biosynthesis, Wnt signaling pathway and GnRH signaling pathway. Consistent with the enrichment signaling pathways, exosomes derived from estrous and non-estrous cow milk both could promote the secretion of estradiol and progesterone in cultured bovine granulosa cells. Furthermore, genes related to hormonal synthesis (CYP19A1, CYP11A1, HSD3B1 and RUNX2) were up-regulated after exosome treatment, while exosomes inhibited the expression of StAR. Moreover, estrous and non-estrous cow-milk-derived exosomes both could increase the expression of bcl2 and decrease the expression of p53, and did not influence the expression of caspase-3. To our knowledge, this is the first study to investigate exosomal miRNA expression patterns during dairy cow estrus and the role of exosomes in hormone secretion by bovine granulosa cells. Our findings provide a theoretical basis for further investigating milk-derived exosomes and exosomal miRNA effects on ovary function and reproduction. Moreover, bovine milk exosomes may have effects on the ovaries of human consumers of pasteurized cow milk. These differential miRNAs might provide candidate biomarkers for the diagnosis of dairy cow estrus and will assist in developing new therapeutic targets for cow infertility.