Diversity of milk traits in 25 goat breeds

Goats are livestock that is mostly raised by small farmers in Indonesia because they are easier to raise. Apart from having the potential to become meat, several breeds of which are kept as milk-purpose. Milk traits of each breed differ from one another. Therefore, this study tried to observe genetic differences of 25 goat breeds with statistical approach. Information about milk traits from 25 goat breeds is obtained from published journal. Multidimensional preference analysis and average linkage cluster analysis were performed using SAS 9.4 to determine the differences in goat breeds from three traits, namely milk yield, fat content, and protein content. Multidimensional preference analysis was able to see the advantages of breeds from the three observed traits. Goat breeds with superior milk yields are Saanen, Camosciata delle Alpi, and Charmoisée. Sarda Primitiva, Sarda, Etawah Grade have high fat content in milk. In addition, Arsi-Bale and Somali have high protein content. Average linkage cluster analysis is able to observe the genetic relationship of goat breeds based on three traits. According to average linkage cluster analysis, we found four clusters for goat breeds in this study. With existing statistical approaches, we can evaluate genetic diversity in milk traits.

Comparative whey proteome analysis of small-tailed Han and DairyMeade ovine milk

We characterized the proteome profile of mid-lactation small-tailed Han (STH) and DairyMeade (DM) ovine milk in order to explore physiological variation and differences in milk traits between the two breeds. Methodology combined a tandem mass tag (TMT) proteomic approach with LC-MS/MS technology. A total of 656 proteins were identified in STH and DM ovine milk, of which 17and 29 proteins were significantly upregulated (P < 0.05) in STH and DM, respectively. Immune-related proteins and disease-related proteins were highly expressed in STH milk, whereas S100A2 and AEBP1 were highly expressed in DM milk, which had beneficial effects on mammary gland development and milk yield. Our results provide a theoretical basis for future breeding of dairy sheep.

Single nucleotide polymorphism in STAT5A could not endorse variation in milk production traits in Indian bovine population

The Signal Transducer and Activator of Transcription 5A (STAT5A) gene involved in activating the transcription of milk protein genes was predicted to be influencing milk production traits. The present study was undertaken to investigate the suitability of the polymorphism of STAT5A as a marker for milk traits in Ongole, crossbred cattle and Murrah buffaloes from Southern India. Blood samples (n = 502) for DNA isolation and milk samples (n = 222) from different genetic groups were collected from various farms. The gene variants upon polymerase chain reaction–restriction fragment length polymorphism (PCR-RFLP) on the exon 7 region of STAT5A were subjected to GLM analysis to evaluate their association with milk production traits. The frequencies of C and T alleles at the STAT5A/AvaI locus were 0.98 and 0.02 (Jersey crossbred), 0.94 and 0.06 [Holstein-Friesian (HF) crossbred], 0.97 and 0.03 (Ongole). T allele was not observed in Murrah buffaloes. The least squares mean lactation milk yield of CC and CT genotypes of STAT5A were 2,096.90 ± 48.63 and 2,294.41 ± 215.85 kg in Jersey crossbred, 2,312.92 ± 91.01 and 2,392.82 ± 207.66 kg in HF crossbred and 528.40 ± 22.10 and 396.37 ± 76.17 kg in Ongole cattle, respectively. The milk fat content of the CC genotype was higher (P > 0.05) in Jersey crossbred cattle. The CT genotypes of Ongole and HF crossbred cattle recorded a higher fat per cent than the CC genotypes. Significant associations were not observed in support of STAT5A as a marker for milk production traits in either Ongole or crossbred cattle of indicine admixture and no reason could be found to consider this locus as universal markers for milk production traits in indicine cattle and buffaloes. Considering the monomorphic nature of the gene in buffaloes and their higher milk fat content as compared to bovine milk, much remains to be explored regarding the underlying differences across the bovine and the bubaline species.

PSVIII-6 Genetic features of Russian Simmental cattle population different origin derived by assessing milk production and fertility traits

Since the beginning of the 20th century, over 43 thousand animals of Simmental cattle and related breeds have been imported to Russia from Europe. This had a significant impact on the selection intensity and genetic structure within the pale-motley population. The research included 42 breeding herds from 14 regions of Russia. The EBV using the BLUPF90 program based on the ANIMAL MODEL procedure was calculated. Totally of 1471 bulls by using 61816 daughters were estimated. The heritability coefficients showed moderate variability for milk yield (MY) h2=0.140, fat percentage (FP) h2=0.194, protein percentage (PP) h2=0.184 and live weight h2=0.163, as an indirect predictor for meat production. The variability for fertility features like number of inseminations per conception and days open was h2=0.073 and h2=0.061, respectively. Genetic correlation between MY and FP was rg=0.149, and for MY and PP – rg=0.180, while between FP and PP – rg=0.226. The average bulls’ EBV for milk traits in Red Holsteins consisted +23 kg MY, +0.002% FP and +0.001% PP, by Austrian Simmental +10 kg MY, +0.013% FP and +0.002% PP. For Russian Simmental origin animals was signed negative selection response for MY (-23 kg), FP (-0.001%) and PP (-0.003%). High average EBV for imported Simmental cows were revealed +146 kg MY, +0.009% FP and +0.004% PP, while in Russian Simmental we got negative values for MY -70 kg and PP -0.004% but only for FP was showed positive level +0.001%. Simmental breed improvement strategy in Russia focused not only to increasing milk yield but also to improving milk compositions with stabilizing cows’ reproductive traits using the world gene pool of related breeds from Europe. The study was funded by Ministry of Science and Higher Education No.0445-2021-0016

156 Genome-wide DNA Methylation Profile of Mammary Gland Tissues from Holstein Cattle Producing Various Milk Protein Yields

Milk protein content is attracting considerable attention due to increasing demand for high-quality products. Epigenetic marks including DNA methylation have demonstrated considerable potential to contribute to the achievement of increased gain in bovine milk traits. To investigate potential roles of DNA methylation in regulating milk protein productivity, whole genome bisulfite sequencing was used to profile the global DNA methylation of mammary gland (MG) tissues from Canadian Holstein cows producing milk with high protein (HMP) (&gt;4.0%, n = 5) or low protein (LMP) (&lt; 3.0%, n = 7) contents. Bioinformatics processing using standard tools and construction of the methylation landscape of MG was based on methylation sites with ≥10× coverage. A total of 2420 differentially methylated CpG (DMC) sites, including 1842 with higher and 578 with lower methylation levels (FDR&lt; 0.1) were identified when HMP group was compared with LMP group. DMCs were most abundant on chromosomes 2 (n=347) and 27 (N=535), respectively. The most DMCs were annotated to mRNAs, followed by lncRNAs, pseudogenes and rRNAs. Eight genes harbored five or more DMCs each, including LOC112443250 (5S ribosomal RNA) and LOC112443149 (liprin-alpha-1-like, LIP1) (harbored 20 hypermethylated and 1 hypomethylated sites, each), followed by miR-2287-1 (12 hypomethylated sites), etc. LIP1, a liprin family member interacts with LAR family members to play important roles in MG development. MiR-2287-1 and other family members are frequently identified in MG tissues and milk and are associated with many livestock diseases. Interestingly, among the DMCs that overlap with QTLs related to milk production were clusters on chromosomes 27 (N=534) and 14 (N=91) that associated with milk protein yield. In conclusion, DNA methylation showed potential involvement in the genetic variation underlying milk protein content and MG biological processes. More analysis with a higher sample size is however necessary to adequately quantify the involvement of DNA methylation in the regulation of milk protein content and mammary gland development.

Modelling lactation curves for fat-to-protein ratio of milk in the first three lactations of Polish Holstein-Friesian cows

Among milk traits, fat-to-protein ratio (FPR) is considered a potential measure of a cow’s energy status and is one of the selection criteria necessary to improve metabolic stability. Further genetic analyses require an appropriate model that describes the pattern of FPR changes throughout lactation. The objective of the study was to examine five mathematical functions to describe the lactation curve for FPR in the first three lactations of Polish Holstein-Friesians. The dataset contained FPR records for 5690 cows in the first lactation, 4081 cows in the second, and 2636 cows in the third lactation based on 48908, 34706, and 22097 test-day (TD) records, respectively. Using the MIXED procedure of SAS statistical analytics software, ten linear models (five with fixed effects only, and five with the additional random effect of cow) were fitted to the TD records. The goodness of fit was tested with Akaike's information criterion, residual variances and the correlation coefficient between the actual and estimated values. The model proposed by Ali and Schaeffer (1987) had the best fit to FPR in the first three parities, and the model of Wilmink (1987) provided the worst fit. The correlation coefficient between the actual and the estimated values of FPR was higher for models that included the random cow effect compared with models without this effect.

Compositional analysis of ruminal bacteria from ewes selected for somatic cell score and milk persistency

Ruminants are dependent on their rumen microbiota to obtain energy from plants. The composition of the microbiome was well-known to be associated with health status, and production traits, but published results are difficult to reproduce due to large sources of variation. The objectives of this study were to evaluate the associations of ruminal microbiota and its association with genetic lines selected by somatic cell score (SCS) or milk persistency (PERS), as well as milk production, somatic cell score, fat and protein contents, and fatty acids and proteins of milk, using the principles of compositional data. A large sample of 700 Lacaune dairy ewes from INRAE La Fage feeding the same diet and belonging to two divergent genetic lines selected for SCS or PERS was used. The ruminal bacterial metagenome was sequenced using the 16S rRNA gene, resulting in 2,059 operational taxonomic units affiliated with 112 genera. The abundance data were centred log-transformed after the replacement of zeros with the geometric Bayesian method. Discriminant analysis of the SCS showed differences between SCS+ and SCS- ewes, while for PERS no difference was obtained. Milk traits as fat content, protein content, saturated fatty acids and caseins of milk were negatively associated with Prevotella (R = [-0.08;-0.16]), Suttonella (R = [-0.09;-0.16]) and Ruminococcus (R = [-0.08;-0.16]), and positively associated with Lachnospiraceae (R = [0.09;0.16]) and Christensenellaceae (R = [0.09;0.16]). Our findings provide an understanding of the application of compositional data to microbiome analysis, and the potential association of Prevotella, Suttonella, Ruminococcaceae and Lachnospiraceae with milk production traits such as milk fatty acids and proteins in dairy sheep.