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Cows are typically milked 2 or more times on a test-day, but not all these milkings are sampled and weighed. The initial approach estimated a test-day yield with doubled morning (AM) or evening (PM) yield in the AM-PM milking plans, assuming equal AM and PM milking intervals. However, AM and PM milking intervals can vary, and milk secretion rates may be different between day and night. Statistical methods have been proposed to estimate daily yields in dairy cows, focusing on various yield correction factors in 2 broad categories: additive correction factors (ACF) and multiplicative correction factors (MCF). The ACF are evaluated by the average differences between AM and PM milk yield for various milking interval classes, coupled with other categorical variables. We show that an ACF model is equivalent to a regression model of daily yield on categorical regressor variables, and a continuous variable for AM or PM yield with a fixed regression coefficient of 2.0. Similarly, a linear regression model can be implemented as an ACF model with the regression coefficient for AM or PM yield estimated from the data. The linear regression models improved the accuracy of the estimates compared with the ACF models. The MCF are ratios of daily yield to yield from single milkings, but their statistical interpretations vary. Overall, MCF were more accurate for estimating daily milk yield than ACF. The MCF have biological and statistical challenges. Systematic biases occurred when ACF or MCF were computed on discretized milking interval classes, leading to accuracy loss. An exponential regression model was proposed as an alternative model for estimating daily milk yields, which improved the accuracy. Characterization of ACF and MCF showed how they improved the accuracy compared with doubling AM or PM yield as the daily milk yield. All the methods performed similarly with equal AM and PM milkings. The methods were explicitly described to estimate daily milk yield in AM and PM milking plans. Still, the principles generally apply to cows milked more than 2 times a day and apply similarly to the estimation of daily fat and protein yields with some necessary modifications., (© 2022.)

The impact of genomic epistasis effects on the accuracy of predicting the phenotypic values of residual feed intake (RFI) in U.S. Holstein cows was evaluated using 6215 Holstein cows and 78,964 SNPs. Two SNP models and seven epistasis models were initially evaluated. Heritability estimates and the accuracy of predicting the RFI phenotypic values from 10-fold cross-validation studies identified the model with SNP additive effects and additive × additive (A×A) epistasis effects (A + A×A model) to be the best prediction model. Under the A + A×A model, additive heritability was 0.141, and A×A heritability was 0.263 that consisted of 0.260 inter-chromosome A×A heritability and 0.003 intra-chromosome A×A heritability, showing that inter-chromosome A×A effects were responsible for the accuracy increases due to A×A. Under the SNP additive model (A-only model), the additive heritability was 0.171. In the 10 validation populations, the average accuracy for predicting the RFI phenotypic values was 0.246 (with range 0.197-0.333) under A + A×A model and was 0.231 (with range of 0.188-0.319) under the A-only model. The average increase in the accuracy of predicting the RFI phenotypic values by the A + A×A model over the A-only model was 6.49% (with range of 3.02-14.29%). Results in this study showed A×A epistasis effects had a positive impact on the accuracy of predicting the RFI phenotypic values when combined with additive effects in the prediction model., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Liang, Prakapenka, Parker Gaddis, VandeHaar, Weigel, Tempelman, Koltes, Santos, White, Peñagaricano, Baldwin VI and Da.)

We profiled landscapes of bovine regulatory elements and explored dynamic changes of chromatin states in rumen development during weaning. The regulatory elements (15 chromatin states) and their coordinated activities in cattle were defined through genome-wide profiling of four histone modifications, CTCF-binding, DNA accessibility, DNA methylation, and transcriptome in rumen epithelial tissues. Each chromatin state presented specific enrichment for sequence ontology, methylation, trait-associated variants, transcription, gene expression-associated variants, selection signatures, and evolutionarily conserved elements. During weaning, weak enhancers and flanking active transcriptional start sites (TSS) were the most dynamic chromatin states and occurred in tandem with significant variations in gene expression and DNA methylation, significantly associated with stature, production, and reproduction economic traits. By comparing with in vitro cultured epithelial cells and in vivo rumen tissues, we showed the commonness and uniqueness of these results, especially the roles of cell interactions and mitochondrial activities in tissue development., (Copyright © 2022. Published by Elsevier Inc.)

We present an analysis of transcriptomic dynamics in rumen epithelium of 18 Holstein calves during the transition from pre-rumination to rumination in cattle-fed hay or concentrated diets at weaning. Three calves each were euthanized at 14 and 42 d of age to exemplify preweaning, and six calves each were provided diets of either milk replacer and grass hay or calf starter to introduce weaning. The two distinct phases of rumen development and function in cattle are tightly regulated by a series of signaling events and clusters of effectors on critical pathways. The dietary shift from liquid to solid feeds prompted the shifting of gene activity. The number of differentially expressed genes increased significantly after weaning. Bioinformatic analysis revealed gene activity shifts underline the functional transitions in the ruminal epithelium and signify the transcriptomic reprogramming. Gene ontogeny (GO) term enrichment shows extensively activated biological functions of differentially expressed genes in the ruminal epithelium after weaning were predominant metabolic functions. The transcriptomic reprogramming signifies a correlation between gene activity and changes in metabolism and energy production in the rumen epithelium, which occur at weaning when transitioning from glucose use to VFA use by epithelium during the weaning.

Beef tenderness contributes significantly to variation of beef palatability, and is largely influenced by various genetic and environmental factors. To identify candidate genes and pathways related to beef tenderness, we analyzed the longissimus dorsi (LD) muscle of Angus cattle that had different degrees of tenderness, measured by Warner-Bratzler shear force (WBSF). Microarray and RT-PCR analyses identified 53 genes that were differentially expressed in LD samples categorized as either tough or tender, including myosin, heavy chain 3 skeletal muscle embryonic (MYH3), myosin heavy chain 8 skeletal muscle perinatal (MYH8), guanylate binding protein 5 (GBP5), fatty acid binding protein 4 (FABP4), Stearoyl-coenzyme A desaturase (SCD), Fatty acid synthase (FASN), ubiquitin-like with PHD and ring finger domains 1 (UHRF1). Most of these genes are involved in lipid metabolism and skeletal muscle contraction. Employing Gene ontology (GO) and Ingenuity Pathway Analysis (IPA), several GO terms and pathways were found to be related to hydrolase, peptidase and GTPase activity, lipid metabolism, small molecule biochemistry, molecular transport, and tissue development. Overall, this analysis provides insight into the metabolic relationships between muscle biology and beef quality.

The temporal sequence of microbial establishment in the rumen of the neonatal ruminant has important ecological and pathophysiological implications. In this study, we characterized the rumen microbiota of pre-ruminant calves fed milk replacer using two approaches, pyrosequencing of hypervariable V3-V5 regions of the 16S rRNA gene and whole-genome shotgun approach. Fifteen bacterial phyla were identified in the microbiota of pre-ruminant calves. Bacteroidetes was the predominant phylum in the rumen microbiota of 42-day-old calves, representing 74.8% of the 16S sequences, followed by Firmicutes (12.0%), Proteobacteria (10.4%), Verrucomicrobia (1.2%) and Synergistetes (1.1%). However, the phylum-level composition of 14-day-old calves was distinctly different. A total of 170 bacterial genera were identified while the core microbiome of pre-ruminant calves included 45 genera. Rumen development seemingly had a significant impact on microbial diversity. The dazzling functional diversity of the rumen microbiota was reflected by identification of 8298 Pfam and 3670 COG protein families. The rumen microbiota of pre-ruminant calves displayed a considerable compositional heterogeneity during early development. This is evidenced by a profound difference in rumen microbial composition between the two age groups. However, all functional classes between the two age groups had a remarkably similar assignment, suggesting that rumen microbial communities of pre-ruminant calves maintained a stable function and metabolic potentials while their phylogenetic composition fluctuated greatly. The presence of all major types of rumen microorganisms suggests that the rumen of pre-ruminant calves may not be rudimentary. Our results provide insight into rumen microbiota dynamics and will facilitate efforts in formulating optimal early-weaning strategies., (Published 2011. This article is a US Government work and is in the public domain in the USA.)

Perchlorate has been detected in U.S. milk samples from many different states. Applying data from a recently reported 9-week experiment in which 16 Holstein dairy cows were administered perchlorate allowed us to derive an equation for the dose-response relationship between perchlorate concentrations in feed/drinking water and its appearance in milk. Examination of background concentrations of perchlorate in the total mixed ration (TMR) fed in addition to the variable dose supplied to treated cows as a ruminal infusate revealed that cows receive significant and variable exposure to perchlorate from the TMR. Weekly examination of the TMR disclosed that a change in ingredients midway through the experiment caused a significant (78%) change in TMR perchlorate concentration. Analyses of the ingredients comprising the TMR revealed that 41.9% of the perchlorate came from corn silage, 22.9% came from alfalfa hay and 11.7% was supplied by sudan grass. Finally, USDA Food and Nutrition Survey data on fluid milk consumption were used to predict potential human exposure from milk that contained concentrations of perchlorate observed in our previous dosing study. The study suggests that reducing perchlorate concentration in dairy feed may reduce perchlorate concentrations in milk as well as the potential to reduce human exposure to perchlorate in milk.