Triennial Lactation Symposium: Opportunities for improving milk production efficiency in dairy cattle

Assessment of milk metabolites as biomarkers for predicting feed efficiency in dairy sheep

Estimating feed efficiency (FE) in dairy sheep is challenging due to the high cost of systems that measure individual feed intake. Identifying proxies that can serve as effective predictors of FE could make it possible to introduce FE into breeding programs. Here, 39 Assaf ewes in first lactation were evaluated regarding their FE by 2 metrics, residual feed intake (RFI) and feed conversion ratio (FCR). The ewes were classified into high, medium and low groups for each metric. Milk samples of the 39 ewes were subjected to untargeted metabolomics analysis. The complete milk metabolomic signature was used to discriminate the FE groups using partial least squares discriminant analysis. A total of 41 and 26 features were selected as the most relevant features for the discrimination of RFI and FCR groups, respectively. The predictive ability when utilizing the complete milk metabolomic signature and the reduced data sets were investigated using 4 machine learning (ML) algorithms and a multivariate regression method. The orthogonal partial least squares algorithm outperformed other ML algorithms for FCR prediction in the scenarios using the complete milk metabolite signature (R2 = 0.62 ± 0.06) and the 26 selected features (R2 = 0.62 ± 0.15). Regarding RFI predictions, the scenarios using the 41 selected features outperformed the scenario with the complete milk metabolite signature, where the multilayer feedforward artificial neural network (R2 = 0.18 ± 0.14) and extreme gradient boosting (R2 = 0.17 ± 0.15) outperformed other algorithms. The functionality of the selected metabolites implied that the metabolism of glucose, galactose, fructose, sphingolipids, amino acids, insulin, and thyroid hormones was at play. Compared with the use of traditional methods, practical applications of these biomarkers might simplify and reduce costs in selecting feed-efficient ewes.

Residual feed intake is related to metabolic and inflammatory response during the preweaning period in Italian Simmental calves

Residual Feed Intake (RFI) is defined as the difference between measured and predicted intake. Understanding its biological regulators could benefit farm profit margins. The most-efficient animals (M-Eff) have observed intake smaller than predicted resulting in negative RFI, whereas the least-efficient (L-Eff) animals have positive RFI. Hence, this observational study aimed at retrospectively comparing the blood immunometabolic profile in calves with divergent RFI during the preweaning period. Twenty-two Italian Simmental calves were monitored from birth through 60 d of age. Calves received 3 L of colostrum from their respective dams. From 2 to 53 d of age, calves were fed a milk replacer twice daily, whereas from 54 to 60 d (i.e., weaning) calves were stepped down to only one meal in the morning. Calves had ad libitum access to concentrate and intakes were recorded daily. The measurement of BW and blood samples were performed at 0, 1, 7, 14, 21, 28, 35, 45, 54, and 60 d of age. Calves were ranked and categorized as M-Eff or L-Eff according to the median RFI value. Median RFI was -0.06 and 0.04 kg of DMI/d for M-Eff and L-Eff, respectively. No evidence for group differences was noted for colostrum and plasma IgG concentrations. Although growth rate was not different, as expected, (0.67 kg/d [95% CI = 0.57-0.76] for both L-Eff and M-Eff) throughout the entire preweaning period (0-60 d), starter intake was greater in L-Eff compared with M-Eff calves (+36%). Overall, M-Eff calves had a greater gain-to-feed ratio compared with L-Eff calves (+16%). Plasma ceruloplasmin, myeloperoxidase, and reactive oxygen metabolites concentrations were greater in L-Eff compared with M-Eff calves. Compared with L-Eff, M-Eff calves had an overall greater plasma concentration of globulin, and γ-glutamyl transferase (indicating a better colostrum uptake) and Zn at 1 d. Retinol and urea were overall greater in L-Eff. The improved efficiency in nutrient utilization observed in M-Eff was paired with a lower grade of oxidative stress and systemic inflammation. L-Eff may have had greater energy expenditure to support the activation of the immune system.

Unraveling the Genetic Basis of Feed Efficiency in Cattle through Integrated DNA Methylation and CattleGTEx Analysis

Feed costs can amount to 75 percent of the total overhead cost of raising cows for milk production. Meanwhile, the livestock industry is considered a significant contributor to global climate change due to the production of greenhouse gas emissions, such as methane. Indeed, the genetic basis of feed efficiency (FE) is of great interest to the animal research community. Here, we explore the epigenetic basis of FE to provide base knowledge for the development of genomic tools to improve FE in cattle. The methylation level of 37,554 CpG sites was quantified using a mammalian methylation array (HorvathMammalMethylChip40) for 48 Holstein cows with extreme residual feed intake (RFI). We identified 421 CpG sites related to 287 genes that were associated with RFI, several of which were previously associated with feeding or digestion issues. Activator of transcription and developmental regulation (AUTS2) is associated with digestive disorders in humans, while glycerol-3-phosphate dehydrogenase 2 (GPD2) encodes a protein on the inner mitochondrial membrane, which can regulate glucose utilization and fatty acid and triglyceride synthesis. The extensive expression and co-expression of these genes across diverse tissues indicate the complex regulation of FE in cattle. Our study provides insight into the epigenetic basis of RFI and gene targets to improve FE in dairy cattle.

Relationship between feed efficiency and resilience in dairy ewes subjected to acute underfeeding

Selection of dairy sheep based on production levels has caused a loss of rusticity, which might compromise their future resilience to nutritional challenges. Although refocusing breeding programs toward improved feed efficiency (FE) is expected, more-efficient ewes also seem to be more productive. As a first step to examine the relationship between FE and resilience in dairy sheep, in this study we explored the variation in the response to and the recovery from an acute nutritional challenge in high-yielding Assaf ewes phenotypically divergent for FE. First, feed intake, milk yield and composition, and body weight changes were recorded individually over a 3-wk period in a total of 40 sheep fed a total mixed ration (TMR) ad libitum. Data were used to calculate their FE index (FEI, defined as the difference between the actual and predicted intake estimated through net energy requirements for maintenance, production, and weight change). The highest and lowest FE ewes (H-FE and L-FE groups, respectively; 10 animals/group) were selected and then subjected to the nutritional challenge (i.e., withdrawing the TMR and limiting their diet only to the consumption of straw for 3 d). Afterward, sheep were fed again the TMR ad libitum. Temporal patterns of variation in performance traits, and ruminal fermentation and blood parameters were examined. A good consistency between FEI, residual feed intake, and feed conversion ratio was observed. Results supported that H-FE were more productive than L-FE sheep at similar intake level. Average time trends of milk yield generated by a piecewise model suggest that temporal patterns of variation in this trait would be related to prechallenge production level (i.e., H-FE presented quicker response and recovery than L-FE). Considering all studied traits, the overall response to and recovery from underfeeding was apparently similar or even better in H-FE than in L-FE. This would refute the initial hypothesis of a poorer resilience of more-efficient sheep to an acute underfeeding. However, the question remains whether a longer term feed restriction might impair the ability of H-FE ewes to maintain or revert to a high-production status, which would require further research.

Plasma and milk metabolomics in lactating sheep divergent for feed efficiency

Enhancing the ability of animals to convert feed into meat or milk by optimizing feed efficiency (FE) has become a priority in livestock research. Although untargeted metabolomics is increasingly used in this field and may improve our understanding of FE, no information in this regard is available in dairy ewes. This study was conducted to (1) discriminate sheep divergent for FE and (2) provide insights into the physiological mechanisms contributing to FE through high-throughput metabolomics. The ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-Q/TOF-MS) technique was applied to easily accessible animal fluids (plasma and milk) to assess whether their metabolome differs between high- and low-feed efficient lactating ewes (H-FE and L-FE groups, respectively; 8 animals/group). Blood and milk samples were collected on the last day of the 3-wk period used for FE estimation. A total of 793 features were detected in plasma and 334 in milk, with 100 and 38 of them, respectively, showing differences between H-FE and L-FE. The partial least-squares discriminant analysis separated both groups of animals regardless of the type of sample. Plasma allowed the detection of a greater number of differential features; however, results also supported the usefulness of milk, more easily accessible, to discriminate dairy sheep divergent for FE. Regarding pathway analysis, nitrogen metabolism (either anabolism or catabolism) seemed to play a central role in FE, with plasma and milk consistently indicating a great impact of AA metabolism. A potential influence of pathways related to energy/lipid metabolism on FE was also observed. The variable importance in the projection plot revealed 15 differential features in each matrix that contributed the most for the separation in H-FE and L-FE, such as l-proline and phosphatidylcholine 20:4e in plasma or l-pipecolic acid and phosphatidylethanolamine (18:2) in milk. Overall, untargeted metabolomics provided valuable information into metabolic pathways that may underlie FE in dairy ewes, with a special relevance of AA metabolism in determining this complex phenotype in the ovine. Further research is warranted to validate these findings.

Application of Genetic, Genomic and Biological Pathways in Improvement of Swine Feed Efficiency

Despite the significant improvement of feed efficiency (FE) in pigs over the past decades, feed costs remain a major challenge for producers profitability. Improving FE is a top priority for the global swine industry. A deeper understanding of the biology underlying FE is crucial for making progress in genetic improvement of FE traits. This review comprehensively discusses the topics related to the FE in pigs including: measurements, genetics, genomics, biological pathways and the advanced technologies and methods involved in FE improvement. We first provide an update of heritability for different FE indicators and then characterize the correlations of FE traits with other economically important traits. Moreover, we present the quantitative trait loci (QTL) and possible candidate genes associated with FE in pigs and outline the most important biological pathways related to the FE traits in pigs. Finally, we present possible ways to improve FE in swine including the implementation of genomic selection, new technologies for measuring the FE traits, and the potential use of genome editing and omics technologies.

Effect of Dietary Supplementation with Lipids of Different Unsaturation Degree on Feed Efficiency and Milk Fatty Acid Profile in Dairy Sheep

Lipids of different unsaturation degree were added to dairy ewe diet to test the hypothesis that unsaturated oils would modulate milk fatty acid (FA) profile without impairing or even improving feed efficiency. To this aim, we examined milk FA profile and efficiency metrics (feed conversion ratio (FCR), energy conversion ratio (ECR), residual feed intake (RFI), and residual energy intake (REI)) in 40 lactating ewes fed a diet with no lipid supplementation (Control) or supplemented with 3 fats rich in saturated, monounsaturated and polyunsaturated FA (i.e., purified palmitic acid (PA), olive oil (OO), and soybean oil (SBO)). Compared with PA, addition of OO decreased milk medium-chain saturated FA and improved the concentration of potentially health-promoting FA, such as cis-9 18:1, trans-11 18:1, cis-9 trans-11 CLA, and 4:0, with no impact on feed efficiency metrics. Nevertheless, FA analysis and decreases in FCR and ECR suggested that SBO supplementation would be a better nutritional strategy to further improve milk FA profile and feed efficiency in dairy ewes. The paradox of differences observed depending on the metric used to estimate feed efficiency (i.e., the lack of variation in RFI and REI vs. changes in FCR and ECR) does not allow solid conclusions to be drawn in this regard.

Multiple Country Approach to Improve the Test-Day Prediction of Dairy Cows' Dry Matter Intake

Simple Summary

Dry matter intake, related to the number of nutrients available to an animal to meet its production and health needs, is crucial for the economic, environmental, and welfare management of dairy herds. Because the equipment required to weigh the ingested food at an individual level is not broadly available, we propose some new ways to approach the actual dry matter consumed by a dairy cow for a given day. To do so, we used regression models using parity (number of lactations), week of lactation, milk yield, milk mid-infrared spectrum, and prediction of bodyweight, fat, protein, lactose, and fatty acids content in milk. We chose these elements to predict individual dry matter intake because they are either easily accessible or routinely provided by regional dairy organizations (often called “dairy herd improvement” associations). We succeeded in producing a model whose dry matter intake predictions were moderately related to the actual values.

Abstract

We predicted dry matter intake of dairy cows using parity, week of lactation, milk yield, milk mid-infrared (MIR) spectrum, and MIR-based predictions of bodyweight, fat, protein, lactose, and fatty acids content in milk. The dataset comprised 10,711 samples of 534 dairy cows with a geographical diversity (Australia, Canada, Denmark, and Ireland). We set up partial least square (PLS) regressions with different constructs and a one-hidden-layer artificial neural network (ANN) using the highest contribution variables. In the ANN, we replaced the spectra with their projections to the 25 first PLS factors explaining 99% of the spectral variability to reduce the model complexity. Cow-independent 10 × 10-fold cross-validation (CV) achieved the best performance with root mean square errors (RMSE_CV) of 3.27 ± 0.08 kg for the PLS regression and 3.25 ± 0.13 kg for ANN. Although the available data were significantly different, we also performed a country-independent validation (CIV) to measure the models’ performance fairly. We found RMSE_CIV varying from 3.73 to 6.03 kg for PLS and 3.69 to 5.08 kg for ANN. Ultimately, based on the country-independent validation, we discussed the developed models’ performance with those achieved by the National Research Council’s equation.

Rumen biohydrogenation and milk fatty acid profile in dairy ewes divergent for feed efficiency

A sustainable increase in livestock production would require selection for improved feed efficiency, but the mechanisms underlying this trait and explaining its large individual variation in dairy ruminants remain unclear. This study was conducted in lactating ewes to test the hypothesis that rumen biohydrogenation (BH) would differ between high- and low-efficiency animals, and these differences would be reflected in rumen fatty acid (FA) profile and affect milk FA composition. A second aim was to identify differences in FA that may serve as biomarkers of feed efficiency. Data of daily feed intake and milk yield and composition, as well as body weight, were collected individually over a 3-wk period in 40 ewes. The difference between the mean actual and predicted feed intake (estimated through metabolizable energy requirements for maintenance, production, and body weight change) over the period was used as the feed efficiency index (FEI) to select 8 of the highest feed efficiency (H-FE) and 8 of the lowest feed efficiency (L-FE) animals. In addition, residual feed intake (RFI) was estimated as the residual term from the regression of feed intake on various energy sinks. Rumen and milk FA composition were characterized by using gas chromatography, and results were analyzed using a statistical model that included the fixed effect of the group (H-FE vs. L-FE). The FEI averaged -0.29 ± 0.046 and 0.81 ± 0.084 in H-FE and L-FE, respectively, whereas RFI averaged -0.16 ± 0.084 and 0.18 ± 0.082, respectively. The correlation coefficient between both metrics was 0.69. Feed intake was similar in both groups, but H-FE showed greater milk yield, with increases in lactose content and yield, and in milk protein and fat production. Results from rumen FA profiles included a lower proportion of 18:2n-6, cis-9 18:1, and of several of their BH metabolites, and a greater concentration of 18:0, which may indicate that the apparent BH would be more complete in more efficient sheep. Milk FA analysis suggested that the greater fat yield in the H-FE group was mostly explained by increased de novo FA synthesis, whereas their milk would have lower proportions of cis-9 18:1 and C20 to 22n-6 polyunsaturated FA than L-FE. Stepwise multiple linear regression suggested that milk C20 to 22n-6 PUFA might be convenient biomarkers to discriminate more efficient dairy sheep. Further research is needed to validate these findings (e.g., under different dietary conditions).

Identification of functional candidate variants and genes for feed efficiency in Holstein and Jersey cattle breeds using RNA-sequencing

The identification of functional genetic variants and associated candidate genes linked to feed efficiency may help improve selection for feed efficiency in dairy cattle, providing economic and environmental benefits for the dairy industry. This study used RNA-sequencing data obtained from liver tissue from 9 Holstein cows [n = 5 low residual feed intake (RFI), n = 4 high RFI] and 10 Jersey cows (n = 5 low RFI, n = 5 high RFI), which were selected from a single population of 200 animals. Using RNA-sequencing, 3 analyses were performed to identify: (1) variants within low or high RFI Holstein cattle; (2) variants within low or high RFI Jersey cattle; and (3) variants within low or high RFI groups, which are common across both Holstein and Jersey cattle breeds. From each analysis, all variants were filtered for moderate, modifier, or high functional effect, and co-localized quantitative trait loci (QTL) classes, enriched biological processes, and co-localized genes related to these variants, were identified. The overlapping of the resulting genes co-localized with functional SNP from each analysis in both breeds for low or high RFI groups were compared. For the first two analyses, the total number of candidate genes associated with moderate, modifier, or high functional effect variants fixed within low or high RFI groups were 2,810 and 3,390 for Holstein and Jersey breeds, respectively. The major QTL classes co-localized with these variants included milk and reproduction QTL for the Holstein breed, and milk, production, and reproduction QTL for the Jersey breed. For the third analysis, the common variants across both Holstein and Jersey breeds, uniquely fixed within low or high RFI groups were identified, revealing a total of 86,209 and 111,126 functional variants in low and high RFI groups, respectively. Across all 3 analyses for low and high RFI cattle, 12 and 31 co-localized genes were overlapping, respectively. Among the overlapping genes across breeds, 9 were commonly detected in both the low and high RFI groups (INSRR, CSK, DYNC1H1, GAB1, KAT2B, RXRA, SHC1, TRRAP, PIK3CB), which are known to play a key role in the regulation of biological processes that have high metabolic demand and are related to cell growth and regeneration, metabolism, and immune function. The genes identified and their associated functional variants may serve as candidate genetic markers and can be implemented into breeding programs to help improve the selection for feed efficiency in dairy cattle.

A new method to estimate residual feed intake in dairy cattle using time series data

In dairy, the usual way to measure feed efficiency is through the residual feed intake (RFI) method. However, this method is, in its classical form, a linear regression, which, by construction, does not take into account the evolution of the RFI components across time, inducing approximations in the results. We present here a new approach that incorporates the dynamic dimension of the data. Using a multitrait random regression model, the correlations between milk, live weight, DM intake (DMI) and body condition score (BCS) were investigated across the lactation. In addition, at each time point, by a matrix regression on the variance-covariance matrix and on the animal effects from the three predictor traits, a predicted animal effect for intake was estimated, which, by difference with the actual animal effect for intake, gave a RFI estimation. This model was tested on historical data from the Aarhus University experimental farm (1 469 lactations out of 740 cows). Correlations between animal effects were positive and high for milk and DMI and for weight and DMI, with a maximum mid-lactation, stable across time at around 0.4 for weight and BCS, and slowly decreasing along the lactation for milk and weight, DMI and BCS, and milk and BCS. At the Legendre polynomial coefficient scale, the correlations were estimated with a high accuracy (averaged SE of 0.04, min = 0.02, max = 0.05). The predicted animal effect for intake was always extremely highly correlated with the milk production and highly correlated with BW for the most part of the lactation, but only slightly correlated with BCS, with the correlation becoming negative in the second half of the lactation. The estimated RFI possessed all the characteristics of a classical RFI, with a mean at zero at each time point and a phenotypic independence from its predictors. The correlation between the averaged RFI over the lactation and RFI at each time point was always positive and above 0.5, and maximum mid-lactation (>0.9). The model performed reasonably well in the presence of missing data. This approach allows a dynamic estimation of the traits, free from all time-related issues inherent to the traditional RFI methodology, and can easily be adapted and used in a genetic or genomic selection context.

Rumen bacteria influence milk protein yield of yak grazing on the Qinghai-Tibet Plateau

Objective

Ruminants are completely dependent on their microbiota for rumen fermentation, feed digestion, and consequently, their metabolism for productivity. This study aimed to evaluate the rumen bacteria of lactating yaks with different milk protein yields, using high-throughput sequencing technology, in order to understand the influence of these bacteria on milk production.

Methods

Yaks with similar high milk protein yield (high milk yield and high milk protein content, HH; n = 12) and low milk protein yield (low milk yield and low milk protein content, LL; n = 12) were randomly selected from 57 mid-lactation yaks. Ruminal contents were collected using an oral stomach tube from the 24 yaks selected. High-throughput sequencing of bacterial 16S rRNA gene was used.

Results

Ruminal ammonia N, total volatile fatty acids, acetate, propionate, and isobutyrate concentrations were found to be higher in HH than LL yaks. Community richness (Chao 1 index) and diversity indices (Shannon index) of rumen microbiota were higher in LL than HH yaks. Relative abundances of the Bacteroidetes and Tenericutes phyla in the rumen fluid were significantly increased in HH than LL yaks, but significantly decreased for Firmicutes. Relative abundances of the Succiniclasticum, Butyrivibrio 2, Prevotella 1, and Prevotellaceae UCG-001 genera in the rumen fluid of HH yaks was significantly increased, but significantly decreased for Christensenellaceae R-7 group and Coprococcus 1. Principal coordinates analysis on unweighted UniFrac distances revealed that the bacterial community structure of rumen differed between yaks with high and low milk protein yields. Furthermore, rumen microbiota were functionally enriched in relation to transporters, ABC transporters, ribosome, and urine metabolism, and also significantly altered in HH and LL yaks.

Conclusion

We observed significant differences in the composition, diversity, fermentation product concentrations, and function of ruminal microorganisms between yaks with high and low milk protein yields, suggesting the potential influence of rumen microbiota on milk protein yield in yaks. A deeper understanding of this process may allow future modulation of the rumen microbiome for improved agricultural yield through bacterial community design.

Metabolomics Analyses in High-Low Feed Efficient Dairy Cows Reveal Novel Biochemical Mechanisms and Predictive Biomarkers

Residual feed intake (RFI) is designed to estimate net efficiency of feed use, so low RFI animals are considered for selection to reduce feeding costs. However, metabolic profiling of cows and availability of predictive metabolic biomarkers for RFI are scarce. Therefore, this study aims to generate a better understanding of metabolic mechanisms behind low and high RFI in Jerseys and Holsteins and identify potential predictive metabolic biomarkers. Each metabolite was analyzed to reveal their associations with two RFIs in two breeds by a linear regression model. An integrative analysis of metabolomics and transcriptomics was performed to explore interactions between functionally related metabolites and genes in the created metabolite networks. We found that three main clusters were detected in the heat map and all identified fatty acids (palmitoleic, hexadecanoic, octadecanoic, heptadecanoic, and tetradecanoic acid) were grouped in a cluster. The lower cluster were all from fatty acids, including palmitoleic acid, hexadecanoic acid, octadecanoic acid, heptadecanoic acid, and tetradecanoic acid. The first component of the partial least squares-discriminant analysis (PLS-DA) explained a majority (61.5%) of variations of all metabolites. A good division between two breeds was also observed. Significant differences between low and high RFIs existed in the fatty acid group (P < 0.001). Statistical results revealed clearly significant differences between breeds; however, the association of individual metabolites (leucine, ornithine, pentadecanoic acid, and valine) with the RFI status was only marginally significant or not significant due to a lower sample size. The integrated gene-metabolite pathway analysis showed that pathway impact values were higher than those of a single metabolic pathway. Both types of pathway analyses revealed three important pathways, which were aminoacyl-tRNA biosynthesis, alanine, aspartate, and glutamate metabolism, and the citrate cycle (TCA cycle). Finally, one gene (2-hydroxyacyl-CoA lyase 1 (+HACL1)) associated with two metabolites (-α-ketoglutarate and succinic acid) were identified in the gene-metabolite interaction network. This study provided novel metabolic pathways and integrated metabolic-gene expression networks in high and low RFI Holstein and Jersey cattle, thereby providing a better understanding of novel biochemical mechanisms underlying variation in feed efficiency.

Nitrogen partitioning and microbial protein synthesis in lactating dairy cows with different phenotypic residual feed intake

Background

Residual feed intake (RFI) is an inheritable measure of feed efficiency that is independent on level of production. However, physiological and metabolic mechanisms underlying divergent RFI are not fully elucidated. This study was conducted to investigate dietary nitrogen (N) partitioning and microbial protein synthesis in lactating dairy cows divergent in phenotypic RFI.

Results

Thirty Holstein dairy cows (milk yield = 35.3 ± 4.71 kg/d; milk protein yield = 1.18 ± 0.13 kg/d; mean ± standard deviation) were selected for the experiment to derive RFI. After the RFI measurement period of 50 d, the 10 lowest RFI cows and 8 highest RFI cows were selected. The low RFI cows had lower dry matter intake (DMI, P < 0.05) than the high RFI cows, but they produced similar energy-corrected milk. The ratios of milk to DMI (1.41 vs. 1.24, P < 0.01) and energy-corrected milk to DMI (1.48 vs. 1.36, P < 0.01) were greater in low RFI cows than those in the high RFI cows. The low RFI cows had lower milk urea nitrogen than that in the high RFI cows (P = 0.05). Apparent digestibility of nutrients did not differ between two groups (P > 0.10). Compared with high RFI animals, the low RFI cows had a lower retention of N (5.72 vs. 51.4 g/d, P < 0.05) and a higher partition of feed N to milk N (29.7% vs. 26.5%, P < 0.05).

Conclusions

The results suggest that differences in N partition, synthesis of microbial protein, and utilization of metabolizable protein could be part of the mechanisms associated with variance in the RFI.

Transient changes in milk production efficiency and bacterial community composition resulting from near-total exchange of ruminal contents between high- and low-efficiency Holstein cows

The objectives of this study were to determine if milk production efficiency (MPE) is altered by near-total exchange of ruminal contents between high- (HE) and low-MPE (LE) cows and to characterize ruminal bacterial community composition (BCC) before exchange and over time postexchange. Three pairs of ruminally cannulated, third-lactation cows were selected whose MPE (energy-corrected milk per unit of dry matter intake) differed over their first 2 lactations. Approximately 95% of ruminal contents were exchanged between cows within each pair. Ruminal pH and volatile fatty acid (VFA) profiles, along with BCC (characterized by sequencing of the variable 4 region of 16S rRNA genes), were assessed just before feeding on d -8, -7, -5, -4, -1, 1, 2, 3, 7, 10, 14, 21, 28, 35, 42, and 56, relative to the exchange date. High-MPE cows had higher total ruminal VFA concentrations, higher molar percentages of propionate and valerate, and lower molar percentages of acetate and butyrate than did LE cows, and re-established these differences 1 d after contents exchange. Across all LE cows, MPE increased during 7 d postexchange but declined thereafter. Two of the 3 HE cows displayed decreases in MPE following introduction of the ruminal contents from the corresponding LE cow, but MPE increased in the third HE cow, which was determined to be an outlier. For all 6 cows, both liquid- and solids-associated BCC differed between individuals within a pair before contents exchange. Upon exchange, BCC of both phases in all 3 pairs was more similar to that of the donor inoculum than to preexchange host BCC. For 5 of 6 cows, the solids-associated community returned within 10 d to more resemble the preexchange community of that host than that of the donor community. Individual variability before the exchange was greater in liquids than in solids, as was the variability in response of bacterial communities to the exchange. Individual cows varied in their response, but generally moved toward re-establishment of their preexchange communities by 10 d after contents exchange. By contrast, ruminal pH and VFA profiles returned to preexchange levels within 1 d. Despite the small number of cows studied, the data suggest an apparent role for the ruminal bacterial community as a determinant of MPE.

RNA-Seq transcriptomics and pathway analyses reveal potential regulatory genes and molecular mechanisms in high- and low-residual feed intake in Nordic dairy cattle

Background

The selective breeding of cattle with high-feed efficiencies (FE) is an important goal of beef and dairy cattle producers. Global gene expression patterns in relevant tissues can be used to study the functions of genes that are potentially involved in regulating FE. In the present study, high-throughput RNA sequencing data of liver biopsies from 19 dairy cows were used to identify differentially expressed genes (DEGs) between high- and low-FE groups of cows (based on Residual Feed Intake or RFI). Subsequently, a profile of the pathways connecting the DEGs to FE was generated, and a list of candidate genes and biomarkers was derived for their potential inclusion in breeding programmes to improve FE.

Results

The bovine RNA-Seq gene expression data from the liver was analysed to identify DEGs and, subsequently, identify the molecular mechanisms, pathways and possible candidate biomarkers of feed efficiency. On average, 57 million reads (short reads or short mRNA sequences < ~200 bases) were sequenced, 52 million reads were mapped, and 24,616 known transcripts were quantified according to the bovine reference genome. A comparison of the high- and low-RFI groups revealed 70 and 19 significantly DEGs in Holstein and Jersey cows, respectively. The interaction analysis (high vs. low RFI x control vs. high concentrate diet) showed no interaction effects in the Holstein cows, while two genes showed interaction effects in the Jersey cows. The analyses showed that DEGs act through certain pathways to affect or regulate FE, including steroid hormone biosynthesis, retinol metabolism, starch and sucrose metabolism, ether lipid metabolism, arachidonic acid metabolism and drug metabolism cytochrome P450.

Conclusion

We used RNA-Seq-based liver transcriptomic profiling of high- and low-RFI dairy cows in two breeds and identified significantly DEGs, their molecular mechanisms, their interactions with other genes and functional enrichments of different molecular pathways. The DEGs that were identified were the CYP’s and GIMAP genes for the Holstein and Jersey cows, respectively, which are related to the primary immunodeficiency pathway and play a major role in feed utilization and the metabolism of lipids, sugars and proteins.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-017-3622-9) contains supplementary material, which is available to authorized users.

Ruminal Bacterial Community Composition in Dairy Cows Is Dynamic over the Course of Two Lactations and Correlates with Feed Efficiency

Fourteen Holstein cows of similar ages were monitored through their first two lactation cycles, during which ruminal solids and liquids, milk samples, production data, and feed consumption data were collected for each cow during early (76 to 82 days in milk [DIM]), middle (151 to 157 DIM), and late (251 to 257 DIM) lactation periods. The bacterial community of each ruminal sample was determined by sequencing the region from V6 to V8 of the 16S rRNA gene using 454 pyrosequencing. Gross feed efficiency (GFE) for each cow was calculated by dividing her energy-corrected milk by dry matter intake (ECM/DMI) for each period of both lactation cycles. Four pairs of cows were identified that differed in milk production efficiency, as defined by residual feed intake (RFI), at the same level of ECM production. The most abundant phyla detected for all cows were Bacteroidetes (49.42%), Firmicutes (39.32%), Proteobacteria (5.67%), and Tenericutes (2.17%), and the most abundant genera included Prevotella (40.15%), Butyrivibrio (2.38%), Ruminococcus (2.35%), Coprococcus (2.29%), and Succiniclasticum (2.28%). The bacterial microbiota between the first and second lactation cycles were highly similar, but with a significant correlation between total community composition by ruminal phase and specific bacteria whose relative sequence abundances displayed significant positive or negative correlation with GFE or RFI. These data suggest that the ruminal bacterial community is dynamic in terms of membership and diversity and that specific members are associated with high and low milk production efficiency over two lactation cycles.

Feeding protein supplements in alfalfa hay-based lactation diets improves nutrient utilization, lactational performance, and feed efficiency of dairy cows

Due to the increasing cost of soybean meal and concerns of excess N being excreted into the environment, new protein supplements have been developed. Two products that have shown potential in increasing N utilization efficiency are slow-release urea (SRU; Optigen; Alltech Inc., Nicholasville, KY) and ruminal-escape protein derived from yeast (YMP; DEMP; Alltech Inc.). The objective of this study was to assess the effects of feeding these 2 supplements in alfalfa hay-based [45.7% of forage dietary dry matter (DM)] dairy diets on nutrient utilization, feed efficiency, and lactational performance of dairy cows. Twelve multiparous dairy cows were used in a triple 4 × 4 Latin square design with one square consisting of ruminally cannulated cows. Treatments included (1) control, (2) SRU-supplemented total mixed ration (SRUT), (3) YMP-supplemented total mixed ration (YMPT), and (4) SRU- and YMP-supplemented total mixed ration (SYT). The control consisted only of a mixture of soybean meal and canola meal in a 50:50 ratio. The SRU and the YMP were supplemented at 0.49 and 1.15% DM, respectively. The experiment consisted of 4 periods lasting 28 d each (21 d of adaptation and 7 d of sampling). Cows fed YMPT and SYT had decreased intake of DM, and all supplemented treatments had lower crude protein intake compared with those fed the control. Milk yield tended to have the greatest increase in YMPT compared with the control (41.1 vs. 39.7 kg/d) as well as a tendency for increased milk fat and protein yields. Feed efficiencies based on yields of milk, 3.5% fat-corrected milk, and energy-corrected milk increased at 10 to 16% due to protein supplementation. Cows fed protein supplements partitioned less energy toward body weight gain, but tended to partition more energy toward milk production. Efficiency of use of feed N to milk N increased by feeding SRUT and YMPT, and milk N-to-manure N ratio increased with YMPT. Overall results from this experiment indicate that replacing the mixture of soybean meal and canola meal with SRU and YMP in alfalfa hay-based dairy diets can be a good approach to improve nutrient utilization efficiencies in lactating dairy cows.

Invited review: Enteric methane in dairy cattle production: quantifying the opportunities and impact of reducing emissions

Many opportunities exist to reduce enteric methane (CH4) and other greenhouse gas (GHG) emissions per unit of product from ruminant livestock. Research over the past century in genetics, animal health, microbiology, nutrition, and physiology has led to improvements in dairy production where intensively managed farms have GHG emissions as low as 1 kg of CO2 equivalents (CO2e)/kg of energy-corrected milk (ECM), compared with >7 kg of CO2 e/kg of ECM in extensive systems. The objectives of this review are to evaluate options that have been demonstrated to mitigate enteric CH4 emissions per unit of ECM (CH4/ECM) from dairy cattle on a quantitative basis and in a sustained manner and to integrate approaches in genetics, feeding and nutrition, physiology, and health to emphasize why herd productivity, not individual animal productivity, is important to environmental sustainability. A nutrition model based on carbohydrate digestion was used to evaluate the effect of feeding and nutrition strategies on CH4/ECM, and a meta-analysis was conducted to quantify the effects of lipid supplementation on CH4/ECM. A second model combining herd structure dynamics and production level was used to estimate the effect of genetic and management strategies that increase milk yield and reduce culling on CH4/ECM. Some of these approaches discussed require further research, but many could be implemented now. Past efforts in CH4 mitigation have largely focused on identifying and evaluating CH4 mitigation approaches based on nutrition, feeding, and modifications of rumen function. Nutrition and feeding approaches may be able to reduce CH4/ECM by 2.5 to 15%, whereas rumen modifiers have had very little success in terms of sustained CH4 reductions without compromising milk production. More significant reductions of 15 to 30% CH4/ECM can be achieved by combinations of genetic and management approaches, including improvements in heat abatement, disease and fertility management, performance-enhancing technologies, and facility design to increase feed efficiency and life-time productivity of individual animals and herds. Many of the approaches discussed are only partially additive, and all approaches to reducing enteric CH4 emissions should consider the economic impacts on farm profitability and the relationships between enteric CH4 and other GHG.

Greenhouse gas emissions intensity of Ontario milk production in 2011 compared with 1991

Jayasundara, S. and Wagner-Riddle, C. 2014. Greenhouse gas emissions intensity of Ontario milk production in 2011 compared with 1991. Can. J. Anim. Sci. 94: 155–173. For identifying opportunities for reducing greenhouse gas (GHG) emissions from milk production in Ontario, this study analyzed GHG intensity of milk [kg CO2 equivalents kg−1 fat and protein corrected milk (FPCM)] in 2011 compared with 1991 considering cow and crop productivity improvements and management changes over this period. It also assessed within-province variability in GHG intensity of milk in 2011 using county-level data related to milk production. After allocating whole-farm GHG emissions between milk and meat using an allocation factor calculated according to the International Dairy Federation equation, GHG intensity of Ontario milk was 1.03 kgCO2eq kg−1 FPCM in 2011, 22% lower than that in 1991 (1.32 kg CO2eq kg−1 FPCM). Greenhouse gas sources directly associated with dairy cattle decreased less (21 and 14% for enteric fermentation and manure management, respectively) than sources associated with feed crop production (30 to 34% for emissions related to N inputs and farm-field work). Proportions of GHG contributed from different life cycle activities did not change, with enteric fermentation contributing 46%, feed crop production 34%, manure management 18% and milking and related activities 2%. Within province, GHG intensity varied from 0.89 to 1.36 kg CO2eq kg−1 FPCM, a variation inversely correlated with milk productivity per cow (kg FPCM sold cow−1 year−1). The existence of a wide variation is strong indication for potential further reductions in GHG intensity of Ontario milk through the identification of practices associated with high efficiency.

Genetic parameters for energy balance, feed efficiency, and related traits in Holstein cattle

Objectives of the current study were to estimate genetic parameters in Holstein cows for energy balance (EB) and related traits including dry matter intake (DMI), body weight (BW), body condition score (BCS), energy-corrected milk (ECM) production, and gross feed efficiency (GFE), defined as the ratio of total ECM yield to total DMI over the first 150 d of lactation. Data were recorded for the first half of lactation on 227 and 175 cows in their first or later lactation, respectively. Random regression models were fitted to longitudinal data. Also, each trait was averaged over monthly intervals and analyzed by single and multivariate animal models. Heritability estimates ranged from 0.27 to 0.63, 0.12 to 0.62, 0.12 to 0.49, 0.63 to 0.72, and 0.49 to 0.53 for DMI, ECM yield, EB, BW, and BCS, respectively, averaged over monthly intervals. Daily heritability estimates ranged from 0.18 to 0.30, 0.10 to 0.26, 0.07 to 0.22, 0.43 to 0.67, and 0.25 to 0.38 for DMI, ECM yield, EB, BW, and BCS, respectively. Estimated heritability for GFE was 0.32. The genetic correlation of EB at 10d in milk (DIM) with EB at 150 DIM was -0.19, suggesting the genetic regulation of this trait differs by stage of lactation. Positive genetic correlations were found among DMI, ECM yield, and BW averaged over monthly intervals, whereas correlations of these traits with BCS depended upon stage of lactation. Total ECM yield for the lactation was positively correlated with DMI, but a negative genetic correlation between total ECM yield and EB was found. However, the genetic correlation between total ECM yield and EB in the first month of lactation was -0.02, indicating that total production is not genetically correlated with EB during the first month of lactation, when negative EB is most closely associated with diminished fitness. The genetic correlation between GFE and EB ranged from -0.73 to -0.99, indicating that selection for more efficient cows would favor a lower energy status. However, the genetic correlation between EB in the first month of lactation and GFE calculated from 75 to 150 DIM was not significant, indicating that the unfavorable correlation between GFE and EB in early lactation may be minimized with alternative definitions of efficiency. Thus, EB, GFE and related traits will likely respond to genetic selection in Holstein cows. However, the impact of selection for improved feed efficiency on EB must be carefully considered to avoid potential negative consequences of further reductions in EB at the onset of lactation.

Analysis of copy number variations in Holstein cows identify potential mechanisms contributing to differences in residual feed intake

Genomic structural variation is an important and abundant source of genetic and phenotypic variation. In this study, we performed an initial analysis of copy number variations (CNVs) using BovineHD SNP genotyping data from 147 Holstein cows identified as having high or low feed efficiency as estimated by residual feed intake (RFI). We detected 443 candidate CNV regions (CNVRs) that represent 18.4 Mb (0.6 %) of the genome. To investigate the functional impacts of CNVs, we created two groups of 30 individual animals with extremely low or high estimated breeding values (EBVs) for RFI, and referred to these groups as low intake (LI; more efficient) or high intake (HI; less efficient), respectively. We identified 240 (~9.0 Mb) and 274 (~10.2 Mb) CNVRs from LI and HI groups, respectively. Approximately 30-40 % of the CNVRs were specific to the LI group or HI group of animals. The 240 LI CNVRs overlapped with 137 Ensembl genes. Network analyses indicated that the LI-specific genes were predominantly enriched for those functioning in the inflammatory response and immunity. By contrast, the 274 HI CNVRs contained 177 Ensembl genes. Network analyses indicated that the HI-specific genes were particularly involved in the cell cycle, and organ and bone development. These results relate CNVs to two key variables, namely immune response and organ and bone development. The data indicate that greater feed efficiency relates more closely to immune response, whereas cattle with reduced feed efficiency may have a greater capacity for organ and bone development.