Review: Selecting for improved feed efficiency and reduced methane emissions in dairy cattle

How much can performance measures explain of the between-cow variation in enteric methane?

Enteric CH4 produced from dairy cows contributes to the emission of greenhouse gases from anthropogenic sources. Recent studies have shown that the selection of lower CH4-emitting cows is possible, but doing so would be simpler if performance measures already recorded on farm could be used, instead of measuring gas emissions from individual cows. These performance measures could be used for selection of low emitting cows. The aim of this analysis was to quantify how much of the between-cow variation in CH4 production can be explained by variation in performance measures. A dataset with 3 experiments and a total of 149 lactating dairy cows with repeated measures was used to estimate the between-cow variation (the variation between cow estimates) for performance and gas measures from GreenFeed (C-Lock, Rapid City, SD). The cow estimates were obtained with a linear mixed model with the diet within period effect as a fixed effect and the cow within experiment as a random effect. The cow estimates for CH4 production were first regressed on the performance and gas measures individually, and then performance and CO2 production measures were grouped in 3 subsets for principal component analysis and principal component regression. The variables that explained most of the between-cow variation in CH4 production were DMI (R2 = 0.44), among the performance measures, and CO2 production (R2 = 0.61), among gas measures. Grouping the measures increased the R2 to 0.53 when only performance measures were used, and to 0.66 when CO2 production was added to the significant performance measures. We found the marginal improvement to be insufficient to justify the use of grouped measures rather than an individual measure because the latter simplifies the model and avoids over-fitting. Investigation of other measures that can be explored to increase explanatory power of between-cow variation in CH4 production is briefly discussed. Finally, the use of residual CH4 as a measure for CH4 efficiency could be considered by using either DMI or CO2 production as the sole predicting variables.

Assessing short-term feed efficiency and its association with biological markers in herbage-fed dairy cows

Feed efficiency is an important trait of dairy production. However, assessing feed efficiency is constrained by the associated cost and difficulty in measuring individual feed intake, especially on pastures. The objective of this study was to investigate short-term feed efficiency traits of herbage-fed dairy cows and screening of potential biomarkers (n = 238). Derived feed efficiency traits were ratio-based (i.e., feed conversion ratio (FCR) and N use efficiency (NUE)) or residual-based (i.e., residual feed intake (RFI), residual energy intake (REI), and residual N intake (RNI)). Thirty-eight Holstein and 16 Swiss Fleckvieh dairy cows underwent a 7-d measurement period during mid- and/or late-lactation. The experimental data (n = 100 measurement points) covered different lactational and herbage-fed system situations: mid-lactation grazing (n = 56), late-lactation grazing (n = 28), and late-lactation barn feeding (n = 16). During each measuring period, the individual herbage intake of each cow was estimated using the n-alkane marker technique. For each cow, biomarkers representing milk constituents (n = 109), animal characteristics (n = 13), behaviour, and activity (n = 46), breath emissions (n = 3), blood constituents (n = 35), surface, and rectal temperature (n = 29), hair cortisol (n = 1), and near-infrared (NIR) spectra of faeces and milk (n = 2) were obtained. The relationships between biomarkers and efficiency traits were statistically analysed with univariate linear regression and for NIR spectra using partial least squares regression with feed efficiency traits. The feed efficiency traits were interrelated with each other (r: -0.57 to -0.86 and 0.49-0.81). The biomarkers showed varying R2 values in explaining the variability of feed efficiency traits (FCR: 0.00-0.66, NUE: 0.00-0.74, RFI: 0.00-0.56, REI: 0.00-0.69, RNI: 0.00-0.89). Overall, the feed efficiency traits were best explained by NIR spectral characteristics of milk and faeces (R2: 0.25-0.89). Biomarkers show potential for predicting feed efficiency in herbage-fed dairy cows. NIR spectra data analysis of milk and faeces presents a promising method for estimating individual feed efficiency upon further validation of prediction models. Future applications will depend on the ability to improve the robustness of biomarkers to predict feed efficiency in a greater variety of environments (locations), managing conditions, feeding systems, production intensities, and other aspects.

Effects of heat stress on feed intake, milk yield, milk composition, and feed efficiency in dairy cows: A meta-analysis

Heat stress compromises dairy production by decreasing feed intake and milk yield, and it may also alter milk composition and feed efficiency. However, little information is available for evaluating such effects across different levels of heat stress and cows enrolled in heat stress studies. The objectives of this study were to evaluate the effects of heat stress on dry matter intake (DMI), energy-corrected milk (ECM), milk composition, and feed efficiency (kg ECM/kg DMI) and to investigate the relationship between such effects and heat stress intervention and animal characteristics by using meta-analytical approaches. Data from 31 studies (34 trials) fulfilled the inclusion criteria and were used for analysis. Results showed that heat stress decreased DMI, ECM, and milk protein concentration, but did not alter milk fat concentration or feed efficiency. Meta-regression confirmed that such reductions in DMI and ECM were significantly associated with increasing temperature-humidity index (THI). Over the period of heat stress, for each unit increase in THI, DMI and ECM decreased by 4.13% and 3.25%, respectively, in mid-lactation cows. Regression models further revealed the existence of a strong interaction between THI and lactation stage, which partially explained the large heterogeneity in effect sizes of DMI and ECM. The results indicated a need for more research on the relationship between the effect of heat stress and animal characteristics. This study calls for the implementation of mitigation strategies in heat-stressed herds due to the substantial decrease in productivity.

A compendium of ruminant gastrointestinal phage genomes revealed a higher proportion of lytic phages than in any other environments

BACKGROUND

Ruminants are important livestock animals that have a unique digestive system comprising multiple stomach compartments. Despite significant progress in the study of microbiome in the gastrointestinal tract (GIT) sites of ruminants, we still lack an understanding of the viral community of ruminants. Here, we surveyed its viral ecology using 2333 samples from 10 sites along the GIT of 8 ruminant species.

RESULTS

We present the Unified Ruminant Phage Catalogue (URPC), a comprehensive survey of phages in the GITs of ruminants including 64,922 non-redundant phage genomes. We characterized the distributions of the phage genomes in different ruminants and GIT sites and found that most phages were organism-specific. We revealed that ~ 60% of the ruminant phages were lytic, which was the highest as compared with those in all other environments and certainly will facilitate their applications in microbial interventions. To further facilitate the future applications of the phages, we also constructed a comprehensive virus-bacteria/archaea interaction network and identified dozens of phages that may have lytic effects on methanogenic archaea.

CONCLUSIONS

The URPC dataset represents a useful resource for future microbial interventions to improve ruminant production and ecological environmental qualities. Phages have great potential for controlling pathogenic bacterial/archaeal species and reducing methane emissions. Our findings provide insights into the virome ecology research of the ruminant GIT and offer a starting point for future research on phage therapy in ruminants. Video Abstract.

Effects of Grape Pomace on Growth Performance, Nitrogen Metabolism, Antioxidants, and Microbial Diversity in Angus Bulls

Polyphenol-rich grape pomace (GP) represents a valuable processing by-product with considerable potential as sustainable livestock feed. This study aimed to investigate the effects of different levels of GP on the growth performance and nitrogen utilization efficiency, antioxidant activity, and rumen and rectum microbiota of Angus bulls. Thirty Angus bulls were allocated three dietary treatments according to a completely randomized design: 0% (G0), 10% (G10), and 20% (G20) corn silage dry matter replaced with dried GP dry matter. The results showed that the average daily gain (ADG) of the G0 group and G10 group was higher than that of the G20 group (p < 0.05); urinary nitrogen levels decreased linearly with the addition of GP (linear, p < 0.05). In terms of antioxidants, the levels of catalase (CAT) in the G10 group were higher than in the G0 and G20 groups (p < 0.05), and the total antioxidative capacity (T-AOC) was significantly higher than that in the G20 group (p < 0.05). In addition, in the analysis of a microbial network diagram, the G10 group had better microbial community complexity and stability. Overall, these findings offer valuable insights into the potential benefits of incorporating GP into the diet of ruminants.

The Resilient Dairy Genome Project-A general overview of methods and objectives related to feed efficiency and methane emissions

The Resilient Dairy Genome Project (RDGP) is an international large-scale applied research project that aims to generate genomic tools to breed more resilient dairy cows. In this context, improving feed efficiency and reducing greenhouse gases from dairy is a high priority. The inclusion of traits related to feed efficiency (e.g., dry matter intake [DMI]) or greenhouse gases (e.g., methane emissions [CH4]) relies on available genotypes as well as high quality phenotypes. Currently, 7 countries (i.e., Australia, Canada, Denmark, Germany, Spain, Switzerland, and United States) contribute with genotypes and phenotypes including DMI and CH4. However, combining data are challenging due to differences in recording protocols, measurement technology, genotyping, and animal management across sources. In this study, we provide an overview of how the RDGP partners address these issues to advance international collaboration to generate genomic tools for resilient dairy. Specifically, we describe the current state of the RDGP database, data collection protocols in each country, and the strategies used for managing the shared data. As of February 2022, the database contains 1,289,593 DMI records from 12,687 cows and 17,403 CH4 records from 3,093 cows and continues to grow as countries upload new data over the coming years. No strong genomic differentiation between the populations was identified in this study, which may be beneficial for eventual across-country genomic predictions. Moreover, our results reinforce the need to account for the heterogeneity in the DMI and CH4 phenotypes in genomic analysis.

Unveiling the Genetic Landscape of Feed Efficiency in Holstein Dairy Cows: Insights into Heritability, Genetic Markers, and Pathways via Meta-Analysis

Improving the feeding efficiency of dairy cows is a key component to improve the utilization of land resources and meet the demand for high-quality protein. Advances in genomic methods and omics techniques have made it possible to breed more efficient dairy cows through genomic selection. The aim of this review is to obtain a comprehensive understanding of the biological background of feed efficiency (FE) complex traits in purebred Holstein dairy cows including heritability estimate, and genetic markers, genes, and pathways participating in FE regulation mechanism. Through a literature search, we systematically reviewed the heritability estimation, molecular genetic markers, genes, biomarkers, and pathways of traits related to feeding efficiency in Holstein dairy cows. A meta-analysis based on a random-effects model was performed to combine reported heritability estimates of FE complex. The heritability of residual feed intake, dry matter intake, and energy balance was 0.20, 0.34, and 0.22, respectively, which proved that it was reasonable to include the related traits in the selection breeding program. For molecular genetic markers, a total of 13 single-nucleotide polymorphisms and copy number variance loci, associated genes, and functions were reported to be significant across populations. A total of 169 reported candidate genes were summarized on a large scale, using a higher threshold (adjusted P value < 0.05). Then, the subsequent pathway enrichment of these genes was performed. The important genes reported in the articles were included in a gene list and the gene list was enriched by gene ontology (GO):biological process (BP), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways analysis. Three GO:BP terms and four KEGG terms were statistically significant, which mainly focused on adenosine triphosphate (ATP) synthesis, electron transport chain, and OXPHOS pathway. Among these pathways, involved genes such as ATP5MC2, NDUFA, COX7A2, UQCR, and MMP are particularly important as they were previously reported. Twenty-nine reported biological mechanisms along with involved genes were explained mainly by four biological pathways (insulin-like growth factor axis, lipid metabolism, oxidative phosphorylation pathways, tryptophan metabolism). The information from this study will be useful for future studies of genomic selection breeding and genetic structures influencing animal FE. A better understanding of the underlying biological mechanisms would be beneficial, particularly as it might address genetic antagonism.

Repeatabilities of individual measures of feed intake and body weight on in-house commercial dairy cattle using a 3-dimensional camera system

In this study a 3-dimensional (3D) camera system was set up to measure individual feed intake of dairy cows in a commercial in-house setting. The system was developed to identify the cows while eating, predict body weight based on the curvature of the back of the cow, and quantify the amount of feed eaten by the cow at each visit of eating. The identification of the cow was based on recognizing the patterns, colors, and curvatures of the back from a reference database obtained in a corridor after milking, where images were taken of all cows with a simultaneous reading of the electronic ear tag. Body weight is predicted using the curvatures of the back of the cow. Feed intake is quantified as the difference in surface of the feed a cow can reach before and after a visit is initiated. This estimate is in liters but converted to kilograms, using the density of the feed in the specific herd. A total of 9,142 cows were measured in 19 herds across 3 breeds: Jersey (2,513 cows), Red Dairy Cattle (2,813 cows), and Holstein (3,816 cows). Mean daily feed intake was higher for Red Dairy Cattle (61.72 kg) and Holstein (64.59 kg) than for Jersey (55.74 kg). Repeatability estimates for daily feed intake as a weekly average was 0.62, 0.65, and 0.63 for Jersey, Red Dairy, and Holstein cattle, respectively. Mean body weight was higher for Red Dairy (647.9 kg) and Holstein (683.8 kg) than for Jersey (469.6 kg). Repeatability estimates for body weight as a weekly average was 0.83, 0.85, and 0.88 for Jersey, Red Dairy, and Holstein, respectively. The perspectives in having such records available is huge both for the farmer and for the dairy industry. The records can both be used for improving management in farms on an individual cow level and herd level, but also for genetic evaluation and selection as well as testing feeding regimens. Feed intake can be measured on an individual level using a 3D camera system.

New insights in improving sustainability in meat production: opportunities and challenges

Treating livestock as senseless production machines has led to rampant depletion of natural resources, enhanced greenhouse gas emissions, gross animal welfare violations, and other ethical issues. It has essentially instigated constant scrutiny of conventional meat production by various experts and scientists. Sustainably in the meat sector is a big challenge which requires a multifaced and holistic approach. Novel tools like digitalization of the farming system and livestock market, precision livestock farming, application of remote sensing and artificial intelligence to manage production and environmental impact/GHG emission, can help in attaining sustainability in this sector. Further, improving nutrient use efficiency and recycling in feed and animal production through integration with agroecology and industrial ecology, improving individual animal and herd health by ensuring proper biosecurity measures and selective breeding, and welfare by mitigating animal stress during production are also key elements in achieving sustainability in meat production. In addition, sustainability bears a direct relationship with various social dimensions of meat production efficiency such as non-market attributes, balance between demand and consumption, market and policy failures. The present review critically examines the various aspects that significantly impact the efficiency and sustainability of meat production.

Ruminal and feces metabolites associated with feed efficiency, water intake and methane emission in Nelore bulls

The objectives of this study were twofold: (1) to identify potential differences in the ruminal and fecal metabolite profiles of Nelore bulls under different nutritional interventions; and (2) to identify metabolites associated with cattle sustainability related-traits. We used different nutritional interventions in the feedlot: conventional (Conv; n = 26), and by-product (ByPr, n = 26). Thirty-eight ruminal fluid and 27 fecal metabolites were significantly different (P < 0.05) between the ByPr and Conv groups. Individual dry matter intake (DMI), residual feed intake (RFI), observed water intake (OWI), predicted water intake (WI), and residual water intake (RWI) phenotypes were lower (P < 0.05) in the Conv group, while the ByPr group exhibited lower methane emission (ME) (P < 0.05). Ruminal fluid dimethylamine was significantly associated (P < 0.05) with DMI, RFI, FE (feed efficiency), OWI and WI. Aspartate was associated (P < 0.05) with DMI, RFI, FE and WI. Fecal C22:1n9 was significantly associated with OWI and RWI (P < 0.05). Fatty acid C14:0 and hypoxanthine were significantly associated with DMI and RFI (P < 0.05). The results demonstrated that different nutritional interventions alter ruminal and fecal metabolites and provided new insights into the relationship of these metabolites with feed efficiency and water intake traits in Nelore bulls.

Genetic parameter estimates for daily predicted gross feed efficiency and its association with energy-corrected milk in South African Holstein cattle

Genetic parameters for daily predicted gross feed efficiency (pGFE) and energy corrected milk (ECM) in the first three parities of South African Holstein cattle were estimated by repeatability animal models. Data comprised of 11,068 test-day milk production records of 1,575 Holstein cows that calved between 2009 and 2019. Heritability estimates for pGFE were 0.12 ± 0.06, 0.09 ± 0.04 and 0.18 ± 0.05 in early, mid and late lactation, respectively. Estimates were moderate for primiparous (0.21 ± 0.05) and low for multiparous (0.10 ± 0.04) cows. Heritability and repeatability across all lactations were 0.14 ± 0.03 and 0.37 ± 0.03, respectively. Genetic correlations between pGFE in different stages of lactation ranged from 0.87 ± 0.24 (early and mid) to 0.97 ± 0.28 (early and late), while a strong genetic correlation (0.90 ± 0.03) was found between pGFE and ECM, across all lactations. The low to moderate heritability estimates for pGFE suggest potential for genetic improvement of the trait through selection, albeit with a modest accuracy of selection. The high genetic correlation of pGFE with ECM may, however, assist to improve accuracy of selection for feed efficiency by including both traits in multi-trait analyses. These genetic parameters may be used to estimate breeding values for pGFE, which will enable the trait to be incorporated in the breeding objective for South African Holstein cattle.

Multi-breed host rumen epithelium transcriptome and microbiome associations and their relationship with beef cattle feed efficiency

Understanding host-microbial interactions in the rumen and its influence on desirable production traits may lead to potential microbiota manipulation or genetic selection for improved cattle feed efficiency. This study investigated the host transcriptome and its correlation with the rumen archaea and bacteria differential abundance of two pure beef cattle breeds (Angus and Charolais) and one composite beef hybrid (Kinsella) divergent for residual feed intake (RFI; low-RFI vs. high-RFI). Using RNA-Sequencing of rumen tissue and 16S rRNA gene amplicon sequencing, differentially expressed genes (FDR ≤ 0.05, |log2(Fold-change) >|2) and differentially abundant (p-value < 0.05) archaea and bacteria amplicon sequence variants (ASV) were determined. Significant correlations between gene expression and ASVs (p-value < 0.05) were determine using Spearman correlation. Interesting associations with muscle contraction and the modulation of the immune system were observed for the genes correlated with bacterial ASVs. Potential functional candidate genes for feed efficiency status were identified for Angus (CCL17, CCR3, and CXCL10), Charolais (KCNK9, GGT1 and IL6), and Kinsella breed (ESR2). The results obtained here provide more insights regarding the applicability of target host and rumen microbial traits for the selection and breeding of more feed efficient beef cattle.

Applying assisted reproductive technology and reproductive management to reduce CO2-equivalent emission in dairy and beef cattle: a review

Methane emission from beef and dairy cattle combined contributes around 4.5-5.0% of total anthropogenic global methane. In addition to enteric methane (CH4) produced by the rumen, cattle production also contributes carbon dioxide (CO2) (feed), nitrous oxide (N2O) (feed production, manure) and other CH4 (manure) to the total greenhouse gas (GHG) budget of beef and dairy production systems. The relative contribution in standard dairy systems is typically enteric CH4 58%, feed 29% and manure 10%. Herds with low production efficiency can have an enteric CH4 contribution up to 90%. Digestibility of feed can impact CH4 emission intensity. Low fertility herds also have a greater enteric CH4 contribution. Animals with good feed conversion efficiency have a lower emission intensity of CH4/kg of meat or milk. Feed efficient heifers tend to be lean and have delayed puberty. Fertility is a major driver of profit in both beef and dairy cattle, and it is highly important to apply multi-trait selection when shifting herds towards improved efficiency and reduced CH4. Single nucleotide polymorphisms (SNPs) have been identified for feed efficiency in cattle and are used in genomic selection. SNPs can be utilized in artificial insemination and embryo transfer to increase the proportion of cattle that have the attributes of efficiency, fertility and reduced enteric CH4. Prepubertal heifers genomically selected for favourable traits can have oocytes recovered to produce IVF embryos. Reproductive technology is predicted to be increasingly adopted to reduce generation interval and accelerate the rate of genetic gain for efficiency, fertility and low CH4 in cattle. The relatively high contribution of cattle to anthropogenic global methane has focussed attention on strategies to reduce enteric CH4 without compromising efficiency and fertility. Assisted reproductive technology has an important role in achieving the goal of multiplying and distributing cattle that have good efficiency, fertility and low CH4.

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.

Seasonal Effect of Grass Nutritional Value on Enteric Methane Emission in Islands Pasture Systems

Quantifying entericCH4 from grazing systems is a challenge for all regions of the world, especially when cattle feed mostly on pasture throughout the year, as pasture quality varies with the seasons. In this study, we examine the influence of seasonality on enteric methane emissions in the Azores, considering the most recent IPCC updates, to minimise errors in estimating enteric methane emissions in this region. For this purpose, samples of corn and grass silage, different types of concentrate, and pasture were collected throughout the year, and their nutritional value and digestibility were determined according to standard conventional methods. The estimation of methane production was conducted using the 2006 IPCC Tier 2 methodology, refined in 2019. The results revealed significant differences (p < 0.05) between the chemical composition of winter and summer pastures. However, it was in the autumn that these pastures presented the best nutritional quality. We estimated that the total volume of enteric methane produced in the Azores was 20,341 t CH4, with peak enteric methane emissions (5837 t CH4) reached during the summer. Breeding bulls, beef cows, and heifers are the categories that produce the highest amount of methane per animal. However, if we consider the total number of animals existing in the region, pregnant dairy cows are the category of cattle with the highest emissions of CH4. Thus, considering the current system of cattle production in the region, we can infer that the pastures are better managed during the autumn, which translates into lower emissions of enteric methane into the atmosphere during this season.

Effect of nitrate supplementation, dietary protein supply, and genetic yield index on performance, methane emission, and nitrogen efficiency in dairy cows

The objective was to investigate the effect of nonprotein nitrogen source, dietary protein supply, and genetic yield index on methane emission, N metabolism, and ruminal fermentation in dairy cows. Forty-eight Danish Holstein dairy cows (24 primiparous cows and 24 multiparous cows) were used in a 6 × 4 incomplete Latin square design with 4 periods of 21-d duration. Cows were fed ad libitum with the following 6 experimental diets: diets with low, medium, or high rumen degradable protein (RDP):rumen undegradable protein (RUP) ratio (manipulated by changing the proportion of corn meal, corn gluten meal, and corn gluten feed) combined with either urea or nitrate (10 g NO₃^-/kg of dry matter) as nonprotein nitrogen source. Samples of ruminal fluid and feces were collected from multiparous cows, and total-tract nutrient digestibility was estimated using TiO₂ as flow marker. Milk samples were collected from all 48 cows. Gas emission (CH₄, CO₂, and H₂) was measured by 4 GreenFeed units. We observed no significant interaction between dietary RDP:RUP ratio and nitrate supplementation, and between nitrate supplementation and genetic yield index on CH₄ emission (production, yield, intensity). As dietary RDP:RUP ratio increased, intake of crude protein, RDP, and neutral detergent fiber and total-tract digestibility of crude protein linearly increased, and RUP intake linearly decreased. Yield of milk, energy-corrected milk, and milk protein and lactose linearly decreased, whereas milk fat and milk urea nitrogen concentrations linearly increased as dietary RDP:RUP ratio increased. The increase in dietary RDP:RUP ratio resulted in a linear increase in the excretion of total purine derivatives and N in urine, but a linear decrease in N efficiency (milk N in % of N intake). Nitrate supplementation reduced dry matter intake (DMI) and increased total-tract organic matter digestibility compared with urea supplementation. Nitrate supplementation resulted in a greater reduction in DMI and daily CH₄ production and a greater increase in daily H₂ production in multiparous cows compared with primiparous cows. Nitrate supplementation also showed a greater reduction in milk protein and lactose yield in multiparous cows than in primiparous cows. Milk protein and lactose concentrations were lower for cows receiving nitrate diets compared with cows receiving urea diets. Nitrate supplementation reduced urinary purine derivatives excretion from the rumen, whereas N efficiency tended to increase. Nitrate supplementation reduced proportion of acetate and propionate in ruminal volatile fatty acids. In conclusion, no interaction was observed between dietary RDP:RUP ratio and nitrate supplementation, and no interaction between nitrate supplementation and genetic yield index on CH₄ emission (production, yield, intensity) was noted. Nitrate supplementation resulted in a greater reduction in DMI and CH₄ production, and a greater increase in H₂ production in multiparous cows than in primiparous cows. As the dietary RDP:RUP ratio increased, CH₄ emission was unaffected and RDP intake increased, but RUP intake and milk yield decreased. Genetic yield index did not affect CH₄ production, yield, or intensity.

Feed Conversion Ratio (FCR) and Performance Group Estimation Based on Predicted Feed Intake for the Optimisation of Beef Production

This paper reports on the use of estimates of individual animal feed intake (made using time spent feeding measurements) to predict the Feed Conversion Ratio (FCR), a measure of the amount of feed consumed to produce 1 kg of body mass, for an individual animal. Reported research to date has evaluated the ability of statistical methods to predict daily feed intake based on measurements of time spent feeding measured using electronic feeding systems. The study collated data of the time spent eating for 80 beef animals over a 56-day period as the basis for the prediction of feed intake. A Support Vector Regression (SVR) model was trained to predict feed intake and the performance of the approach was quantified. Here, feed intake predictions are used to estimate individual FCR and use this information to categorise animals into three groups based on the estimated Feed Conversion Ratio value. Results provide evidence of the feasibility of utilising the 'time spent eating' data to estimate feed intake and in turn Feed Conversion Ratio (FCR), the latter providing insights that guide farmer decisions on the optimisation of production costs.

Rumen Microbiota Predicts Feed Efficiency of Primiparous Nordic Red Dairy Cows

Efficient feed utilization in dairy cows is crucial for economic and environmental reasons. The rumen microbiota plays a significant role in feed efficiency, but studies utilizing microbial data to predict host phenotype are limited. In this study, 87 primiparous Nordic Red dairy cows were ranked for feed efficiency during their early lactation based on residual energy intake, and the rumen liquid microbial ecosystem was subsequently evaluated using 16S rRNA amplicon and metagenome sequencing. The study used amplicon data to build an extreme gradient boosting model, demonstrating that taxonomic microbial variation can predict efficiency (r_test = 0.55). Prediction interpreters and microbial network revealed that predictions were based on microbial consortia and the efficient animals had more of the highly interacting microbes and consortia. Rumen metagenome data was used to evaluate carbohydrate-active enzymes and metabolic pathway differences between efficiency phenotypes. The study showed that an efficient rumen had a higher abundance of glycoside hydrolases, while an inefficient rumen had more glycosyl transferases. Enrichment of metabolic pathways was observed in the inefficient group, while efficient animals emphasized bacterial environmental sensing and motility over microbial growth. The results suggest that inter-kingdom interactions should be further analyzed to understand their association with the feed efficiency of animals.

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.

Feed efficiency in dairy sheep: An insight from the milk transcriptome

Introduction

As higher feed efficiency in dairy ruminants means a higher capability to transform feed nutrients into milk and milk components, differences in feed efficiency are expected to be partly linked to changes in the physiology of the mammary glands. Therefore, this study aimed to determine the biological functions and key regulatory genes associated with feed efficiency in dairy sheep using the milk somatic cell transcriptome.

Material and methods

RNA-Seq data from high (H-FE, n = 8) and low (L-FE, n = 8) feed efficiency ewes were compared through differential expression analysis (DEA) and sparse Partial Least Square-Discriminant analysis (sPLS-DA).

Results

In the DEA, 79 genes were identified as differentially expressed between both conditions, while the sPLS-DA identified 261 predictive genes [variable importance in projection (VIP) &gt; 2] that discriminated H-FE and L-FE sheep.

Discussion

The DEA between sheep with divergent feed efficiency allowed the identification of genes associated with the immune system and stress in L-FE animals. In addition, the sPLS-DA approach revealed the importance of genes involved in cell division (e.g., KIF4A and PRC1) and cellular lipid metabolic process (e.g., LPL, SCD, GPAM, and ACOX3) for the H-FE sheep in the lactating mammary gland transcriptome. A set of discriminant genes, commonly identified by the two statistical approaches, was also detected, including some involved in cell proliferation (e.g., SESN2, KIF20A, or TOP2A) or encoding heat-shock proteins (HSPB1). These results provide novel insights into the biological basis of feed efficiency in dairy sheep, highlighting the informative potential of the mammary gland transcriptome as a target tissue and revealing the usefulness of combining univariate and multivariate analysis approaches to elucidate the molecular mechanisms controlling complex traits.

Invited review: Rumen modifiers in today's dairy rations

Our aim was to review feed additives that have a potential ruminal mechanism of action when fed to dairy cattle. We discuss how additives can influence ruminal fermentation stoichiometry through electron transfer mechanisms, particularly the production and usage of dihydrogen. Lactate accumulation should be avoided, especially when acidogenic conditions suppress ruminal neutral detergent fiber digestibility or lead to subclinical acidosis. Yeast products and other probiotics are purported to influence lactate uptake, but growing evidence also supports that yeast products influence expression of gut epithelial genes promoting barrier function and resulting inflammatory responses by the host to various stresses. We also have summarized methane-suppressing additives for potential usage in dairy rations. We focused on those with potential to decrease methane production without decreasing fiber digestibility or milk production. We identified some mitigating factors that need to be addressed more fully in future research. Growth factors such as branched-chain volatile fatty acids also are part of crucial cross-feeding among groups of microbes, particularly to optimize fiber digestibility in the rumen. Our developments of mechanisms of action for various rumen-active modifiers should help nutrition advisors anticipate when a benefit in field conditions is more likely.

Effects of Dietary Nonfibrous Carbohydrate/Neutral Detergent Fiber Ratio on Methanogenic Archaea and Cellulose-Degrading Bacteria in the Rumen of Karakul Sheep: a 16S rRNA Gene Sequencing Study

The study was conducted to investigate the effects of dietary nonfibrous carbohydrate (NFC)/neutral detergent fiber (NDF) ratio on methanogenic archaea and cellulose-degrading bacteria in Karakul sheep by 16S rRNA gene sequencing. Twelve Karakul sheep were randomly divided into four groups, each group with three replicates, and they were fed with four dietary NFC/NDF ratios at 0.54, 0.96, 1.37, and 1.90 as groups 1, 2, 3, and 4, respectively. The experiment lasted for four periods: I (1 to 18 days), II (19 to 36 days), III (37 to 54 days), and IV (55 to 72 days); during each period, rumen contents were collected before morning feeding to investigate on methanogenic archaea and cellulose-degrading bacteria. The results showed that with an increase in dietary NFC/NDF ratio, the number of rumen archaea operational taxonomic units and the diversity of archaea decrease. The most dominant methanogens did not change with dietary NFC/NDF ratio and prolongation of experimental periods. Methanobrevibacter was the most dominant genus. At the species level, the relative abundance of Methanobrevibacter ruminantium first increased and then decreased when the NFC/NDF ratio increased. When the dietary NFC/NDF ratio was 0.96, the structure of archaea was largely changed, and the relative abundance of Fibrobacter sp. strain UWCM, Ruminococcus flavefaciens, and Ruminococcus albus were the highest. When the dietary NFC/NDF ratio was 1.37, the relative abundance of Butyrivibrio fibrisolvens was higher than for other groups. Based on all the data, we concluded that a dietary NFC/NDF ratio of ca. 0.96 to 1.37 was a suitable ratio to support optimal sheep production. IMPORTANCE CH₄ produced by ruminants aggravates the greenhouse effect and cause wastage of feed energy, and CH₄ emissions are related to methanogens. According to the current literature, there is a symbiotic relationship between methanogens and cellulolytic bacteria, so reducing methane will inevitably affect the degradation of fiber materials. This experiment used 16S rRNA gene high-throughput sequencing technology to explore the balance relationship between methanogens and cellulolytic bacteria for the first time through a long-term feeding period. The findings provide fundamental data, supporting for the diet structures with potential to reduce CH₄ emission.

Genetic analysis of production traits and body size measurements and their relationships with metabolic diseases in German Holstein cattle

This study sheds light on the genetic complexity and interplay of production, body size, and metabolic health in dairy cattle. Phenotypes for body size-related traits from conformation classification (130,166 animals) and production (101,562 animals) of primiparous German Holstein cows were available. Additionally, 21,992, 16,641, and 7,096 animals were from herds with recordings of the metabolic diseases ketosis, displaced abomasum, and milk fever in first, second, and third lactation. Moreover, all animals were genotyped. Heritabilities of traits and genetic correlations between all traits were estimated and GWAS were performed. Heritability was between 0.240 and 0.333 for production and between 0.149 and 0.368 for body size traits. Metabolic diseases were lowly heritable, with estimates ranging from 0.011 to 0.029 in primiparous cows, from 0.008 to 0.031 in second lactation, and from 0.037 to 0.052 in third lactation. Production was found to have negative genetic correlations with body condition score (BCS; -0.279 to -0.343) and udder depth (-0.348 to -0.419). Positive correlations were observed for production and body depth (0.138-0.228), dairy character (DCH) (0.334-0.422), and stature (STAT) (0.084-0.158). In first parity cows, metabolic disease traits were unfavorably correlated with production, with genetic correlations varying from 0.111 to 0.224, implying that higher yielding cows have more metabolic problems. Genetic correlations of disease traits in second and third lactation with production in primiparous cows were low to moderate and in most cases unfavorable. While BCS was negatively correlated with metabolic diseases (-0.255 to -0.470), positive correlations were found between disease traits and DCH (0.269-0.469) as well as STAT (0.172-0.242). Thus, the results indicate that larger and sharper animals with low BCS are more susceptible to metabolic disorders. Genome-wide association studies revealed several significantly associated SNPs for production and conformation traits, confirming previous findings from literature. Moreover, for production and conformation traits, shared significant signals on Bos taurus autosome (BTA) 5 (88.36 Mb) and BTA 6 (86.40 to 87.27 Mb) were found, implying pleiotropy. Additionally, significant SNPs were observed for metabolic diseases on BTA 3, 10, 14, 17, and 26 in first lactation and on BTA 2, 6, 8, 17, and 23 in third lactation. Overall, this study provides important insights into the genetic basis and interrelations of relevant traits in today's Holstein cattle breeding programs, and findings may help to improve selection decisions.

Exploring variation in the fecal microbial communities of Kasaragod Dwarf and Holstein crossbred cattle

The gut microbiota and its impact on health and nutrition in animals, including cattle has been of intense interest in recent times. Cattle, in particular indigenous varieties like Kasaragod Dwarf cow, have not received the due consideration given to other non-native cattle breeds, and the composition of their fecal microbiome is yet to be established. This study applied 16S rRNA high-throughput sequencing of fecal samples and compared the Kasaragod Dwarf with the highly prevalent Holstein crossbred cattle. Variation in their microbial composition was confirmed by marker gene-based taxonomic analysis. Principle Coordinate Analysis (PCoA) showed the distinct microbial architecture of the two cattle types. While the two cattle types possess unique signature taxa, in Kasaragod Dwarf cattle, many of the identified genera, including Anaerovibrio, Succinivibrio, Roseburia, Coprococcus, Paludibacter, Sutterella, Coprobacillus, and Ruminobacter, have previously been shown to be present in higher abundance in animals with higher feed efficiency. This is the first report of Kasaragod Dwarf cattle fecal microbiome profiling. Our findings highlight the predominance of specific taxa potentially associated with different fermentation products and feed efficiency phenotypes in Kasaragod Dwarf cattle compared to Holstein crossbred cattle.

Unraveling feed and nutrient use efficiencies in grassland-based dairy farms

Grassland-based dairy farms are important for the provisioning of milk and ecosystem services. However, the key factors and interactions that influence the feed use efficiency of grassland-based dairy farms in practice are not well known and understood, and as a consequence no well-targeted recommendations can be provided. This paper addresses the question ‘what are the main factors that determine the variations in calculated feed efficiency and N and P use efficiencies on dairy farms subjected to agri-environmental regulations’. Monitoring and modeling data from ~12000 grassland-based dairy farms in The Netherlands over a 4 year period (2017–2020), collected through the KringloopWijzer model, were analyzed and the data from 2020 were statistically analyzed in detail. Farms greatly differed in milk production intensity (range &lt; 10 to &gt;25 Mg per ha per yr) and in the amount of purchased feed. The 5 and 95 percentile values of frequency distribution of the calculated annual mean feed efficiency at herd level were 0.9 and 1.3 kg milk per kg feed dry matter, respectively. Feed efficiency was statistically related to milk yield and number of young stock per cow, the share of concentrates and silage maize in the ration, and the net energy content of silage grass. At herd level, the 5 and 95 percentile values of the calculated annual mean N use efficiency increased with feed efficiency from 21 to 28%, and those of the annual mean P use efficiency from 32 to 40%. Contrary to expectations, mean surpluses of N and P at farm level remained more or less constant with feed efficiency and the intensity of milk production, but the amounts of purchased feed and manure export strongly increased with the intensity of milk production. The N and P surpluses and use efficiencies at farm level were sensitive to accounting for the externalization of feed production and manure utilization. The modeled ammonia and methane emissions per kg milk produced were relatively low on farms with high feed efficiency. In conclusion, feed use and N and P use efficiencies are key indicator for the profitability and environmental performance of dairy farms. Differences between farms in these key indicators were large, and these differences were related to a limited number of explanatory variables. Our study provides lessons for improving the profitability and environmental performance of grassland-based dairy farms.

Feed efficiency of lactating Holstein cows is repeatable within diet but less reproducible when changing dietary starch and forage concentrations

Improving feed efficiency has become an important target for dairy farmers to produce more milk with fewer feed resources. With decreasing availability of arable land to produce feeds that are edible for human consumption, it will be important to increase the proportion of feeds in the diets for dairy cattle that are less edible for human consumption. The current research analyzed the ability of lactating dairy cows to maintain their feed efficiency when switching between a high starch diet (HS diet: 27% starch, 29% NDF, 47.1% forages on a DM basis) and a low starch diet (LS diet: 13% starch, 37% NDF, 66.4% forages on a DM basis). Sixty-two lactating Holstein cows (137 ± 23 days in milk (DIM) at the start of experiment), of which 29 were primiparous cows, were utilized in a crossover design with two 70-d experimental periods, including a 14-d adaption period for each. Feed efficiency was estimated as the individual deviation from the population average intercept in a mixed model predicting DM intake (DMI) with net energy in milk, maintenance and BW gain and loss. Repeatability was estimated within each diet by comparing feed efficiency estimated over the first 28-day period and the second 28-day period within each diet, using Pearson's and intraclass correlations, and the estimation of error of repeatability. Similarly, reproducibility was estimated by comparing the second 28-day period of one diet with the first 28-day period of the other diet. Feed efficiency was less reproducible across diets than repeatable within the same diet. This was shown by lower intraclass correlations (0.399) across diets compared to that in the HS diet (0.587) and LS diet (0.806), as well as a lower Pearson's correlation coefficient (0.418) across diets compared to that in the HS diet (0.630) and LS diet (0.809). In addition, the estimation of error of repeatability was higher (0.830 kg DM/d) across diets compared to that in the HS diet (0.761 kg DM/d) and LS diet (0.504 kg DM/d). This means that the feed efficiency of dairy cows is more likely to change after a diet change than over subsequent lactation stages. Other determinants, such as digestive processes, need to be further investigated to determine its effects on estimating feed efficiency.

Specifics of vitrification of in vitro-produced cattle embyos at various development stages

Producing embryos in vitro is an important technology used to improve the genetic potential of cattle and perfect the programs of their breeding. Regardless of the way they are produced, all embryos that had not been used for transplantation to recipients must be conserved. Because of significantly increased interest in the problem of cryoconservation of embryos, both coming from scientists and businesses, there are emerging new commercial environments that allow the facilitation of cryoconservation and the increase in the embryo survival. Oocyte-cumulus complexes obtained from the ovaries of slaughtered clinically healthy cows matured in 22–24 h in in vitro conditions. The oocytes were co-cultured with spermatozoids in Fertilization medium, and the obtained zygotes were cultured in Culture medium with Sodium-Pyruvate for 4 or 7 days up to the stage of morula or blastocyste, respectively. For the vitrification of cow embryos, we used a commercial kit for the vitrification of human embryos, having compared the duration of equilibration. According to the results of the studies, we observed high efficiency of cryoconservation of cow embryos using the commercial kit for vitrification of human embryos. The results revealed the significant effect of equilibration on survival and further development of embryos. In addition, we described the dependence of development stage of cattle embryo on the duration of the contact of embryo with equilibration solution. Therefore, optimal time of contact of cattle embryos at the morula stage with equilibration solution was 12 minutes. On the 24th h after thawing, 46.7 ± 3.3% of the embryos were observed to undergo blastulation, and on 48th h, this parameter increased to 96.7 ± 3.3%, which corresponded to the parameters in the group of embryos that had not been subjected to cryoconservation. In the conditions of further cultivation, the percentage of blastocystes that hatched in the experimental group was no different from that of the control. At the same time, the highest efficiency of vitrification of blastocystes of cows was seen after the contact with the equilibration solution for 15 min, since the percentage of hatched blastocystes was the same as in the control group. Therefore, using the commercial kit for vitrification of human embryos is beneficial, for it promotes the parameters of cow embryos after vitrification/thawing that are similar to such of intact embryos (without freezing). The data we analyzed and presented in the paper could help to increase the efficiency of cryoconservation of cattle embryos for both scientific and commercial purposes.

Eating Time as a Genetic Indicator of Methane Emissions and Feed Efficiency in Australian Maternal Composite Sheep

Previous studies have shown reduced enteric methane emissions (ME) and residual feed intake (RFI) through the application of genomic selection in ruminants. The objective of this study was to evaluate feeding behaviour traits as genetic indicators for ME and RFI in Australian Maternal Composite ewes using data from an automated feed intake facility. The feeding behaviour traits evaluated were the amount of time spent eating per day (eating time; ETD; min/day) and per visit (eating time per event; ETE; min/event), daily number of events (DNE), event feed intake (EFI; g/event) and eating rate (ER; g/min). Genotypes and phenotypes of 445 ewes at three different ages (post-weaning, hogget, and adult) were used to estimate the heritability of ME, RFI, and the feeding behaviour traits using univariate genomic best linear unbiased prediction models. Multivariate models were used to estimate the correlations between these traits and within each trait at different ages. The response to selection was evaluated for ME and RFI with direct selection models and indirect models with ETE as an indicator trait, as this behaviour trait was a promising indicator based on heritability and genetic correlations. Heritabilities were between 0.12 and 0.18 for ME and RFI, and between 0.29 and 0.47 for the eating behaviour traits. In our data, selecting for more efficient animals (low RFI) would lead to higher methane emissions per day and per kg of dry matter intake. Selecting for more ETE also improves feed efficiency but results in more methane per day and per kg dry matter intake. Based on our results, ETE could be evaluated as an indicator trait for ME and RFI under an index approach that allows simultaneous selection for improvement in emissions and feed efficiency. Selecting for ETE may have a tremendous impact on the industry, as it may be easier and cheaper to obtain than feed intake and ME data. As the data were collected using individual feeding units, the findings on this research should be validated under grazing conditions.

Bovine host genome acts on rumen microbiome function linked to methane emissions

Our study provides substantial evidence that the host genome affects the comprehensive function of the microbiome in the rumen of bovines. Of 1,107/225/1,141 rumen microbial genera/metagenome assembled uncultured genomes (RUGs)/genes identified from whole metagenomics sequencing, 194/14/337 had significant host genomic effects (heritabilities ranging from 0.13 to 0.61), revealing that substantial variation of the microbiome is under host genomic control. We found 29/22/115 microbial genera/RUGs/genes host-genomically correlated (|0.59| to |0.93|) with emissions of the potent greenhouse gas methane (CH4), highlighting the strength of a common host genomic control of specific microbial processes and CH4. Only one of these microbial genes was directly involved in methanogenesis (cofG), whereas others were involved in providing substrates for archaea (e.g. bcd and pccB), important microbial interspecies communication mechanisms (ABC.PE.P), host-microbiome interaction (TSTA3) and genetic information processes (RP-L35). In our population, selection based on abundances of the 30 most informative microbial genes provided a mitigation potential of 17% of mean CH4 emissions per generation, which is higher than for selection based on measured CH4 using respiration chambers (13%), indicating the high potential of microbiome-driven breeding to cumulatively reduce CH4 emissions and mitigate climate change.

Board Invited Review: Enteric methane mitigation interventions

Mitigation of enteric methane (CH₄) presents a feasible approach to curbing agriculture’s contribution to climate change. One intervention for reduction is dietary reformulation, which manipulates the composition of feedstuffs in ruminant diets to redirect fermentation processes toward low CH₄ emissions. Examples include reducing the relative proportion of forages to concentrates, determining the rate of digestibility and passage rate from the rumen, and dietary lipid inclusion. Feed additives present another intervention for CH₄ abatement and are classified based on their mode of action. Through inhibition of key enzymes, 3-nitrooxypropanol (3-NOP) and halogenated compounds directly target the methanogenesis pathway. Rumen environment modifiers, including nitrates, essential oils, and tannins, act on the conditions that affect methanogens and remove the accessibility of fermentation products needed for CH₄ formation. Low CH₄-emitting animals can also be directly or indirectly selected through breeding interventions, and genome-wide association studies are expected to provide efficient selection decisions. Overall, dietary reformulation and feed additive inclusion provide immediate and reversible effects, while selective breeding produces lasting, cumulative CH₄ emission reductions.

Evaluation of the Links between Lamb Feed Efficiency and Rumen and Plasma Metabolomic Data

Feed efficiency is one of the keystones that could help make animal production less costly and more environmentally friendly. Residual feed intake (RFI) is a widely used criterion to measure feed efficiency by regressing intake on the main energy sinks. We investigated rumen and plasma metabolomic data on Romane male lambs that had been genetically selected for either feed efficiency (line rfi−) or inefficiency (line rfi+). These investigations were conducted both during the growth phase under a 100% concentrate diet and later on under a mixed diet to identify differential metabolite expression and to link it to biological phenomena that could explain differences in feed efficiency. Nuclear magnetic resonance (NMR) data were analyzed using partial least squares discriminant analysis (PLS-DA), and correlations between metabolites’ relative concentrations were estimated to identify relationships between them. High levels of plasma citrate and malate were associated with genetically efficient animals, while high levels of amino acids such as L-threonine, L-serine, and L-leucine as well as beta-hydroxyisovalerate were associated with genetically inefficient animals under both diets. The two divergent lines could not be discriminated using rumen metabolites. Based on phenotypic residual feed intake (RFI), efficient and inefficient animals were discriminated using plasma metabolites determined under a 100% concentrate diet, but no discrimination was observed with plasma metabolites under a mixed diet or with rumen metabolites regardless of diet. Plasma amino acids, citrate, and malate were the most discriminant metabolites, suggesting that protein turnover and the mitochondrial production of energy could be the main phenomena that differ between efficient and inefficient Romane lambs.

Translational multi-omics microbiome research for strategies to improve cattle production and health

Cattle microbiome plays a vital role in cattle growth and performance and affects many economically important traits such as feed efficiency, milk/meat yield and quality, methane emission, immunity and health. To date, most cattle microbiome research has focused on metataxonomic and metagenomic characterization to reveal who are there and what they may do, preventing the determination of the active functional dynamics in vivo and their causal relationships with the traits. Therefore, there is an urgent need to combine other advanced omics approaches to improve microbiome analysis to determine their mode of actions and host-microbiome interactions in vivo. This review will critically discuss the current multi-omics microbiome research in beef and dairy cattle, aiming to provide insights on how the information generated can be applied to future strategies to improve production efficiency, health and welfare, and environment-friendliness in cattle production through microbiome manipulations.

Host Genome-Metagenome Analyses Using Combinatorial Network Methods Reveal Key Metagenomic and Host Genetic Features for Methane Emission and Feed Efficiency in Cattle

Cattle production is one of the key contributors to global warming due to methane emission, which is a by-product of converting feed stuff into milk and meat for human consumption. Rumen hosts numerous microbial communities that are involved in the digestive process, leading to notable amounts of methane emission. The key factors underlying differences in methane emission between individual animals are due to, among other factors, both specific enrichments of certain microbial communities and host genetic factors that influence the microbial abundances. The detection of such factors involves various biostatistical and bioinformatics methods. In this study, our main objective was to reanalyze a publicly available data set using our proprietary Synomics Insights platform that is based on novel combinatorial network and machine learning methods to detect key metagenomic and host genetic features for methane emission and residual feed intake (RFI) in dairy cattle. The other objective was to compare the results with publicly available standard tools, such as those found in the microbiome bioinformatics platform QIIME2 and classic GWAS analysis. The data set used was publicly available and comprised 1,016 dairy cows with 16S short read sequencing data from two dairy cow breeds: Holstein and Nordic Reds. Host genomic data consisted of both 50 k and 150 k SNP arrays. Although several traits were analyzed by the original authors, here, we considered only methane emission as key phenotype for associating microbial communities and host genetic factors. The Synomics Insights platform is based on combinatorial methods that can identify taxa that are differentially abundant between animals showing high or low methane emission or RFI. Focusing exclusively on enriched taxa, for methane emission, the study identified 26 order-level taxa that combinatorial networks reported as significantly enriched either in high or low emitters. Additionally, a Z-test on proportions found 21/26 (81%) of these taxa were differentially enriched between high and low emitters (p value <.05). In particular, the phylum of Proteobacteria and the order Desulfovibrionales were found enriched in high emitters while the order Veillonellales was found to be more abundant in low emitters as previously reported for cattle (Wallace et al., 2015). In comparison, using the publicly available tool ANCOM only the order Methanosarcinales could be identified as differentially abundant between the two groups. We also investigated a link between host genome and rumen microbiome by applying our Synomics Insights platform and comparing it with an industry standard GWAS method. This resulted in the identification of genetic determinants in cows that are associated with changes in heritable components of the rumen microbiome. Only four key SNPs were found by both our platform and GWAS, whereas the Synomics Insights platform identified 1,290 significant SNPs that were not found by GWAS. Gene Ontology (GO) analysis found transcription factor as the dominant biological function. We estimated heritability of a core 73 taxa from the original set of 150 core order-level taxonomies and showed that some species are medium to highly heritable (0.25–0.62), paving the way for selective breeding of animals with desirable core microbiome characteristics. We identified a set of 113 key SNPs associated with >90% of these core heritable taxonomies. Finally, we have characterized a small set (<10) of SNPs strongly associated with key heritable bacterial orders with known role in methanogenesis, such as Desulfobacterales and Methanobacteriales.

Phenotypic differences for growth, feed efficiency, and age of first calving of Brazilian zebu females

This study investigated phenotypic differences of zebu females from four breeds using variables of growth, feed efficiency, and age at first calving. Weights throughout the life were recorded, and a growth curve was fitted using the Gompertz model. The growth was also evaluated at standardized ages (205, 365, and 550 days) using the body weight and the total and daily weight gains. The Kleiber index and age at first calving were used as measures of feed efficiency and sexual precocity, respectively, totaling 25 variables. New variables were created using the factor analysis and used in new multivariate analyzes. Only six factors explained 95.41% of the total variance and were used for the subsequent analyses. The factors were defined as maturity, precocity, feed efficiency postweaning, feed efficiency post 1 year of age, puberty, and birth weight. There were differences between breeds according to the multivariate analysis of variance. Each breed appeared in a quadrant on the Biplot graph, showing relationship with different factors, demonstrating the diversity of zebu females. There is a difference in growth, feed efficiency, and sexual precocity in Brazilian zebu females, allowing the identification of potentials of the animals and help breeders and decision-makers.

Integrated meta-omics reveals new ruminal microbial features associated with feed efficiency in dairy cattle

BACKGROUND

As the global population continues to grow, competition for resources between humans and livestock has been intensifying. Increasing milk protein production and improving feed efficiency are becoming increasingly important to meet the demand for high-quality dairy protein. In a previous study, we found that milk protein yield in dairy cows was associated with the rumen microbiome. The objective of this study was to elucidate the potential microbial features that underpins feed efficiency in dairy cows using metagenomics, metatranscriptomics, and metabolomics.

RESULTS

Comparison of metagenomic and metatranscriptomic data revealed that the latter was a better approach to uncover the associations between rumen microbial functions and host performance. Co-occurrence network analysis of the rumen microbiome revealed differential microbial interaction patterns between the animals with different feed efficiency, with high-efficiency animals having more and stronger associations than low-efficiency animals. In the rumen of high-efficiency animals, Selenomonas and members of the Succinivibrionaceae family positively interacted with each other, functioning as keystone members due to their essential ecological functions and active carbohydrate metabolic functions. At the metabolic level, analysis using random forest machine learning suggested that six ruminal metabolites (all derived from carbohydrates) could be used as metabolic markers that can potentially differentiate efficient and inefficient microbiomes, with an accuracy of prediction of 95.06%.

CONCLUSIONS

The results of the current study provided new insights into the new ruminal microbial features associated with feed efficiency in dairy cows, which may improve the ability to select animals for better performance in the dairy industry. The fundamental knowledge will also inform future interventions to improve feed efficiency in dairy cows. Video Abstract.

Dose-dependent effect of plants of the Lamiaceae family on the concentration of methane, fatty acids and nitrogen in the ecosystem in vitro

Fermentation processes in the rumen of ruminants determine how much final metabolites and their derivatives will be formed, which are necessary for the full development of the organism, the level of productivity, and also affect the level of formation of endogenous substances, namely, greenhouse gas emissions. These criteria lead us to the search for new feed products that improve the metabolic processes of the rumen and the digestive system as a whole, so phyto-substances can serve as an alternative. The article presents the results of in vitro study of the influence of Salviae folia, Scutellaria baicalensis, Oríganum vulgáre on formation of methane, synthesis of volatile fatty acids and nitrogen, as the main indicator parameters of the enzymatic activity of the rumen of ruminants. It was found that when using phyto- substances: Salviae folia and Scutellaria baicalensis, more acetic and propionic acid was formed, Oríganum vulgare in various dosages shifted towards propionic and valeric acid. Formation of a larger amount of microbial protein (P≤0.05) with use of Salviae folia, Scutellaria baicalensis, Oríganum vulgáre in various dosages was established. Methane production decreased with use of Oríganum vulgáre.

Genome-wide association study for methane emission traits in Danish Holstein cattle

Selecting for lower methane emitting cows requires insight into the most biologically relevant phenotypes for methane emission, which are close to the breeding goal. Several methane phenotypes have been suggested over the last decade. However, the (dis)similarity of their underlying genetic architecture and correlation structures are poorly understood. Therefore, the objective of this study was to test association of SNP and genomic regions through GWAS on 8 CH₄ emission traits in Danish Holstein cattle. The traits studied were methane concentration (MeC; ppm), methane production (MeP ; g/d), 2 definitions of residual methane (RMETc and RMETp: MeC and MeP regressed on metabolic body weight and energy-corrected milk, respectively), 2 definitions of methane intensity (MeI; MeIc = MeC/ECM and MeIp = MeP/ECM); 2 definitions of methane yield per kilogram of dry matter intake (MeY; MeYc = MeC/dry matter intake and MeYp = MeP/dry matter intake). A total of 1,962 cows with genotypes (Illumina BovineSNP50 Chip or Eurogenomic custom SNP chip) and repeated records of the above-mentioned 8 methane traits were analyzed. Strong associations were found with 3 traits (MeC, MeP, and MeYc) on chromosome 13 and with 5 traits (MeC, MeP, MeIp, MeYp, and MeYc) on chromosome 26. For MeIc, MeIp, RMETc, MeYc, and MeYp, some suggestive association signals were identified on chromosome 1. Genomic segments of 1 Mbp (n = 2,525) were tested for their association with these traits, which identified between 33 to 54 significantly associated regions. In a pairwise comparison, MeC and MeP were the traits that shared the highest number of significant segments (17). The same trend was observed when comparing SNP significantly associated with the traits MeC and MeP shared from 23 to 25 SNP (most of which were located in chromosomes 11, 13, and 26). Based on our results on GWAS and genetic correlations, we conclude that MeC is (genetically) more closely linked to MeP than any of the other methane traits analyzed.

Apart From the Diet, the Ruminal Microbiota of Lambs Is Modified in Relation to Their Genetic Potential for Feed Efficiency or Feeding Behavior

Using two successive types of diets (100% concentrate and 67% forage), this study explores the relationship between the ruminal microbiota of 78 Romane lambs and their feed efficiency (residual feed intake trait) or feeding behavior (feeding rate trait). Analysis was carried out phenotypically by correlating feed efficiency or feeding behavior traits with the relative abundance of bacteria at the phylum, family, and genus levels, and then genetically by comparing the microbiota of lambs selected for extreme breeding values for residual feed intake or feeding rate. Our results confirmed the major effect of diet on the ruminal microbiota composition. The microbiota of lambs consuming a forage-based diet was distinguished by higher microbial diversity and also by higher relative abundance of Firmicutes, whereas Bacteriodetes and Actinobacteria were relatively more abundant in the microbiota of lambs consuming a concentrate-based diet. Moreover, the comparison of lambs divergent for residual feed intake breeding values revealed that regardless of diet, more efficient lambs possessed a ruminal microbiota enriched in Coprococcus, Moryella, [Eubacterium] Brachy group, and [Eubacterium] hallii group, but depleted in Lachnospiraceae FD2005 and Shuttleworthia. The connection between microbiota composition and feeding rate was more tenuous, with no link between the abundance of particular genera and lambs genetically divergent for feeding rate.

An alternative interpretation of residual feed intake by phenotypic recursive relationships in dairy cattle

There has been increasing interest in residual feed intake (RFI) as a measure of net feed efficiency in dairy cattle. Residual feed intake phenotypes are obtained as residuals from linear regression encompassing relevant factors (i.e., energy sinks) to account for body tissue mobilization. By rearranging the single-trait linear regression, we showed a causal RFI interpretation underlying the linear regression for RFI. It postulates recursive effects in energy allocation from energy sinks on dry matter intake, but the feedback or simultaneous effects are nonexistent. A Bayesian recursive structural equation model was proposed for directly predicting RFI and energy sinks and estimating relevant genetic parameters simultaneously. A simplified Markov chain Monte Carlo algorithm was described. The recursive model is asymptotically equivalent to one-step linear regression for RFI, yet extends the analytical capacity to multiple-trait analysis.

In Vitro Incubations Do Not Reflect In Vivo Differences Based on Ranking of Low and High Methane Emitters in Dairy Cows

This study evaluated if ranking dairy cows as low and high CH₄ emitters using the GreenFeed system (GF) can be replicated in in vitro conditions using an automated gas system and its possible implications in terms of fermentation balance. Seven pairs of low and high emitters fed the same diet were selected on the basis of residual CH₄ production, and rumen fluid taken from each pair incubated separately in the in vitro gas production system. In total, seven in vitro incubations were performed with inoculums taken from low and high CH₄ emitting cows incubated in two substrates differing in forage-to-concentrate proportion, each without or with the addition of cashew nutshell liquid (CNSL) as an inhibitor of CH₄ production. Except for the aimed differences in CH₄ production, no statistical differences were detected among groups of low and high emitters either in in vivo animal performance or rumen fermentation profile prior to the in vitro incubations. The effect of in vivo ranking was poorly replicated in in vitro conditions after 48 h of anaerobic fermentation. Instead, the effects of diet and CNSL were more consistent. The inclusion of 50% barley in the diet (SB) increased both asymptotic gas production by 17.3% and predicted in vivo CH₄ by 26.2%, when compared to 100% grass silage (S) substrate, respectively. The SB diet produced on average more propionate (+28 mmol/mol) and consequently less acetate compared to the S diet. Irrespective of CH₄ emitter group, CNSL decreased predicted in vivo CH₄ (26.7 vs. 11.1 mL/ g of dry matter; DM) and stoichiometric CH₄ (CH₄VFA; 304 vs. 235 moles/mol VFA), with these being also reflected in decreased total gas production per unit of volatile fatty acids (VFA). Microbial structure was assessed on rumen fluid sampled prior to in vitro incubation, by sequencing of the V4 region of 16S rRNA gene. Principal coordinate analysis (PCoA) on operational taxonomic unit (OTU) did not show any differences between groups. Some differences appeared of relative abundance between groups in some specific OTUs mainly related to Prevotella. Genus Methanobrevibacter represented 93.7 ± 3.33% of the archaeal sequences. There were no clear differences between groups in relative abundance of Methanobrevibacter.

The potential for mitigation of methane emissions in ruminants through the application of metagenomics, metabolomics, and other -OMICS technologies

Ruminant supply chains contribute 5.7 gigatons of CO_2-eq per annum, which represents approximately 80% of the livestock sector emissions. One of the largest sources of emission in the ruminant sector is methane (CH₄), accounting for approximately 40% of the sectors total emissions. With climate change being a growing concern, emphasis is being put on reducing greenhouse gas emissions, including those from ruminant production. Various genetic and environmental factors influence cattle CH₄ production, such as breed, genetic makeup, diet, management practices, and physiological status of the host. The influence of genetic variability on CH₄ yield in ruminants indicates that genomic selection for reduced CH₄ emissions is possible. Although the microbiology of CH₄ production has been studied, further research is needed to identify key differences in the host and microbiome genomes and how they interact with one another. The advancement of “-omics” technologies, such as metabolomics and metagenomics, may provide valuable information in this regard. Improved understanding of genetic mechanisms associated with CH₄ production and the interaction between the microbiome profile and host genetics will increase the rate of genetic progress for reduced CH₄ emissions. Through a systems biology approach, various “-omics” technologies can be combined to unravel genomic regions and genetic markers associated with CH₄ production, which can then be used in selective breeding programs. This comprehensive review discusses current challenges in applying genomic selection for reduced CH₄ emissions, and the potential for “-omics” technologies, especially metabolomics and metagenomics, to minimize such challenges. The integration and evaluation of different levels of biological information using a systems biology approach is also discussed, which can assist in understanding the underlying genetic mechanisms and biology of CH₄ production traits in ruminants and aid in reducing agriculture’s overall environmental footprint.

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.

Estimating methane coefficients to predict the environmental impact of traits in the Australian dairy breeding program

The dairy industry has been scrutinized for the environmental impact associated with rearing and maintaining cattle for dairy production. There are 3 possible opportunities to reduce emissions through genetic selection: (1) a direct methane trait, (2) a reduction in replacements, and (3) an increase in productivity. Our aim was to estimate the independent effects of traits in the Australian National Breeding Objective on the gross methane production and methane intensity (EI) of the Australian dairy herd of average genetic potential. Based on similar published research, the traits determined to have an effect on emissions include production, fertility, survival, health, and feed efficiency. The independent effect of each trait on the gross emissions produced per animal due to genetic improvement and change in EI due to genetic improvement (intensity value, IV) were estimated and compared. Based on an average Australian dairy herd, the gross emissions emitted per cow per year were 4,297.86 kg of carbon dioxide equivalents (CO₂-eq). The annual product output, expressed in protein equivalents (protein-eq), and EI per cow were 339.39 kg of protein-eq and 12.67 kg of CO₂-eq/kg of protein-eq, respectively. Of the traits included in the National Breeding Objective, genetic progress in survival and feed saved were consistently shown to result in a favorable environmental impact. Conversely, production traits had an unfavorable environmental impact when considering gross emissions, and favorable when considering EI. Fertility had minimal impact as its effects were primarily accounted for through survival. Mastitis resistance only affected IV coefficients and to a very limited extent. These coefficients may be used in selection indexes to apply emphasis on traits based on their environmental impact, as well as applied by governments and stakeholders to track trends in industry emissions. Although initiatives are underway to develop breeding values to reduce methane by combining small methane data sets internationally, alternative options to reduce emissions by utilizing selection indexes should be further explored.

Relationships among feed efficiency traits across production segments and production cycles in cattle

Understanding the relationships between feed efficiency traits measured in different stages of production is necessary to improve feed efficiency across the beef value chain. The objective of this study was to evaluate relationships among feed efficiency traits measured as growing heifers and breeding females and in their progeny in three full production cycles, and relationships of dam residual feed intake (RFI) with lifetime and lifecycle cow efficiency traits. Data were collected on 160 mixed-breed heifers from 240 d of age to weaning of their third progeny, and postweaning performance of progeny until harvest in experiments initiated in 1953, 1954, 1959, 1964, 1969, and 1974. Individual feed offered was recorded daily, and feed refusals measured every 28 d. Milk yield was measured at 14-d intervals throughout lactation by machine or hand milking. Females and progeny were weighed at 28-d intervals and progeny were harvested at a constant endpoint of live grade or age depending upon the experiment. Feed efficiency traits of RFI and residual BW gain (RG) were computed as the residual from linear regression for developing heifers, dams (RFI and residual energy-corrected milk [RECM]), and postweaning progeny. Feed:gain ratio (FCR) was computed for developing heifers and postweaning progeny, and feed:milk energy ratio (FME) was computed for dams. Various measures of cow efficiency were calculated on either a life cycle or lifetime basis using ratios of progeny and dam weight outputs to progeny and dam feed inputs. Pearson correlations were computed among traits adjusted for a random year-breed-diet group effect. Heifer RFI (0.74) and RG (-0.32) were correlated (P ≤ 0.05) with dam RFI in parity 1 only, but were not correlated (P > 0.05) with dam RECM in any parity. Heifer RFI was correlated (P ≤ 0.05) with progeny RFI (0.17) in parity 3 only. Heifer FCR was not correlated with dam FME or progeny FCR in any parity. Dam RFI was weakly correlated (r = 0.25 to 0.36; P ≤ 0.05) among parities, whereas dam FME and RECM were strongly correlated (r = 0.49 to 0.72; P ≤ 0.05) among parities. Dam RFI in parity 1 and 2 was weakly correlated (r = -0.20 to -0.33; P ≤ 0.05) with cow efficiency ratios that included dam weight as an output, whereas dam RFI in parity 3 was not correlated with any cow efficiency ratio. In conclusion, feed efficiency traits were poorly correlated across production segments, but moderately repeatable across production cycles.