Cattle selected for lower residual feed intake have reduced daily methane production

Effect of dietary restriction and subsequent re-alimentation on the transcriptional profile of bovine ruminal epithelium

Compensatory growth (CG) is utilised worldwide in beef production systems as a management approach to reduce feed costs. However the underlying biology regulating the expression of CG remains to be fully elucidated. The objective of this study was to examine the effect of dietary restriction and subsequent re-alimentation induced CG on the global gene expression profile of ruminal epithelial papillae. Holstein Friesian bulls (n = 60) were assigned to one of two groups: restricted feed allowance (RES; n = 30) for 125 days (Period 1) followed by ad libitum access to feed for 55 days (Period 2) or (ii) ad libitum access to feed throughout (ADLIB; n = 30). At the end of each period, 15 animals from each treatment were slaughtered and rumen papillae harvested. mRNA was isolated from all papillae samples collected. cDNA libraries were then prepared and sequenced. Resultant reads were subsequently analysed bioinformatically and differentially expressed genes (DEGs) are defined as having a Benjamini-Hochberg P value of <0.05. During re-alimentation in Period 2, RES animals displayed CG, growing at 1.8 times the rate of their ADLIB contemporary animals in Period 2 (P < 0.001). At the end of Period 1, 64 DEGs were identified between RES and ADLIB, with only one DEG identified at the end of Period 2. When analysed within RES treatment (RES, Period 2 v Period 1), 411 DEGs were evident. Genes identified as differentially expressed in response to both dietary restriction and subsequent CG included those involved in processes such as cellular interactions and transport, protein folding and gene expression, as well as immune response. This study provides an insight into the molecular mechanisms underlying the expression of CG in rumen papillae of cattle; however the results suggest that the role of the ruminal epithelium in supporting overall animal CG may have declined by day 55 of re-alimentation.

Biomethane: The energy storage, platform chemical and greenhouse gas mitigation target

Results in three areas of anaerobic microbiology in which methane formation and utilization plays central part are reviewed. a.) Bio-methane formation by reduction of carbon dioxide in the power-to-gas process and the various possibilities of improvement of the process is a very intensively studied topic recently. From the numerous potential methods of exploiting methane of biological origin two aspects are discussed in detail. b.) Methane can serve as a platform chemical in various chemical and biochemical synthetic processes. Particular emphasis is put on the biochemical conversion pathways involving methanotrophs and their methane monooxygenase-catalyzed reactions leading to various small molecules and polymeric materials such as extracellular polysaccharides, polyhydroxyalkanoates and proteins. c.) The third area covered concerns methane-consuming reactions and methane emission mitigation. These investigations comprise the anaerobic microbiology of ruminants and approaches to diminishing methane emissions from ruminant animals.

The ruminal microbiome associated with methane emissions from ruminant livestock

Methane emissions from ruminant livestock contribute significantly to the large environmental footprint of agriculture. The rumen is the principal source of methane, and certain features of the microbiome are associated with low/high methane phenotypes. Despite their primary role in methanogenesis, the abundance of archaea has only a weak correlation with methane emissions from individual animals. The composition of the archaeal community appears to have a stronger effect, with animals harbouring the Methanobrevibacter gottschalkii clade tending to be associated with greater methane emissions. Ciliate protozoa produce abundant H₂, the main substrate for methanogenesis in the rumen, and their removal (defaunation) results in an average 11% lower methane emissions in vivo, but the results are not consistent. Different protozoal genera seem to result in greater methane emissions, though community types (A, AB, B and O) did not differ. Within the bacteria, three different ‘ruminotypes’ have been identified, two of which predispose animals to have lower methane emissions. The two low-methane ruminotypes are generally characterized by less abundant H₂-producing bacteria. A lower abundance of Proteobacteria and differences in certain Bacteroidetes and anaerobic fungi seem to be associated with high methane emissions. Rumen anaerobic fungi produce abundant H₂ and formate, and their abundance generally corresponds to the level of methane emissions. Thus, microbiome analysis is consistent with known pathways for H₂ production and methanogenesis, but not yet in a predictive manner. The production and utilisation of formate by the ruminal microbiota is poorly understood and may be a source of variability between animals.

Application of meta-omics techniques to understand greenhouse gas emissions originating from ruminal metabolism

Methane emissions from ruminal fermentation contribute significantly to total anthropological greenhouse gas (GHG) emissions. New meta-omics technologies are beginning to revolutionise our understanding of the rumen microbial community structure, metabolic potential and metabolic activity. Here we explore these developments in relation to GHG emissions. Microbial rumen community analyses based on small subunit ribosomal RNA sequence analysis are not yet predictive of methane emissions from individual animals or treatments. Few metagenomics studies have been directly related to GHG emissions. In these studies, the main genes that differed in abundance between high and low methane emitters included archaeal genes involved in methanogenesis, with others that were not apparently related to methane metabolism. Unlike the taxonomic analysis up to now, the gene sets from metagenomes may have predictive value. Furthermore, metagenomic analysis predicts metabolic function better than only a taxonomic description, because different taxa share genes with the same function. Metatranscriptomics, the study of mRNA transcript abundance, should help to understand the dynamic of microbial activity rather than the gene abundance; to date, only one study has related the expression levels of methanogenic genes to methane emissions, where gene abundance failed to do so. Metaproteomics describes the proteins present in the ecosystem, and is therefore arguably a better indication of microbial metabolism. Both two-dimensional polyacrylamide gel electrophoresis and shotgun peptide sequencing methods have been used for ruminal analysis. In our unpublished studies, both methods showed an abundance of archaeal methanogenic enzymes, but neither was able to discriminate high and low emitters. Metabolomics can take several forms that appear to have predictive value for methane emissions; ruminal metabolites, milk fatty acid profiles, faecal long-chain alcohols and urinary metabolites have all shown promising results. Rumen microbial amino acid metabolism lies at the root of excessive nitrogen emissions from ruminants, yet only indirect inferences for nitrogen emissions can be drawn from meta-omics studies published so far. Annotation of meta-omics data depends on databases that are generally weak in rumen microbial entries. The Hungate 1000 project and Global Rumen Census initiatives are therefore essential to improve the interpretation of sequence/metabolic information.

Effect of different forage types and concentrate levels on energy conversion, enteric methane production, and animal performance of Holstein × Zebu heifers

The aim of this study was to evaluate the effect of diets containing corn silage (CS) or sugarcane (SC) with 300 or 500 g/kg of concentrate (on a DM basis) on energy conversion, enteric methane (CH4) production, and the animal performance of Holstein × Zebu heifers. An experiment was conducted while using comparative slaughter. Twenty Holstein × Zebu heifers with an average age of 12 ± 1.0 months and an average bodyweight of 218 ± 36.5 kg were used. Four heifers were assigned to a baseline group, whereas the remaining 16 heifers were distributed in a completely randomised design using a 2 × 2 factorial scheme (n = 4), with two types of roughage (CS or SC) and two levels of concentrate (300 or 500 g/kg) on a DM basis of the diet over the course of 112 days. For the evaluation of the apparent total-tract digestibility of diets and energy losses, a digestibility assay was performed by using the total collection of faeces and urine over three consecutive days. The enteric CH4 production was quantified by continuous analysis of regular samples of air excreted by the animals throughout the day. The greatest (P < 0.05) average daily gain was observed for heifers that were fed CS-based diets or with 500 g/kg of concentrate. Greater (P < 0.05) daily CH4 emissions were observed for heifers that were fed 500 g/kg of concentrate; CH4 production as a function of DM intake was greater (P < 0.05) for heifers that were fed SC-based diets. The efficiency of the conversion from digestible energy (DE) to metabolisable energy (ME) was not influenced (P > 0.05) by variables that were analysed in this study. However, the mean value that was observed in the present study was above those values proposed by the main evaluation systems of feedstuffs and nutrient requirements of ruminants. Therefore, we concluded that CS-based diets allow for better animal performance of Holstein × Zebu heifers in relation to SC-based diets. Also, the increased concentrate improves the performance of growing heifers. A greater inclusion of concentrate in SC-based diets can allow for a reduction of CH4 emissions per consumed unit and per gain unit. The mean suggested value for the ME : DE ratio based on this study is 0.86. However, more studies are necessary to validate this result.

The impact of genetic selection on greenhouse-gas emissions in Australian dairy cattle

In Australia, dairy cattle account for ~12% of the nation’s agricultural greenhouse-gas (GHG) emissions. Genetic selection has had a positive impact, reducing GHG emissions from dairy systems mainly due to increased production per cow, which has led to (1) requiring fewer cows to produce the same amount of milk and (2) lowering emissions per unit of milk produced (emission intensity). The objective of the present study was to evaluate the consequences of previous and current genetic-selection practices on carbon emissions, using realised and predicted responses to selection for key traits that are included in the Australian national breeding objective. A farm model was used to predict the carbon dioxide equivalent (CO2-eq) emissions per unit change of these traits, while holding all other traits constant. Estimates of the realised change in annual CO2-eq emissions per cow over the past decade were made by multiplying predicted CO2-eq emissions per unit change of each trait under selection by the realised rates of genetic gain in each of those traits. The total impact is estimated to be an increase of 55 kg CO2-eq/cow.year after 10 years of selection. The same approach was applied to future CO2-eq emissions, except predicted rates of genetic gain assumed to occur over the next decade through selection on the Balanced Performance Index (BPI) were used. For an increase of AU$100 in BPI (~10 years of genetic improvement), we predict that the increase of per cow emissions will be reduced to 37 kg CO2-eq/cow.year. Since milk-production traits are a large part of the breeding goal, the GHG emitted per unit of milk produced will reduce as a result of improvements in efficiency and dilution of emissions per litre of milk produced at a rate estimated to be 35.7 g CO2-eq/kg milk solids per year in the past decade and is predicted to reduce to 29.5 g CO2-eq/kg milk solids per year after a conservative 10-year improvement in BPI (AU$100). In fact, cow numbers have decreased over the past decade and production has increased; altogether, we estimate that the net impact has been a reduction of CO2-eq emissions of ~1.0% in total emissions from the dairy industry per year. Using two future scenarios of either keeping the number of cows or amount of product static, we predict that net GHG emissions will reduce by ~0.6%/year of total dairy emissions if milk production remains static, compared with 0.3%/year, if cow numbers remain the same and there is genetic improvement in milk-production traits.

Partitioning of energy and nitrogen in lactating primiparous and multiparous Holstein–Friesian cows with divergent residual feed intake

Residual feed intake (RFI) is the difference between an animal’s actual and expected feed intake. Two experiments were conducted comparing energy and nitrogen partitioning in mid-lactation, in Holstein–Friesian cows selected for high or low RFI measured previously as growing calves. Each experiment used 16 cows (8 high-RFI and 8 low-RFI); the first used primiparous (PP) cows and the second used multiparous (MP) cows. Cows were housed individually for 4 days in metabolism stalls, then open-circuit respiration chambers for 3 days. Each cow was offered ad libitum lucerne hay cubes plus 6 kg DM per day of crushed wheat grain. Individual feed intake, milk yield, milk composition and faecal and urine output were measured. Methane and carbon dioxide output and oxygen consumption were measured in the chambers. In MP cows, a greater proportion of energy intake was partitioned to milk and less to heat in low-RFI than high-RFI cows. The proportion of gross-energy intake per kilogram metabolic bodyweight partitioned to milk production was greater and the proportion partitioned to methane and heat production was lower in MP than in PP cows. Energy from tissue mobilisation was not affected by RFI or parity. The amount of nitrogen consumed from feed was greater in MP than PP cows. As a percentage of N intake, N partitioned to milk was greater in PP than in MP cows, but there were no overall effects of RFI on N partitioning. However, there was a trend towards a positive association between N excreted in the urine and RFI, which could have environmental implications. Both RFI and parity were associated with variation in energy and nitrogen partitioning and should be examined in a larger subset of animals in future.

Grazing management: setting the table, designing the menu and influencing the diner

Pastoral livestock-production systems are under increasing environmental, social and consumer pressures to reduce environmental impacts and to enhance biodiversity and animal welfare. At the same time, farmers face the challenge of managing grazing, which is intimately linked with profitability. Recent advances in understanding grazing patterns and nutritional ecology may help alleviate such pressures. For instance, by managing grazing to (1) manipulate links between ingestive–digestive decisions and temporal patterns of nutrient excretion, (2) provide phytochemically diverse diets at appropriate temporal (the menu) and spatial (the table) scales and (3) influence the behaviour of animals (the diners) on the basis of their specific ‘personalities’ and needs, to overcome or enhance animal differences, thereby enhancing their and farm productivity and welfare, as well as our health. Under pastoral systems, synergies between animals’ and farmers’ grazing decisions have the potential to offer greater benefits to the animal, the environment and the farm than does simple and parsimonious grazing management based on a single component of the system. In the present review, we look at grazing and its management through an alternate lens, drawing ideas and hypotheses to stimulate thinking, dialogue and discussions that we anticipate will evolve into innovative research programs and grazing strategies. To do so, we combined experimental and observational studies from a wide range of disciplines with simulation-modelling exercises. We envisage a more holistic approach to manage grazing based on recent advances in the understanding of the nutritional ecology of grazing animals, and propose management practices that may enable pastoral livestock-production systems to evolve continually as complex creative systems.

Daily methane emissions and emission intensity of grazing beef cattle genetically divergent for residual feed intake

As daily methane production (DMP; g CH4/day) is strongly correlated with dry matter intake (DMI), the breeding of cattle that require less feed to achieve a desired rate of average daily gain (ADG) by selection for a low residual feed intake (RFI) can be expected to reduce DMP and also emission intensity (EI; g CH4/kg ADG). An experiment was conducted to compare DMP and EI of Angus cattle genetically divergent for RFI and 400-day weight (400dWT). In a 6-week grazing study, 64 yearling-age cattle (30 steers, 34 heifers) were grazed on temperate pastures, with heifers and steers grazing separate paddocks. Liveweight (LW) was monitored weekly and DMP of individual cattle was measured by a GreenFeed emission monitoring unit in each paddock. Thirty-nine of the possible 64 animals had emission data recorded for 15 or more days, and only data for these animals were analysed. For these cattle, regression against their mid-parent estimated breeding value (EBV) for post-weaning RFI (RFI-EBV) showed that a lower RFI-EBV was associated with higher LW at the start of experiment. Predicted dry matter intake (pDMI), predicted DMP (pDMP) and measured DMP (mDMP) were all negatively correlated with RFI-EBV (P < 0.05), whereas ADG, EI, predicted CH4 yield (pMY; g CH4/kg DMI) were not correlated with RFI-EBV (P > 0.1). Daily CH4 production was positively correlated with animal LW and ADG (P < 0.05). The associations between ADG and its dependent traits EI and pMY and predicted feed conversion ratio (kg pDMI/kg ADG) were strongly negative (r = –0.82, –0.57 and –0.85, P < 0.001) implying that faster daily growth by cattle was accompanied by lower EI, MY and feed conversion ratio. These results show that cattle genetically divergent for RFI do not necessarily differ in ADG, EI or pMY on pasture and that, if heavier, cattle with lower RFI-EBV can actually have higher DMP while grazing moderate quality pastures.

Effect of divergence in phenotypic residual feed intake on methane emissions, ruminal fermentation, and apparent whole-tract digestibility of beef heifers across three contrasting diets

This study aimed to examine the effect of divergent phenotypic ranking for residual feed intake (RFI) on ruminal CH emissions, diet digestibility, and indices of ruminal fermentation in heifers across 3 commercially relevant diets. Twenty-eight Limousin × Friesian heifers were used and were ranked on the basis of phenotypic RFI: 14 low-RFI and 14 high-RFI animals. Ruminal CH emissions were estimated over 5 d using the SF tracer gas technique on 3 successive occasions: 1) at the end of a 6-wk period (Period 1) on grass silage (GS), 2) at the end of an 8-wk period (Period 2) at pasture, and 3) at the end of a 5-wk period (Period 3) on a 30:70 corn silage:concentrate total mixed ration (TMR). Animals were allowed ad libitum access to feed and water at all times. Individual DMI was estimated during CH measurement and rumen samples were taken at the end of each CH measurement period. Diet type affected all feed intake and CH traits measured ( < 0.01) but was unavoidably confounded with animal age/size and experimental period. Correlation coefficients between RFI and DMI were significant ( < 0.05) only when animals were fed the TMR. Daily CH correlated with DMI ( = 0.42, < 0.05) only when animals grazed pasture. Daily DMI was lower in low-RFI animals ( = 0.047) but only when expressed as grams per kilogram metabolic BW. Absolute CH emissions did not differ between RFI groups ( > 0.05), but CH yield was greatest in low-RFI heifers ( = 0.03) as a proportion of both DMI and GE intake. Interactions between the main effects were observed ( < 0.05) for CP digestibility (CPD), DM digestibility (DMD), ruminal propionate, and the acetate:propionate ratio. Low-RFI animals had greater ( < 0.05) CPD and DMD than their high-RFI contemporaries when offered GS but not the other 2 diets. Low-RFI heifers also had greater OM digestibility ( = 0.027). Additionally, low-RFI heifers had a lower concentration of propionate ( < 0.05) compared with high-RFI heifers when fed GS, resulting in a greater ( < 0.05) acetate:propionate ratio. However, these differences were not evident for the other 2 diets. Energetically efficient animals do not have a lower ruminal methanogenic potential compared with their more inefficient counterparts and, indeed, some evidence to the contrary was found, which may reflect the greater nutrient digestive potential observed in low-RFI cattle.

Examination of the molecular control of ruminal epithelial function in response to dietary restriction and subsequent compensatory growth in cattle

BACKGROUND

The objective of this study was to investigate the effect of dietary restriction and subsequent compensatory growth on the relative expression of genes involved in volatile fatty acid transport, metabolism and cell proliferation in ruminal epithelial tissue of beef cattle. Sixty Holstein Friesian bulls (mean liveweight 370 ± 35 kg; mean age 479 ± 15 d) were assigned to one of two groups: (i) restricted feed allowance (RES; n = 30) for 125 d (Period 1) followed by ad libitum access to feed for 55 d (Period 2) or (ii) ad libitum access to feed throughout (ADLIB; n = 30). Target growth rate for RES was 0.6 kg/d during Period 1. At the end of each dietary period, 15 animals from each treatment group were slaughtered and ruminal epithelial tissue and liquid digesta harvested from the ventral sac of the rumen. Real-time qPCR was used to quantify mRNA transcripts of 26 genes associated with ruminal epithelial function. Volatile fatty acid analysis of rumen fluid from individual animals was conducted using gas chromatography.

RESULTS

Diet × period interactions were evident for genes involved in ketogenesis (BDH2, P = 0.017), pyruvate metabolism (LDHa, P = 0.048; PDHA1, P = 0.015) and cellular transport and structure (DSG1, P = 0.019; CACT, P = 0.027). Ruminal concentrations of propionic acid (P = 0.018) and n-valeric acid (P = 0.029) were lower in RES animals, compared with ADLIB, throughout the experiment. There was also a strong tendency (P = 0.064) toward a diet × period interaction for n-butyric with higher concentrations in RES animals, compared with ADLIB, during Period 1.

CONCLUSIONS

These data suggest that following nutrient restriction, the structural integrity of the rumen wall is compromised and there is upregulation of genes involved in the production of ketone bodies and breakdown of pyruvate for cellular energy. These results provide an insight into the potential molecular mechanisms regulating ruminal epithelial absorptive metabolism and growth following nutrient restriction and subsequent compensatory growth.

Changes throughout lactation in phenotypic and genetic correlations between methane emissions and milk fatty acid contents predicted from milk mid-infrared spectra

The aim of this study was to estimate phenotypic and genetic correlations between methane production (Mp) and milk fatty acid contents of first-parity Walloon Holstein cows throughout lactation. Calibration equations predicting daily Mp (g/d) and milk fatty acid contents (g/100 dL of milk) were applied on milk mid-infrared spectra related to Walloon milk recording. A total of 241,236 predictions of Mp and milk fatty acids were used. These data were collected between 5 and 305 d in milk in 33,555 first-parity Holstein cows from 626 herds. Pedigree data included 109,975 animals. Bivariate (i.e., Mp and a fatty acid trait) random regression test-day models were developed to estimate phenotypic and genetic parameters of Mp and milk fatty acids. Individual short-chain fatty acids (SCFA) and groups of saturated fatty acids, SCFA, and medium-chain fatty acids showed positive phenotypic and genetic correlations with Mp (from 0.10 to 0.16 and from 0.23 to 0.30 for phenotypic and genetic correlations, respectively), whereas individual long-chain fatty acids (LCFA), and groups of LCFA, monounsaturated fatty acids, and unsaturated fatty acids showed null to positive phenotypic and genetic correlations with Mp (from -0.03 to 0.13 and from -0.02 to 0.32 for phenotypic and genetic correlations, respectively). However, these correlations changed throughout lactation. First, de novo individual and group fatty acids (i.e., C4:0, C6:0, C8:0, C10:0, C12:0, C14:0, SCFA group) showed low phenotypic or genetic correlations (or both) in early lactation and higher at the end of lactation. In contrast, phenotypic and genetic correlations between Mp and C16:0, which could be de novo synthetized or derived from blood lipids, were more stable during lactation. This fatty acid is the most abundant fatty acid of the saturated fatty acid and medium-chain fatty acid groups of which correlations with Mp showed the same pattern across lactation. Phenotypic and genetic correlations between Mp and C17:0 and C18:0 were low in early lactation and increased afterward. Phenotypic and genetic correlations between Mp and C18:1 cis-9 originating from the blood lipids were negative in early lactation and increased afterward to become null from 18 wk until the end of lactation. Correlations between Mp and groups of LCFA, monounsaturated fatty acids, and unsaturated fatty acids showed a similar or intermediate pattern across lactation compared with fatty acids that compose them. Finally, these results indicate that correlations between Mp and milk fatty acids vary following lactation stage of the cow, a fact still often ignored when trying to predict Mp from milk fatty acid profile.

Utilization of macrominerals and trace elements in pregnant heifers with distinct feed efficiencies

The objective of the study was to evaluate utilization of dietary minerals and trace elements in pregnant heifers with distinct residual feed intakes (RFI). Feed intake, body weight (BW), and body composition traits were recorded in 36 crossbred heifers over a period of 37 wk, starting shortly after weaning at 8.3 (0.10; standard deviation) mo of age with an average BW of 276 (7.8) kg. Both BW and body composition were monitored regularly throughout the study, whereas individual feed intake was assessed during the last 84 d of the trial. Data recorded were used to calculate RFI for each heifer. Heifers were ranked based on RFI and assigned to high (n=14) or low (n=10) RFI groups. After the RFI study, 24 selected heifers [age 18.2 (0.14) mo; 87.5 (4.74) d in gestation; 497 (8.5) kg of BW] were used in an indirect digestibility trial (lignin as internal marker). Heifers were fed a ration containing corn silage, haylage, and a mineral premix in which Ca, P, K, Na, Mg, S, Cu, Fe, Mn, Mo, Se, Zn, and Co were provided in the diet according to National Research Council requirements of pregnant replacement heifers. The digestibility trial lasted 1 wk, during which samples of feces were gathered twice daily, and blood and liver biopsy samples were collected on the last day. We noted no significant differences between low- and high-RFI heifers in dry matter digestibility. Apparent absorption of Cu, Zn, and Mn was increased in heifers with low RFI, and apparent absorption of Co tended to be greater for these animals. Concentrations of macrominerals and trace elements in serum of pregnant heifers were similar for both groups except for Se, which was increased in the serum of low-RFI heifers. Liver concentrations of Cu, Fe, Mn, Mo, Se, and Zn did not differ between low- and high-RFI heifers. In conclusion, whereas improved absorption of some trace elements (Cu, Zn, Mn, and Co) and increased Se serum concentration appear to be associated with superior feed efficiency in pregnant heifers, further studies are needed to investigate the causality of such relationships.

Oral Samples as Non-Invasive Proxies for Assessing the Composition of the Rumen Microbial Community

Microbial community analysis was carried out on ruminal digesta obtained directly via rumen fistula and buccal fluid, regurgitated digesta (bolus) and faeces of dairy cattle to assess if non-invasive samples could be used as proxies for ruminal digesta. Samples were collected from five cows receiving grass silage based diets containing no additional lipid or four different lipid supplements in a 5 x 5 Latin square design. Extracted DNA was analysed by qPCR and by sequencing 16S and 18S rRNA genes or the fungal ITS1 amplicons. Faeces contained few protozoa, and bacterial, fungal and archaeal communities were substantially different to ruminal digesta. Buccal and bolus samples gave much more similar profiles to ruminal digesta, although fewer archaea were detected in buccal and bolus samples. Bolus samples overall were most similar to ruminal samples. The differences between both buccal and bolus samples and ruminal digesta were consistent across all treatments. It can be concluded that either proxy sample type could be used as a predictor of the rumen microbial community, thereby enabling more convenient large-scale animal sampling for phenotyping and possible use in future animal breeding programs aimed at selecting cattle with a lower environmental footprint.

RUMINANT NUTRITION SYMPOSIUM: Use of genomics and transcriptomics to identify strategies to lower ruminal methanogenesis

Globally, methane (CH4) emissions account for 40% to 45% of greenhouse gas emissions from ruminant livestock, with over 90% of these emissions arising from enteric fermentation. Reduction of carbon dioxide to CH4 is critical for efficient ruminal fermentation because it prevents the accumulation of reducing equivalents in the rumen. Methanogens exist in a symbiotic relationship with rumen protozoa and fungi and within biofilms associated with feed and the rumen wall. Genomics and transcriptomics are playing an increasingly important role in defining the ecology of ruminal methanogenesis and identifying avenues for its mitigation. Metagenomic approaches have provided information on changes in abundances as well as the species composition of the methanogen community among ruminants that vary naturally in their CH4 emissions, their feed efficiency, and their response to CH4 mitigators. Sequencing the genomes of rumen methanogens has provided insight into surface proteins that may prove useful in the development of vaccines and has allowed assembly of biochemical pathways for use in chemogenomic approaches to lowering ruminal CH4 emissions. Metagenomics and metatranscriptomic analysis of entire rumen microbial communities are providing new perspectives on how methanogens interact with other members of this ecosystem and how these relationships may be altered to reduce methanogenesis. Identification of community members that produce antimethanogen agents that either inhibit or kill methanogens could lead to the identification of new mitigation approaches. Discovery of a lytic archaeophage that specifically lyses methanogens is 1 such example. Efforts in using genomic data to alter methanogenesis have been hampered by a lack of sequence information that is specific to the microbial community of the rumen. Programs such as Hungate1000 and the Global Rumen Census are increasing the breadth and depth of our understanding of global ruminal microbial communities, steps that are key to using these tools to further define the science of ruminal methanogenesis.

A universal equation to predict methane production of forage-fed cattle in Australia

The methods for estimating methane emissions from cattle as used in the Australian national inventory are based on older data that have now been superseded by a large amount of more recent data. Recent data suggested that the current inventory emissions estimates can be improved. To address this issue, a total of 1034 individual animal records of daily methane production (MP) was used to reassess the relationship between MP and each of dry matter intake (DMI) and gross energy intake (GEI). Data were restricted to trials conducted in the past 10 years using open-circuit respiration chambers, with cattle fed forage-based diets (forage >70%). Results from diets considered to inhibit methanogenesis were omitted from the dataset. Records were obtained from dairy cattle fed temperate forages (220 records), beef cattle fed temperate forages (680 records) and beef cattle fed tropical forages (133 records). Relationships were very similar for all three production categories and single relationships for MP on a DMI or GEI basis were proposed for national inventory purposes. These relationships were MP (g/day) = 20.7 (±0.28) × DMI (kg/day) (R2 = 0.92, P < 0.001) and MP (MJ/day) = 0.063 (±0.008) × GEI (MJ/day) (R2 = 0.93, P < 0.001). If the revised MP (g/day) approach is used to calculate Australia’s national inventory, it will reduce estimates of emissions of forage-fed cattle by 24%. Assuming a global warming potential of 25 for methane, this represents a 12.6 Mt CO2-e reduction in calculated annual emissions from Australian cattle.

Climate Clever Beef: options to improve business performance and reduce greenhouse gas emissions in northern Australia

The Rangeland Journal – Climate Clever Beef special issue examines options for the beef industry in northern Australia to contribute to the reduction in global greenhouse gas (GHG) emissions and to engage in the carbon economy. Relative to its gross value (A$5 billion), the northern beef industry is responsible for a sizable proportion of national reportable GHG emissions (8–10%) through enteric methane, savanna burning, vegetation clearing and land degradation. The industry occupies large areas of land and has the potential to impact the carbon cycle by sequestering carbon or reducing carbon loss. Furthermore, much of the industry is currently not achieving its productivity potential, which suggests that there are opportunities to improve the emissions intensity of beef production. Improving the industry’s GHG emissions performance is important for its environmental reputation and may benefit individual businesses through improved production efficiency and revenue from the carbon economy. The Climate Clever Beef initiative collaborated with beef businesses in six regions across northern Australia to better understand the links between GHG emissions and carbon stocks, land condition, herd productivity and profitability. The current performance of businesses was measured and alternate management options were identified and evaluated. Opportunities to participate in the carbon economy through the Australian Government’s Emissions Reduction Fund (ERF) were also assessed. The initiative achieved significant producer engagement and collaboration resulting in practice change by 78 people from 35 businesses, managing more than 1 272 000 ha and 132 000 cattle. Carbon farming opportunities were identified that could improve both business performance and emissions intensity. However, these opportunities were not without significant risks, trade-offs and limitations particularly in relation to business scale, and uncertainty in carbon price and the response of soil and vegetation carbon sequestration to management. This paper discusses opportunities for reducing emissions, improving emission intensity and carbon sequestration, and outlines the approach taken to achieve beef business engagement and practice change. The paper concludes with some considerations for policy makers.

Milk mid-infrared spectra enable prediction of lactation-stage-dependent methane emissions of dairy cattle within routine population-scale milk recording schemes

Mitigating the proportion of energy intake lost as methane could improve the sustainability and profitability of dairy production. As widespread measurement of methane emissions is precluded by current in vivo methods, the development of an easily measured proxy is desirable. An equation has been developed to predict methane from the mid-infrared (MIR) spectra of milk within routine milk-recording programs. The main goals of this study were to improve the prediction equation for methane emissions from milk MIR spectra and to illustrate its already available usefulness as a high throughput phenotypic screening tool. A total of 532 methane measurements considered as reference data (430 ± 129 g of methane/day) linked with milk MIR spectra were obtained from 165 cows using the SF6 technique. A first derivative was applied to the MIR spectra. Constant (P0), linear (P1) and quadratic (P2) modified Legendre polynomials were computed from each cows stage of lactation (days in milk), at the day of SF6 methane measurement. The calibration model was developed using a modified partial least-squares regression on first derivative MIR data points × P0, first derivative MIR data points × P1, and first derivative MIR data points × P2 as variables. The MIR-predicted methane emissions (g/day) showed a calibration coefficient of determination of 0.74, a cross-validation coefficient of determination of 0.70 and a standard error of calibration of 66 g/day. When applied to milk MIR spectra recorded in the Walloon Region of Belgium (≈2 000 000 records), this equation was useful to study lactational, annual, seasonal, and regional methane emissions. We conclude that milk MIR spectra has potential to be used to conduct high throughput screening of lactating dairy cattle for methane emissions. The data generated enable monitoring of methane emissions and production characteristics across and within herds. Milk MIR spectra could now be used for widespread screening of dairy herds in order to develop management and genetic selection tools to reduce methane emissions.

Reducing the carbon footprint of Australian milk production by mitigation of enteric methane emissions

This review examines research aimed at reducing enteric methane emissions from the Australian dairy industry. Calorimeter measurements of 220 forage-fed cows indicate an average methane yield of 21.1 g methane (CH4)/kg dry matter intake. Adoption of this empirical methane yield, rather than the equation currently used in the Australian greenhouse gas inventory, would reduce the methane emissions attributed to the Australian dairy industry by ~10%. Research also indicates that dietary lipid supplements and feeding high amounts of wheat substantially reduce methane emissions. It is estimated that, in 1980, the Australian dairy industry produced ~185 000 t of enteric methane and total enteric methane intensity was ~33.6 g CH4/kg milk. In 2010, the estimated production of enteric methane was 182 000 t, but total enteric methane intensity had declined ~40% to 19.9 g CH4/kg milk. This remarkable decline in methane intensity and the resultant improvement in the carbon footprint of Australian milk production was mainly achieved by increased per-cow milk yield, brought about by the on-farm adoption of research findings related to the feeding and breeding of dairy cows. Options currently available to further reduce the carbon footprint of Australian milk production include the feeding of lipid-rich supplements such as cottonseed, brewers grains, cold-pressed canola, hominy meal and grape marc, as well as feeding of higher rates of wheat. Future technologies for further reducing methane emissions include genetic selection of cows for improved feed conversion to milk or low methane intensity, vaccines to reduce ruminal methanogens and chemical inhibitors of methanogenesis.

Infrared thermography as a tool to evaluate body surface temperature and its relationship with feed efficiency in Bos indicus cattle in tropical conditions

The aims of this study were to evaluate the use of infrared thermography (IRT) images as a tool for monitoring body surface temperature and to study its relationship with residual feed intake (RFI) in Nellore cattle. We also evaluated IRT as an indicator of feed efficiency in Bos indicus cattle. In this study, 144 Nellore steers were fed high-concentrate diets for 70 days to evaluate feedlot performance. We examined nine animals classified as high RFI and nine animals classified as low RFI by measuring rectal temperature (RT), respiratory frequency (RF), and IRT in the front, eye, ocular area, cheek, flank, ribs, rump, and front feet. The measurements were taken at 0700, 1200, and 1600 hours. The IRT temperatures measured at the eye, cheek, flank, ribs, rump, and front feet were positively associated with RF and RT. These results indicate that increases in the temperatures are associated with increased RF and RT. There was an effect in the RFI group in the front region where IRT correlates with RT. The front IRT for high-RFI cattle was lower (P < 0.01) than that for low-RFI cattle. The higher skin temperature measured by IRT for animals in the RFI group may be related to improved efficiency of thermoregulatory mechanisms because the RT remained lower in the low-RFI group. IRT can be used in the head for studies related to RFI in beef cattle.

Measuring Methane Production from Ruminants

Radiative forcing of methane (CH4) is significantly higher than carbon dioxide (CO2) and its enteric production by ruminant livestock is one of the major sources of greenhouse gas emissions. CH4 is also an important marker of farming productivity, because it is associated with the conversion of feed to product in livestock. Consequently, measurement of enteric CH4 is emerging as an important research topic. In this review, we briefly describe the conversion of carbohydrate to CH4 by the bacterial community within gut, and highlight some of the key host-microbiome interactions. We then provide a picture of current progress in techniques for measuring enteric CH4, the context in which these technologies are used, and the challenges faced. We also discuss solutions to existing problems and new approaches currently in development.

Estimation of genomic breeding values for residual feed intake in a multibreed cattle population

Residual feed intake (RFI) is a measure of the efficiency of animals in feed utilization. The accuracies of GEBV for RFI could be improved by increasing the size of the reference population. Combining RFI records of different breeds is a way to do that. The aims of this study were to 1) develop a method for calculating GEBV in a multibreed population and 2) improve the accuracies of GEBV by using SNP associated with RFI. An alternative method for calculating accuracies of GEBV using genomic BLUP (GBLUP) equations is also described and compared to cross-validation tests. The dataset included RFI records and 606,096 SNP genotypes for 5,614 Bos taurus animals including 842 Holstein heifers and 2,009 Australian and 2,763 Canadian beef cattle. A range of models were tested for combining genotype and phenotype information from different breeds and the best model included an overall effect of each SNP, an effect of each SNP specific to a breed, and a small residual polygenic effect defined by the pedigree. In this model, the Holsteins and some Angus cattle were combined into 1 "breed class" because they were the only cattle measured for RFI at an early age (6-9 mo of age) and were fed a similar diet. The average empirical accuracy (0.31), estimated by calculating the correlation between GEBV and actual phenotypes divided by the square root of estimated heritability in 5-fold cross-validation tests, was near to that expected using the GBLUP equations (0.34). The average empirical and expected accuracies were 0.30 and 0.31, respectively, when the GEBV were estimated for each breed separately. Therefore, the across-breed reference population increased the accuracy of GEBV slightly, although the gain was greater for breeds with smaller number of individuals in the reference population (0.08 in Murray Grey and 0.11 in Hereford for empirical accuracy). In a second approach, SNP that were significantly (P < 0.001) associated with RFI in the beef cattle genomewide association studies were used to create an auxiliary genomic relationship matrix for estimating GEBV in Holstein heifers. The empirical (and expected) accuracy of GEBV within Holsteins increased from 0.33 (0.35) to 0.39 (0.36) and improved even more to 0.43 (0.50) when using a multibreed reference population. Therefore, a multibreed reference population is a useful resource to find SNP with a greater than average association with RFI in 1 breed and use them to estimate GEBV in another breed.

The rumen microbial metagenome associated with high methane production in cattle

Background

Methane represents 16 % of total anthropogenic greenhouse gas emissions. It has been estimated that ruminant livestock produce ca. 29 % of this methane. As individual animals produce consistently different quantities of methane, understanding the basis for these differences may lead to new opportunities for mitigating ruminal methane emissions. Metagenomics is a powerful new tool for understanding the composition and function of complex microbial communities. Here we have applied metagenomics to the rumen microbial community to identify differences in the microbiota and metagenome that lead to high- and low-methane-emitting cattle phenotypes.

Methods

Four pairs of beef cattle were selected for extreme high and low methane emissions from 72 animals, matched for breed (Aberdeen-Angus or Limousin cross) and diet (high or medium concentrate). Community analysis was carried out by qPCR of 16S and 18S rRNA genes and by alignment of Illumina HiSeq reads to the GREENGENES database. Total genomic reads were aligned to the KEGG genes databasefor functional analysis.

Results

Deep sequencing produced on average 11.3 Gb per sample. 16S rRNA gene abundances indicated that archaea, predominantly Methanobrevibacter, were 2.5× more numerous (P = 0.026) in high emitters, whereas among bacteria Proteobacteria, predominantly Succinivibrionaceae, were 4-fold less abundant (2.7 vs. 11.2 %; P = 0.002). KEGG analysis revealed that archaeal genes leading directly or indirectly to methane production were 2.7-fold more abundant in high emitters. Genes less abundant in high emitters included acetate kinase, electron transport complex proteins RnfC and RnfD and glucose-6-phosphate isomerase. Sequence data were assembled de novo and over 1.5 million proteins were annotated on the subsequent metagenome scaffolds. Less than half of the predicted genes matched matched a domain within Pfam. Amongst 2774 identified proteins of the 20 KEGG orthologues that correlated with methane emissions, only 16 showed 100 % identity with a publicly available protein sequence.

Conclusions

The abundance of archaeal genes in ruminal digesta correlated strongly with differing methane emissions from individual animals, a finding useful for genetic screening purposes. Lower emissions were accompanied by higher Succinovibrionaceae abundance and changes in acetate and hydrogen production leading to less methanogenesis, as similarly postulated for Australian macropods. Large numbers of predicted protein sequences differed between high- and low-methane-emitting cattle. Ninety-nine percent were unknown, indicating a fertile area for future exploitation.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-2032-0) contains supplementary material, which is available to authorized users.

Is there a relationship between genetic merit and enteric methane emission rate of lactating Holstein-Friesian dairy cows?

The present study was undertaken to examine the effect of cow genetic merit on enteric methane (CH4) emission rate. The study used a data set from 32 respiration calorimeter studies undertaken at this Institute between 1992 and 2010, with all studies involving lactating Holstein-Friesian dairy cows. Cow genetic merit was defined as either profit index (PIN) or profitable lifetime index (PLI), with these two United Kingdom genetic indexes expressing the expected improvement in profit associated with an individual cow, compared with the population average. While PIN is based solely on milk production, PLI includes milk production and a number of other functional traits including health, fertility and longevity. The data set had a large range in PIN (n=736 records, -£30 to +£63) and PLI (n=548 records, -£131 to +£184), days in milk (18 to 354), energy corrected milk yield (16.0 to 45.6 kg/day) and CH(4) emission (138 to 598 g/day). The effect of cow genetic merit (PIN or PLI) was evaluated using ANOVA and linear mixed modelling techniques after removing the effects of a number of animal and diet factors. The ANOVA was undertaken by dividing each data set of PIN and PLI into three sub-groups (PIN:£15, PLI:£67) with these being categorised as low, medium and high genetic merit. Within the PIN and PLI data sets there was no significant differences among the three sub-groups in terms of CH(4) emission per kg feed intake or per kg energy corrected milk yield, or CH(4) energy (CH(4)-E) output as a proportion of energy intake. Linear regression using the whole PIN and PLI data sets also demonstrated that there was no significant relationship between either PIN or PLI, and CH(4) emission per kg of feed intake or CH(4)-E output as a proportion of energy intake. These results indicate that cow genetic merit (PIN or PLI) has little effect on enteric CH(4) emissions as a proportion of feed intake. Instead enteric CH(4) production may mainly relate to total feed intake and dietary nutrient composition.

Animal board invited review: genetic possibilities to reduce enteric methane emissions from ruminants

Measuring and mitigating methane (CH₄) emissions from livestock is of increasing importance for the environment and for policy making. Potentially, the most sustainable way of reducing enteric CH₄ emission from ruminants is through the estimation of genomic breeding values to facilitate genetic selection. There is potential for adopting genetic selection and in the future genomic selection, for reduced CH₄ emissions from ruminants. From this review it has been observed that both CH₄ emissions and production (g/day) are a heritable and repeatable trait. CH₄ emissions are strongly related to feed intake both in the short term (minutes to several hours) and over the medium term (days). When measured over the medium term, CH₄ yield (MY, g CH₄/kg dry matter intake) is a heritable and repeatable trait albeit with less genetic variation than for CH₄ emissions. CH₄ emissions of individual animals are moderately repeatable across diets, and across feeding levels, when measured in respiration chambers. Repeatability is lower when short term measurements are used, possibly due to variation in time and amount of feed ingested prior to the measurement. However, while repeated measurements add value; it is preferable the measures be separated by at least 3 to 14 days. This temporal separation of measurements needs to be investigated further. Given the above issue can be resolved, short term (over minutes to hours) measurements of CH₄ emissions show promise, especially on systems where animals are fed ad libitum and frequency of meals is high. However, we believe that for short-term measurements to be useful for genetic evaluation, a number (between 3 and 20) of measurements will be required over an extended period of time (weeks to months). There are opportunities for using short-term measurements in standardised feeding situations such as breath ‘sniffers’ attached to milking parlours or total mixed ration feeding bins, to measure CH₄. Genomic selection has the potential to reduce both CH₄ emissions and MY, but measurements on thousands of individuals will be required. This includes the need for combined resources across countries in an international effort, emphasising the need to acknowledge the impact of animal and production systems on measurement of the CH₄ trait during design of experiments.

Feed conversion efficiency in dairy cows: Repeatability, variation in digestion and metabolism of energy and nitrogen, and ruminal methanogens

The objective was to study repeatability and sources of variation in feed conversion efficiency [FCE, milk kg/kg dry matter intake (DMI)] of lactating cows in mid to late lactation. Trials 1 and 2 used 16 cows (106 to 368 d in milk) grouped in 8 pairs of 1 high- and 1 low-FCE cow less than 16 d in milk apart. Trial 1 determined the repeatability of FCE during a 12-wk period. Trial 2 quantified the digestive and metabolic partitioning of energy and N with a 3-d total fecal and urine collection and measurement of CH4 and CO2 emission. Trial 3 studied selected ruminal methanogens in 2 pairs of cows fitted with rumen cannulas. Cows received a single diet including 28% corn silage, 27% alfalfa silage, 17% crude protein, and 28% neutral detergent fiber (dry matter basis). In trial 1, mean FCE remained repeatedly different and averaged 1.83 and 1.03 for high- and low-FCE cows, respectively. In trial 2, high-FCE cows consumed 21% more DMI, produced 98% more fat- and protein-corrected milk, excreted 42% less manure per kilogram of fat- and protein-corrected milk, but emitted the same daily amount of CH4 and CO2 compared with low-FCE cows. Percentage of gross energy intake lost in feces was higher (28.6 vs. 25.9%), but urinary (2.76 vs. 3.40%) and CH4 (5.23 vs. 6.99%) losses were lower in high- than low-FCE cows. Furthermore, high-FCE cows partitioned 15% more of gross energy intake toward net energy for maintenance, body gain, and lactation (37.5 vs. 32.6%) than low-FCE cows. Lower metabolic efficiency and greater heat loss in low-FCE cows might have been associated in part with greater energy demand for immune function related to subclinical mastitis, as somatic cell count was 3.8 fold greater in low- than high-FCE cows. As a percentage of N intake, high-FCE cows tended to have greater fecal N (32.4 vs. 30.3%) and had lower urinary N (32.2 vs. 41.7%) and greater milk N (30.3 vs. 19.1%) than low-FCE cows. In trial 3, Methanobrevibacter spp. strain AbM4 was less prevalent in ruminal content of high-FCE cows, which emitted less CH4 per unit of DMI and per unit of neutral detergent fiber digested than low-FCE cows. Thus lower digestive efficiency was more than compensated by greater metabolic efficiencies in high- compared with low-FCE cows. There was not a single factor, but rather a series of mechanisms involved in the observed differences in efficiency of energy utilization of the lactating cows in this study.

Invited review: overview of new traits and phenotyping strategies in dairy cattle with a focus on functional traits

For several decades, breeding goals in dairy cattle focussed on increased milk production. However, many functional traits have negative genetic correlations with milk yield, and reductions in genetic merit for health and fitness have been observed. Herd management has been challenged to compensate for these effects and to balance fertility, udder health and metabolic diseases against increased production to maximize profit without compromising welfare. Functional traits, such as direct information on cow health, have also become more important because of growing concern about animal well-being and consumer demands for healthy and natural products. There are major concerns about the impact of drugs used in veterinary medicine on the spread of antibiotic-resistant strains of bacteria that can negatively impact human health. Sustainability and efficiency are also increasingly important because of the growing competition for high-quality, plant-based sources of energy and protein. Disruptions to global environments because of climate change may encourage yet more emphasis on these traits. To be successful, it is vital that there be a balance between the effort required for data recording and subsequent benefits. The motivation of farmers and other stakeholders involved in documentation and recording is essential to ensure good data quality. To keep labour costs reasonable, existing data sources should be used as much as possible. Examples include the use of milk composition data to provide additional information about the metabolic status or energy balance of the animals. Recent advances in the use of mid-infrared spectroscopy to measure milk have shown considerable promise, and may provide cost-effective alternative phenotypes for difficult or expensive-to-measure traits, such as feed efficiency. There are other valuable data sources in countries that have compulsory documentation of veterinary treatments and drug use. Additional sources of data outside of the farm include, for example, slaughter houses (meat composition and quality) and veterinary labs (specific pathogens, viral loads). At the farm level, many data are available from automated and semi-automated milking and management systems. Electronic devices measuring physiological status or activity parameters can be used to predict events such as oestrus, and also behavioural traits. Challenges concerning the predictive biology of indicator traits or standardization need to be solved. To develop effective selection programmes for new traits, the development of large databases is necessary so that high-reliability breeding values can be estimated. For expensive-to-record traits, extensive phenotyping in combination with genotyping of females is a possibility.

Environmental performances of Sardinian dairy sheep production systems at different input levels

Although sheep milk production is a significant sector for the European Mediterranean countries, it shows serious competitiveness gaps. Minimizing the ecological impacts of dairy sheep farming systems could represent a key factor for farmers to bridging the gaps in competitiveness of such systems and also obtaining public incentives. However, scarce is the knowledge about the environmental performance of Mediterranean dairy sheep farms. The main objectives of this paper were (i) to compare the environmental impacts of sheep milk production from three dairy farms in Sardinia (Italy), characterized by different input levels, and (ii) to identify the hotspots for improving the environmental performances of each farm, by using a Life Cycle Assessment (LCA) approach. The LCA was conducted using two different assessment methods: Carbon Footprint-IPCC and ReCiPe end-point. The analysis, conducted "from cradle to gate", was based on the functional unit 1 kg of Fat and Protein Corrected Milk (FPCM). The observed trends of the environmental performances of the studied farming systems were similar for both evaluation methods. The GHG emissions revealed a little range of variation (from 2.0 to 2.3 kg CO2-eq per kg of FPCM) with differences between farming systems being not significant. The ReCiPe end-point analysis showed a larger range of values and environmental performances of the low-input farm were significantly different compared to the medium- and high-input farms. In general, enteric methane emissions, field operations, electricity and production of agricultural machineries were the most relevant processes in determining the overall environmental performances of farms. Future research will be dedicated to (i) explore and better define the environmental implications of the land use impact category in the Mediterranean sheep farming systems, and (ii) contribute to revising and improving the existing LCA dataset for Mediterranean farming systems.

QTLs associated with dry matter intake, metabolic mid-test weight, growth and feed efficiency have little overlap across 4 beef cattle studies

Background

The identification of genetic markers associated with complex traits that are expensive to record such as feed intake or feed efficiency would allow these traits to be included in selection programs. To identify large-effect QTL, we performed a series of genome-wide association studies and functional analyses using 50 K and 770 K SNP genotypes scored in 5,133 animals from 4 independent beef cattle populations (Cycle VII, Angus, Hereford and Simmental × Angus) with phenotypes for average daily gain, dry matter intake, metabolic mid-test body weight and residual feed intake.

Results

A total of 5, 6, 11 and 10 significant QTL (defined as 1-Mb genome windows with Bonferroni-corrected P-value <0.05) were identified for average daily gain, dry matter intake, metabolic mid-test body weight and residual feed intake, respectively. The identified QTL were population-specific and had little overlap across the 4 populations. The pleiotropic or closely linked QTL on BTA 7 at 23 Mb identified in the Angus population harbours a promising candidate gene ACSL6 (acyl-CoA synthetase long-chain family member 6), and was the largest effect QTL associated with dry matter intake and mid-test body weight explaining 10.39% and 14.25% of the additive genetic variance, respectively. Pleiotropic or closely linked QTL associated with average daily gain and mid-test body weight were detected on BTA 6 at 38 Mb and BTA 7 at 93 Mb confirming previous reports. No QTL for residual feed intake explained more than 2.5% of the additive genetic variance in any population. Marker-based estimates of heritability ranged from 0.21 to 0.49 for residual feed intake across the 4 populations.

Conclusions

This GWAS study, which is the largest performed for feed efficiency and its component traits in beef cattle to date, identified several large-effect QTL that cumulatively explained a significant percentage of additive genetic variance within each population. Differences in the QTL identified among the different populations may be due to differences in power to detect QTL, environmental variation, or differences in the genetic architecture of trait variation among breeds. These results enhance our understanding of the biology of growth, feed intake and utilisation in beef cattle.

The early impact of genomics and metagenomics on ruminal microbiology

Knowledge gained from early and recent studies that define the functions of microbial populations within the rumen microbiome is essential to allow for directed rumen manipulation strategies. A large number of omic studies have focused on carbohydrate active enzymes either for improved fiber digestion within the animal or for use in industries such as biofuels. Studies of the rumen microbiome with respect to methane production and abatement strategies have led to initiatives for defining the microbiome of low- and high-methane-emitting animals while ensuring optimal feed conversion. With advances in omic technologies, the ability to link host genetics and the rumen microbiome by studying all the biological components (holobiont) through the use of hologenomics has begun. However, a program to culture and isolate microbial species for the purpose of standard microbial characterization to aid in assigning function to genomic data remains critical, especially for genes of unknown function.

Nutrient utilisation and methane emissions in Sahiwal calves differing in residual feed intake

The presented study aimed at investigating the residual feed intake (RFI) of Sahiwal calves, nutrient utilisation as affected by RFI and its relationship with methane (CH4) emissions and some blood metabolites. Eighteen male Sahiwal calves (10-18 months of age; mean body weight 133 kg) were fed ad libitum with a total mixed ration. After calculating RFI for individual calves (-0.40 to +0.34 kg DM/d), they were divided into three groups with low, medium and high RFI, respectively. Dry matter intake (DMI) was higher (p < 0.05) in Group High RFI, whereas digestibility of all nutrients except crude protein and ether extract was significantly higher in Group Low RFI. Nitrogen balance was also significantly higher in Group Low RFI (20.2 g/d) than in Group High RFI (17.0 g/d). Average daily gain and feed conversion ratio were similar among the groups. With exception of glucose, concentrations of all measured blood metabolites were higher in Group High RFI (p < 0.05). Compared with Group High RFI, the CH4 emission of Group Low RFI was significantly lower (on the basis g/d and g/kg DMI by 11% and 19%, respectively). Furthermore, the CH4 emission [g/d] was significantly correlated with RFI (r = 0.77). Because higher feed efficiency and less CH4 production were observed in Group Low RFI, it was concluded that RFI can be used as a measure of feed efficiency, which has a potential to select Sahiwal calves for lowered CH4 emissions.

Quantitative analysis of ruminal methanogenic microbial populations in beef cattle divergent in phenotypic residual feed intake (RFI) offered contrasting diets

Background

Methane (CH₄) emissions in cattle are an undesirable end product of rumen methanogenic fermentative activity as they are associated not only with negative environmental impacts but also with reduced host feed efficiency. The aim of this study was to quantify total and specific rumen microbial methanogenic populations in beef cattle divergently selected for residual feed intake (RFI) while offered (i) a low energy high forage (HF) diet followed by (ii) a high energy low forage (LF) diet. Ruminal fluid was collected from 14 high (H) and 14 low (L) RFI animals across both dietary periods. Quantitative real time PCR (qRT-PCR) analysis was conducted to quantify the abundance of total and specific rumen methanogenic microbes. Spearman correlation analysis was used to investigate the association between the relative abundance of methanogens and animal performance, rumen fermentation variables and diet digestibility.

Results

Abundance of methanogens, did not differ between RFI phenotypes. However, relative abundance of total and specific methanogen species was affected (P < 0.05) by diet type, with greater abundance observed while animals were offered the LF compared to the HF diet.

Conclusions

These findings suggest that differences in abundance of specific rumen methanogen species may not contribute to variation in CH₄ emissions between efficient and inefficient animals, however dietary manipulation can influence the abundance of total and specific methanogen species.

Methane emissions from beef and dairy cattle: quantifying the effect of physiological stage and diet characteristics

The prediction of methane outputs from ruminant livestock data at farm, national, and global scales is a vital part of greenhouse gas calculations. The objectives of this work were to quantify the effect of physiological stage (lactating or nonlactating) on predicting methane (CH4) outputs and to illustrate the potential improvement for a beef farming system of using more specific mathematical models to predict CH4 from cattle at different physiological stages and fed different diet types. A meta-analysis was performed on 211 treatment means from 38 studies where CH4, intake, animal, and feed characteristics had been recorded. Additional information such as type of enterprise, diet type, physiological stage, CH4 measurement technique, intake restriction, and CH4 reduction treatment application from these studies were used as classificatory factors. A series of equations for different physiological stages and diet types based on DMI or GE intake explained 96% of the variation in observed CH4 outputs (P<0.001). Resulting models were validated with an independent dataset of 172 treatment means from 20 studies. To illustrate the scale of improvement on predicted CH4 outputs from the current whole-farm prediction approach (Intergovernmental Panel on Climate Change [IPCC]), equations developed in the present study (NewEqs) were compared with the IPCC equation {CH4 (g/d)=[(GEI×Ym)×1,000]/55.65}, in which GEI is GE intake and Ym is the CH4 emission factor, in calculating CH4 outputs from 4 diverse beef systems. Observed BW and BW change data from cows with calves at side grazing either hill or lowland grassland, cows and overwintering calves and finishing steers fed contrasting diets were used to predict energy requirements, intake, and CH4 outputs. Compared with using this IPCC equation, NewEqs predicted up to 26% lower CH4 on average from individual lactating grazing cows. At the herd level, differences between equation estimates from 10 to 17% were observed in total annual accumulated CH4 when applied to the 4 diverse beef production systems. Overall, despite the small number of animals used it was demonstrated that there is a biological impact of using more specific CH4 prediction equations. Based on this approach, farm and national carbon budgets will be more accurate, contributing to reduced uncertainty in assessing mitigation options at farm and national level.

Methane yield phenotypes linked to differential gene expression in the sheep rumen microbiome

Ruminant livestock represent the single largest anthropogenic source of the potent greenhouse gas methane, which is generated by methanogenic archaea residing in ruminant digestive tracts. While differences between individual animals of the same breed in the amount of methane produced have been observed, the basis for this variation remains to be elucidated. To explore the mechanistic basis of this methane production, we measured methane yields from 22 sheep, which revealed that methane yields are a reproducible, quantitative trait. Deep metagenomic and metatranscriptomic sequencing demonstrated a similar abundance of methanogens and methanogenesis pathway genes in high and low methane emitters. However, transcription of methanogenesis pathway genes was substantially increased in sheep with high methane yields. These results identify a discrete set of rumen methanogens whose methanogenesis pathway transcription profiles correlate with methane yields and provide new targets for CH₄ mitigation at the levels of microbiota composition and transcriptional regulation.