Sheep (Ovis aries) represent one of the most important livestock species for global animal protein and wool production. However, little is known about the genetic and biological basis of ovine phenotypes, particularly those with high economic value and environmental impact. Here, by integrating 1413 RNA sequencing (RNA-seq) samples from 51 distinct tissues across 14 developmental time points, representing early-prenatal, late-prenatal, neonatal, lamb, juvenile, adult, and elderly stages, we constructed a high-resolution Developmental Gene Expression Atlas (dGEA) in sheep. We observed dynamic patterns of gene expression and regulatory networks across tissues and developmental stages. Leveraging this resource to interpret genetic associations for 48 monogenic and 12 complex traits in sheep, we found that genes upregulated at prenatal developmental stages played more important roles in shaping these phenotypes than those upregulated at postnatal stages. For instance, genetic associations of crimp number, mean staple length (MSL), and individual birthweight were significantly enriched in the prenatal rather than postnatal skin and immune tissues. By comprehensively integrating genome-wide association study (GWAS) fine-mapping results with the sheep dGEA, we identified several candidate genes for complex traits in sheep, such as SOX9 for MSL, GNRHR for litter size at birth, and PRKDC for live weight. These results provide novel insights into the developmental and molecular architecture of ovine phenotypes. The dGEA (https://sheepdgea.njau.edu.cn/) will serve as an invaluable resource for sheep developmental biology, genetics, genomics, and selective breeding.

Abstract Australia is one of the largest beef and lamb producers in the world, with a wide diversity of grazing systems ranging from intensive, integrated crop-livestock systems in the temperate south to the extensive, low-input beef systems of the hot, arid rangelands of north and central Australia. To help understand and predict animal performance across these diverse production systems, Australian researchers have built decision support tools (DSTs) specifically for these grazing conditions. Some examples of DSTs designed for Australian ruminant production systems include the GRAZPLAN suite of software models, the Crop and Livestock Enterprise Model (CLEM), DairyMod, BreedCow, and the Drought and Supplementary Feeding Calculator (DAFSC), and many of these include a biophysical model based on the Australian ruminant feeding standards. Widely used for a range of industry and research applications, these tools are key to helping the livestock industry improve the environmental and economic sustainability of livestock production in the face of a changing climate. Historically DSTs have been used by producers to predict animal performance for a given feedbase, allowing for prediction of short-term (≤ 30 d) performance and optimizing supplemental feeding. Over time, the use of DSTs has shifted and expanded, and they are increasingly being used in tactical forecasting to help explore the impacts of different management strategies in response to variation in seasonal feed, climate, and rain forecasts. Because these tools can represent a wide range of temperate and tropical pasture species and animal genotypes, they can be used to explore the effects of using different breeds and species to respond to climate change, or to explore the effects of genetic selection within herds. Tools that use a systems approach to modelling, such as GRAZPLAN, CLEM, and Breedcow, can also be used to help producers navigate sustainability credentialling, compare the effects of management strategies on environmental sustainability and economic sustainability, as well as to explore the broader impacts of on-farm management decisions in terms of sustainability and efficiency at the regional or food system level. While these tools were developed for Australian production systems, many of these have international parallels, such as beef and sheep grazing systems in the semi-arid rangeland of the western USA and central Queensland and New South Wales; sheep grazing in the Mediterranean rangelands of California and the southern coast of Western Australia; and the temperate pasture-based diary regions of Tasmania, New Zealand, and Ireland. Because of these similarities, the ability of these models to flexibly represent diverse production systems gives them strong potential for use by industry and research at a broader scale by international audiences.

Context Selection for growth rate has received considerable attention in beef cattle but the evidence for an improvement in the efficiency of feed conversion is equivocal. Aim To examine whether feed efficiency by beef cattle finished in a feedlot had been changed in response to divergence selection for growth rate. Methods The Angus cattle used came from three lines of cattle selected for over five generations for fast growth rate to yearling age (High-line), slow growth (Low-line), or from an unselected Control-line. Over sequential years, a cohort of steers, then of heifers and then of steers, representative of the lines, were measured for feedlot performance, and carcase- and meat-quality traits. The animals were fed a high-energy feedlot ration and after an adjustment period they underwent a performance test of at least 70 days of duration. After slaughter, muscle samples were taken for subsequent measurement of the components of the endogenous calpain proteolytic enzyme system. Their carcasses underwent a standard chiller assessment and meat samples were taken after 1 day and 14 days (steers) or 17 days (heifers) for objective measurement of tenderness. Key results Cattle from the High-line grew 48% faster (P < 0.05), and ate 48% more feed (P < 0.05) than did those from the Low-line, but had similar (P > 0.05) feed conversion ratio and residual feed intake. There were no differences between the High-line and Low-line in the visual meat-quality attributes of meat colour, fat colour and marbling, and no differences in the objective measurements of tenderness and connective-tissue toughness. There was no evidence of a selection response in the circulating concentrations of the metabolites and hormones measured, nor in the endogenous calpain proteolytic enzyme system in muscle. Conclusions The superior growth demonstrated by the High-line cattle over the feedlot test was accompanied by a higher feed intake, with no evidence for an improvement in feed efficiency. Implications Selection for growth rate is a powerful tool to alter animal performance but the beef industry needs to be cognisant of the proportional increase in feed requirement from breeding bigger animals.

A mechanistic, dynamic model was developed to calculate body composition in growing lambs by calculating heat production (HP) internally from energy transactions within the body. The model has a fat pool (f) and three protein pools: visceral (v), nonvisceral (m), and wool (w). Heat production is calculated as the sum of fasting heat production, heat of product formation (HrE), and heat associated with feeding (HAF). Fasting heat production is represented as a function of visceral and nonvisceral protein mass. Heat associated with feeding (HAF) is calculated as ((1 - km) x MEI), where km is partial efficiency of ME use for maintenance, and MEI = metabolizable energy intake) applies at all levels above and below maintenance. The value of km derived from data where lambs were fed above maintenance was 0.7. Protein change (dp/dt) is the sum of change in the m, v, and w pools, and change in fat is equal to net energy available for gain minus dp/dt. Heat associated with a change in body composition (HrE) is calculated from the change in protein and fat with estimated partial efficiencies of energy use of 0.4 and 0.7 for protein and fat, respectively. The model allows for individuals to gain protein while losing fat or vice versa.When evaluated with independent data, the model performed better than the current Australian feeding standards () for predicting protein gain in the empty body but did not perform as well as for gain of fat and fleece-free empty body weight. Models performed similarly for predicting clean wool growth. By explicit representation of the major energy using processes in the body, and through simplification of the way body composition is computed in growing animals, the model is more transparent than current feeding systems while achieving similar performance. An advantage of this approach is that the model has the potential for wider applicability across different growth trajectories and can explicitly account for the effects of systematic changes on energy transactions, such as the effects of selective breeding, growth manipulation, or environmental changes. This paper presents a revised dynamic, mechanistic model of heat production and body composition in sheep where heat production is calculated internally as the sum of fasting heat production, heat associated with feeding, and heat from changes in bodily protein and fat pools. The resulting model reflects the variation in heat production that arises both from feed, the animal, and the intersection of these two sources, and is a simpler and more flexible way to predict energy requirements and heat production in growing ruminants than traditional feeding systems. Based on prior work by , a revised dynamic, mechanistic model was developed to improve the prediction of the composition of protein and fat in the body of growing ruminants. The revised model calculates heat production (HP) internally as a function of fasting HP, heat associated with feeding, and HP from changes in fat and protein within the body. Heat associated with product formation is calculated from changes in body protein and fat, with separate efficiencies for each, while heat associated with feeding is a constant proportion of metabolizable energy intake and applies at all levels of feeding above and below maintenance. When evaluated against novel data, the revised model performed similarly to current Australian feeding standards () Unlike the Freer model, the revised model captures variation in HP arising from feed as well as gain of protein and fat. The revised model explicitly represents protein in the body as two pools with markedly different rates of energy expenditure, improving representation of the underlying biology compared to current feeding systems. This provides a more flexible way to predict energy requirements and body composition in growing animals while achieving similar performance to current feeding systems.

Sheep (Ovis aries) represents one of the most important livestock species for animal protein and wool production worldwide. However, little is known about the genetic and biological basis of ovine phenotypes, particularly for those of high economic value and environmental impact. Here, by generating and integrating 1,413 RNA-seq samples from 51 distinct tissues across 14 developmental time points, representing early prenatal, late prenatal, neonate, lamb, juvenile, adult, and elderly stages, we built a high-resolution developmental Gene Expression Atlas (dGEA) in sheep. We observed dynamic patterns of gene expression and regulatory networks across tissues and developmental stages. When harnessing this resource for interpreting genomic associations of 48 monogenetic and 12 complex traits in sheep, we found that genes upregulated at prenatal developmental stages played more important roles in shaping these phenotypes than those upregulated at postnatal stages. For instance, genetic associations of crimp number, mean staple length (MSL), and individual birth weight were significantly enriched in the prenatal rather than postnatal skin and immune tissues. By comprehensively integrating fine-mapping results and the sheep dGEA, we identified several key genes associated with complex traits in sheep, such as SOX9 (associated with MSL), GNRHR (associated with litter size at birth), and PRKDC (associated with live weight). These results provide novel insights into the gene regulatory and developmental architecture underlying ovine phenotypes. The dGEA (https://sheepdgea.njau.edu.cn/) will serve as an invaluable resource for sheep developmental biology, genetics, genomics, and selective breeding. ### Competing Interest Statement The authors have declared no competing interest.

Context Ruminant livestock industries are seeking to improve efficiency of feed use and reduce greenhouse gas emissions. Aims The research aimed to measure variation in feed intake and residual feed intake (RFI) in growing lambs and examine the inter-relationships of related traits and diet effects. Methods In Phase 1, 6-month-old Merino wethers (n = 113) were fed a base diet ad libitum for 60 days to measure dry matter intake (DMI), liveweight (LWT) and average daily gain (ADG). Whilst being fed the same base diet, measures of body composition (using computer tomography scanning) and methane emissions were collected. For Phase 2, lambs selected for low or high RFI in Phase 1 were randomly assigned to either a low or high diet and fed ad libitum for 30 days. They were assessed for intake, growth, body composition and CH4 emissions. Key results In Phase 1 there was significant variation in DMI, which was explained by these traits in order of significance (R2 additive): LWT (R2 = 63.9%), ADG (R2 = 70.4%) and fat gain (R2 = 75.7%). In Phase 2, high RFI lambs had higher metabolisable energy intake (MEI; P < 0.05) compared to low RFI lambs. In lambs fed the high diet, intake (DMI and MEI P < 0.001), LWT (P < 0.05), ADG (P < 0.001), fat and lean gain (P < 0.001) were higher than in lambs fed the low diet. Daily methane emissions were highest (P < 0.05) in high RFI lambs fed the high diet. There were no significant effects of RFI or diet on methane yield (MY; g methane/kg DM). Differences in RFI or RFI adjusted for fat gain did not persist to the end of the 30 day feeding period in Phase 2. Conclusions Lambs with low RFI had lower MEI for the same liveweight as well as lower fat and lean gain in the empty bodyweight. They also had lower daily methane emissions compared to those that had high RFI and ate more. Implications The opportunity to select sheep at a young age with lower RFI and lower MEI is of significant production and environmental importance.

BACKGROUND:Producing animal protein while reducing the animal's impact on the environment, e.g., through improved feed efficiency and lowered methane emissions, has gained interest in recent years. Genetic selection is one possible path to reduce the environmental impact of livestock production, but these traits are difficult and expensive to measure on many animals. The rumen microbiome may serve as a proxy for these traits due to its role in feed digestion. Restriction enzyme-reduced representation sequencing (RE-RRS) is a high-throughput and cost-effective approach to rumen metagenome profiling, but the systematic (e.g., sequencing) and biological factors influencing the resulting reference based (RB) and reference free (RF) profiles need to be explored before widespread industry adoption is possible.RESULTS:Metagenome profiles were generated by RE-RRS of 4,479 rumen samples collected from 1,708 sheep, and assigned to eight groups based on diet, age, time off feed, and country (New Zealand or Australia) at the time of sample collection. Systematic effects were found to have minimal influence on metagenome profiles. Diet was a major driver of differences between samples, followed by time off feed, then age of the sheep. The RF approach resulted in more reads being assigned per sample and afforded greater resolution when distinguishing between groups than the RB approach. Normalizing relative abundances within the sampling Cohort abolished structures related to age, diet, and time off feed, allowing a clear signal based on methane emissions to be elucidated. Genus-level abundances of rumen microbes showed low-to-moderate heritability and repeatability and were consistent between diets.CONCLUSIONS:Variation in rumen metagenomic profiles was influenced by diet, age, time off feed and genetics. Not accounting for environmental factors may limit the ability to associate the profile with traits of interest. However, these differences can be accounted for by adjusting for Cohort effects, revealing robust biological signals. The abundances of some genera were consistently heritable and repeatable across different environments, suggesting that metagenomic profiles could be used to predict an individual's future performance, or performance of its offspring, in a range of environments. These results highlight the potential of using rumen metagenomic profiles for selection purposes in a practical, agricultural setting.

Enteric methane (CH4) emissions from sheep contribute to global greenhouse gas emissions from livestock. However, as already available for dairy and beef cattle, empirical models are needed to predict CH4 emissions from sheep for accounting purposes. The objectives of this study were to: 1) collate an intercontinental database of enteric CH4 emissions from individual sheep; 2) identify the key variables for predicting enteric sheep CH4 absolute production (g/d per animal) and yield [g/kg dry matter intake (DMI)] and their respective relationships; and 3) develop and cross-validate global equations as well as the potential need for age-, diet-, or climatic region-specific equations. The refined intercontinental database included 2,135 individual animal data from 13 countries. Linear CH4 prediction models were developed by incrementally adding variables. A universal CH4 production equation using only DMI led to a root mean square prediction error (RMSPE, % of observed mean) of 25.4% and an RMSPE-standard deviation ratio (RSR) of 0.69. Universal equations that, in addition to DMI, also included body weight (DMI + BW), and organic matter digestibility (DMI + OMD + BW) improved the prediction performance further (RSR, 0.62 and 0.60), whereas diet composition variables had negligible effects. These universal equations had lower prediction error than the extant IPCC 2019 equations. Developing age-specific models for adult sheep (>1-year-old) including DMI alone (RSR = 0.66) or in combination with rumen propionate molar proportion (for research of more refined purposes) substantially improved prediction performance (RSR = 0.57) on a smaller dataset. On the contrary, for young sheep (<1-year-old), the universal models could be applied, instead of age-specific models, if DMI and BW were included. Universal models showed similar prediction performances to the diet- and region-specific models. However, optimal prediction equations led to different regression coefficients (i.e. intercepts and slopes) for universal, age-specific, diet-specific, and region-specific models with predictive implications. Equations for CH4 yield led to low prediction performances, with DMI being negatively and BW and OMD positively correlated with CH4 yield. In conclusion, predicting sheep CH4 production requires information on DMI and prediction accuracy will improve national and global inventories if separate equations for young and adult sheep are used with the additional variables BW, OMD and rumen propionate proportion. Appropriate universal equations can be used to predict CH4 production from sheep across different diets and climatic conditions.

Context Measurement of weight provides the basis of most performance-recording schemes for beef cattle around the world. The limitation of faster growth rate as a breeding objective, without considering changes in mature-cow weight, is the expected increase in cow size and, hence, feed requirements. Aims To measure the correlated changes in feed intake and efficiency of cows, calves and the cow–calf unit following divergent selection for growth rate. Methods The cows and their calves came from three lines of Angus cattle selected for either fast weight gain to yearling age (the High-line), slow weight gain (the Low-line), or from an unselected Control-line. Efficiency was evaluated over an annual production cycle. Individual cow weights and feed intakes, and calf growth and feed intake (including milk), were recorded. Milk production, milk composition and body composition were also measured so that correlated changes in efficiency of use of energy and nitrogen could be determined. Key results The High-line cows were 18% (P < 0.05) heavier than the Low-line cows at the start and consumed 7% (P < 0.05) more feed than did the Low-line cows. Feed efficiency of the cow–calf unit was 12% higher (P < 0.05) in the High-line cows and calves than in the Low-line cows and calves. When compared on the basis of feed used relative to their weight and weight gain there was no difference (P > 0.05) between the selection lines. Divergent selection was accompanied by a change in body composition, with the High-line cows containing proportionally less protein and more fat in their bodies than did the Low-line cows. There was no evidence for change in the efficiency of feed energy use, but there was a 10% (P < 0.05) improvement in nitrogen efficiency of the cow–calf unit in the High-line compared with the Low-line. Conclusions Divergent selection for weight gain led to a correlated change in cow size and cow feed requirements. Implications This experiment supported the consensus among earlier reviews that there is little evidence that selection for growth rate or size, without moderating change in mature-cow weight, is associated with improved efficiency of feed energy use in maternal beef breeds.

Context Feedlotting lambs has the potential to considerably increase the efficiency of lamb production in Australia. Many producers have turned to grain-finishing lambs to capitalise on high lamb prices and, due to the perceived profitability of this practice, further research to improve production has not been prioritised. Lambs are, however, difficult to adapt to a predominantly grain-based diet, often resulting in highly variable feed intake and growth rates. Aims The aim of this survey was to investigate the apparent growth rates and feed conversion ratios of lambs in current feedlotting enterprises. A secondary aim was to identify research priorities that could improve feedlot production efficiency. Methods A cross-sectional survey was conducted between February and May 2020 among Australian lamb producers, with the target population being lamb producers using feedlots to finish lambs. Producer responses from 59 current lamb feedlotters were collated and analysed. Key results The most frequently reported growth rates were between 300 and 350 g/day, and most respondents reported a feed conversion ratio of 5:1. The incidence of shy feeders was a median of 3.5% and mortality was a median of 1%, with acidosis reported as the major contributor to mortality. Conclusions The results of the current survey indicate that for the majority of responding producers, lamb growth rates and feed conversion ratios are consistent with those predicted by the nutrient requirements of domesticated ruminants (CSIRO 2007), and improvements in production are unlikely without significantly increasing nutrient intake. Shy feeders, acidosis and the intake of lowly digestible feeds are the clear limitations to production efficiency. Implications Research to improve productivity of lambs in feedlots needs to prioritise the implementation of feeding strategies that minimise social and nutritional issues, and promote maximum intake of nutrients.

Context Genotype by environment interaction or sire re-ranking between measurements of methane emission in different environments or from using different measurement protocols can affect the efficiency of selection strategies to abate methane emission. Aim This study tested the hypothesis that measurements of methane emission from grazing sheep under field conditions, where the feed intake is unknown, are genetically correlated to measurements in a controlled environment where feed intake is known. Methods Data on emission of methane and carbon dioxide and uptake of oxygen were measured using portable accumulation chambers from 499 animals in a controlled environment in New South Wales and 1382 animals in a grazing environment in Western Australia were analysed. Genetic linkage between both environments was provided by 140 sires with progeny in both environments. Multi-variate animal models were used to estimate genetic parameters for the three gas traits corrected for liveweight. Genetic groups were fitted in the models to account for breed differences. Genetic correlations between the field and controlled environments for the three traits were estimated using bivariate models. Key results Animals in the controlled environment had higher methane emission compared to the animals in the field environment (37.0 ± s.d 9.3 and 35.3 ± s.d 9.4 for two protocols vs 12.9 ± s.d 5.1 and 14.6 ± s.d 4.8 mL/min for lambs and ewes (±s.d); P < 0.05) but carbon dioxide emission and oxygen uptake did not significantly differ. The heritability estimates for methane emission, carbon dioxide emission and oxygen uptake were 0.15, 0.06 and 0.11 for the controlled environment and 0.17, 0.27 and 0.35 for the field environment. The repeatability for the traits in the controlled environment ranged from 0.51 to 0.59 and from 0.24 to 0.38 in the field environment. Genetic correlations were high (0.85–0.99) but with high standard errors. Conclusion Methane emission phenotypes measured using portable accumulation chambers in grazing sheep can be used in genetic evaluation to estimate breeding values for genetic improvement of emission related traits. The combined measurement protocol-environment did not lead to re-ranking of sires. Implication These results suggest that both phenotypes could be used in selection for reduced methane emission in grazing sheep. However, this needs to be consolidated using a larger number of animals and sires with larger progeny groups in different environments.

Background Ruminant livestock are a major contributor to Australian agricultural sector carbon emissions. Variation in methane (CH4) produced from enteric microbial fermentation of feed in the reticulo-rumen of sheep differs with different digestive functions. Method We isolated rumen epithelium enzymatically to extract membrane and cytosol proteins from sheep with high (H) and low (L) CH4 emission. Protein abundance was quantified using SWATH-mass spectrometry. Results The research found differences related to the metabolism of glucose, lactate and processes of cell defence against microbes in sheep from each phenotype. Enzymes in the methylglyoxal pathway, a side path of glycolysis, resulting in D-lactate production, differed in abundance. In the H CH4 rumen epithelium the enzyme hydroxyacylglutathione hydrolase (HAGH) was 2.56 fold higher in abundance, whereas in the L CH4 epithelium lactate dehydrogenase D (LDHD) was 1.93 fold higher. Malic enzyme 1 which converts D-lactate to pyruvate via the tricarboxylic cycle was 1.57 fold higher in the L CH4 phenotype. Other proteins that are known to regulate cell defence against microbes had differential abundance in the epithelium of each phenotype. Conclusion Differences in the abundance of enzymes involved in the metabolism of glucose were associated with H and L CH4 phenotype sheep. Potentially this represents an opportunity to use protein markers in the rumen epithelium to select low CH4 emitting sheep.

Variation in nutrition is a key determinant of growth, body composition, and the ability of animals to perform to their genetic potential. Depending on the quality of feed available, animals may be able to overcome negative effects of prior nutritional restriction, increasing intake and rates of tissue gain, but full compensation may not occur. A 2 × 3 × 4 factorial serial slaughter study was conducted to examine the effects of prior nutritional restriction, dietary energy density, and supplemental rumen undegradable protein (RUP) on intake, growth, and body composition of lambs. After an initial slaughter (n = 8), 124 4-mo-old Merino cross wethers (28.4 ± 1.8 kg) were assigned to either restricted (LO, 500 g/d) or unrestricted (HI, 1500 g/d) intake of lucerne and oat pellets. After 8 wk, eight lambs/group were slaughtered and tissue weights and chemical composition were measured. Remaining lambs were randomly assigned to a factorial combination of dietary energy density (7.8, 9.2, and 10.7 MJ/kg DM) and supplemental RUP (0, 30, 60, and 90 g/d) and fed ad libitum for a 12- to 13-wk experimental period before slaughter and analysis. By week 3 of the experimental period, lambs fed the same level of energy had similar DMI (g/d) and MEI (MJ/d) (P > 0.05), regardless of prior level of nutrition. Restricted-refed (LO) lambs had higher rates of fat and protein gain than HI lambs (P < 0.05) but had similar visceral masses (P > 0.05). However, LO lambs were lighter and leaner at slaughter, with proportionally larger rumens and livers (P < 0.05). Tissue masses increased with increasing dietary energy density, as did DMI, energy and nitrogen (N) retention (% intake), and rates of protein and fat gain (P < 0.05). The liver increased proportionally with increasing dietary energy density and RUP (P < 0.05), but rumen size decreased relative to the empty body as dietary energy density increased (P < 0.05) and did not respond to RUP (P > 0.05). Fat deposition was greatest in lambs fed 60 g/d supplemental RUP (P < 0.05). However, lambs fed 90 g/d were as lean as lambs that did not receive supplement (P0, P > 0.05), with poorer nitrogen retention and proportionally heavier livers than P0 lambs (P < 0.05). In general, visceral protein was the first tissue to respond to increased intake during refeeding, followed by non-visceral protein and fat, highlighting the influence of differences in tissue response over time on animal performance and body composition.