Meat and milk from ruminants provide an important source of protein and other nutrients for human consumption. Although ruminants have a unique advantage of being able to consume forages and graze lands not suitable for arable cropping, 2% to 12% of the gross energy consumed is converted to enteric CH4 during ruminal digestion, which contributes approximately 6% of global anthropogenic greenhouse gas emissions. Thus, ruminant producers need to find cost-effective ways to reduce emissions while meeting consumer demand for food. This paper provides a critical review of the substantial amount of ruminant CH4-related research published in past decades, highlighting hydrogen flow in the rumen, the microbiome associated with methanogenesis, current and future prospects for CH4 mitigation and insights into future challenges for science, governments, farmers and associated industries. Methane emission intensity, measured as emissions per unit of meat and milk, has continuously declined over the past decades due to improvements in production efficiency and animal performance, and this trend is expected to continue. However, continued decline in emission intensity will likely be insufficient to offset the rising emissions from increasing demand for animal protein. Thus, decreases in both emission intensity (g CH4/animal product) and absolute emissions (g CH4/day) are needed if the ruminant industries continue to grow. Providing producers with cost-effective options for decreasing CH4 emissions is therefore imperative, yet few cost-effective approaches are currently available. Future abatement may be achieved through animal genetics, vaccine development, early life programming, diet formulation, use of alternative hydrogen sinks, chemical inhibitors and fermentation modifiers. Individually, these strategies are expected to have moderate effects (<20% decrease), with the exception of the experimental inhibitor 3-nitrooxypropanol for which decreases in CH4 have consistently been greater (20% to 40% decrease). Therefore, it will be necessary to combine strategies to attain the sizable reduction in CH4 needed, but further research is required to determine whether combining anti-methanogenic strategies will have consistent additive effects. It is also not clear whether a decrease in CH4 production leads to consistent improved animal performance, information that will be necessary for adoption by producers. Major constraints for decreasing global enteric CH4 emissions from ruminants are continued expansion of the industry, the cost of mitigation, the difficulty of applying mitigation strategies to grazing ruminants, the inconsistent effects on animal performance and the paucity of information on animal health, reproduction, product quality, cost-benefit, safety and consumer acceptance.

In animal sciences, the number of published meta-analyses is increasing at a rate of 15% per year. This current review focuses on the good practices and the potential pitfalls in the conduct of meta-analyses in animal sciences, nutrition in particular. Once the study objectives have been defined, several key phases must be considered when doing a meta-analysis. First, as a principle of traceability, criteria used to select or discard publications should be clearly stated in a way that one could reproduce the final selection of data. Then, the coding phase, aiming to isolate specific experimental factors for an accurate graphical and statistical interpretation of the database, is discussed. Following this step, the study of the levels of independence of factors and of the degree of data balance of the meta-design represents an essential phase to ensure the validity of statistical processing. The consideration of the study effect as fixed or random must next be considered. It appears based on several examples that this choice does not generally have any influence on the conclusions of a meta-analysis when the number of experiments is sufficient.

Performance and feeding behaviour traits in growing pigs could be affected by social interaction effects when animals are raised in group. So, properly knowing the genetic correlations between direct and social interaction effects among performance and feeding behaviour traits could improve the accuracy of the genetic evaluations. Our aim was to explore the role of feeding behaviour traits (FBT) and indirect genetic effects (IGEs) in the genetic evaluations of growing pigs. Thus, genetic parameters were estimated for production traits (PT): average daily gain, average daily feed consumption, feed conversion ratio and backfat thickness; as well as for FBT: average daily feeding rate, average daily feeding frequency, average daily occupation time and average daily time between consecutive visits. Traits were recorded in 1144 Duroc pigs during the fattening period. Two bivariate models were fitted: classic animal model and an animal model fitting IGE. Estimations were done following Bayesian procedures. Heritability estimates obtained with classic animal model for all studied traits were medium-high. The additional heritable variation captured by IGE supposed that the ratios of total genetic variance to phenotypic variance (T2) were higher than the heritability estimates obtained with the classic model, except for occupation time trait, when a lower value (0.20 ± 0.19) was estimated. This is due to a high and negative correlation between IGE and direct genetic effects (DGEs) of this particular trait (−0.78 ± 0.27). Results from classic animal model do not evidence a clear role of FBT to improve the accuracy of breeding value predictions for PT; only average daily feeding rate seems to show a positive correlation (around 0.50 to 0.60) with average daily gain, average daily feed consumption and backfat thickness. However, when IGE model was fitted, the number of estimates of genetic correlations between FBT and PT showing a relevant magnitude increased, generally for the correlations between IGE of FBT and DGE of PT; or particularly for the correlations between IGE of average daily feeding frequency, and the IGE of all the PT, except average daily gain. Thus, in evaluations using the animal model with IGE fitted, the inclusion of FBT could aid the improvement of the accuracy of breeding value predictions for PT. This is a consequence of the improved genetic relationships between traits that can be fitted when considering such models.

Less than 2% of mammalian genomes code for proteins, but ‘the majority of its bases can be found in primary transcripts’ – a phenomenon termed the pervasive transcription, which was first reported in 2007. Even though most of the transcripts do not code for proteins, they play a variety of biological functions, with regulation of gene expression appearing as the most common one. Those transcripts are divided into two groups based on their length: small non-coding RNAs, which are maximally 200 bp long, and long non-coding RNAs (lncRNAs), which are longer than 200 nucleotides. The advances in next-generation sequencing methods provided a new possibility of investigating the full set of RNA molecules in the cell. In this review, we summarized the current state of knowledge on lncRNAs in three major livestock species – Sus scrofa, Bos taurus and Gallus gallus, based on the literature and the content of biological databases. In the NONCODE database, the largest number of identified lncRNA transcripts is available for pigs, but cattle have the largest number of lncRNA genes. Poultry is represented by less than a half of records. Genomic annotation of lncRNAs showed that the majority of them are assigned to introns (pig, poultry) or intergenic (cattle). The comparison with well-annotated human and mouse genomes indicates that such annotation is a result of lack of proper lncRNA annotation data. Since lncRNAs play an important role in genomic studies, their characterization in farm animals’ genomes is critical in bridging the gap between genotype and phenotype.

Hungarian Grey is an indigenous cattle breed that is one of the national symbols of Hungary. However, genetic description of the Hungarian Grey cattle has not yet been conducted based on whole-genome screening. Using the GeneSeek high-density Bovine SNP (single nucleotide polymorphism) 150 K BeadChip, we sampled the genome of 36 Hungarian Grey, 12 Maremmana, 13 Hungarian Fleckvieh and 5 Holstein-Friesian cattle for population studies and used data of 139 other cattle from an additional dataset created on European cattle breeds (Upadhyay et al.2017. Heredity 118, 169–176). The performance of a multidimensional scaling plot showed that Hungarian Grey clustered independently from other European cattle. The number and total length of runs of homozygosity (ROH) is similar or slightly below the value of other European cattle; FROH coefficients (proportion of the autosomal genome covered by ROH) are similar to Maremmana and Maronesa. The frequency of ROH does not show increased values as it can be noticed in Heck and Maltese. These results indicate that the Hungarian Grey cattle have been successfully maintained avoiding negative genetic effects, and reflect the uniqueness among European cattle. The identification of breed-specific loci has been aimed at differentiating Hungarian Grey (n = 136 in this case) from other cattle breeds (n = 169). Ten loci (−log10P > 5) were identified as markers capable for differentiation of Hungarian Grey. These markers are located on chromosomes 6, 14, 15, 16, 20 and 24.

In order to map quantitative trait loci (QTLs) for allometries of body compositions and metabolic traits in chicken, we phenotypically characterize the allometric growths of multiple body components and metabolic traits relative to BWs using joint allometric scaling models and then establish random regression models (RRMs) to fit genetic effects of markers and minor polygenes derived from the pedigree on the allometric scalings. Prior to statistically inferring the QTLs for the allometric scalings by solving the RRMs, the LASSO technique is adopted to rapidly shrink most of marker genetic effects to zero. Computer simulation analysis confirms the reliability and adaptability of the so-called LASSO-RRM mapping method. In the F2 population constructed by multiple families, we formulate two joint allometric scaling models of body compositions and metabolic traits, in which six of nine body compositions are tested as significant, while six of eight metabolic traits are as significant. For body compositions, a total of 14 QTLs, of which 9 dominant, were detected to be associated with the allometric scalings of drumstick, fat, heart, shank, liver and spleen to BWs; while for metabolic traits, a total of 19 QTLs also including 9 dominant be responsible for the allometries of T4, IGFI, IGFII, GLC, INS, IGR to BWs. The detectable QTLs or highly linked markers can be used to regulate relative growths of the body components and metabolic traits to BWs in marker-assisted breeding of chickens.

Understanding existing levels of genetic variability of camel populations is capital for conservation activities. This study aims to provide information on the genetic diversity of four dromedary populations, including Guerzni, Harcha, Khouari and Marmouri. Blood samples from 227 individuals belonging to the aforementioned populations were obtained and genotyped by 16 microsatellite markers. A total of 215 alleles were observed, with the mean number of alleles per locus being 13.4 ± 6.26. All loci were polymorphic in the studied populations. The average expected heterozygosity varied from a maximum of 0.748 ± 0.122 in Guerzni population to a minimum of 0.702 ± 0.128 in Harcha population; Guerzni population showed the highest value of observed heterozygosity (0.699 ± 0.088), whereas Harcha population the lowest (0.646 ± 0.130). Mean estimates of F-statistics obtained over loci were FIS = 0.0726, FIT = 0.0876 and FST = 0.0162. The lowest genetic distance was obtained between Guerzni and Khouari (0.023), and the highest genetic distance between Harcha and Marmouri (0.251). The neighbour-joining phylogenetic tree showed two groups of populations indicating a cluster of Guerzni, Khouari and Marmouri, and a clear isolation of Harcha. The genetic distances, the factorial correspondence analysis, the analysis of genetic structure and the phylogenetic tree between populations revealed significant differences between Harcha and other populations, and a high similarity between Guerzni, Khouari and Marmouri. It is concluded from this study that the camel genetic resources studied are well diversified. However, the herd management, especially the random selection of breeding animals, can increase the level of genetic mixing between different populations, mainly among Guerzni, Khouari and Marmouri, that live in the same habitat and grazing area.

Lamb live weight is one of the key drivers of profitability on sheep farms. Previous studies in Ireland have estimated genetic parameters for live weight and carcass composition traits using a multi-breed population rather than on an individual breed basis. The objective of the present study was to undertake genetic analyses of three lamb live weight and two carcass composition traits pertaining to purebred Texel, Suffolk and Charollais lambs born in the Republic of Ireland between 2010 and 2017, inclusive. Traits (with lamb age range in parenthesis) considered in the analyses were: pre-weaning weight (20 to 65 days), weaning weight (66 to 120 days), post-weaning weight (121 to 180 days), muscle depth (121 to 180 days) and fat depth (121 to 180 days). After data edits, 137 402 records from 50 372 lambs across 416 flocks were analysed. Variance components were derived using animal linear mixed models separately for each breed. Fixed effects included for all traits were contemporary group, age at first lambing of the dam, parity of the dam, a gender by age of the lamb interaction and a birth type by rearing type of the lamb interaction. Random effects investigated in the pre-weaning and weaning weight analyses included animal direct additive genetic, dam maternal genetic, litter common environment, dam permanent environment and residual variances. The model of analysis for post-weaning, muscle and fat depth included an animal direct additive genetic and litter common environment effect only. Significant direct additive genetic variation existed in all cases. Direct heritability for pre-weaning weight ranged from 0.14 to 0.30 across the three breeds. Weaning weight had a direct heritability ranging from 0.17 to 0.27 and post-weaning weight had a direct heritability ranging from 0.15 to 0.27. Muscle and fat depth heritability estimates ranged from 0.21 to 0.31 and 0.15 to 0.20, respectively. Positive direct correlations were evident for all traits. Results revealed ample genetic variation among animals for the studied traits and significant differences between breeds to suggest that genetic evaluations could be conducted on a per-breed basis.

The success in competitions may be stressful for animals and costly in terms of immune functions and longevity. Focusing on Aosta Chestnut and Aosta Black Pied cattle, selected for their fighting ability in traditional competitions, this study investigated the genetic relationships of fighting ability with udder health traits (somatic cell score and two threshold traits for somatic cells), longevity (length of productive life and number of calvings) and test-day milk, fat and protein yield. Herdbook information and phenotypic records that have been routinely collected for breeding programs in 16 years were used for the abovementioned traits. Data belonged to 9328 cows and 19 283 animals in pedigree. Single-trait animal model analyses were run using a Gibbs sampling algorithm to estimate the variance components of traits, and bivariate analyses were then performed to estimate the genetic correlations. Moderate positive genetic correlations (ra) were found for fighting ability with somatic cell score (ra=0.255), suggesting that greater fighting ability is genetically related to a detriment in udder health, in agreement with the theory. The high positive genetic correlation between fighting ability and longevity (average ra=0.669) suggests that the economic importance of fighting ability (the winning cows get an higher price at selling) had probably masked the true genetic covariances. The genetic correlation between milk yield traits and fighting ability showed large intervals, but the negative values (average ra=−0.121) agreed with previous research. This study is one of the few empirical studies on genetic correlations for the competitive success v. immune functions and longevity traits. The knowledge of the genetic correlations among productive and functional traits of interest, including fighting ability, is important in animal breeding for a sustainable genetic improvement.

Conservation of animal genetic resources requires regular monitoring and interventions to maintain population size and manage genetic variability. This study uses genealogical information to evaluate the impact of conservation measures in Europe, using (i) data from the Domestic Animal Diversity Information System (DAD-IS) and (ii) a posteriori assessment of the impact of various conservation measures on the genetic variability of 17 at-risk breeds with a wide range of interventions. Analysis of data from DAD-IS showed that 68% of national breed populations reported to receive financial support showed increasing demographic trends, v. 51% for those that did not. The majority of the 17 at-risk breeds have increased their numbers of registered animals over the last 20 years, but the changes in genetic variability per breed have not always matched the trend in population size. These differences in trends observed in the different metrics might be explained by the tensions between interventions to maintain genetic variability, and development initiatives which lead to intensification of selection.

Developing alternatives to antibiotics is an urgent need in livestock production. Antimicrobial peptides (AMPs) are regarded as powerful antibiotic substitutes (ASs) because AMPs have broad-spectrum antimicrobial activities and growth-promoting ability. Here, we aimed to comprehensively assess the effects of AMPs on the growth performance, diarrhea rate, intestinal morphology and immunity of healthy or challenged piglets, compared with an antibiotics group or negative control group. We performed a set of meta-analyses of feeding trials from database inception to 27 May 2019. Among the 1379 identified studies, 20 were included in our meta-analyses (56 arms and 4067 piglets). The meta-analyses revealed that (1) compared with the negative control group, AMPs significantly improved the healthy piglets’ average daily gain (ADG), average daily feed intake (ADFI), gain : feed ratio (G/F), levels of immune globulin (Ig) IgM and IgG, and intestinal villus height : crypt depth ratio (V/C) (P < 0.05). Meanwhile, AMPs significantly increased the challenged piglets’ ADG, ADFI, G/F and V/C of the jejunum and ileum, and notably deceased the diarrhea rate (P < 0.05); (2) compared with antibiotics group, the effects of AMPs were slightly weaker than those of antibiotics in the healthy piglets, but AMPs have similar effects to those of antibiotics in challenged piglets. In a higher purity, the optimal dose of AMPs may be approximately 0.01%. Our findings indicate that AMPs can improve piglet growth performance, enhance immunity, benefit intestinal morphology and decrease the diarrheal rate. AMPs could be great ASs especially under infection conditions.

A key concern in beef production is how to improve carcass and meat quality traits. Identifying the genomic regions and biological pathways that contribute to explaining variability in these traits is of great importance for selection purposes. In this study, genome wide-association (GWAS) and pathway-based analyses of carcass traits (age at slaughter (AS), carcass weight (CW), carcass daily gain (CDG), conformation score and rib-eye muscle area) and meat quality traits (pH, Warner-Bratzler shear force, purge loss, cooking loss and colour parameters (lightness, redness, yellowness, chroma, hue)) were conducted using genotype data from the ‘GeneSeek Genomic Profiler Bovine LD’ array in a cohort of 1166 double-muscled Piemontese beef cattle. The genome wide-association analysis was based on the GRAMMAR-GC approach and identified 37 significant single nucleotide polymorphisms (SNPs), which were associated with 12 traits (P<5 × 10−5). In particular, 14 SNPs associated with CW, CDG and AS were located at 38.57 to 38.94 Mb on Bos taurus autosome 6 and mapped within four genes, that is, Leucine Aminopeptidase 3, Family with Sequence Similarity 184 Member B, Non-SMC Condensin I Complex Subunit G and Ligand-Dependent Nuclear Receptor Corepressor-Like. Strong pairwise linkage disequilibrium was found in this region. For meat quality traits, most associations were 1 SNP per trait, except for a signal on BTA25 (at ~11.96 Mb), which was significant for four of the five meat colour parameters assessed. Gene-set enrichment analyses yielded significant results for six traits (right-sided hypergeometric test, false discovery rate <0.05). In particular, several pathways related to transmembrane transport (i.e., oxygen, calcium, ion and cation) were overrepresented for meat colour parameters. The results obtained provide useful information for genomic selection for beef production and quality in the Piemontese breed.

Large ham weight losses (WL) in dry-curing are undesired as they lead to a loss of marketable product and penalise the quality of the dry-cured ham. The availability of early predictions of WL may ease the adaptation of the dry-curing process to the characteristics of the thighs and increase the effectiveness of selective breeding in enhancing WL. Aims of this study were (i) to develop Bayesian and Random Forests (RFs) regression models for the prediction of ham WL during dry-curing using on-site infrared spectra of raw ham subcutaneous fat, carcass and raw ham traits as predictors and (ii) to estimate genetic parameters for WL and their predictions (P-WL). Visible-near infrared spectra were collected on the transversal section of the subcutaneous fat of raw hams. Carcass traits were carcass weight, carcass backfat depth, lean meat content and weight of raw hams. Raw ham traits included measures of ham subcutaneous fat depth and linear scores for round shape, subcutaneous fat thickness and marbling of the visible muscles of the thigh. Measures of WL were available for 1672 hams. The best prediction accuracies were those of a Bayesian regression model including the average spectrum, carcass and raw ham traits, with R2 values in validation of 0.46, 0.55 and 0.62, for WL at end of salting (23 days), resting (90 days) and curing (12 months), respectively. When WL at salting was used as an additional predictor of total WL, the R2 in validation was 0.67. Bayesian regressions were more accurate than RFs models in predicting all the investigated traits. Restricted maximum likelihood (REML) estimates of genetic parameters for WL and P-WL at the end of curing were estimated through a bivariate animal model including 1672 measures of WL and 8819 P-WL records. Results evidenced that the traits are heritable (h2 ± SE was 0.27 ± 0.04 for WL and 0.39 ± 0.04 for P-WL), and the additive genetic correlation is positive and high (ra = 0.88 ± 0.03). Prediction accuracy of ham WL is high enough to envisage a future use of prediction models in identifying batches of hams requiring an adaptation of the processing conditions to optimise results of the manufacturing process. The positive and high genetic correlation detected between WL and P-WL at the end of dry-curing, as well as the estimated heritability for P-WL, suggests that P-WL can be successfully used as an indicator trait of the measured WL in pig breeding programs.

Single nucleotide polymorphism (SNP) genotyping tools, which can analyse thousands of SNPs covering the whole genome, have opened new opportunities to estimate the inbreeding level of animals directly using genome information. One of the most commonly used genomic inbreeding measures considers the proportion of the autosomal genome covered by runs of homozygosity (ROH), which are defined as continuous and uninterrupted chromosome portions showing homozygosity at all loci. In this study, we analysed the distribution of ROH in three commercial pig breeds (Italian Large White, n = 1968; Italian Duroc, n = 573; and Italian Landrace, n = 46) and four autochthonous breeds (Apulo-Calabrese, n = 90; Casertana, n = 90; Cinta Senese, n = 38; and Nero Siciliano, n = 48) raised in Italy, using SNP data generated from Illumina PorcineSNP60 BeadChip. We calculated ROH-based inbreeding coefficients (FROH) using ROH of different minimum length (1, 2, 4, 8, 16 Mbp) and compared them with several other genomic inbreeding coefficients (including the difference between observed and expected number of homozygous genotypes (FHOM)) and correlated all these genomic-based measures with the pedigree inbreeding coefficient (FPED) calculated for the pigs of some of these breeds. Autochthonous breeds had larger mean size of ROH than all three commercial breeds. FHOM was highly correlated (0.671 to 0.985) with FROH measures in all breeds. Apulo-Calabrese and Casertana had the highest FROH values considering all ROH minimum lengths (ranging from 0.273 to 0.189 and from 0.226 to 0.152, moving from ROH of minimum size of 1 Mbp (FROH1) to 16 Mbp (FROH16)), whereas the lowest FROH values were for Nero Siciliano (from 0.072 to 0.051) and Italian Large White (from 0.117 to 0.042). FROH decreased as the minimum length of ROH increased for all breeds. Italian Duroc had the highest correlations between all FROH measures and FPED (from 0.514 to 0.523) and between FHOM and FPED (0.485). Among all analysed breeds, Cinta Senese had the lowest correlation between FROH and FPED. This might be due to the imperfect measure of FPED, which, mainly in local breeds raised in extensive production systems, cannot consider a higher level of pedigree errors and a potential higher relatedness of the founder population. It appeared that ROH better captured inbreeding information in the analysed breeds and could complement pedigree-based inbreeding coefficients for the management of these genetic resources.

Knowledge of population structure and breed composition of a population can be advantageous for a number of reasons; these include designing optimal (cross)breeding strategies in order to maximise non-additive genetic effects, maintaining flockbook integrity by authenticating animals being registered and as a quality control measure in the genotyping process. The objectives of the present study were to 1) describe the population structure of 24 sheep breeds, 2) quantify the breed composition of both flockbook-recorded and crossbred animals using single nucleotide polymorphism BLUP (SNP-BLUP), and 3) quantify the accuracy of breed composition prediction from low-density genotype panels containing between 2000 and 6000 SNPs. In total, 9334 autosomal SNPs on 11 144 flockbook-recorded animals and 1172 crossbred animals were used. The population structure of all breeds was characterised by principal component analysis (PCA) as well as the pairwise breed fixation index (Fst). The total number of animals, all of which were purebred, included in the calibration population for SNP-BLUP was 2579 with the number of animals per breed ranging from 9 to 500. The remaining 9559 flockbook-recorded animals, composite breeds and crossbred animals represented the test population; three breeds were excluded from breed composition prediction. The breed composition predicted using SNP-BLUP with 9334 SNPs was considered the gold standard prediction. The pairwise breed Fst ranged from 0.040 (between the Irish Blackface and Scottish Blackface) to 0.282 (between the Border Leicester and Suffolk). Principal component analysis revealed that the Suffolk from Ireland and the Suffolk from New Zealand formed distinct, non-overlapping clusters. In contrast, the Texel from Ireland and that from New Zealand formed integrated, overlapping clusters. Composite animals such as the Belclare clustered close to its founder breeds (i.e., Finn, Galway, Lleyn and Texel). When all 9334 SNPs were used to predict breed composition, an animal that had a majority breed proportion predicted to be ≥0.90 was defined as purebred for the present study. As the panel density decreased, the predicted breed proportion threshold, used to identify animals as purebred, also decreased (≥0.85 with 6000 SNPs to ≥0.60 with 2000 SNPs). In all, results from the study suggest that breed composition for purebred and crossbred animals can be determined with SNP-BLUP using ≥5000 SNPs.

In the mink industry, feed costs are the largest variable expense and breeding for feed efficient animals is warranted. Implementation of selection for feed efficiency must consider the relationships between feed efficiency and the current selection traits BW and litter size. Often, feed intake (FI) is recorded on a cage with a male and a female and there is sexual dimorphism that needs to be accounted for. Study aims were to (1) model group recorded FI accounting for sexual dimorphism, (2) derive genetic residual feed intake (RFI) as a measure of feed efficiency, (3) examine the relationship between feed efficiency and BW in males (BWM) and females (BWF) and litter size at day 21 after whelping (LS21) in Danish brown mink and (4) investigate direct and correlated response to selection on each trait of interest. Feed intake records from 9574 cages, BW records on 16 782 males and 16 875 females and LS21 records on 6446 yearling females were used for analysis. Genetic parameters for FI, BWM, BWF and LS21 were obtained using a multivariate animal model, yielding sex-specific additive genetic variances for FI and BW to account for sexual dimorphism. The analysis was performed in a Bayesian setting using Gibbs sampling, and genetic RFI was obtained from the conditional distribution of FI given BW using genetic regression coefficients. Responses to single trait selection were defined as the posterior distribution of genetic superiority of the top 10% of animals after conditioning on the genetic trends. The heritabilities ranged from 0.13 for RFI in females and LS21 to 0.59 for BWF. Genetic correlations between BW in both sexes and LS21 and FI in both sexes were unfavorable, and single trait selection on BW in either sex showed increased FI in both sexes and reduced litter size. Due to the definition of RFI and high genetic correlation between BWM and BWF, selection on RFI did not significantly alter BW. In addition, selection on RFI in either sex did not affect LS21. Genetic correlation between sexes for FI and BW was high but significantly lower than unity. The high correlations across sex allowed for selection on standardized averages of animals’ breeding values (BVs) for RFI, FI and BW, which yielded selection responses approximately equal to the responses obtained using the sex-specific BVs. The results illustrate the possibility of selecting against RFI in mink with no negative effects on BW and litter size.

Remarkable increases in the production of dairy animals have negatively impacted their tolerance to heat stress (HS). The evaluation of the effect of HS on milk yield is based on the direct impact of HS on performance. However, in practical terms, HS also exerts its influence during gestation (indirect effect). The main purpose of this study was to identify and characterize the genotype by environment interaction (G × E) due to HS during the last 60 days of gestation (THI_g) and also the HS postpartum (THI_m) over first lactation milk production of Brazilian Holstein cattle. A total of 389 127 test day milk yield (TD) records from 1572 first lactation Holstein cows born in Brazil (daughters of 1248 dams and 70 sires) and the corresponding temperature–humidity index (THI) obtained between December 2007 and January 2013 were analyzed using different random regression models. Cows in the cold environment (THI_g = 64 to 73) during the last 60 days of gestation produced more milk than those cows in a hot environment (THI_g = 74 to 84), particularly during the first 150 days of lactation (DIM). The heritabilities (h2) of TD were similar throughout DIM for cows in THI_g hot (0.11 to 0.20) or (0.10 to 0.22), while the genetic correlations (rg) for TD between these two environments ranged from 0.11 to 0.52 along the first 250 DIM. The h2 estimates for TD across THI_m were similar for cows in THI_g hot (0.07 to 0.25) and THI_g cold (0.08 to 0.19). The rg estimates ranged from 0.17 to 0.42 along THI_m between TD of cows in cold and hot THI_g. The results were consistent in demonstrating the existence of an additional source of G × E for TD due to THI_g and THI_m. The present study is probably the first to provide evidence of this source of G × E; further research is needed because of its importance when the breeding objective is to select animals that are more tolerant to HS.

Pregastric fermentation along with production practices that are dependent on high-energy diets means ruminants rely heavily on starch and protein assimilation for a substantial portion of their nutrient needs. While the majority of dietary starch may be fermented in the rumen, significant portions can flow to the small intestine. The initial phase of small intestinal digestion requires pancreatic α-amylase. Numerous nutritional factors have been shown to influence pancreatic α-amylase secretion with starch producing negative effects and casein, certain amino acids and dietary energy having positive effects. To date, manipulation of α-amylase secretion has not resulted in substantial changes in digestibility. The second phase of digestion involves the actions of the brush border enzymes sucrase-isomaltase and maltase-glucoamylase. Genetically, ruminants appear to possess these enzymes; however, the absence of measurable sucrase activity and limited adaptation with changes in diet suggests a reduced capacity for this phase of digestion. The final phase of carbohydrate assimilation is glucose transport. Ruminants possess Na+-dependent glucose transport that has been shown to be inducible. Because of the nature of pregastric fermentation, ruminants see a near constant flow of microbial protein to the small intestine. This results in a nutrient supply, which places a high priority on protein digestion and utilization. Comparatively, little research has been conducted describing protein assimilation. Enzymes and processes appear consistent with non-ruminants and are likely not limiting for efficient digestion of most feedstuffs. The mechanisms regulating the nutritional modulation of digestive function in the small intestine are complex and coordinated via the substrate, neural and hormonal effects in the small intestine, pancreas, peripheral tissues and the pituitary—hypothalamic axis. More research is needed in ruminants to help unravel the complexities by which small intestinal digestion is regulated with the aim of developing approaches to enhance and improve the efficiency of small intestinal digestion.

Accurate estimates of methane (CH4) production by cattle in different contexts are essential to developing mitigation strategies in different regions. We aimed to: (i) compile a database of CH4 emissions from Brazilian cattle studies, (ii) evaluate prediction precision and accuracy of extant proposed equations for cattle and (iii) develop specialized equations for predicting CH4 emissions from cattle in tropical conditions. Data of nutrient intake, diet composition and CH4 emissions were compiled from in vivo studies using open-circuit respiratory chambers, SF6 technique or the GreenFeed® system. A final dataset containing intake, diet composition, digestibility and CH4 emissions (677 individual animal observations, 40 treatment means) obtained from 38 studies conducted in Brazil was used. The dataset was divided into three groups: all animals (GEN), lactating dairy cows (LAC) and growing cattle and non-lactating dairy cows (GCNL). A total of 54 prediction equations available in the literature were evaluated. A total of 96 multiple linear models were developed for predicting CH4 production (MJ/day). The predictor variables were DM intake (DMI), gross energy (GE) intake, BW, DMI as proportion of BW, NDF concentration, ether extract (EE) concentration, dietary proportion of concentrate and GE digestibility. Model selection criteria were significance (P < 0.05) and variance inflation factor lower than three for all predictors. Each model performance was evaluated by leave-one-out cross-validation. The Intergovernmental Panel on Climate Change (2006) Tier 2 method performed better for GEN and GCNL than LAC and overpredicted CH4 production for all datasets. Increasing complexity of the newly developed models resulted in greater performance. The GCNL had a greater number of equations with expanded possibilities to correct for diet characteristics such as EE and NDF concentrations and dietary proportion of concentrate. For the LAC dataset, equations based on intake and animal characteristics were developed. The equations developed in the present study can be useful for accurate and precise estimation of CH4 emissions from cattle in tropical conditions. These equations could improve accuracy of greenhouse gas inventories for tropical countries. The results provide a better understanding of the dietary and animal characteristics that influence the production of enteric CH4 in tropical production systems.

Feeding costs represent one of the highest expenditures in animal production systems. Breeding efficient animals that express their growth potential while eating less is therefore a major objective for breeders. We estimated the genetic parameters for feed intake, feed efficiency traits (residual feed intake (RFI) and feed conversion ratio (FCR)), growth and body composition traits in the Romane meat sheep breed. In these traits, selection responses to single-generation divergent selection on RFI were evaluated. From 2009 to 2016, a total of 951 male lambs were tested for 8 weeks starting from 3 months of age. They were weighed at the beginning and at the end of the testing period. Backfat thickness and muscle depth were recorded at the end of the testing period through ultrasound measurements. Feed intake was continuously recorded over the testing period using the automatic concentrate feeders. The heritability of RFI was estimated at 0.45 ± 0.08, which was higher than the heritability of FCR (0.30 ± 0.08). No significant genetic correlations were observed between RFI and growth traits. A favourable low negative genetic correlation was estimated between RFI and muscle depth (−0.30 ± 0.15), though additional data are needed to confirm these results. The selection of low RFI sires based on their breeding values led to the production of lambs eating significantly less concentrate (3% decrease in the average daily feed intake), but with the same growth as lambs from sires selected based on high RFI breeding values. We concluded that in meat sheep, RFI is a heritable trait that is genetically independent of post-weaning growth and body composition traits. A one-generation divergent selection based on RFI breeding values highlighted that substantial gains in feeding costs can be expected in selection schemes for meat sheep breeds.