Selection For Residual Feed Intake Research Articles

Relationship between feed efficiency and gut microbiota in laying chickens under contrasting feeding conditions

The gut microbiota is known to play an important role in energy harvest and is likely to affect feed efficiency. In this study, we used 16S metabarcoding sequencing to analyse the caecal microbiota of laying hens from feed-efficient and non-efficient lines obtained by divergent selection for residual feed intake. The two lines were fed either a commercial wheat-soybean based diet (CTR) or a low-energy, high-fibre corn-sunflower diet (LE). The analysis revealed a significant line x diet interaction, highlighting distinct differences in microbial community composition between the two lines when hens were fed the CTR diet, and more muted differences when hens were fed the LE diet. Our results are consistent with the hypothesis that a richer and more diverse microbiota may play a role in enhancing feed efficiency, albeit in a diet-dependent manner. The taxonomic differences observed in the microbial composition seem to correlate with alterations in starch and fibre digestion as well as in the production of short-chain fatty acids. As a result, we hypothesise that efficient hens are able to optimise nutrient absorption through the activity of fibrolytic bacteria such as Alistipes or Anaerosporobacter, which, via their production of propionate, influence various aspects of host metabolism.

Genomic analysis of feed efficiency traits in beef cattle using random regression models.

Feed efficiency plays a major role in the overall profitability and sustainability of the beef cattle industry, as it is directly related to the reduction of the animal demand for input and methane emissions. Traditionally, the average daily feed intake and weight gain are used to calculate feed efficiency traits. However, feed efficiency traits can be analysed longitudinally using random regression models (RRMs), which allow fitting random genetic and environmental effects over time by considering the covariance pattern between the daily records. Therefore, the objectives of this study were to: (1) propose genomic evaluations for dry matter intake (DMI), body weight gain (BWG), residual feed intake (RFI) and residual weight gain (RWG) data collected during an 84-day feedlot test period via RRMs; (2) compare the goodness-of-fit of RRM using Legendre polynomials (LP) and B-spline functions; (3) evaluate the genetic parameters behaviour for feed efficiency traits and their implication for new selection strategies. The datasets were provided by the EMBRAPA-GENEPLUS beef cattle breeding program and included 2920 records for DMI, 2696 records for BWG and 4675 genotyped animals. Genetic parameters and genomic breeding values (GEBVs) were estimated by RRMs under ssGBLUP for Nellore cattle using orthogonal LPs and B-spline. Models were compared based on the deviance information criterion (DIC). The ranking of the average GEBV of each test week and the overall GEBV average were compared by the percentage of individuals in common and the Spearman correlation coefficient (top 1%, 5%, 10% and 100%). The highest goodness-of-fit was obtained with linear B-Spline function considering heterogeneous residual variance. The heritability estimates across the test period for DMI, BWG, RFI and RWG ranged from 0.06 to 0.21, 0.11 to 0.30, 0.03 to 0.26 and 0.07 to 0.27, respectively. DMI and RFI presented within-trait genetic correlations ranging from low to high magnitude across different performance test-day. In contrast, BWG and RWG presented negative genetic correlations between the first 3 weeks and the other days of performance tests. DMI and RFI presented a high-ranking similarity between the GEBV average of week eight and the overall GEBV average, with Spearman correlations and percentages of individuals selected in common ranging from 0.95 to 1.00 and 93 to 100, respectively. Week 11 presented the highest Spearman correlations (ranging from 0.94 to 0.98) and percentages of individuals selected in common (ranging from 85 to 94) of BWG and RWG with the average GEBV of the entire period of the test. In conclusion, the RRM using linear B-splines is a feasible alternative for the genomic evaluation of feed efficiency. Heritability estimates of DMI, RFI, BWG and RWG indicate enough additive genetic variance to achieve a moderate response to selection. A new selection strategy can be adopted by reducing the performance test to 56 days for DMI and RFI selection and 77 days for BWG and RWG selection.

Small networks of expressed genes in the whole blood and relationships to profiles in circulating metabolites provide insights in inter-individual variability of feed efficiency in growing pigs

BackgroundFeed efficiency is a research priority to support a sustainable meat production. It is recognized as a complex trait that integrates multiple biological pathways orchestrated in and by various tissues. This study aims to determine networks between biological entities to explain inter-individual variation of feed efficiency in growing pigs.ResultsThe feed conversion ratio (FCR), a measure of feed efficiency, and its two component traits, average daily gain and average daily feed intake, were obtained from 47 growing pigs from a divergent selection for residual feed intake and fed high-starch or high-fat high-fiber diets during 58 days. Datasets of transcriptomics (60 k porcine microarray) in the whole blood and metabolomics (1H-NMR analysis and target gas chromatography) in plasma were available for all pigs at the end of the trial. A weighted gene co-expression network was built from the transcriptomics dataset, resulting in 33 modules of co-expressed molecular probes. The eigengenes of eight of these modules were significantly (P le 0.05) or tended to be (0.05 < P le 0.10) correlated to FCR. Great homogeneity in the enriched biological pathways was observed in these modules, suggesting co-expressed and co-regulated constitutive genes. They were mainly enriched in genes participating to immune and defense-related processes, and to a lesser extent, to translation, cell development or learning. They were also generally associated with growth rate and percentage of lean mass. In the whole network, only one module composed of genes participating to the response to substances, was significantly associated with daily feed intake and body adiposity. The plasma profiles in circulating metabolites and in fatty acids were summarized by weighted linear combinations using a dimensionality reduction method. Close association was thus found between a module composed of co-expressed genes participating to T cell receptor signaling and cell development process in the whole blood and related to FCR, and the circulating concentrations of polyunsaturated fatty acids in plasma.ConclusionThese systemic approaches have highlighted networks of entities driving key biological processes involved in the phenotypic difference in feed efficiency between animals. Connecting transcriptomics and metabolic levels together had some additional benefits.

Transcriptome analysis of divergent residual feed intake phenotypes in the M. longissimus thoracis et lumborum of Wannan Yellow rabbits

Introduction: Feed efficiency is an important economic trait in rabbit meat production. The identification of molecular mechanisms and candidate genes for feed efficiency may improve the economic and environmental benefits of the rabbit meat industry. As an alternative to the conventional feed conversion ratio, residual feed intake (RFI) can be used as an accurate indicator of feed efficiency.Methods: RNA sequencing was used to identify the differentially expressed genes (DEGs) in the M. longissimus thoracis et lumborum of eight Wannan Yellow rabbits with excessively high or low RFIs (HRFI or LRFI, respectively). Thereafter, Gene Ontology (GO) analysis, enrichment using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, gene set enrichment analysis (GSEA), and protein–protein interaction (PPI) network analysis was conducted.Results: In total, 445 DEGs were identified in the M. longissimus thoracis et lumborum of rabbits with high and low RFIs. The significantly enriched GO terms identified in these two groups were primarily involved in energy and mitochondrial metabolism and oxidation–reduction processes. KEGG analysis identified 11 significantly enriched pathways, including oxidative phosphorylation, PI3K-Akt signaling, and extracellular matrix-receptor interaction pathways. According to GSEA, the expressions of genes and pathways related to mitochondrial function were upregulated in HRFI rabbits, whereas genes with upregulated expressions in LRFI rabbits were related to immune response and energy metabolism. Additionally, PPI network analysis revealed five potential candidate genetic markers.Conclusion: Comparative analysis of the M. longissimus thoracis et lumborum transcriptomes in HRFI and LRFI rabbits revealed FOS, MYC, PRKACB, ITGA2, and FN1 as potential candidate genes that affect feed efficiency in rabbits. In addition, key signaling pathways involved in oxidative phosphorylation and PI3K-Akt and ECM-receptor interaction signaling impact rabbit feed efficiency. These findings will aid in breeding programs to improve feed efficiency and optimize RFI selection of rabbits for meat production.

A machine learning approach to predict the most and the least feed–efficient groups in beef cattle

The present study evaluated three strategies to find the optimum subset of DNA markers from the 50 K Illumina Bovine panel to classify beef cattle into the most and the least feed-efficient groups without using individual feed intake and performance measures. Residual feed intake (RFI) and 50 K single nucleotide polymorphisms (SNPs) genotype data of 4,057 beef animals from research and commercial herds were included. Initially, all cattle were ranked based on their phenotypic RFI values. Then different datasets were created by selecting animals from the 1%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, and 45% range of top and bottom of the ranked RFI values. SNP subsets were selected based on the top-ranked SNPs contributing to the variance of RFI (first strategy), selecting SNPs from the SNP subsets created in the first strategy (strategy 2), and extracting SNPs from 50k SNPs (strategy 3). Then eleven ML algorithms were employed to classify the most and the least feed-efficient groups using 260 datasets generated by combinations of ten RFI phenotype percentage groups and 6, 18, and 2 SNP subsets in the first, second and third strategies, respectively. There was a high degree of accuracy (>69%) for classifying animals in the range of 1% for all ML algorithms under the three strategies and different SNP subsets. Implementing the linear Support Vector Machine algorithm for 15 K SNPs obtained in the first strategy predicted the 1% of the most and the least feed-efficient animals with an accuracy of 84%. In the second strategy, selecting 524 SNPs from the 15 K SNPs subset outperformed the other strategies with an accuracy of 81% for 1% of the population using the Naive Bayes algorithm. It was concluded that a smaller number of SNPs (524) could be used to predict the most and the least feed-efficient animals with an acceptable accuracy to reduce the cost of selection for RFI using genomic information.

O57 Energy efficiency of beef cattle in grazing production systems – I. Effect of selection for residual feed intake

O57 Energy efficiency of beef cattle in grazing production systems – I. Effect of selection for residual feed intake

Predicting feed efficiency traits in growing lambs from their ruminal microbiota

Selecting feed-efficient sheep could improve the sustainability of this livestock production. However, most sheep breeding companies cannot afford to record feed intake to select feed-efficient animals. Past studies underlined the potential of omics data, including microbiota metabarcoding data, as proxies for feed efficiency. The study involved 277 Romane lambs from two lines divergently selected for residual feed intake (RFI). There were two objectives: check the consequences of selecting for feed efficiency over the rumen microbiota, and assess the predictive ability of the rumen microbiota for host traits. The study assessed two contrasting diets (concentrate diet and mixed diet) and two microbial groups (prokaryotes and eukaryotes). Discriminant analyses did not highlight any significant effect of sheep selection for residual feed intake on the rumen microbiota composition. Indeed, prokaryotic and eukaryotic microbiota compositions poorly discriminated the RFI lines, with averaged balanced error rates ranging from 45% to 55%. Correlations between host traits (feed efficiency and production traits) and their predictions from microbiota data varied between −0.07 and 0.56, depending on the trait, diet and sequencing. Feed intake was the most accurately predicted trait. However, predictions from fixed effects and BW were more accurate than or as accurate as predictions from the microbiota. Environmental effects can greatly affect the variability of microbiota compositions. Considering batch and environmental effects should be paramount when the predictive ability of the microbiota is assessed. This study argues why metabarcoding the rumen microbiota is not the best way to predict meat sheep production traits: fixed effects and BW were more cost-effective proxies and they led to similar or better predictive accuracies than microbiota metabarcoding (16S and 18S sequencing).

Genetic association between feed efficiency, growth, scrotal circumference, and carcass traits in Guzerat cattle.

The objective of this study was to estimate the genetic parameters for feed efficiency-related traits and their genetic correlations with growth, male fertility, and carcass traits using multi-trait analysis in Guzerat cattle. Further, it aimed to predict the direct and correlated responses for feed efficiency traits when selection was applied for growth, male fertility, and carcass traits. The evaluated traits were adjusted weight at 120 (W120), 210 (W210), 365 (W365), and 450days of age (W450), adjusted scrotal circumference at 365days of age (SC365) and at 450days of age (SC450), scrotal circumference, ribeye area (REA), backfat thickness (BFT), rump fat thickness (RFT), residual feed intake (RFI), and dry matter intake (DMI). The genetic parameters were obtained by the restricted maximum likelihood method (REML), using an animal model in multi-trait analyses. The heritability estimates for W120, W210, W365, W450, SC365, and SC450 varied from low to high (0.17 to 0.39). The carcass traits, REA, BFT, and RFT, displayed low to moderate heritability estimates, 0.27, 0.10, and 0.31, respectively. The heritability estimates for RFI (0.15) and DMI (0.23) were low and moderate, respectively. The RFI showed low genetic correlations with growth traits, ranging from - 0.07 to 0.22, from 0.03 to 0.05 for scrotal circumference, and from - 0.35 to 0.16 for carcass, except for DMI, which ranged from 0.42 to 0.46. The RFI and DMI presented enough additive genetic variability to be used as selection criteria in Guzerat breed genetic improvement program. Additionally, the response to selection for RFI would be higher when selection is performed directly for this trait. The selection for residual feed intake would not promote unfavorable correlated responses for scrotal circumference, carcass (yield and finish), and growth traits. Therefore, the selection for more efficient animals would not compromise the productive, reproductive, and carcass performance, contributing to reduce the production costs, increasing the profitability and sustainability of beef cattle production in tropical areas.

Genetic correlation between feed efficiency and carcass traits in Nellore cattle in Brazil

The aim was to estimate the genetic correlations between residual feed intake (RFI) and dry matter intake (DMI) with carcass finish (CF), rib eye area (REA), and marbling (MAR) of Nellore cattle. Data from 7,808 animals were considered. In addition, data from 2,261 females included in the complete database were also considered. Estimates of variance and covariance components, as well as heritabilities and genetic correlations were obtained by means of two-character analysis under animal model. Heritability estimates were found to be moderate for the RFI (0.22) and DMI (0.29) traits. It was observed that genetic correlation was close to zero for all traits, except between RFI and REA (-0.11). However, considering the female population, there was an increase in the estimated genetic correlation between RFI and DMI, although still a favorable genetic association of low magnitude (-0.30). There was also an increase in the genetic association of REA with RFI (-0.21). It can be concluded that the direct selection for RFI and DMI will not influence the CF, MAR, or REA of Nellore cattle. However, this selection may generate some favorable responses in MAR and REA in Nellore females.

Assessment of Feed Efficiency and Its Relationship with Egg Quality in Two Purebred Chicken Lines and Their Reciprocal Crosses

Crossbreeding is normally applied to improve the economical traits of chickens. However, feed efficiency and its relationship with egg quality have rarely been explored in crossbreds. Herein, White Leghorn and Beijing You chickens were selected to generate purebreds (WW, YY) and reciprocal crossbreds (YW, WY), which were evaluated in terms of daily feed intake (DFI), feed conversion ratio (FCR), and residual feed intake (RFI) at 43 to 46 and 69 to 72 weeks of age, respectively. We found that WY was more efficient than YW in both laying periods. The correlation analysis showed that RFI was highly correlated with DFI (0.49 to 0.84) but unrelated to egg mass, and FCR was negatively correlated with egg mass (−0.77 to −0.43) in both purebreds and crossbreds. Moreover, RFI was not correlated with egg quality traits within each genetic group, except for the egg yolk ratio (0.27) in WW. FCR was negatively correlated with eggshell weight and thickness (−0.33 to −0.19) in WW and WY. Compared to FCR, selection for RFI could improve feed efficiency without significant changes in egg mass and quality in chickens. These findings provide new insights into the improvement of feed efficiency using rational parental lines in chicken crossbreeding.

Long-term divergent selection for residual feed intake in Chinese broiler chickens

This study aimed to assess the effect of inbreeding on production traits using a long-term closed-line population recorded for residual feed intake (RFI). The study first used data from a previously reported population to determine the appropriate period of divergent selection for RFI. The results showed that RFI had similar moderate heritability estimates (0.28-0.34) during the fast-growing period (7-12 wk), and RFI at 7 to 10 wk had the highest heritability (0.34). Therefore, divergent selection was performed in a Chinese broiler population for RFI at 7 to 10 wk; the total sample size from generations zero (G0) to 13 was 9050. The divergence between the 2 lines increased steadily throughout generations, resulting in G13 with average RFI values of 304.55 in high RFI (HRFI) males, -160.31 in low RFI (LRFI) males, 296.30 in HRFI females and -157.55 in LRFI females. The feed intake (FI) and feed conversion ratio were almost higher in HRFI broilers than in LRFI broilers, and the magnitude of the difference in FI increased from approximately 4% for both sexes in G1 to approximately 33% in G13. Body weight gain was irregular from G1 to G13 and higher in LRFI broilers than in HRFI broilers after G10. Indeed, the HRFI broilers consumed more food, but they were lighter than LRFI broilers. In G13, LRFI males had heavier slaughter weight, longer cecum length, more white blood cells (WBC), red blood cells (RBC) and hemoglobin (HGB), but triglycerides, lower dressed percentage, percentage of half eviscerated yield, and eviscerated yield than HRFI males. LRFI females had a higher percentage of breast muscle and gizzard yield, longer cecum length, and more WBCs, RBCs and HGB but less abdominal fat and serum total cholesterol than HRFI females. This study was the first to verify that long-term divergent selection for RFI in Chinese broiler chickens is positive and beneficial.

23 Sustainable Livestock Breeding with a Focus on Heat Stress

Abstract The genetic selection is a form of optimization. Traits in explicit or implicit selection index are improved, while other traits change according to genetic correlations among the traits. After long selection, usually production traits improve while fitness traits deteriorate. At the gene level, it seems that genes associated with positive effects on major traits tend to fixation, and remaining genes with large effect exhibit pleiotropy. While selection for fitness traits is moderately successful because of small heritability, constantly improving management counterbalances the deterioration of fitness traits. Treating the selection as an optimization raises a question about selection limits, particular with feed conversion. Latest experiences suggest that eventually strong selection for residual feed intake reduces fertility and increases late mortality. The environment changes, with climate change having a profound effect. The industry faces a choice of either breeding for new conditions or devising new managemental modifications. The choice depends on species as the environment can be more easily improved for animals in confinement or raised in intensive conditions (pigs, broilers, dairy cattle), but less for animals on pasture (beef cattle and sheep). The choice depends on financials and speed. An interesting example of such a trade-off is in dairy industry approach to mitigate heat stress, which results in plummeting fertility, decreased milk yield, and premature culling leading to insufficient replacements. To counter these challenges, a methodology for genetic evaluation for heat tolerance was developed and applied to US national data for Holsteins. Instead of genetics, the industry implemented managemental modifications: improved cooling devices, timed AI increased fertility, and the use of sexed semen. In pigs and chicken, that the response to stress is less in nucleus and stronger in commercial environment, and selection for commercial performance is paramount. In summary, mitigations of stress involve a combination of genetic and environmental factors.

Poor hygiene of housing conditions influences energy metabolism in a muscle type-dependent manner in growing pigs differing in feed efficiency

The ability of pigs to cope with inflammatory challenges may by modified by selection for residual feed intake (RFI), a measure of feed efficiency. In the current study, we evaluated skeletal muscle metabolic responses to degraded hygiene conditions in pigs divergently selected for RFI. At 82 d of age, low RFI and high RFI pigs were housed in either poor or good hygiene conditions. After a 6-week challenge, the poor hygiene conditions induced a decrease in growth performance (P < 0.001) and in plasma IGF-I concentrations (P < 0.003) in both lines. In the slow-twitch oxidative semispinalis muscle, poor hygiene conditions induced a shift towards a more oxidative metabolism and an activation of the AMPK pathway in pigs of both RFI lines. In the fast-twitch glycolytic longississimus muscle, poor hygiene conditions were associated to a less glycolytic metabolism in the HRFI line only. Poor hygiene conditions also increased the protein level of lipidation of microtubule-associated protein 1 light-chain 3β (LC3-II) in both RFI lines, suggesting an activation of the autophagy pathway. Altogether, the data revealed muscle-type specific metabolic adaptations to poor hygiene conditions, which may be related to different strategies to fuel the activated immune system.

Estimates of variance components for feedlot traits of the Simmentaler breed in South Africa

Breeding of beef cattle is changing, with more emphasis on efficiency of production. Feed cost is the highest expense, and reducing it has the potential to increase profitability. Common measures of efficiency are ratio traits such as feed conversion (feed consumed/weight gain) and feed efficiency (weight gain / feed consumed). Feed conversion ratio is commonly used in South Africa in an attempt to improve feed efficiency. These ratio traits are associated with growth rate. Selection for them would result in higher growth as a correlated response and might also increase the mature size of the cows and their maintenance cost. Thus, alternative efficiency traits such as residual feed intake and residual daily gain have been proposed. In this study, variance components, and genetic parameters for feedlot traits for the South African Simmentaler breed were estimated, with emphasis on the efficiency traits. The focus was to evaluate the use of residual feed intake as an alternative trait. The results indicate non-significant correlations between residual feed intake and body weight and growth traits, implying that residual feed intake should have little effect on the other traits. This is in contrast to the moderate to strong correlations of feed conversion ratio with the same traits. The study demonstrates that considerable genetic variation exists for residual feed intake, which can be exploited. Selection for residual feed intake can reduce the carbon footprint of beef due to the associated lower methane emissions.

Effects of feed efficiency and diet on performance and carcass characteristics in growing wether lambs

Selection for feed efficiency may lead to decreased production inputs; however, associations between feed efficiency and other phenotypic traits of interest in sheep are not well understood. The objectives of this study were to 1) determine the effect of diet on feed intake traits, 2) determine the effect of dietary change on residual feed intake (RFI) and performance traits, and 3) determine relationships of RFI with carcass characteristics in lambs fed either a concentrate or forage-based diet. In Trial 1, growing wethers (initial live weight (LW) = 51.3 ± 1.2 kg; n = 78) of Hampshire (n = 35), Rambouillet (n = 26), and Suffolk (n = 17) breed types were blocked by breed and initial LW and randomly allocated to receive a concentrate (50.2% corn, 31.0% wheat middlings, 10.0% corn gluten, 2.5% cane molasses, 1.8% calcium carbonate, 1.0% dried distillers grains with soluble, 0.8% calcium sulfate, 0.2% potassium chloride, 0.4% trace minerals and vitamins; 91.6% DM; 12.1% CP, 17.6% NDF, 3.0 Mcal/kg ME; n = 40) or forage-based (67.7% alfalfa, 27.5% wheat middlings, 2.5% cane molasses, 1.3% salt, 0.6% calcium carbonate, 0.3% trace minerals and vitamins; 92.3% DM, 16.2% CP, 36.3% NDF, 2.3 Mcal/kg ME; n = 38) pelleted diet. Individual feed intake was recorded using a GrowSafe System for 49 days and RFI was estimated for each wether. Using RFI to rank the wethers for feed efficiency, the 20% most (n = 8) and the 20% least (n = 8) efficient wethers from each diet (n = 32 total) were slaughtered and carcass data were recorded. Remaining wethers from the forage diet were subsequently changed to the concentrate diet for Trial 2; individual feed intake was again collected using the GrowSafe System for 79 days, and RFI calculated for each wether. The MIXED procedure of SAS was used to determine the effect of diet and diet change on performance traits in Trials 1 and 2, respectively, and the effects of diet, RFI class (most or least efficient), and their interaction on carcass traits using data from selected wethers (n = 32) from Trial 1; breed and pen were included as random effects. The CORR procedure of SAS was used to determine relationships of RFI with performance traits and carcass characteristics. Overall, feed intake was less variable for concentrate-fed (σ2 = 0.13 kg2) than forage-fed wethers (σ2 = 0.25 kg2). Feed intake and average daily gain (ADG) were greater (P ≤ 0.001) in forage-fed compared to concentrate-fed wethers, although the gain to feed ratio (G:F) was not affected by diet type (P = 0.23). While RFI and RFI rankings were moderately correlated (r = 0.51, r = 54, respectively; P ≤ 0.02) in wethers subjected to the diet change (forage to concentrate), some re-ranking was observed, especially in low efficiency lambs. Boneless cut percentage tended (P = 0.10) to be greater in forage versus concentrate wethers; there were no other effects (P ≥ 0.13) of diet on carcass measures. Residual feed intake and USDA quality grade tended (P = 0.10) to be positively correlated, but no other relationships (P ≥ 0.17) between RFI and carcass measures were observed. These data suggest that feed intake and ADG are affected by diet type, and that greater variation in feed intake is associated with a forage-based pelleted diet. Additionally, selection against low feed efficiency may be most effective in improving flock feed efficiency genetics when compared with selection for greater efficiency. Furthermore, selection for RFI should not unfavorably affect carcass traits in sheep.

Exploring Biological Impacts of Prenatal Nutrition and Selection for Residual Feed Intake on Beef Cattle Using Omics Technologies: A Review.

Approximately 70% of the cost of beef production is impacted by dietary intake. Maximizing production efficiency of beef cattle requires not only genetic selection to maximize feed efficiency (i.e., residual feed intake (RFI)), but also adequate nutrition throughout all stages of growth and development to maximize efficiency of growth and reproductive capacity, even during gestation. RFI as a measure of feed efficiency in cattle has been recently accepted and used in the beef industry, but the effect of selection for RFI upon the dynamics of gestation has not been extensively studied, especially in the context of fluctuating energy supply to the dam and fetus. Nutrient restriction during gestation has been shown to negatively affect postnatal growth and development as well as fertility of beef cattle offspring. This, when combined with the genetic potential for RFI, may significantly affect energy partitioning in the offspring and subsequently important performance traits. In this review, we discuss: 1) the importance of RFI as a measure of feed efficiency and how it can affect other economic traits in beef cattle; 2) the influence of prenatal nutrition on physiological phenotypes in calves; 3) the benefits of investigating the interaction of genetic selection for RFI and prenatal nutrition; 4) how metabolomics, transcriptomics, and epigenomics have been employed to investigate the underlying biology associated with prenatal nutrition, RFI, or their interactions in beef cattle; and 5) how the integration of omics information is adding a level of deeper understanding of the genetic architecture of phenotypic traits in cattle.

Impact of genetic potential for residual feed intake and diet fed during early- to mid-gestation in beef heifers on carcass characteristics and meat quality attributes of their castrated male offspring

Carcass attributes of steers were examined for influences of selection for residual feed intake (RFI), and exposure to different levels of prenatal nutrition. Heifers characterized for RFI corrected for backfat were mated to bulls with genetic potential for either High-RFI or Low-RFI, such that the progeny were expected to be H/H or L/L RFI (sire/dam). Pregnant heifers were assigned to a low diet (Ldiet; 0.40 kg/d ADG), or moderate diet (Mdiet; 0.57 kg/d ADG), from 30 to 150 days of gestation, after which all heifers were managed similarly. Steer offspring (n = 23) were also managed similarly until slaughter. Dressing percentage of steers from H-RFI dams/sires exposed to Ldiet during gestation was lower than all other groups (P = 0.02). Marbling was greater for steers from H-RFI parents, as was fat content of longissimus thoracis et lumborum and triceps brachii (P ≤ 0.02). Results suggest that parental selection for RFI and prenatal maternal diet can influence carcass characteristics of progeny.

Genetic relationships between feed efficiency and gut microbiome in pig lines selected for residual feed intake.

This study aimed to evaluate the genetic relationship between faecal microbial composition and five feed efficiency (FE) and production traits, residual feed intake (RFI), feed conversion ratio (FCR), daily feed intake (DFI), average daily gain (ADG) and backfat thickness (BFT). A total of 588 samples from two experimental pig lines developed by divergent selection for RFI were sequenced for the 16 rRNA hypervariable V3‐V4 region. The 75 genera with less than 20% zero values (97% of the counts) and two α‐diversity indexes were analysed. Line comparison of the microbiota traits and estimations of heritability (h2) and genetic correlations (r g) were analysed. A non‐metric multidimensional scaling showed line differences between genera. The α‐diversity indexes were higher in the LRFI line than in the HRFI line (p < .01), with h2 estimates of 0.19 ± 0.08 (Shannon) and 0.12 ± 0.06 (Simpson). Forty‐eight genera had a significant h2 (>0.125). The r g of the α‐diversities indexes with production traits were negative. Some r g of genera belonging to the Lachnospiraceae, Ruminococcaceae, Prevotellaceae, Lactobacillaceae, Streptococcaceae, Rikenellaceae and Desulfovibrionaceae families significantly differed from zero (p < .05) with FE traits, RFI (3), DFI (7) and BFT (11). These results suggest that a sizable part of the variability of the gut microbial community is under genetic control and has genetic relationships with FE, including diversity indicators. It offers promising perspectives for selection for feed efficiency using gut microbiome composition in pigs.

Thermoregulation at birth differs between piglets from two genetic lines divergent for residual feed intake

Thermoregulation is essential to piglets' neonatal survival. This study used infrared thermography (IRT) to assess thermoregulation abilities of piglets from two lines divergent for residual feed intake (RFI). At birth, morphology (weight, length, width and circumference), vigour (respiration, mobility and vocalisation), and rectal temperature were recorded from piglets of the 11th generation of the low RFI (LRFI, more efficient; n = 34) and the high RFI (HRFI, less efficient; n = 28) lines. Infrared thermography images were taken at 8, 15, 30 and 60 min post partum. Temperatures of the ear base and tip, and of the back (i.e. shoulders to rumps) were extracted (Thermacam Researcher Pro 2.0) and analysed with linear mixed models (SAS 9.4). Piglets had different average hourly weight gain (HRFI = 7.1 ± 1.3 g/h, LRFI = 3.6 ± 1.3 g/h; P < 0,001) but did not differ in morphology or vigour. All temperatures increased overtime. At birth, piglets' rectal temperature was correlated with the initial temperature of the ear base and the maximum back temperature (0.37 and 0.33, respectively; P < 0.05). High residual feed intake piglets had lower ear tip temperatures than LRFI piglets at 15 (24.7 ± 0.37 °C vs. 26.3 ± 0.36 °C, respectively; F1, 63.5 = 9.11, P < 0.005) and 30 min post partum (26.2 ± 0.47 °C vs. 27.6 ± 0.44 °C, respectively; F1, 66.9 = 4.52, P < 0.05). Moreover, thermal pattern of the ear tip differed between the two genetic lines. In conclusion, IRT allowed non-invasive assessment of piglets' thermoregulation abilities and indicated an influence of genetic selection for RFI on neonatal thermoregulation abilities.

Genetics of feed intake traits in Czech Large White pig population

Genetics of feed intake traits in Czech Large White pig population