Measures Of Residual Feed Intake Research Articles

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.

Common and diet-specific metabolic pathways underlying residual feed intake in fattening Charolais yearling bulls

Residual feed intake (RFI) is one of the preferred traits for feed efficiency animal breeding. However, RFI measurement is expensive and time-consuming and animal ranking may depend on the nature of the diets. We aimed to explore RFI plasma biomarkers and to unravel the underlying metabolic pathways in yearling bulls fed either a corn-silage diet rich in starch (corn diet) or a grass-silage diet rich in fiber (grass diet). Forty-eight extreme RFI animals (Low-RFI, n = 24, versus High-RFI, n = 24, balanced per diet) were selected from a population of 364 Charolais bulls and their plasma was subjected to a targeted LC-MS metabolomic approach together with classical metabolite and hormonal plasma analyses. Greater lean body mass and nitrogen use efficiency, and lower protein turnover were identified as common mechanisms underlying RFI irrespective of the diet. On the other hand, greater adiposity and plasma concentrations of branched-chain amino acids (BCAA) together with lower insulin sensitivity in High-RFI animals were only observed with corn diet. Conversely, greater plasma concentrations of BCAA and total triglycerides, but similar insulin concentrations were noted in efficient RFI cattle with grass diet. Our data suggest that there are diet-specific mechanisms explaining RFI differences in fattening Charolais yearling bulls.

Genetic Parameters for Different Measures of Feed Efficiency and Their Relationship to Production Traits in Three Purebred Pigs.

Residual feed intake (RFI) gained attention as a potential alternative to the feed conversion ratio (FCR). Thus, this study aimed to estimate genetic parameters for different feed efficiency (FE) traits (FCR, RFI1 to RFI5) and their genetic correlation to on-test daily weight gain (ADG), backfat (BFT), loin muscle area (LMA), lean percentage (LP), and total feed intake (FI) for 603 Male Duroc (DD), 295 Landrace (LL), and 341 Yorkshire (YY). The common spatial pen effect was also estimated in these traits. Five RFI measures were estimated by regressing daily feed intake on initial testing age (ITA), initial testing weight (IBW), and ADG for RFI1; other models were the same as RFI1 except for additional BFT for RFI2; LMA for RFI3; BFT and LMA for RFI4; BFT, LMA, and average metabolic body weight (AMBW) instead of IBW for RFI5. Genetic parameters estimated using two animal models and the REML method showed moderate heritability for FCR in all breeds (0.22 and 0.28 for DD, 0.31 and 0.39 for LL, 0.17 and 0.22 for YY), low heritability for the majority of RFI measures in DD (0.15 to 0.23) and YY (0.14 to 0.20) and moderate heritability for all RFI measures in LL (0.31 to 0.34). Pen variance explained 7% to 22% for FE and 0% to 9% for production traits’ phenotypic variance. The genetic correlation revealed that selection against less complex RFI1 in DD and LL and RFI2 in YY would bring the most advantageous reduction to FI (0.71 for DD, 0.49 for LL, 0.43 YY) without affecting ADG in all breeds (0.06 for DD, −0.11 for LL, 0.05 for YY), decrease in BFT, and increase in LP in DD (0.51 in BFT, −0.77 in LP) and LL (0.45 in BFT, −0.83 in LP). Therefore, inclusion of these breed-specific RFI measures in the future selection criteria would help improve feed efficiency in the swine industry.

Genetics of feed intake traits in Czech Large White pig population

Genetics of feed intake traits in Czech Large White pig population

Development and comparison of RNA-sequencing pipelines for more accurate SNP identification: practical example of functional SNP detection associated with feed efficiency in Nellore beef cattle

BackgroundOptimization of an RNA-Sequencing (RNA-Seq) pipeline is critical to maximize power and accuracy to identify genetic variants, including SNPs, which may serve as genetic markers to select for feed efficiency, leading to economic benefits for beef production. This study used RNA-Seq data (GEO Accession ID: PRJEB7696 and PRJEB15314) from muscle and liver tissue, respectively, from 12 Nellore beef steers selected from 585 steers with residual feed intake measures (RFI; n = 6 low-RFI, n = 6 high-RFI). Three RNA-Seq pipelines were compared including multi-sample calling from i) non-merged samples; ii) merged samples by RFI group, iii) merged samples by RFI and tissue group. The RNA-Seq reads were aligned against the UMD3.1 bovine reference genome (release 94) assembly using STAR aligner. Variants were called using BCFtools and variant effect prediction (VeP) and functional annotation (ToppGene) analyses were performed.ResultsOn average, total reads detected for Approach i) non-merged samples for liver and muscle, were 18,362,086.3 and 35,645,898.7, respectively. For Approach ii), merging samples by RFI group, total reads detected for each merged group was 162,030,705, and for Approach iii), merging samples by RFI group and tissues, was 324,061,410, revealing the highest read depth for Approach iii). Additionally, Approach iii) merging samples by RFI group and tissues, revealed the highest read depth per variant coverage (572.59 ± 3993.11) and encompassed the majority of localized positional genes detected by each approach. This suggests Approach iii) had optimized detection power, read depth, and accuracy of SNP calling, therefore increasing confidence of variant detection and reducing false positive detection. Approach iii) was then used to detect unique SNPs fixed within low- (12,145) and high-RFI (14,663) groups. Functional annotation of SNPs revealed positional candidate genes, for each RFI group (2886 for low-RFI, 3075 for high-RFI), which were significantly (P < 0.05) associated with immune and metabolic pathways.ConclusionThe most optimized RNA-Seq pipeline allowed for more accurate identification of SNPs, associated positional candidate genes, and significantly associated metabolic pathways in muscle and liver tissues, providing insight on the underlying genetic architecture of feed efficiency in beef cattle.

Association of residual feed intake with growth performance, carcass traits, meat quality, and blood variables in native chickens.

Improving feed efficiency is a primary goal in poultry breeding strategies. Residual feed intake (RFI) in chickens typically calculated during the growing period is a measure of feed efficiency that is independent of the level of production. The objective of this study was to evaluate phenotypic correlations of growth performance, carcass traits, meat quality, and blood variables with RFI in growing native chickens. A total of 1,008 chickens were selected for the experiment to derive RFI. After the RFI measurement period of 42 d, 25 chickens with low RFI values, 25 chickens with medium RFI values, and 25 chickens with high RFI values were selected. The RFI was significantly positively correlated with feed conversion ratio and average daily feed intake, while it was not significantly correlated with initial body weight (BW), final BW, average daily body weight gain, and metabolic BW0.75. The abdominal fat weight and yield of high RFI group were significantly greater than those of medium and low RFI groups, and the abdominal fat yield was significantly positively correlated with RFI. Moreover, the plasma insulin-like growth factor 1 (IGF-1) content of low RFI group was significantly greater than those of high and medium RFI groups. The plasma concentrations of adrenocorticotropic hormone, triiodothyronine (T3), and cortisol of high RFI birds were significantly greater than that of low RFI birds. RFI was significantly positively correlated with plasma concentrations of T3 and cortisol, while it was significantly negatively correlated with plasma concentration of IGF-1. In addition, the serum levels of glucose and triglyceride of high RFI birds were significantly lower than that of low RFI birds. The serum low-density lipoprotein cholesterol (LDL-C) content of high RFI group was significantly greater than that of medium and low RFI groups, and it was significantly positively correlated with RFI. Our data suggested that selection of chickens with low RFI values may be beneficial to reduce fat deposition in native chickens without affecting the meat quality. Circulating IGF-1, T3, cortisol, and LDL-C concentrations can be used as indirect selection indicators of feed efficiency in native chickens. The effect of IGF-1, T3, cortisol, and LDL-C on feed efficiency of native chickens should be carefully examined and validated in future breeding programs.

Three-breed rotational crossbreds of Montbéliarde, Viking Red, and Holstein compared with Holstein cows for feed efficiency, income over feed cost, and residual feed intake

Rotational 3-breed crossbred cows of Montbéliarde, Viking Red, and Holstein (CB) were compared with Holstein (HO) cows for alternative measures of feed efficiency as well as income over feed cost (IOFC) and residual feed intake (RFI) during the first 150 d of first, second, and third lactations. Primiparous and multiparous CB (n = 63 and n = 43, respectively) and HO (n = 60 and n = 37, respectively) cows were fed the same total mixed ration twice daily with refusals weighed once daily. Feed was analyzed for dry matter content, net energy for lactation, and crude protein content. Body weight (BW) was recorded twice weekly. Daily production of milk, fat, and protein were estimated from monthly test days with best prediction. Measures of efficiency from 4 to 150 d in milk (DIM) were feed conversion efficiency (FCE), defined as fat plus protein production (kg) per kilogram of dry matter intake (DMI); ECM/DMI, defined as kilograms of energy-corrected milk (ECM) per kilogram of DMI; net energy for lactation efficiency (NELE), defined as ECM (kg) per megacalorie of net energy for lactation intake; crude protein efficiency (CPE), defined as true protein production (kg) per kilogram of crude protein intake; and DMI/BW, defined as DMI (kg) per kilogram of BW. The IOFC was defined as revenue from fat plus protein production minus feed cost. The RFI from 4 to 150 DIM for each lactation was the residual error remaining from regression of DMI on milk energy output (Mcal), metabolic BW, and energy required for change in BW (Mcal). Statistical analysis of measures of feed efficiency and RFI for primiparous cows included the fixed effects of year of calving and breed group. For multiparous cows, statistical analysis included breed as a fixed effect and cow as a repeated effect nested within breed group. Primiparous CB cows had higher means for FCE (+5.5%), ECM/DMI (+4.0%), NELE (+4.0%), and CPE (+5.2%) and a lower mean DMI/BW (-5.3%) than primiparous HO cows. Primiparous CB cows ($875) also had higher mean IOFC than primiparous HO cows ($825). In addition, mean RFI from 4 to 150 DIM was significantly lower (more desirable) for primiparous CB cows than HO cows. Likewise, multiparous CB cows had higher means for FCE (+8.2%), ECM/DMI (+5.9%), NELE (+5.8%), and CPE (+8.1%) and a lower mean for DMI/BW (-4.8%) than multiparous HO cows. Multiparous CB cows ($1,296) also had a higher mean for IOFC than multiparous HO cows ($1,208) and a lower mean for RFI from 4 to 150 DIM than HO cows.

Growth performance, rumen fermentation, bacteria composition, and gene expressions involved in intracellular pH regulation of rumen epithelium in finishing Hu lambs differing in residual feed intake phenotype.

The objective of this study was to evaluate the effect of residual feed intake (RFI) on rumen function in finishing lambs. A total of 60 male Hu lambs (average initial BW = 25.2 ± 2.5kg) were used and were offered a pelleted high-concentrate diet, of which the forage to concentrate ratio was 25:75. Individual feed intake was recorded over a period of 42 d, then 10 lambs with the lowest RFI and the highest RFI were selected, respectively. The rumen fluid used for fermentation variables and relative abundance of bacteria measurement was obtained on d 10 and 20 after RFI measurement. At the end of this experiment, the selected lambs were slaughtered and rumen epithelium and liver tissues were collected for RNA extraction. Low-RFI lambs had lower ( < 0.01) DMI and greater ( < 0.05) G:F than the high-RFI ones, while the RFI groups did not differ in ADG and BW ( > 0.05). Additionally, RFI was positively ( = 0.57; < 0.01) correlated with DMI and negatively ( = -0.53; < 0.05) correlated with G:F. Total VFA and individual VFA decreased ( < 0.05) over time. The concentrations of total VFA, acetate, valerate, isobutyrate, isovalerate, and rumen pH ( > 0.05) were not affected by RFI classification. Nonetheless, low-RFI group lambs had a greater ( < 0.05) concentration of propionate, a lower ( < 0.05) concentration of butyrate, and a lower ( < 0.05) acetate to propionate ratio compared with the high-RFI group. There was a significant ( < 0.05) effect of RFI on the relative abundance of and . The relative abundance of , , and decreased ( < 0.05) over time in high-RFI group. And the relative abundance of in high-RFI group was greater ( < 0.05) than its low-RFI counterpart. Furthermore, RFI had no effect ( > 0.05) on gene expression associated with intracellular pH regulation (, , , , , , , and ) in rumen epithelium and β-hydroxybutyrate metabolism () in both rumen epithelium and liver tissues. In conclusion, even though low-RFI lambs had lower DMI, however, the number of was lower. Additionally, there was no difference in gene expressions level associated with intracellular pH regulation in rumen epithelium between RFI groups.

Evaluation of the effect of alternative measurements of body weight gain and dry matter intake for the calculation of residual feed intake in growing purebred Charolais and Red Angus cattle.

The objective of this study was to determine the effects of alternative-measurements of body weight and DMI used to evaluate residual feed intake (RFI). Weaning weight (WW), ADG, and DMI were recorded on 970 growing purebred Charolais bulls (n = 519) and heifers (n = 451) and 153 Red Angus growing steers (n = 69) and heifers (n = 84) using a GrowSafe (GrowSafe, Airdrie, Alberta, Canada) system. Averages of individual DMI were calculated in 10-d increments and compared to the overall DMI to identify the magnitude of the errors associated with measuring DMI. These incremental measurements were also used in calculation of RFI, computed from the linear regression of DMI on ADG and midtest body weight0.75 (MMWT). RFI_Regress was calculated using ADG_Regress (ADG calculated as the response of BW gain and DOF) and MMWT_PWG (metabolic midweight calculated throughout the postweaning gain test), considered the control in Red Angus. A similar calculation served as control for Charolais; RFI was calculated using 2-d consecutive start and finish weights (RFI_Calc). The RFI weaning weight (RFI_WW) was calculated using ADG_WW (ADG from weaning till the final out weight of the postweaning gain test) and MMWT_WW, calculated similarly. Overall average estimated DMI was highly correlated to the measurements derived over shorter periods, with 10 d being the least correlated and 60 d being the most correlated. The ADG_Calc (calculated using 2-d consecutive start and finish weight/DOF) and ADG_WW were highly correlated in Charolais. The ADG_Regress and ADG_Calc were highly correlated, and ADG_Regress and ADG_WW were moderately correlated in Red Angus. The control measures of RFI were highly correlated with the RFI_WW in Charolais and Red Angus. The outcomes of including abbreviated period DMI in the model with the weaning weight gain measurements showed that the model using 10 d of intake (RFI WW_10) was the least correlated with the control measures. The model with 60 d of intake had the largest correlation with the control measures. The fewest measured intake days coupled with the weaning weight values providing acceptable predictive value was RFI_WW_40, being highly correlated with the control measures. As established in the literature, at least 70 d is required to accurately measure ADG. However, we conclude that a shorter period, possibly as few as 40 d is needed to accurately estimate DMI for a reliable calculation of RFI.

Considerations when combining data from multiple nutrition experiments to estimate genetic parameters for feed efficiency

Prior to genomic selection on a trait, a reference population needs to be established to link marker genotypes with phenotypes. For costly and difficult-to-measure traits, international collaboration and sharing of data between disciplines may be necessary. Our aim was to characterize the combining of data from nutrition studies carried out under similar climate and management conditions to estimate genetic parameters for feed efficiency. Furthermore, we postulated that data from the experimental cohorts within these studies can be used to estimate the net energy of lactation (NEL) densities of diets, which can provide estimates of energy intakes for use in the calculation of the feed efficiency metric, residual feed intake (RFI), and potentially reduce the effect of variation in energy density of diets. Individual feed intakes and corresponding production and body measurements were obtained from 13 Midwestern nutrition experiments. Two measures of RFI were considered, RFIMcal and RFIkg, which involved the regression of NEL intake (Mcal/d) or dry matter intake (DMI; kg/d) on 3 expenditures: milk energy, energy gained or lost in body weight change, and energy for maintenance. In total, 677 records from 600 lactating cows between 50 and 275 d in milk were used. Cows were divided into 46 cohorts based on dietary or nondietary treatments as dictated by the nutrition experiments. The realized NEL densities of the diets (Mcal/kg of DMI) were estimated for each cohort by totaling the average daily energy used in the 3 expenditures for cohort members and dividing by the cohort’s total average daily DMI. The NEL intake for each cow was then calculated by multiplying her DMI by her cohort’s realized energy density. Mean energy density was 1.58 Mcal/kg. Heritability estimates for RFIkg, and RFIMcal in a single-trait animal model did not differ at 0.04 for both measures. Information about realized energy density could be useful in standardizing intake data from different climate conditions or management systems, as well as investigating potential genotype by diet interactions.

Genome-wide association and pathway analysis of feed efficiency in pigs reveal candidate genes and pathways for residual feed intake

Residual feed intake (RFI) is a complex trait that is economically important for livestock production; however, the genetic and biological mechanisms regulating RFI are largely unknown in pigs. Therefore, the study aimed to identify single nucleotide polymorphisms (SNPs), candidate genes and biological pathways involved in regulating RFI using Genome-wide association (GWA) and pathway analyses. A total of 596 Yorkshire boars with phenotypes for two different measures of RFI (RFI1 and 2) and 60k genotypic data was used. GWA analysis was performed using a univariate mixed model and 12 and 7 SNPs were found to be significantly associated with RFI1 and RFI2, respectively. Several genes such as xin actin-binding repeat-containing protein 2 (XIRP2),tetratricopeptide repeat domain 29 (TTC29),suppressor of glucose, autophagy associated 1 (SOGA1),MAS1,G-protein-coupled receptor (GPCR) kinase 5 (GRK5),prospero-homeobox protein 1 (PROX1),GPCR 155 (GPR155), and FYVE domain containing the 26 (ZFYVE26) were identified as putative candidates for RFI based on their genomic location in the vicinity of these SNPs. Genes located within 50 kbp of SNPs significantly associated with RFI and RFI2 (q-value ≤ 0.2) were subsequently used for pathway analyses. These analyses were performed by assigning genes to biological pathways and then testing the association of individual pathways with RFI using a Fisher’s exact test. Metabolic pathway was significantly associated with both RFIs. Other biological pathways regulating phagosome, tight junctions, olfactory transduction, and insulin secretion were significantly associated with both RFI traits when relaxed threshold for cut-off p-value was used (p ≤ 0.05). These results implied porcine RFI is regulated by multiple biological mechanisms, although the metabolic processes might be the most important. Olfactory transduction pathway controlling the perception of feed via smell, insulin pathway controlling food intake might be important pathways for RFI. Furthermore, our study revealed key genes and genetic variants that control feed efficiency that could potentially be useful for genetic selection of more feed efficient pigs.

Relationships between residual feed intake and hepatic mitochondrial function in growing beef cattle.

The objective of this study was to evaluate the relationship between hepatic mitochondrial function and residual feed intake (RFI) in growing beef cattle. In Trial 1, RFI was measured in 29 Angus heifers (initial BW = 258.0 ± 24.9 kg) from divergent IGF-I selection lines created at the Eastern Agricultural Research Station (The Ohio State University) fed a grain-based diet (calculated ME = 2.85 Mcal/kg DM). In Trial 2, RFI was measured in 119 Santa Gertrudis steers (initial BW = 308.4 ± 28.1 kg) fed a roughage-based diet (calculated ME = 2.21 Mcal/kg DM). At the end of the RFI measurement period, cattle in Trial 1 (n = 7 low RFI and n = 7 high RFI) and in Trial 2 (n = 6 low RFI and n = 8 high RFI) with measures of RFI exceeding 0.5 (Trial 1) or 1.0 (Trial 2) SD from the mean RFI were selected to measure mitochondrial function. Overall ADG, DMI, and RFI were 1.19 ± 0.15, 9.31 ± 1.12, and 0.00 ± 0.63 kg/d and 0.83 ± 0.16, 9.48 ± 1.00, and 0.00 ± 0.86 kg/d in Trial 1 and 2, respectively. Cattle with low RFI consumed 13 and 24% less (P < 0.05) DM and had 14 and 56% greater (P < 0.05) G:F than cattle with high RFI in Trial 1 and 2, respectively, even though ADG and BW were similar (P > 0.10). In Trial 1, cattle with low RFI tended (P = 0.06) to have greater state 3 respiration rates than cattle with high RFI, but state 3 respiration rates were similar (P > 0.10) between cattle with low and high RFI in Trial 2. In both trials, cattle with low RFI had greater (P < 0.05) acceptor control ratios than their high RFI counterparts. The respiratory control ratio tended (P = 0.09) to be greater for cattle with low RFI compared with high RFI cattle in Trial 1, but no difference (P > 0.10) was observed in Trial 2. Proton-leak kinetics were similar (P > 0.05) between cattle with low and high RFI in both trials. These data suggest that ADP has greater control of oxidative phosphorylation in liver mitochondrial of cattle with low RFI compared to their high RFI counterparts.

Genome-wide association and systems genetic analyses of residual feed intake, daily feed consumption, backfat and weight gain in pigs

BackgroundFeed efficiency is one of the major components determining costs of animal production. Residual feed intake (RFI) is defined as the difference between the observed and the expected feed intake given a certain production. Residual feed intake 1 (RFI1) was calculated based on regression of individual daily feed intake (DFI) on initial test weight and average daily gain. Residual feed intake 2 (RFI2) was as RFI1 except it was also regressed with respect to backfat (BF). It has been shown to be a sensitive and accurate measure for feed efficiency in livestock but knowledge of the genomic regions and mechanisms affecting RFI in pigs is lacking. The study aimed to identify genetic markers and candidate genes for RFI and its component traits as well as pathways associated with RFI in Danish Duroc boars by genome-wide associations and systems genetic analyses.ResultsPhenotypic and genotypic records (using the Illumina Porcine SNP60 BeadChip) were available on 1,272 boars. Fifteen and 12 loci were significantly associated (p < 1.52 × 10-6) with RFI1 and RFI2, respectively. Among them, 10 SNPs were significantly associated with both RFI1 and RFI2 implying the existence of common mechanisms controlling the two RFI measures. Significant QTL regions for component traits of RFI (DFI and BF) were detected on pig chromosome (SSC) 1 (for DFI) and 2 for (BF). The SNPs within MAP3K5 and PEX7 on SSC 1, ENSSSCG00000022338 on SSC 9, and DSCAM on SSC 13 might be interesting markers for both RFI measures. Functional annotation of genes in 0.5 Mb size flanking significant SNPs indicated regulation of protein and lipid metabolic process, gap junction, inositol phosphate metabolism and insulin signaling pathway are significant biological processes and pathways for RFI, respectively.ConclusionsThe study detected novel genetic variants and QTLs on SSC 1, 8, 9, 13 and 18 for RFI and indicated significant biological processes and metabolic pathways involved in RFI. The study also detected novel QTLs for component traits of RFI. These results improve our knowledge of the genetic architecture and potential biological pathways underlying RFI; which would be useful for further investigations of key candidate genes for RFI and for development of biomarkers.

Methane emissions, body composition, and rumen fermentation traits of beef heifers differing in residual feed intake1

This study examined the relationship of residual feed intake (RFI) and performance with methane emissions, rumen fermentation, and digestion in beef heifers. Individual DMI and growth performance were measured for 22 Simmental heifers (mean initial BW 449 kg, SD = 46.2 kg) offered grass silage ad libitum for 120 d. Ultrasonically scanned muscle and fat depth, BCS, muscularity score, skeletal measurements, blood variables, rumen fermentation (via stomach tube), and total tract digestibility (indigestible marker) were measured. Methane production was estimated using the sulfur hexafluoride tracer gas technique over two 5-d periods beginning on d 20 and 75 of the RFI measurement period. Phenotypic RFI was calculated as actual DMI minus expected DMI. The residuals of the regression of DMI on ADG and midtest metabolic body weight, using all heifers, were used to compute individual RFI coefficients. Heifers were ranked by RFI and assigned to low (efficient), medium, or high (inefficient) groupings. Overall ADG and DMI were 0.58 kg (SD = 0.18) and 7.40 kg (SD = 0.72), respectively. High-RFI heifers consumed 9 and 15% more (P < 0.05) than medium- and low-RFI groups, respectively. Body weight, growth, skeletal, and composition traits did not differ (P > 0.05) between low- and high-RFI groups. High-RFI heifers had higher concentrations of plasma glucose (6%) and urea (13%) and lower concentrations of plasma creatinine (9%) than low-RFI heifers (P < 0.05). Rumen pH and apparent in vivo digestibility did not differ (P > 0.05) between RFI groups, although acetate:propionate ratio was lowest (P = 0.07) for low-RFI (3.5) and highest for high-RFI (4.6) heifers. Methane production expressed as grams per day or grams per kilogram metabolic body weight was greater (P < 0.05) for high (297 g/d and 2.9 g/kg BW0.75) compared with low (260 g/d and 2.5 g/kg BW0.75) RFI heifers, with medium (275 g/d and 2.7 g/kg BW0.75) RFI heifers being intermediate. Regression analysis indicated that a 1 kg DM/d increase in RFI was associated with a 23 g/d increase (P = 0.09) in methane emissions. Results suggest that improved RFI will reduce methane emissions without affecting productivity of growing beef cattle.

Genetic parameters for different measures of feed efficiency and related traits in boars of three pig breeds1

Residual feed intake (RFI) is commonly used as a measure of feed efficiency at a given level of production. A total of 16,872 pigs with their pedigree traced back as far as possible was used to estimate genetic parameters for RFI, growth performance, food conversion ratio (FCR), body conformation, and feeding behavior traits in 3 Danish breeds [Duroc (DD), Landrace (LL), and Yorkshire (YY)]. Two measures of RFI were considered: residual feed intake 1 (RFI1) was calculated based on regression of daily feed intake (DFI) from 30 to 100 kg on initial test weight and ADG from 30 to 100 kg (ADG2). Residual feed intake 2 (RFI2) was as RFI1, except it was also regressed with respect to backfat (BF). The estimated heritabilities for RFI1 and RFI2 were 0.34 and 0.38 in DD, 0.34 and 0.36 in LL, and 0.39 and 0.40 in YY, respectively. The heritabilities ranged from 0.32 (DD) to 0.54 (LL) for ADG2, from 0.54 (DD) to 0.67 (LL) for BF, and from 0.13 (DD) to 0.19 (YY) for body conformation. Feeding behavior traits including DFI, number of visits to feeder per day (NVD), total time spent eating per day (TPD), feed intake rate (FR), feed intake per visit (FPV), and time spent eating per visit (TPV) were moderately to highly heritable. Residual feed intake 2 was genetically independent of ADG2 and BF in all breeds, except it had low genetic correlation to ADG2 in YY (0.2). Residual feed intake 1 was also genetically independent of ADG2 in DD and LL. Both RFI traits had strong genetic correlations with DFI (0.85 to 0.96) and FCR (0.76 to 0.99). They had low or no genetic correlations with feeding behavior traits. Unfavorable genetic correlations were found between ADG2 and both BF and DFI. Among feeding behavior traits, DFI had low genetic correlations to other traits in all breeds. High and negative genetic correlations were also found between TPD with FR (-0.79 in YY to -0.88 in DD), NVD, and TPD (-0.91 in DD to -0.94 in YY) and between NVD and FPV (-0.83 in DD to -0.91 in YY) in all breeds. The genetic trend for feed efficiency was favorable in all breeds regardless of the definition of feed efficiency used. In summary, RFI1 and RFI2 were heritable and selection for reduced RFI2 can be performed without adversely affecting ADG and BF and could replace FCR in the selection index for the Danish pig breeds. Selection could also be based on RFI1 for breeds with fewer concerns about a negative effect of BF or for breeds that do not have BF records.

Grazed grass herbage intake and performance of beef heifers with predetermined phenotypic residual feed intake classification

Data were collected on 85 Simmental and Simmental × Holstein–Friesian heifers. During the indoor winter period, they were offered grass silage ad libitum and 2 kg of concentrate daily, and individual dry matter intake (DMI) and growth was recorded over 84 days. Individual grass herbage DMI was determined at pasture over a 6-day period, using the n-alkane technique. Body condition score, skeletal measurements, ultrasonic fat and muscle depth, visual muscularity score, total tract digestibility, blood hormones, metabolites and haematology variables and activity behaviour were measured for all heifers. Phenotypic residual feed intake (RFI) was calculated for each animal as the difference between actual DMI and expected DMI during the indoor winter period. Expected DMI was calculated for each animal by regressing average daily DMI on mid-test live weight (LW)0.75 and average daily gain (ADG) over an 84-day period. Standard deviations above and below the mean were used to group animals into high (>0.5 s.d.), medium (±0.5 s.d.) and low (<0.5 s.d.) RFI. Overall mean (s.d.) values for DMI (kg/day), ADG (kg), feed conversion ratio (FCR) kg DMI/kg ADG and RFI (kg dry matter/day) were 5.82 (0.73), 0.53 (0.18), 12.24 (4.60), 0.00 (0.43), respectively, during the RFI measurement period. Mean DMI (kg/day) and ADG (kg) during the grazing season was 9.77 (1.77) and 0.77 (0.14), respectively. The RFI groups did not differ (P > 0.05) in LW, ADG or FCR at any stage of measurement. RFI was positively correlated (r = 0.59; P < 0.001) with DMI during the RFI measurement period but not with grazed grass herbage DMI (r = 0.06; P = 0.57). Low RFI heifers had 0.07 greater (P < 0.05) concentration of plasma creatinine than high RFI heifers and, during the grazed herbage intake period, spent less time standing and more time lying (P < 0.05) than high RFI heifers. However, low and high RFI groups did not differ (P > 0.05) in ultrasonic backfat thickness or muscle depth, visual muscle scores, skeletal size, total tract digestibility or blood hormone and haematology variables at any stage of the experiment. Despite a sizeable difference in intake of grass silage between low and high RFI heifers during the indoor winter period, there were no detectable differences between RFI groupings for any economically important performance traits measured when animals were offered ensiled or grazed grass herbage.

Identification of genetic markers associated with residual feed intake and meat quality traits in the pig

Residual feed intake (RFI) has become increasingly important and is being considered as a more reasonable approach to evaluate feed efficiency in livestock. However, the cost and technical difficulties in measuring this trait restrict the extensive adoption of RFI selection, and this makes marker assisted selection (MAS) a feasible tool. In addition, the effects on meat quality caused by low RFI selection have yet to be clarified. In this study, 11 SNPs from eight candidate genes were evaluated in a Yorkshire pig experimental population (n=169) consisting of a low RFI selection line and a randomly selected control line. Associations of these SNPs with RFI, growth rate, carcass composition, and meat quality measures including water holding capacity, pH at 2d postmortem, meat color and sensory traits were analyzed. The SNPs FTO p.Ala198Ala and TCF7L2 c.646+514A>G showed significant (P<0.05) and suggestively significant (P<0.1) associations with RFI, respectively. The MC4R SNP p.Asp298Asn was associated with backfat but it was not with ADG and meat quality attributes. Both SNPs within HNF1A were associated with intramuscular lipid content and sensory juiciness. The SNPs ACC1 c(*)384C>T and TCF7L2 c.646+514A>G were significantly (P<0.05) associated with ADG. The SNPs CTSZ p.Arg64Lys and TCF7L2 c.646+514A>G were associated with both visual scoring of meat color and the objective L-value measure of meat color. This study has identified potential genetic markers suitable for MAS in improving RFI, ADG, and meat color traits, but these associations need to be validated in other larger populations.

Genetic associations of residual feed intake with serum insulin-like growth factor-I and leptin concentrations, meat quality, and carcass cross sectional fat area ratios in Duroc pigs

Genetic relationships of measures of residual feed intake and daily feed intake with serum IGF-I concentrations at 8 wk of age and at 105 kg of BW, serum leptin concentration at 105 kg of BW, meat quality, and different fat accumulation traits on 834 Duroc pigs in 7 generations were estimated. Two measures of residual feed intake were estimated from the differences between actual and predicted feed intake: phenotypic residual feed intake (RFI(phe)) and nutritional residual feed intake (RFI(nut)). Meat quality traits included drip loss, cooking loss, pork color score, pork lightness (L*), and pH, whereas fat accumulation traits were subcutaneous fat, intermuscular fat, and total fat percent at 5-6th thoracic vertebra; subcutaneous fat, intermuscular fat, abdominal fat, and total fat percent at one-half body length and at last thoracic vertebra, and seam fat score. The IGF-I concentrations at 8 wk of age and 105 kg of BW had weak genetic correlations with measures of residual feed intake and daily feed intake (absolute values ranging from 0.14 to 0.24). The genetic correlations between measures of residual feed intake and serum leptin concentration were strong and positive (r(g) with RFI(phe) and RFI(nut) were 0.74 and 0.80, respectively). Residual feed intake was moderately but negatively correlated with cooking loss (r(g) with RFI(phe) and RFI(nut) were -0.42 and -0.49, respectively), whereas daily feed intake was moderately and positively correlated with drip loss and pH (0.33 and 0.36, respectively). Daily feed intake was also moderately correlated with subcutaneous fat accumulations at the 5-6th thoracic vertebra (0.31) and one-half body length (0.31) regions and was strongly correlated with accumulations at the last thoracic vertebra region (0.57). The genetic correlations between daily feed intake and intermuscular fat accumulations at all of the carcass sites were strong (0.60, 0.76, and 0.56 for intermuscular fat at 5-6th thoracic vertebra, one-half body length, and last thoracic vertebra, respectively). Residual feed intake was strongly and positively correlated with all of the fat accumulation traits (ranging from 0.53 to 0.88). The results indicate that reducing residual feed intake (increased efficiency) would lead to increased cooking loss and darkness, and decreased serum leptin concentration, fat accumulations at the different sites, and seam fat at the 6th rib interface of pork carcasses.

Genetic parameters for production traits and measures of residual feed intake in Duroc and Landrace pigs

ABSTRACTData on 380 Duroc boars from seven generations, and 1026 Landrace pigs (341 boars and 685 gilts) from six generations were used to estimate genetic parameters for daily gain (DG), backfat thickness (BF), metabolic weight (MWT), daily feed intake (FI), feed conversion ratio (FCR) and residual feed intake (RFI). Two measures of RFI were estimated as the difference between actual feed intake and that predicted from models that included initial test age and weight and DG (RFI1); and initial test age and weight, DG and BF (RFI2). Heritability estimates for DG, MWT and FI were moderate for both breeds. BF estimates were high for both the breeds. The measures of feed efficiency (FCR and RFI) were moderately heritable. Genetic correlations of BF with measures of RFI were stronger when BF was not included in the estimation of RFI (0.40 and 0.46 for Duroc and Landrace, respectively (for RFI1), compared with 0.05 and 0.06 for Duroc and Landrace, respectively (for RFI2)). Genetic correlations of MWT with measures of RFI were all negative and low. Genetic and phenotypic correlations between DG and measures of RFI were close to zero, which indicated that selection for reduced RFI could be made without adversely affecting DG. BF should also decrease, and MWT should increase under selection for reduced RFI. The reduction in BF would depend on the measure of RFI used.

Genetic parameters for measures of residual feed intake and growth traits in seven generations of Duroc pigs

Residual feed intake (RFI) represents the deviation of the actual feed consumption of an animal from that predicted from combination of growth traits. Data on 1642 Duroc (380 boars, 868 gilts, and 394 barrows) pigs in seven generations were used to estimate genetic parameters for measures of RFI, daily feed intake (FI), average daily gain (ADG), backfat (BF), and loin eye area (LEA). Four measures of RFI were estimated from models that included initial test age and weight, and ADG (RFI1); initial test age and weight, ADG, and BF (RFI2); initial test age and weight, ADG and LEA (RFI3); and initial test age and weight, ADG, BF, and LEA (RFI4). Genetic parameters were estimated using an animal model by the REML method. Heritability estimates for measures of RFI were moderate (ranged from 0.22 to 0.38). The corresponding estimates for FI, ADG, and LEA were also moderate (ranging from 0.45 to 0.49), while the estimate for BF was high (0.72). Genetic correlations of FI with ADG (0.84) and BF (0.67) were high. LEA negatively correlated with FI (− 0.42), ADG (− 0.11) and BF (− 0.44). Genetic correlations of BF with measures of RFI were higher when BF was not included in the estimation of RFI (0.77 with RFI1 and 0.76 with RFI3 vs. 0.11 with RFI2 and 0.07 with RFI4). Genetic correlations of LEA with measures of RFI were all negative (ranged from − 0.30 to − 0.60). Selection for ADG, LEA, BF, and intramuscular fat has resulted in small but favourable genetic changes in measures of RFI. Phenotypic correlations between measures of RFI were zero, and genetic correlations between them were low (0.17 to 0.23). FI was strongly correlated with all the measures of RFI, both genetically (ranged from 0.56 to 0.77) and phenotypically (ranged from 0.56 to 0.66). The results suggested that selection against RFI may cause a reduction in FI. BF should also decrease, and LEA should increase. The amount of change in BF or LEA would vary depending on whether RFI was adjusted for BF.