Genetic relationship of feed efficiency traits of bulls with growth and carcass traits of their progeny for Japanese Black (Wagyu) cattle

Genetic parameters for feed efficiency traits of 740 Wagyu bulls and growth and carcass traits of 591 of their progeny, and the genetic relationship between the traits of bulls and their progeny were estimated with the residual maximum likelihood procedure. The estimations were made for the test periods of 140 days (77 bulls), 112 days (663 bulls) and 364 days (591 steer progeny). Feed efficiency traits of bulls included feed conversion ratio (FCR), phenotypic residual feed intake (RFI_phe) and genetic residual feed intake (RFI_gen). Progeny traits were bodyweight at the start of the test (BWS), bodyweight at finish (BWF), average daily gain (ADG), rib eye area (REA), marbling score (MSR), dressing percentage (DRS) and subcutaneous fat thickness (SFT). The estimated heritability for MSR (0.52) was high and for BWS (0.35), BWF (0.40) and ADG (0.30) were moderate, whereas REA, DRS and SFT were low. Positive genetic correlations among BWS, BWF, ADG and SFT and negative genetic correlations between MSR and DRS and between REA and SFT were found. The genetic correlations between residual feed intake (RFI_phe and RFI_gen) of bulls and bodyweights (BWS and BWF) of their progeny ranged from ?0.27 to ?0.61. Residual feed intake was positively correlated with REA and DRS and negatively correlated with MSR and SFT. No responses in ADG and weakly correlated responses in REA and DRS of progeny were found to select against feed efficiency traits of bulls. The present experiment provides evidence that selection against lower RFI (higher feed efficiency) would be better than selection against lower FCR for getting better correlated responses in bodyweights.     

Genetic parameters for feed efficiency and body weight traits in Japanese quail

1. The objectives of the present study were to estimate heritability and genetic correlations for feed efficiency and body weight (BW) in Japanese quail.

2. Recorded traits during different weeks of the growing period were BW from hatch to 35 d, feed intake (FI), feed conversion ratio (FCR) and residual feed intake (RFI) from hatch to 28 d of age.

3. Genetic parameters were estimated by restricted maximum likelihood method using ASREML software. The results showed that heritability estimates for BW ranged from 0.11 to 0.22, and maternal permanent environmental effect was the highest at hatch (0.45). FCR, RFI and FI showed moderate heritabilities ranging from 0.13 to 0.40.

4.Genetic correlations of BW₂₈ with FI_0–28 (0.88) and RFI_0–28 (0.1) and genetic correlation of FI_0–28 with FCR_0–28 (0.13) and RFI_0–28 (0.52) were positive. A negative genetic correlation was found between BW₂₈ and FCR_0–28 (?0.49). There was a high positive genetic correlation (0.67) between RFI_0–28 and FCR_0–28.

5. In conclusion, selection for increased BW and reduced FI in a selection index could be recommended to improve feed efficiency traits including FCR and RFI in Japanese quail.     

Genetic relationship between different measures of feed efficiency and its component traits in Japanese Black (Wagyu) bulls

Genetic parameters of average daily gain (ADG), metabolic body weight (MWT), body weight at finish (BWF), daily feed intake (DFI), feed conversion ratio (FCR), and residual feed intake (RFI) were estimated in 740 Japanese Black bulls. RFI was calculated as the difference between actual and expected feed intake predicted by the residual of multiple regression (RFI_phe) and genetic regression (RFI_gen) from the multivariate analysis for DFI, MWT, and ADG. The estimations were made for the test periods of 140 days (77 bulls) and 112 days (663 bulls). The mean for RFI_phe was close to zero and RFI_gen was negative. Most of the traits studied were moderately heritable (ranging from 0.24 to 0.49), except for ADG and FCR (0.20 and 0.15, respectively). The genetic correlations among growth traits (ADG, MWT and BWF) and between DFI and growth traits were high, while the phenotypic correlations between them were moderate to high. The genetic and phenotypic correlations between RFI_phe and RFI_gen were > 0.95 implying that they are regarded as the same trait and the genetic correlations of RFI (RFI_phe and RFI_gen) with FCR and DFI were favorably high. RFI_phe was phenotypically independent of its component traits, MWT (r_p = − 0.01) and ADG (r_p = 0.01). RFI_gen was genetically independent of MWT (r_g = − 0.07), while there was a weak genetic relationship (r_g = 0.18) between RFI_gen and ADG. These results provide evidence that RFI_gen should be included for genetic improvement of feed efficiency in Japanese Black breeding program.     

Genetic parameters for carcass traits of field progeny and their relationships with feed efficiency traits of their sire population for Japanese Black cattle

Genetic parameters for carcass traits of 1774 field progeny (1281 steers and 493 heifers), and their genetic relationships with feed efficiency traits of their sire population (740 bulls) were estimated with REML. Feed efficiency traits included feed conversion ratio (FCR) and residual feed intake (RFI). RFI was calculated by the residual of phenotypic (RFI_phe) and genetic (RFI_gen) regression from the multivariate analysis of feed intake on metabolic weight and daily gain. Progeny traits were carcass weight (CWT), rib eye area (REA), rib thickness (RBT), subcutaneous fat, yield estimate (YEM), marbling score (MSR), meat quality grade, meat color, fat color, meat firmness and meat texture. The estimated heritability for CWT (0.70) was high and heritabilities for all the other traits were moderate (ranged from 0.32 to 0.47), except for meat and fat color and meat texture which were low (ranged from 0.02 to 0.25). The high genetic correlation (0.62) between YEM and MSR suggests that simultaneous improvement of high carcass yield and beef marbling is possible. Estimated genetic correlations of RFI (RFI_phe and RFI_gen) of sires with CWT (− 0.60 and − 0.53) and MSR (− 0.62 and − 0.50) of their progeny were favorably negative indicating that the selection against RFI of sires may have contributed to produce heavier carcass and increase in beef marbling. The correlated responses in CWT, REA and RBT of progeny were higher to selection against RFI than those to selection against FCR of sires. This study provides evidence that selection against RFI is preferred over selection against FCR in sire population for getting better correlated responses in carcass traits of their progeny.     

Simultaneous Bayesian estimation of genetic parameters for curves of weight,feed intake,and residual feed intake in beef cattle

Rates of gain and feed efficiency are important traits in most breeding programs for growing farm animals. The rate of gain (GAIN) is usually expressed over a certain age period and feed efficiency is often expressed as residual feed intake (RFI), defined as observed feed intake (FI) minus expected feed intake based on live weight (WGT) and GAIN. However, the basic traits recorded are always WGT and FI and other traits are derived from these basic records. The aim of this study was to develop a procedure for simultaneous analysis of the basic records and then derive linear traits related to feed efficiency without retorting to any approximation. A bivariate longitudinal random regression model was employed on 13,791 individual longitudinal records of WGT and FI from 2,827 bulls of six different beef breeds tested for their own performance in the period from 7 to 13 mo of age. Genetic and permanent environmental covariance functions for curves of WGT and FI were estimated using Gibbs sampling. Genetic and permanent covariance functions for curves of GAIN were estimated from the first derivative of the function for WGT and finally the covariance functions were extended to curves for RFI, based on the conditional distribution of FI given WGT and GAIN. Furthermore, the covariance functions were extended to include GAIN and RFI defined over different periods of the performance test. These periods included the whole test period as normally used when predicting breeding values for GAIN and RFI for beef bulls. Based on the presented method, breeding values and genetic parameters for derived traits such as GAIN and RFI defined longitudinally or integrated over (parts of) of the test period can be obtained from a joint analysis of the basic records. The resulting covariance functions for WGT, FI, GAIN, and RFI are usually singular but the method presented here does not suffer from the estimation problems associated with defining these traits individually before the genetic analysis. All the results are thus estimated simultaneously, and the set of parameters is consistent.     

Is neutral genetic diversity related to quantitative variation in semen traits in bulls?

Conservation decisions based on neutral genetic diversity have been observed to promote retention of useful quantitative variation in biological populations. An experiment was undertaken to determine the association between microsatellite marker polymorphisms and phenotypic variation in semen production and cryosurvival traits in bulls. Thirty-five ejaculates were collected from ten bulls of two breeds and evaluated before and after cryopreservation for several semen traits. The bulls were also genotyped using a set of sixteen bovine-specific microsatellite marker loci. Fixation indices (F_ST), heterozygosity and Nei's genetic distance measures were computed from allele frequency data for each of the bulls. Molecular and phenotypic data were used to compute tri-distance matrices for the ten bulls and correlated using Mantel's test in GenAIEx 6.5. The study revealed extensive heterogeneity in semen traits, heterozygosity and F_ST values among the bulls. Large pairwise phenotypic and genetic distances were also observed. Correlation between pairwise genetic distances and phenotypic distances was significant and highly positive for sperm viability (r = .61, p < .001) and moderately positive for sperm motility (r = .40–42, p < .05) variables. For sperm morphology, ejaculate volume and sperm concentration, correlation with genetic distances was positive, low and not significantly different from zero (p > .05). A tendency for a triangular-shaped relationship between genetic and phenotypic distances for post-thaw motility and viability traits was also observed. Accordingly, association with neutral genetic diversity was absent for semen production traits and moderate to highly positive for sperm cryosurvival traits. Given these findings, conservation decisions based on neutral genetic diversity may capture variation in some adaptive traits, but not others.     

Genetic parameters for feed efficiency traits and their relationships with growth and carcass traits in Duroc pigs

Genetic parameters for feed efficiency traits of 380 boars and growth and carcass traits of 1642 pigs (380 boars, 868 gilts and 394 barrows) in seven generations of Duroc population were estimated. Feed efficiency traits included the feed conversion ratio (FCR), and nutritional (RFI(nut)), phenotypic (RFI(phe)) and genetic (RFI(gen)) residual feed intake. Growth and carcass traits were the age to reach 105-kg body weight (A105), loin eye muscle area (EMA), backfat (BF), intra-muscular fat (IMF) and meat tenderness. The mean values for RFI(phe) and RFI(gen) were close to zero and for RFI(nut) was negative. All the measures of feed efficiency were moderately heritable (h(2) = 0.31, 0.38, 0.40 and 0.27 for RFI(nut), RFI(phe), RFI(gen) and FCR respectively). The heritabilities for all growth and carcass traits were moderate (ranged from 0.37 to 0.45), except for BF, which was high (0.72). The genetic correlations of RFI(phe) and RFI(gen) with A105 were positive and high. Measures of RFI were correlated negatively with EMA. BF was more strongly correlated with measures of RFI (r(g) > or = 0.73) than with FCR (r(g) = 0.52). Selection for daily gain, EMA, BF and IMF caused favourable genetic changes in feed efficiency traits. Results of this study indicate that selection against either RFI(phe) or RFI(gen) would give a similar correlated response in carcass traits.     

Genetic and phenotypic relationships of feed intake and measures of efficiency with growth and carcass merit of beef cattle

Feed intake and efficiency of growth are economically important traits of beef cattle. This study determined the relationships of daily DMI, feed:gain ratio [F:G, which is the reciprocal of the efficiency of gain (G:F) and therefore increases as the efficiency of gain decreases and vice versa, residual feed intake (RFI), and partial efficiency of growth (efficiency of ADG, PEG) with growth and carcass merit of beef cattle. Residual feed intake was calculated from phenotypic regression (RFIp) or genetic regression (RFIg) of ADG and metabolic BW on DMI. An F1 half-sib pedigree file containing 28 sires, 321 dams, and 464 progeny produced from crosses between Alberta Hybrid cows and Angus, Charolais, or Alberta Hybrid bulls was used. Families averaged 20 progeny per sire (range = 3 to 56). Performance, ultrasound, and DMI data was available on all progeny, of which 381 had carcass data. Phenotypic and genetic parameters were obtained using SAS and ASREML software, respectively. Differences in RFIp and RFIg, respectively, between the most and least efficient steers (i.e., steers with the lowest PEG) were 5.59 and 6.84 kg of DM/d. Heritabilities for DMI, F:G, PEG, RFIp, and RFIg were 0.54 +/- 0.15, 0.41 +/- 0.15, 0.56 +/- 0.16, 0.21 +/- 0.12, and 0.42 +/- 0.15, respectively. The genetic (r = 0.92) and phenotypic (r = 0.97) correlations between RFIp and RFIg indicated that the 2 indices are very similar. Both indices of RFI were favorably correlated phenotypically (P < 0.001) and genetically with DMI, F:G, and PEG. Residual feed intake was tendentiously genetically correlated with ADG (r = 0.46 +/- 0.45) and metabolic BW (r = 0.27 +/- 0.33), albeit with high SE. Genetically, RFIg was independent of ADG and BW but showed a phenotypic correlation with ADG (r = -0.21; P < 0.05). Daily DMI was correlated genetically (r = 0.28) and phenotypically (r = 0.30) with F:G. Both DMI and F:G were strongly correlated with ADG (r > 0.50), but only DMI had strong genetic (r = 0.87 +/- 0.10) and phenotypic (r = 0.65) correlations with metabolic BW. Generally, the phenotypic and genetic correlations of RFI with carcass merit were not different from zero, except genetic correlations of RFI with ultrasound and carcass LM area and carcass lean yield and phenotypic correlations of RFI with backfat thickness (P < 0.01). Daily DMI had moderate to high phenotypic (P < 0.01) and genetic correlations with all the ultrasound and carcass traits. Depending on how RFI technology is applied, adjustment for body composition in addition to growth may be required to minimize the potential for correlated responses to selection in cattle.     

Selection for feed efficiency does not change the selection for growth and carcass traits in Nellore cattle

The objectives were to conduct a genetic evaluation of residual feed intake (RFI) and residual feed intake adjusted for fat (RFIFat) and to analyse the effect of selection for these traits on growth, carcass and reproductive traits. Data from 945 Nellore bulls in seven feed efficiency tests in a feedlot were analysed. Genetic evaluation was performed using an animal model in which the feed efficiency test and age of the animal at the beginning of the test were considered as a systematic effect. Direct additive genetic and residual effects were considered as random effects. Correlations and genetic gains were estimated by two‐trait analysis between feed efficiency measures (RFI and RFIFat) and other traits. Feed conversion showed low heritability (0.06), but dry matter intake (DMI), average daily gain, RFI, RFIFat, metabolic body weight and scrotal circumference measured at 450 days of age (SC450) showed moderate to high heritability (0.49, 0.28, 0.33, 0.36, 0.38 and 0.80, respectively). Similarly, ribeye area, backfat thickness, rump cap fat thickness, marbling score and subcutaneous fat thickness also had high heritability values (0.46, 0.37, 0.57, 0.51 and 0.47, respectively). Genetic correlations between RFI and SC450 were null, and between RFIFat and SC450 were strongly positive. Genetic and phenotypic correlations of RFI and RFIFat with carcass traits were not different from zero, as correlated responses for carcass traits were also not different from zero. The Nellore selection for feed efficiency by RFI or RFIFat allows the recognition of feed efficient animals, with DMI reduction and without significant changes in growth and carcass traits. However, because of the observed results between RFIFat and SC450, selection of animals should be analysed with caution and a preselection for reproductive traits is necessary to avoid reproductive impairments in the herd.     

Genetic parameters for measures of energetic efficiency of bulls and their relationships with carcass traits of field progeny in Japanese Black cattle

Records on 514 bulls from the sire population born from 1978 to 2004, and on 22,099 of their field progeny born from 1997 to 2003 with available pedigree information (total number = 124,458) were used to estimate genetic parameters for feed intake and energy efficiency traits of bulls and their relationships with carcass traits of field progeny. Feed intake and energetic efficiency traits were daily feed intake, TDN intake, feed conversion ratio (FCR), TDN conversion ratio (TDNCR), residual feed intake (RFI), partial efficiency of growth, relative growth rate, and Kleiber ratio. Progeny carcass traits were carcass weight (CWT), yield estimate, ribeye area, rib thickness, subcutaneous fat thickness (SFT), marbling score (MSR), meat color standard (MCS), fat color standard (FCS), and meat quality grade. All measures of feed intake and energetic efficiency were moderately heritable (ranged from 0.24 to 0.49), except for partial efficiency of growth and relative growth rate, which were high (0.58) and low (0.14), respectively. The phenotypic and genetic correlations between FCR and TDNCR were >or=0.93. Selection for Kleiber ratio will improve all of the energetic efficiency traits with no effect on feed intake measures (daily feed intake and TDN intake). The genetic correlations of FCR, TDNCR, and RFI of bulls with most of the carcass traits of their field progeny were favorable (ranged from -0.24 to -0.72), except with fat color standard (no correlation), MCS, and SFT. Positive (unfavorable) genetic correlations of MCS with FCR, TDNCR, and RFI (0.79, 0.70, and 0.51, respectively) were found. The SFT was negatively genetically correlated with FCR and TDNCR (-0.32 and -0.20, respectively); however, the genetic correlation between RFI and SFT was not significantly different from zero (r(g) = -0.08 +/- 0.12). Favorable correlated responses in CWT, yield estimate, ribeye area, rib thickness, MSR, and meat quality grade would be predicted for selection against any measure of energetic efficiency. The correlated responses in CWT and MSR of progeny were greater for selection against RFI than for selection against any other energetic efficiency trait. Results of this study indicate that RFI should be preferred over other measures of energetic efficiency to include in selection programs.     

Estimation of genetic parameters for somatic cell count in the first three lactations using random regression

Genetic parameters were estimated for log_e somatic cell count (LSCC) for the first three lactations of 31 236 Holstein/Friesian cows with 308 534, 236 277 and 206 729 test day yields in parities 1, 2 and 3, respectively. An animal random regression model was employed in the analyses using Gibbs sampling with each parity regarded as different traits. Linear and quadratic functions were fitted for the animal and permanent environmental effects respectively, using orthogonal polynomials. Daily heritabilities increased with days in milk (DIM) and averaged about 0.07 in all three parities. This increase in heritabilities with DIM was due to an increase in genetic variance and decreases in both permanent and residual environmental variances with DIM. Environmental effects have a large influence on LSCC in early lactation in all three parities. Within lactation, genetic correlations were highest between adjacent DIM but decreased as DIM got further apart. However, this decrease was slowest in parity one and greatest in parity three. The lowest correlation within lactation was 0.10 between DIM 7 and 305 in parity 3. Across lactations, genetic correlations were highest between parities 2 and 3, intermediate between 1 and 3, and lowest between 1 and 2. The genetic correlations computed for completed lactations were 0.69, 0.79 and 0.98 between parities 1 and 2, 1 and 3, and 2 and 3, respectively. Corresponding phenotypic correlations between parities were 0.38, 0.31 and 0.52, respectively. A test day model, accounting for these variations in heritabilities and genetic correlations, should result in a more accurate evaluation.     

Two-step and random regression analyses of weight gain of station-tested beef bulls

Our objectives were to compare a two-step model and a joint procedure via random regression model for evaluating weight gain of beef bulls, weighed every 28 d on 140-d test, and to estimate genetic, environmental, and phenotypic parameters. Two-step analysis consisted of fitting fixed linear regressions to weights of each bull to determine weight gain on test. In the second step, gain on test was analyzed by a mixed model that included fixed effects of breed, test group, and starting age and random effects of weaning herd-year group and animal (additive genetic). The random regression model included the same effects as the two-step mixed-model analysis with an additional random animal permanent environment effect. Fourth-order Legendre polynomials of days on test were fitted for all fixed and random effects in the random regression model, except for breed. Breed effects and residual variances varied for each measurement period. Variance components and EBV for gain were obtained from the covariance function and estimates of random regression coefficients for weight, respectively. Random regression heritability estimates for gain on test increased over time, being maximum at end of test (0.38) and equal to two-step estimate. Permanent environment variance ratio estimates also increased over time and were greater than heritability estimates. Estimate of weaning herd-year variance ratio was approximately constant over time, being equal to 0.07 at end of test and similar to two-step estimate. Genetic correlations between gain through different periods on test given by random regression model were high (from 0.81, between 28 and 140-d gain on test, to 0.99, between 112 and 140-d gain on test). Genetic correlations between gain on discrete 28-d intervals were moderate to high (e.g., 0.49 and 0.99 between the last 28 d on test and the first and fourth 28 d, respectively). Rank correlations between EBV for 140-d gain by the two procedures were 0.98, 0.84, and 0.73 for all bulls and the 5% and 1% of bulls with highest random regression EBV, respectively. Results indicated that the two procedures rank top bulls quite differently for 140-d gain on test. Random regression model accounted for changes over time of genetic and environmental effects on the test weight gain curve of the bulls. Use of 112-d instead of a 140-d test provided similar ranking of bulls on the basis of EBV for gain on test.     

Genetic parameters for measures of the efficiency of gain of boars and the genetic relationships with its component traits in Duroc pigs

Genetic parameters for the efficiency of gain traits on 380 boars and the genetic relationships with component traits were estimated in 1,642 pigs (380 boars, 868 gilts, and 394 barrows) in 7 generations of a Duroc population. The efficiency of gain traits included the feed conversion ratio (FCR) and residual feed intake (RFI) and their component traits, ADG, metabolic BW (MWT), and daily feed intake (FI). The RFI was calculated as the difference between the actual and expected FI. The expected FI was predicted by the nutritional requirement and by the residual of phenotypic (RFI(phe)) and genetic (RFI(gen)) regressions from the multivariate analysis for FI on MWT and ADG. The means for RFI(phe) and RFI(gen) were close to zero, and the mean for nutritional RFI was negative (-0.11 kg/d). The traits studied were moderately heritable (ranging from 0.27 to 0.53). The genetic and phenotypic correlations between ADG and FI were moderate to high, whereas the genetic correlation between MWT and FI was moderate, and the phenotypic correlation between them was low. The corresponding correlations between RFI(phe) and RFI(gen) were > 0.95, implying that they can be regarded as the same trait. The genetic and phenotypic correlations of FCR with measures of RFI were high but lower than unity. The RFI(phe) was phenotypically independent of its component traits, MWT (r(p) = 0.01) and ADG (r(p) = 0.03). The RFI(gen) was genetically independent of MWT (r(g) = -0.04), whereas there was a weak genetic relationship (r(g) = 0.15) between RFI(gen) and ADG. Residual FI was more heritable than FCR, and the genetic and phenotypic correlations of RFI(phe) and RFI(gen) with FI were positive and stronger than that of FCR with FI. These results provide evidence that RFI(phe) or RFI(gen) should be included in breeding programs for Duroc pigs to make genetic improvement in the efficiency of gain.     

Effects of divergent selection for serum insulin-like growth factor-I concentration on performance, feed efficiency, and ultrasound measures of carcass composition traits in Angus bulls and heifers

Angus bulls and heifers from lines divergently selected for serum IGF-I concentration were used to evaluate the effects of IGF-I selection line on growth performance and feed efficiency in 2 studies. In study 1, bulls (low line, n = 9; high line, n = 8; initial BW = 367.1 +/- 22.9 kg) and heifers (low line, n = 9; high line, n = 13; initial BW = 286.4 +/- 28.6 kg) were adapted to a roughage-based diet (ME = 1.95 Mcal/kg of DM) for 24 d and fed individually for 77 d by using Calan gate feeders. In study 2, bulls (low line, n = 15; high line, n = 12; initial BW = 297.5 +/- 34.4 kg) and heifers (low line, n = 9; high line, n = 20; initial BW = 256.0 +/- 25.1 kg) were adapted to a grain-based diet (ME = 2.85 Mcal/kg of DM) for 32 d and fed individually for 70 d by using Calan gate feeders. Blood samples were collected at weaning and at the start and end of each study, and serum IGF-I concentration was determined. Residual feed intake (RFI) was calculated, within study, as the residual from the linear regression of DMI on midtest BW(0.75), ADG, sex, sex by midtest BW(0.75) and sex by ADG. In study 1, calves from the low IGF-I selection line had similar initial and final BW and ADG, compared with calves from the high IGF-I selection line. In addition, DMI and feed conversion ratio were similar between IGF-I selection lines; however, calves from the low IGF-I selection line tended (P < 0.10) to have lesser RFI than calves from the high IGF-I selection line (-0.26 vs. 0.24 +/- 0.31 kg/d). In study 2, IGF-I selection line had no influence on performance or feed efficiency traits. However, there was a tendency (P = 0.15) for an IGF-I selection line x sex interaction for RFI. Bulls from the low IGF-I selection line had numerically lesser RFI than those from the high IGF-I selection line, whereas in heifers, the IGF-I selection line had no effect on RFI. In studies 1 and 2, weaning and initial IGF-I concentrations were not correlated with either feed conversion ratio or RFI. However, regression analysis revealed a sex x IGF-I concentration interaction for initial IGF-I concentration in study 1 and weaning IGF-I concentration in study 2 such that the regression coefficient was positive for bulls and negative for heifers. These data suggest that genetic selection for postweaning serum IGF-I concentration had a minimal effect on RFI in beef cattle.     

Impact of selection for residual feed intake on breeding soundness and reproductive performance of bulls on pasture-based multisire mating

There is concern in the beef industry that selecting bulls for feed efficiency based on residual feed intake (RFI) may have a negative impact on bull reproductive performance and fertility. Here we investigated the impact of selection of bulls for low RFI on breeding soundness evaluation (BSE), reproductive performance, and fertility of bulls under natural service in multisire mating groups on pasture. Of the 412 RFI-tested bulls available, 98 (23.8%) were culled for performance, type, temperament, or other reasons, and 88 (21.4%) were culled for failing BSE, for an overall cull rate of 45.1%. From among the 314 bulls subjected to BSE, 32 (10.2%), 20 (6.4%), and 36 (11.4%) were culled for poor feet and legs, scrotal circumference, and semen quality, respectively. The BSE traits were not different (P > 0.10) between bulls categorized as either inefficient (+RFI) or efficient (-RFI), but the proportion of bulls that failed to meet the 60% minimum sperm motility requirement tended (P = 0.07) to be greater in the -RFI group than in the +RFI group (10.2% vs. 4.4%, respectively). In a subpopulation of 115 bulls, individual progressive sperm motility was greater (P < 0.05) in +RFI (85%) than -RFI (80%) bulls. A multisire natural mating experiment was conducted during 2 consecutive breeding seasons (2006 to 2007 and 2007 to 2008) using 18 +RFI and 18 -RFI bulls. The overall calving rate (calves born/cows exposed) was 72.9%. Mean number of progeny per sire was significantly greater (P < 0.01) in -RFI bulls (18.3) than in +RFI bulls (11.8). Selection for feed efficiency based on RFI appears to have no detrimental impact on reproductive performance and fertility in beef bulls bred in multisire groups on pasture. However, the decreased sperm motility and the greater number of progeny per sire associated with -RFI status need further investigation.     

The relationship between residual feed intake and feed intake behavior in group-housed Duroc barrows

Because feed is the major input in pork production, conversion of feed into lean tissue at minimum costs has been a focus for improvement. Several researchers have proposed using residual feed intake (RFI) rather than feed conversion ratio (FCR) for genetic improvement of feed efficiency. Little is known about the variation in RFI in pigs. As several studies suggest a greater RFI is related to greater animal activity levels, the current study investigated the phenotypic relationship between RFI and feed intake (FI) behavior of 104 group-housed growing Duroc barrows allowed ad libitum access to feed. Feed intake, BW gain, feeding time (TIME), feeding frequency (VISITS), RFI, and FCR were calculated for 5 periods of 14, 23, 28, 21, or 23 d in length (periods 1 through 5, respectively) on animals that were between 73 to 95 d of age at the start of the testing period. Barrows that grew faster consumed more feed (P < 0.001), and barrows that consumed more feed were fatter (P < 0.01). There were no correlations between VISITS and TIME, between VISITS and FI, or between VISITS and RFI. Barrows that spent more time at the feeder, however, consumed more feed (P < 0.05) and had greater RFI in periods 1, 3, and 5 (P < 0.05). As expected, FI and FCR were highly correlated with RFI (P < 0.001). These results suggest that a greater FI rather than greater feed intake activity resulted in greater RFI values.     

Genetic parameters and genotype x environment interaction for feed efficiency traits in steers fed grower and finisher diets

The objective of this study was to examine the genetic parameters and genetic correlations of feed efficiency traits in steers (n = 490) fed grower or finisher diets in 2 feeding periods. A bivariate model was used to estimate phenotypic and genetic parameters using steers that received the grower and finisher diets in successive feeding periods, whereas a repeated animal model was used to estimate the permanent environmental effects. Genetic correlations between the grower-fed and finisher-fed regimens were 0.50 ± 0.48 and 0.78 ± 0.43 for residual feed intake (RFI) and G:F, respectively. The moderate genetic correlation between the 2 feeding regimens may indicate the presence of a genotype × environment interaction for RFI. Permanent environmental effects (expressed in percentage of phenotypic variance) were detected in the grower-fed steers for ADG (38%), DMI (30%), RFI (18%), and G:F (40%) and also in the finisher-fed steers for ADG (28%), DMI (35%), metabolic mid-weight (23%), and RFI (10%). Heritability estimates were 0.08 ± 0.10 and 0.14 ± 0.15 for the grower-fed steers and 0.42 ± 0.16 and 0.40 ± 17 for the finisher-fed steers for RFI and G:F, respectively. The dependency of the RFI on the feeding regimen may have serious implications when selecting animals in the beef industry. Because of the higher cost of grains, feed efficiency in the feedlot might be overemphasized, whereas efficiency in the cow herd and the backgrounding segments may have less emphasis. These results may also favor the retention (for subsequent breeding) of cows whose steers were efficient in the feedlot sector. Therefore, comprehensive feeding trials may be necessary to provide more insight into the mechanisms surrounding genotype × environment interaction in steers.     

Genome‐wide association study and genomic evaluation of feed efficiency traits in Japanese Black cattle using single‐step genomic best linear unbiased prediction method

The objectives of this study were to better understand the genetic architecture and the possibility of genomic evaluation for feed efficiency traits by (i) performing genome‐wide association studies (GWAS), and (ii) assessing the accuracy of genomic evaluation for feed efficiency traits, using single‐step genomic best linear unbiased prediction (ssGBLUP)‐based methods. The analyses were performed in residual feed intake (RFI), residual body weight gain (RG), and residual intake and body weight gain (RIG) during three different fattening periods. The phenotypes from 4,578 Japanese Black steers, which were progenies of 362 progeny‐tested bulls and the genotypes from the bulls were used in this study. The results of GWAS showed that a total of 16, 8, and 12 gene ontology terms were related to RFI, RG, and RIG, respectively, and the candidate genes identified in RFI and RG were involved in olfactory transduction and the phosphatidylinositol signaling system, respectively. The realized reliabilities of genomic estimated breeding values were low to moderate in the feed efficiency traits. In conclusion, ssGBLUP‐based method can lead to understand some biological functions related to feed efficiency traits, even with small population with genotypes, however, an alternative strategy will be needed to enhance the reliability of genomic evaluation.     

Assessing the accuracy of modelling weight gain of cattle using feed efficiency data

Different methods of estimating weight gain were compared for accuracy and utility, using the amount of error variation from fitting the residual feed intake (RFI) model. Data were collected on 1481 cattle of temperate and tropically adapted breeds, feedlot-finished for the domestic (liveweight 400 kg), Korean (520 kg), or Japanese (steers only; 600 kg) markets. Cattle were tested in 36 groups over 4 years. The aim was to estimate weight gain over the period feed intake was measured, which was at least 49 days and averaged 63 days, including time for animals to adapt to the automatic feeding system. The different estimates were derived from linear and quadratic regressions of weight over time fitted to: F1) all weighings in the feedlot and F2) all weighings in the feedlot excluding atypical records in the first few weeks following feedlot entry. More complex linear and quadratic models were also fitted to weighings when feed intake was being measured, using the amount of feed eaten on the day of weighing, and previous days, to adjust for gut fill. Finally, a random regression model including general trends in the growth of each animal and short term measurement error was fitted to dataset F2 to estimate weight gain for the period feed intake was measured.The RFI equation: feed intake=intercept(s)+β_w*mean(weight^0.73)+β_g*weight gain+error (i.e. RFI) was fitted using the different weight gain estimates. Based on mean squared errors from fitting this equation, longer measurement periods generally resulted in more accurate estimates of weight gain. The increased accuracy from using all weight measurements in the feedlot outweighed the loss from not measuring over the desired time interval—i.e. the period for which feed intake was measured.     

Genetic parameters for semen production traits in Swiss dairy bulls

Variance components (VC) were estimated for the semen production trait ejaculate volume, sperm concentration and sperm motility in the Swiss cattle breeds Brown Swiss (BS), Original Braunvieh (OB), Holstein (HO), Red‐Factor‐Carrier (RF), Red Holstein (RH), Swiss Fleckvieh (SF) and Simmental (SI). For this purpose, semen production traits from 2,617 bulls with 124,492 records were used. The data were collected in the years 2000–2012. The model for genetic parameter estimation across all breeds included the fixed effects age of bull at collection, year of collection, month of collection, number of collection per bull and day, interval between consecutive collections, semen collector, bull breed as well as a random additive genetic component and a permanent environmental effect. The same model without a fixed breed effect was used to estimate VC and repeatabilities separately for each of the breeds BS, HO, RH, SF and SI. Estimated heritabilities across all breeds were 0.42, 0.25 and 0.09 for ejaculate volume, sperm concentration and sperm motility, respectively. Different heritabilities were estimated for ejaculate volume (0.42; 0.45; 0.49; 0.40; 0.10), sperm concentration (0.34; 0.30; 0.20; 0.07; 0.23) and number of semen portions (0.18; 0.30; 0.04; 0.14; 0.04) in BS, HO, RH, SF and SI breed, respectively. The phenotypic and genetic correlations across all breeds between ejaculate volume and sperm concentration were negative (?0.28; ?0.56). The other correlations across all breeds were positive. The phenotypic and genetic correlations were 0.01 and 0.19 between sperm motility and ejaculate volume, respectively. Between sperm motility and sperm concentration, the phenotypic and genetic correlations were 0.20 and 0.36, respectively. The results are consistent with other analyses and show that genetic improvement through selection is possible in bull semen production traits.