Effects of a mastitis J5 bacterin vaccination on the productive performance of dairy cows: An observational study using propensity score matching techniques.

Inferring causal effects between variables when utilizing observational data is challenging due to confounding factors not controlled through a randomized experiment. Propensity score matching can decrease confounding in observational studies and offers insights about potential causal effects of prophylactic management interventions such as vaccinations. The objective of this study was to determine potential causality and impact of vaccination with an Escherichia coli J5 bacterin on the productive performance of dairy cows applying propensity score matching techniques to farm-recorded (e.g., observational) data. Traits of interest included 305-d milk yield (MY305), 305-d fat yield (FY305), 305-d protein yield (PY305), and somatic cell score (SCS). Records from 6,418 lactations generated by 5,121 animals were available for the analysis. Vaccination status of each animal was obtained from producer-recorded information. Confounding variables considered were herd-year-season groups (56 levels), parity (5 levels: 1, 2, 3, 4, and ≥5), and genetic quartile groups (4 levels: top 25% through bottom 25%) derived from genetic predictions for MY305, FY305, PY305, and SCS, as well as for the genetic susceptibility to mastitis. A logistic regression model was applied to estimate the propensity score (PS) for each cow. Subsequently, PS values were used to form pairs of animals (1 vaccinated with 1 unvaccinated control), depending on their PS similarities (difference in PS values of cows within a match required to be <20% of 1 standard deviation of the logit of PS). After the matching process, 2,091 pairs of animals (4,182 records) remained available to infer the causal effects of vaccinating dairy cows with the E. coli J5 bacterin. Causal effects estimation was performed using 2 approaches: simple matching and a bias-corrected matching. According to the PS methodology, causal effects of vaccinating dairy cows with a J5 bacterin on their productive performance were identified for MY305. The simple matched estimator suggested that vaccinated cows produced 163.89 kg more milk over an entire lactation when compared with nonvaccinated counterparts, whereas the bias-corrected estimator suggested that such increment in milk production was of 150.48 kg. Conversely, no causal effects of immunizing dairy cows with a J5 bacterin were identified for FY305, PY305, or SCS. In conclusion, the utilization of PS matching techniques applied to farm-recorded data was feasible and allowed us to identify that vaccination with an E. coli J5 bacterin relates to an overall milk production increment without compromising milk quality.

Relationship among performance, carcass, and feed efficiency characteristics, and their ability to predict economic value in the feedlot.

A 4-yr study was conducted using 736 steers of known Angus, Simmental, or Simmental × Angus genetics to determine performance, carcass, and feed efficiency factors that explained variation in economic performance. Steers were pen fed and individual DMI was recorded using a GrowSafe automated feeding system (GrowSafe Systems Ltd., Airdrie, Alberta, Canada). Steers consumed a similar diet and received similar management each year. The objectives of this study were to: 1) determine current economic value of feed efficiency and 2) identify performance, carcass, and feed efficiency characteristics that predict: carcass value, profit, cost of gain, and feed costs. Economic data used were from 2011 values. Feed efficiency values investigated were: feed conversion ratio (FCR; feed to gain), residual feed intake (RFI), residual BW gain (RG), and residual intake and BW gain (RIG). Dependent variables were carcass value ($/steer), profit ($/steer), feed costs ($/steer • d(-1)), and cost of gain ($/kg). Independent variables were year, DMI, ADG, HCW, LM area, marbling, yield grade, dam breed, and sire breed. A 10% improvement in RG (P < 0.05) yielded the lowest cost of gain at $0.09/kg and highest carcass value at $17.92/steer. Carcass value increased (P < 0.05) as feed efficiency improved for FCR, RG, and RIG. Profit increased with a 10% improvement in feed efficiency (P < 0.05) with FCR at $34.65/steer, RG at $31.21/steer, RIG at $21.66/steer, and RFI at $11.47/steer. The carcass value prediction model explained 96% of the variation among carcasses and included HCW, marbling score, and yield grade. Average daily gain, marbling score, yield grade, DMI, HCW, and year born constituted 81% of the variation for prediction of profit. Eighty-five percent of the variation in cost of gain was explained by ADG, DMI, HCW, and year. Prediction equations were developed that excluded ADG and DMI, and included feed efficiency values. Using these equations, cost of gain was explained primarily by FCR (R(2) = 0.71). Seventy-three percent of profitability was explained, with 55% being accounted for by RG and marbling. These prediction equations represent the relative importance of factors contributing to economic success in feedlot cattle based on current prices.

The effect of breed and individual heterosis on the feed efficiency, performance, and carcass characteristics of feedlot steers.

This study was conducted to evaluate maternal breed effects, direct breed effects, and individual heterosis on subsequent steer performance, carcass, and feed efficiency traits. This was a consecutive 2-yr trial using 158 steers. The same dam breeds, Angus (AN) and purebred Simmental (SM), were used both years. Also, the same AN and SM sires (n=11) were used both years. Steers were AN, SM, or AN×SM breed composition. Steers were managed similarly before weaning and early weaned at 56±9 d of age. Steers were then randomly allotted to pens and fed a common finishing ration. Contrasts were written to evaluate direct and maternal breed effects and individual heterosis in the PROC MIXED procedure of SAS (SAS Inst. Inc., Cary, NC) using dam breed, sire breed, and year as fixed effects. Simmental direct breed effect resulted in a 26 kg heavier initial BW (P<0.05) and a 46 kg heavier final BW (P<0.05). Simmental maternal breed effect increased initial BW by 43.5 kg (P<0.05). Dry matter intake was not impacted by direct breed effects, maternal breed effects, or individual heterosis. Individual heterosis did improve G:F 3.4% (P<0.05) and residual BW gain 0.048 kg/d (P<0.05). Residual intake and BW gain tended (P=0.07) to improve as a result of individual heterosis. Residual feed intake (RFI) was impacted by direct breed effect with SM cattle having a more desirable RFI (P=0.05). Angus direct breed effect increased backfat (P<0.05) and improved marbling score by 126 units (P<0.05). Simmental direct breed effect increased LM area (P<0.05), had the highest HCW at 410 kg (P<0.05), and had the most desirable yield grade at 2.74 (P<0.05). Individual heterosis improved marbling score (P=0.05). Maternal breed effect increased HCW (P<0.05) as a result of the SM dam. Direct breed effects were present for performance, feed efficiency measures, and carcass traits. Overall, heterosis impacted feedlot performance, carcass characteristics, and feed efficiency, which impacts beef production.

Evaluation of inbreeding depression in Holstein cattle using whole-genome SNP markers and alternative measures of genomic inbreeding.

The effects of increased pedigree inbreeding in dairy cattle populations have been well documented and result in a negative impact on profitability. Recent advances in genotyping technology have allowed researchers to move beyond pedigree analysis and study inbreeding at a molecular level. In this study, 5,853 animals were genotyped for 54,001 single nucleotide polymorphisms (SNP); 2,913 cows had phenotypic records including a single lactation for milk yield (from either lactation 1, 2, 3, or 4), reproductive performance, and linear type conformation. After removing SNP with poor call rates, low minor allele frequencies, and departure from Hardy-Weinberg equilibrium, 33,025 SNP remained for analyses. Three measures of genomic inbreeding were evaluated: percent homozygosity (FPH), inbreeding calculated from runs of homozygosity (FROH), and inbreeding derived from a genomic relationship matrix (FGRM). Average FPH was 60.5±1.1%, average FROH was 3.8±2.1%, and average FGRM was 20.8±2.3%, where animals with larger values for each of the genomic inbreeding indices were considered more inbred. Decreases in total milk yield to 205d postpartum of 53, 20, and 47kg per 1% increase in FPH, FROH, and FGRM, respectively, were observed. Increases in days open per 1% increase in FPH (1.76 d), FROH (1.72 d), and FGRM (1.06 d) were also noted, as well as increases in maternal calving difficulty (0.09, 0.03, and 0.04 on a 5-point scale for FPH, FROH, and FGRM, respectively). Several linear type traits, such as strength (-0.40, -0.11, and -0.19), rear legs rear view (-0.35, -0.16, and -0.14), front teat placement (0.35, 0.25, 0.18), and teat length (-0.24, -0.14, and -0.13) were also affected by increases in FPH, FROH, and FGRM, respectively. Overall, increases in each measure of genomic inbreeding in this study were associated with negative effects on production and reproductive ability in dairy cows.

Accuracy of genomic breeding values for residual feed intake in crossbred beef cattle.

The benefit of using genomic breeding values (GEBV) in predicting ADG, DMI, and residual feed intake for an admixed population was investigated. Phenotypic data consisting of individual daily feed intake measurements for 721 beef cattle steers tested over 5 yr was available for analysis. The animals used were an admixed population of spring-born steers, progeny of a cross between 3 sire breeds and a composite dam line. Training and validation data sets were defined by randomly splitting the data into training and testing data sets based on sire family so that there was no overlap of sires in the 2 sets. The random split was replicated to obtain 5 separate data sets. Two methods (BayesB and random regression BLUP) were used to estimate marker effects and to define marker panels and ultimately the GEBV. The accuracy of prediction (the correlation between the phenotypes and GEBV) was compared between SNP panels. Accuracy for all traits was low, ranging from 0.223 to 0.479 for marker panels with 200 SNP, and 0.114 to 0.246 for marker panels with 37,959 SNP, depending on the genomic selection method used. This was less than accuracies observed for polygenic EBV accuracies, which ranged from 0.504 to 0.602. The results obtained from this study demonstrate that the utility of genetic markers for genomic prediction of residual feed intake in beef cattle may be suboptimal. Differences in accuracy were observed between sire breeds when the random regression BLUP method was used, which may imply that the correlations obtained by this method were confounded by the ability of the selected SNP to trace breed differences. This may also suggest that prediction equations derived from such an admixed population may be useful only in populations of similar composition. Given the sample size used in this study, there is a need for increased feed intake testing if substantially greater accuracies are to be achieved.

Associations of marker panel scores with feed intake and efficiency traits in beef cattle using preselected single nucleotide polymorphisms.

Because of the moderate heritability and the expense associated with collecting feed intake data, effective selection for residual feed intake would be enhanced if marker-assisted evaluation were used for accurate estimation of genetic merit. In this study, a suite of genetic markers predictive of residual feed intake, DMI, and ADG were preselected using single-marker regression analysis, and the top 100 SNP were analyzed further to provide prediction equations for the traits. The data used consisted of 728 spring-born beef steers, offspring of a cross between a composite dam line and Angus, Charolais, or University of Alberta hybrid bulls. Feed intake data were collected over a 5-yr period, with 2 groups (fall-winter and winter-spring) tested every year. Training and validation data sets were obtained by splitting the data into 2 distinct sets, by randomly splitting the data into training and testing sets based on sire family (split 1) in 5 replicates or by retaining all animals with no known pedigree relationships as the validation set (split 2). A total of 37,959 SNP were analyzed by single-marker regression, of which only the top 100 that corresponded to a P-value <0.002 were retained. The 100 SNP were then analyzed using random regression BLUP, and only SNP that were jointly significant (P < 0.05) were included in the final marker panels. The marker effects from the selected panels were used to derive the molecular breeding values, which were calculated as a weighted sum of the number of copies of the more frequent allele at each SNP locus, with the weights being the allele substitution effects. The correlation between molecular breeding value and phenotype represented the accuracy of prediction. For all traits evaluated, accuracy across breeds was low, ranging between 0.007 and 0.414. Accuracy was least in data split 2, where the validation individuals had no pedigree relationship with animals in the training data. Given the low predictive ability observed, a large number of individuals may be needed for prediction when using such an admixed population. Further, these results suggest that breed composition of the target population in which the marker panels are likely to be used should be an important consideration when developing prediction equations across breeds, especially where an admixed population is used as the training data set.

Whole genome single nucleotide polymorphism associations with feed intake and feed efficiency in beef cattle.

Feed intake and efficiency are economically important traits because feed is the greatest variable cost in beef production. Feed efficiency can be measured as residual feed intake (RFI), which is the difference between actual DMI of an animal and the expected DMI based on its BW and growth rate. Feed conversion ratio (FCR) is the inverse of gross feed efficiency and is the ratio of DMI to ADG. A total of 2,633 SNP across the 29 bovine autosomes were analyzed in 464 steers sired by Angus, Charolais, or Alberta Hybrid bulls for associations with RFI. A total of 150 SNP were associated with RFI at P < 0.05 of which 23 were significant at P < 0.01. Nine of the SNP pairs show high linkage disequilibrium (r(2) > 0.80), so only 1 of the SNP pairs was used in further multiple-marker analyses. Two methods were used to create a panel of SNP that were maximally informative for RFI based on the data. In the first method, 141 unique SNP were combined in a single multivariate model and a backward elimination model was used to drop SNP until all SNP left in the model were significant at P < 0.05. The SNP had greater effects when combined in the multivariate model than when tested individually. In the second method, the estimates from the 141 SNP were used to create a sequential molecular breeding value (MBV) according to the compound covariate prediction (CCP) procedure. The sequential MBV was built by adding the estimated effects one at a time, but only keeping SNP effects in the sequential MBV if the test statistic and the proportion of variance explained were improved. Predictabilities of the 2 methods were compared by regressing RFI on a final MBV created from SNP that remained in each analytical model. The MBV from the compound covariate prediction model produced an r(2) of 0.497, whereas the multivariate model MBV had a decreased r(2) of 0.416. The significant SNP were also tested for associations with DMI and FCR. The SNP showed different combinations of associations with the 4 traits, including some that were only associated with RFI. About 9.5% of the SNP from the 2 models were within 5 cM of previously identified RFI QTL and pinpoint areas to further explore for positional candidate genes. In conclusion, this study has identified a panel of SNP with significant effects on RFI that need to be validated in an independent population and provides continued progress toward selecting markers for use in marker-assisted selection for feed efficiency in beef cattle.

Genetic evaluation of Angus cattle for carcass marbling using ultrasound and genomic indicators.

The objectives were to estimate genetic parameters needed to elucidate the relationships of a molecular breeding value (MBV) for marbling, intramuscular fat (IMF) of yearling bulls measured with ultrasound, and marbling score (MRB) of slaughtered steers, and to assess the utility of MBV and IMF in predicting the breeding value for MRB. Records for MRB (n = 38,296) and IMF (n = 6,594) were from the American Angus Association database used for national cattle evaluation. A total of 1,006 records of MBV were used in this study. (Co)variance components were estimated with ASREML, fitting an animal model with fixed contemporary groups for MRB and IMF similar to those used in the Angus national genetic evaluation. The overall mean was the only fixed effect included in the model for MBV. Heritability estimates for carcass measures were 0.48 +/- 0.03, 0.31 +/- 0.03, and 0.98 +/- 0.05 for MRB, IMF, and MBV, respectively. Genetic correlations of IMF and MBV with MRB were 0.56 +/- 0.09 and 0.38 +/- 0.10, respectively. The genetic correlation between IMF and MBV was 0.80 +/- 0.22. These results indicate the MBV evaluated may yield a greater genetic advance of approximately 20% when used as an indicator trait for genetic prediction of MRB compared with IMF. However, neither of these indicators alone provides sufficient information to produce highly accurate prediction of breeding value for the economically relevant trait MRB. Given that the goal is a highly accurate prediction of true breeding value for MRB, results of this work point to the need to 1) continue progeny testing, and 2) continue increasing the genetic correlation between the MBV and MRB.

Polymorphisms in the STAT6 gene and their association with carcass traits in feedlot cattle.

Identification of the genes and polymorphisms underlying quantitative traits, and understanding how these genes and polymorphisms affect economic traits, are important for successful marker-assisted selection and more efficient management strategies in commercial cattle populations. Signal transducer and activator of transcription 6 (STAT6) gene is tightly connected to IL-4 and IL-13 signalling and plays a key role in T(H)2 polarization of the immune system. In addition, STAT6 acts as a mediator of leptin signalling and has been associated with body weight regulation. The objective of this study was to determine if SNPs within the bovine STAT6 gene are associated with economically important traits in feedlot cattle. The approach consisted of resequencing STAT6 using a panel of DNA from unrelated animals of different beef breeds. Specifically, 16 kb of STAT6 was resequenced in 47 animals and the process revealed 39 SNPs. From the 39 SNPs, a panel of 15 tag SNPs was genotyped in 1500 beef cattle samples with phenotypes to perform a marker-trait association analysis. Among the 15 tag SNPs, five and six were polymorphic in Bos taurus and Bos indicus respectively. An association analysis was performed between the 15 tag SNPs and 14 performance and production traits. SNP ss115492459:C > A, ss115492461:A > G and ss115492458:G > C were significantly associated with back fat, calculated yield grade, cutability, hot carcass weight, dry matter intake, days on feed, back fat rate and average daily gain. These three SNPs were present in all Bos taurus beef breeds examined. Our results provide evidence that polymorphisms in STAT6 are associated with carcass and growth efficiency traits, and may be used for marker-assisted selection and management in feedlot cattle.

Polymorphisms in positional candidate genes on BTA14 and BTA26 affect carcass quality in beef cattle.

Several studies have reported the presence of carcass quality QTL on BTA14 and BTA26, with no specific genes being conclusively linked as their cause. The aim of this study was to identify polymorphisms in genes known to affect lipid metabolism in other species and to assess their association with carcass quality traits. Two genes located on BTA14, 2,4 dienoyl CoA reductase 1 (DECR1) and core binding factor, runt domain, alpha subunit 2, translocated to 1 gene (CBFA2T1), have been previously evaluated in other species and found to contain polymorphisms influencing lipid metabolism. A gene on BTA26, fibroblast growth factor 8 (FGF8), has in recent studies been linked to several QTL affecting obesity in mice, indicating its potential for regulating adiposity in other species. Sequencing analysis identified 9 polymorphisms in DECR1, 4 in CBFA2T1, and 4 in FGF8. Multiple sequence alignment of DECR1 among cattle, humans, and mice showed that 4 of these mutations lie in conserved regions across these species. Using 464 Angus, Charolais, and crossbred animals produced associations with ultrasound marbling score (CBFA2T1, P = 0.019), ultrasound backfat (DECR1, P = 0.012), carcass backfat (FGF8, P = 0.004), and lean meat yield (FGF8, P = 0.005). Quantitative trait loci analysis including a set of previously genotyped markers on BTA14, and 1 DECR1 polymorphism resulted in several significant QTL peaks: ultrasound backfat (UBF) at 91 cM, lean meat yield at 86 cM, carcass gradefat at 15 cM, and yield grade at 87 cM, all at the P < 0.05 level. Using DECR1 as a genetic covariate removed the UBF QTL, indicating that this SNP was contributing to the variation observed in UBF. A similar analysis was performed on BTA26 using 1 of the FGF8 polymorphisms. Results showed significant peaks for lean meat yield at 2 cM and for yield grade at 25 cM, both at P < 0.01, and for carcass backfat at 25 cM (P < 0.05). Removal of FGF8 SNP in further analysis resulted in the disappearance of the carcass backfat QTL. These results suggest that polymorphisms discovered in DECR1, CBFA2T1, and FGF8 may play a role in the lipid metabolism pathway affecting carcass quality traits in beef cattle. However, further studies are needed to confirm that these polymorphisms are responsible for the differences observed in carcass quality in beef cattle.

Modeling methane production from beef cattle using linear and nonlinear approaches.

Canada is committed to reducing its greenhouse gas emissions to 6% below 1990 amounts between 2008 and 2012, and methane is one of several greenhouse gases being targeted for reduction. Methane production from ruminants is one area in which the agriculture sector can contribute to reducing our global impact. Through mathematical modeling, we can further our understanding of factors that control methane production, improve national or global greenhouse gas inventories, and investigate mitigation strategies to reduce overall emissions. The purpose of this study was to compile an extensive database of methane production values measured on beef cattle, and to generate linear and nonlinear equations to predict methane production from variables that describe the diet. Extant methane prediction equations were also evaluated. The linear equation developed with the smallest root mean square prediction error (RMSPE, % observed mean) and residual variance (RV) was Eq. I: CH(4), MJ/d=2.72 (+/-0.543) + [0.0937 (+/-0.0117) x ME intake, MJ/d] + [4.31 (+/-0.215) x Cellulose, kg/d] - [6.49 (+/-0.800) x Hemicellulose, kg/d] - [7.44 (+/-0.521) x Fat, kg/d] [RMSPE=26.9%, with 94% of mean square prediction error (MSPE) being random error; RV=1.13]. Equations based on ratios of one diet variable to another were also generated, and Eq. P, CH(4), MJ/d=2.50 (+/-0.649) - [0.367 (+/-0.0191) x (Starch:ADF)] + [0.766 (+/-0.116) x DMI, kg/d], resulted in the smallest RMSPE values among these equations (RMSPE=28.6%, with 93.6% of MSPE from random error; RV=1.35). Among the nonlinear equations developed, Eq. W, CH(4), MJ/d=10.8 (+/-1.45) x (1-e([-0.141 (+/-0.0381) x DMI, kg/d])), performed well (RMSPE=29.0%, with 93.6% of MSPE from random error; RV=3.06), as did Eq. W(3), CH(4), MJ/d=10.8 (+/-1.45) x [1-e({-[-0.034 x (NFC/NDF)+0.228] x DMI, kg/d})] (RMSPE=28.0%, with 95% of MSPE from random error). Extant equations from a previous publication by the authors performed comparably with, if not better than in some cases, the newly developed equations. Equation selection by users should be based on RV and RMSPE analysis, input variables available to the user, and the diet fed, because the equation selected must account for divergence from a "normal" diet (e.g., high-concentrate diets, high-fat diets).

Fine mapping quantitative trait loci for feed intake and feed efficiency in beef cattle.

Feed intake and feed efficiency are economically important traits in beef cattle because feed is the greatest variable cost in production. Feed efficiency can be measured as feed conversion ratio (FCR, intake per unit gain) or residual feed intake (RFI, measured as DMI corrected for BW and growth rate, and sometimes a measure of body composition, usually carcass fatness, RFI(bf)). The goal of this study was to fine map QTL for these traits in beef cattle using 2,194 markers on 24 autosomes. The animals used were from 20 half-sib families originating from Angus, Charolais, and University of Alberta Hybrid bulls. A mixed model with random sire and fixed QTL effect nested within sire was used to test each location (cM) along the chromosomes. Threshold levels were determined at the chromosome and genome levels using 20,000 permutations. In total, 4 QTL exceeded the genome-wise threshold of P < 0.001, 3 exceeded at P < 0.01, 17 at P < 0.05, and 30 achieved significance at the chromosome-wise threshold level (at least P < 0.05). No QTL were detected on BTA 8, 16, and 27 above the 5% chromosome-wise significance threshold for any of the traits. Nineteen chromosomes contained RFI QTL significant at the chromosome-wise level. The RFI(bf) QTL results were generally similar to those of RFI, the positions being similar, but occasionally differing in the level of significance. Compared with RFI, fewer QTL were detected for both FCR and DMI, 12 and 4 QTL, respectively, at the genome-wise thresholds. Some chromosomes contained FCR QTL, but not RFI QTL, but all DMI QTL were on chromosomes where RFI QTL were detected. The most significant QTL for RFI was located on BTA 3 at 82 cM (P = 7.60 x 10(-5)), for FCR on BTA 24 at 59 cM (P = 0.0002), and for DMI on BTA 7 at 54 cM (P = 1.38 x 10(-5)). The RFI QTL that showed the most consistent results with previous RFI QTL mapping studies were on BTA 1, 7, 18, and 19. The identification of these QTL provides a starting point to identify genes affecting feed intake and efficiency for use in marker-assisted selection and management.

Identification of polymorphisms influencing feed intake and efficiency in beef cattle.

Feed efficiency is an economically important trait in beef cattle. Net feed efficiency, measured as residual feed intake (RFI), is the difference between actual feed intake and the predicted feed intake required for maintenance and gain of the animal. SNPs that show associations with RFI may be useful quantitative trait nucleotides for marker-assisted selection. This study identified associations between SNPs underlying five RFI QTL on five bovine chromosomes (BTA2, 5, 10, 20 and 29) with measures of dry matter intake (DMI), RFI and feed conversion ratio (FCR) in beef cattle. Six SNPs were found to have effects on RFI (P < 0.05). The largest single SNP allele substitution effect for RFI was -0.25 kg/day located on BTA2. The combined effects of the SNPs found significant in this experiment explained 6.9% of the phenotypic variation of RFI. Not all the RFI SNPs showed associations with DMI and FCR even though these traits are highly correlated with RFI (r = 0.77 and r = 0.62 respectively). This shows that these SNPs may be affecting the underlying biological mechanisms of feed efficiency beyond feed intake control and weight gain efficiency. These SNPs can be used in marker-assisted selection but first it will be important to verify these effects in independent populations of cattle.

Polymorphisms and haplotypes in the bovine neuropeptide Y, growth hormone receptor, ghrelin, insulin-like growth factor 2, and uncoupling proteins 2 and 3 genes and their associations with measures of growth, performance, feed efficiency, and carcass merit in beef cattle.

Genes that regulate metabolism and energy partitioning have the potential to influence economically important traits in farm animals, as do polymorphisms within these genes. In the current study, SNP in the bovine neuropeptide Y (NPY), growth hormone receptor (GHR), ghrelin (GHRL), uncoupling proteins 2 and 3 (UCP2 and UCP3), IGF2, corticotrophin-releasing hormone (CRH), cocaine and amphetamine regulated transcript (CART), melanocortin-4 receptor (MC4R), proopiomelanocortin (POMC), and GH genes were evaluated for associations with growth, feed efficiency, and carcass merit in beef steers. In total, 24 SNP were evaluated for associations with these traits and haplotypes were constructed within each gene when 2 or more SNP showed significant associations. An A/G SNP located in intron 4 of the GHR gene had the largest effects on BW of the animals (dominance effect P < 0.01) and feed efficiency (allele substitution effect P < 0.05). Another A/G SNP located in the promoter region of GHR had similar effects but the haplotypes of these 2 SNP reduced the effects of the SNP located in intron 4. Three SNP in the NPY gene showed associations to marbling (P < 0.001) as well as with ADG, BW, and feed conversion ratio (FCR; P < 0.05). The combination of these 3 SNP into haplotypes generally improved the association or had a similar scale of association as each single SNP. Only 1 SNP in UCP3, an A/G SNP in intron 3, was associated with ADG (P = 0.025), partial efficiency of growth, and FCR (P < 0.01). Three SNP in UCP2 gene were in almost complete linkage disequilibrium and showed associations with lean meat yield, yield grade, DMI, and BW (P < 0.05). Haplo-types between the SNP in UCP3 and UCP2 generally reduced the associations seen individually in each SNP. An A/G SNP in the GHRL gene tended to show effects on residual feed intake, FCR, and partial efficiency of growth (P < 0.10). The IGF2 SNP most strongly affected LM area (P < 0.01), back fat, ADG, and FCR (P < 0.05). The SNP in the CART, MC4R, POMC, GH, and CRH genes did not show associations at P < 0.05 with any of the traits. Although most of the SNP that showed associations do not cause amino acid changes, these SNP could be linked to other yet to be detected causative mutations or nearby QTL. It will be very important to verify these results in other cattle populations.

Primary genome scan to identify putative quantitative trait loci for feedlot growth rate, feed intake, and feed efficiency of beef cattle.

Feed intake and feed efficiency of beef cattle are economically relevant traits. The study was conducted to identify QTL for feed intake and feed efficiency of beef cattle by using genotype information from 100 microsatellite markers and 355 SNP genotyped across 400 progeny of 20 Angus, Charolais, or Alberta Hybrid bulls. Traits analyzed include feedlot ADG, daily DMI, feed-to-gain ratio [F:G, which is the reciprocal of the efficiency of gain (G:F)], and residual feed intake (RFI). A mixed model with sire as random and QTL effects as fixed was used to generate an F-statistic profile across and within families for each trait along each chromosome, followed by empirical permutation tests to determine significance thresholds for QTL detection. Putative QTL for ADG (chromosome-wise P < 0.05) were detected across families on chromosomes 5 (130 cM), 6 (42 cM), 7 (84 cM), 11 (20 cM), 14 (74 cM), 16 (22 cM), 17 (9 cM), 18 (46 cM), 19 (53 cM), and 28 (23 cM). For DMI, putative QTL that exceeded the chromosome-wise P < 0.05 threshold were detected on chromosomes 1 (93 cM), 3 (123 cM), 15 (31 cM), 17 (81 cM), 18 (49 cM), 20 (56 cM), and 26 (69 cM) in the across-family analyses. Putative across-family QTL influencing F:G that exceeded the chromosome-wise P < 0.05 threshold were detected on chromosomes 3 (62 cM), 5 (129 cM), 7 (27 cM), 11 (16 cM), 16 (30 cM), 17 (81 cM), 22 (72 cM), 24 (55 cM), and 28 (24 cM). Putative QTL influencing RFI that exceeded the chromosome-wise P < 0.05 threshold were detected on chromosomes 1 (90 cM), 5 (129 cM), 7 (22 cM), 8 (80 cM), 12 (89 cM), 16 (41 cM), 17 (19 cM), and 26 (48 cM) in the across-family analyses. In addition, a total of 4, 6, 1, and 8 chromosomes showed suggestive evidence (chromosome-wise, P < 0.10) for putative ADG, DMI, F:G, and RFI QTL, respectively. Most of the QTL detected across families were also detected within families, although the locations across families were not necessarily the locations within families, which is likely because of differences among families in marker informativeness for the different linkage groups. The locations and direction of some of the QTL effects reported in this study suggest potentially favorable pleiotropic effects for the underlying genes. Further studies will be required to confirm these QTL in other populations so that they can be fine-mapped for potential applications in marker-assisted selection and management of beef cattle.

Genetic and phenotypic relationships of feeding behavior and temperament with performance, feed efficiency, ultrasound, and carcass merit of beef cattle.

Feeding behavior and temperament may be useful in genetic evaluations either as indicator traits for other economically relevant traits or because the behavior traits may have a direct economic value. We determined the variation in feeding behavior and temperament of beef cattle sired by Angus, Charolais, or Hybrid bulls and evaluated their associations with performance, efficiency, and carcass merit. The behavior traits were daily feeding duration, feeding head down (HD) time, feeding frequency (FF), and flight speed (FS, as a measure of temperament). A pedigree file of 813 animals forming 28 paternal half-sib families with about 20 progeny per sire was used. Performance, feeding behavior, and efficiency records were available on 464 animals of which 381 and 302 had records on carcass merit and flight speed, respectively. Large SE reflect the number of animals used. Direct heritability estimates were 0.28 +/- 0.12 for feeding duration, 0.33 +/- 0.12 for HD, 0.38 +/- 0.13 for FF, and 0.49 +/- 0.18 for FS. Feeding duration had a weak positive genetic (r(g)) correlation with HD (r(g) = 0.25 +/- 0.32) and FS (r(g) = 0.42 +/- 0.26) but a moderate negative genetic correlation with FF (r(g) = -0.40 +/- 0.30). Feeding duration had positive phenotypic (r(p)) and genetic correlations with DMI (r(p) = 0.27; r(g) = 0.56 +/- 0.20) and residual feed intake (RFI; r(p) = 0.49; r(g) = 0.57 +/- 0.28) but was unrelated phenotypically with feed conversion ratio [FCR; which is the reciprocal of the efficiency of growth (G:F)]. Feeding duration was negatively correlated with FCR (r(g) = -0.25 +/- 0.29). Feeding frequency had a moderate to high negative genetic correlation with DMI (r(g) = -0.74 +/- 0.15), FCR (r(g) = -0.52 +/- 0.21), and RFI (r(g) = -0.77 +/- 0.21). Flight speed was negatively correlated phenotypically with DMI (r(p) = -0.35) but was unrelated phenotypically with FCR or RFI. On the other hand, FS had a weak negative genetic correlation with DMI (r(g) = -0.11 +/- 0.26), a moderate genetic correlation with FCR (r(g) = 0.40 +/- 0.26), and a negative genetic correlation with RFI (r(g) = -0.59 +/- 0.45). The results indicate that behavior traits may contribute to the variation in the efficiency of growth of beef cattle, and there are potential correlated responses to selection to improve efficiency. Feeding behavior and temperament may need to be included in the definition of beef cattle breeding goals, and approaches such as the culling of unmanageable cattle and the introduction of correct handling facilities or early life provision of appropriate experiences to improve handling will be useful.

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.

Genetic and phenotypic relationships of serum leptin concentration with performance, efficiency of gain, and carcass merit of feedlot cattle.

Leptin is the hormone product of the obese gene that is synthesized and predominantly expressed by adipocytes. This study estimated the genetic variation in serum leptin concentration and evaluated the genetic and phenotypic relationships of serum leptin concentration with performance, efficiency of gain, and carcass merit. There were 464 steers with records for serum leptin concentration, performance, and efficiency of gain and 381 steers with records for carcass traits. The analyses included a total of 813 steers, including those without phenotypic records. Phenotypic and genetic parameter estimates were obtained using SAS and ASREML, respectively. Serum leptin concentration was moderately heritable (h2 = 0.34 +/- 0.13) and averaged 13.91 (SD = 5.74) ng/mL. Sire breed differences in serum leptin concentration correlated well with breed differences in body composition. Specifically, the serum leptin concentration was 20% greater in Angus-sired steers compared with Charolais-sired steers (P < 0.001). Consequently, ultrasound backfat (27%), carcass 12th-rib fat (31%), ultrasound marbling (14%), and carcass marbling (15%) were less in Charolais- than Angus-sired steers (P < 0.001). Conversely, carcass LM area (P = 0.05) and carcass lean meat yield (P < 0.001) were greater in Charolais- compared with Angus-sired steers. Steers with greater serum leptin concentration also had greater DMI (P < 0.001), greater residual feed intake (P = 0.04), and partial efficiency of growth (P = 0.01), but did not differ in feed conversion ratio (P > 0.10). Serum leptin concentration was correlated phenotypically with ultrasound backfat (r = 0.41; P < 0.001), carcass 12th-rib fat (r = 0.42; P < 0.001), ultrasound marbling (r = 0.25; P < 0.01), carcass marbling (r = 0.28; P < 0.01), ultrasound LM area (r = -0.19; P < 0.01), carcass LM area (r = -0.17; P < 0.05), lean meat yield (r = -0.38; P < 0.001), and yield grade (r = 0.32; P < 0.001). The corresponding genetic correlations were generally greater than the phenotypic correlations and included ultrasound backfat (r = 0.76 +/- 0.19), carcass 12th-rib fat (r = 0.54 +/- 0.23), ultrasound marbling (r = 0.27 +/- 0.22), carcass marbling (r = 0.76 +/- 0.21), ultrasound LM area (r = -0.71 +/- 0.19), carcass LM area (r = -0.75 +/- 0.20), lean meat yield (r = -0.59 +/- 0.22), and yield grade (r = 0.39 +/- 0.26). Serum leptin concentration can be a valuable tool that can be incorporated into appropriate selection programs to favorably improve the carcass merit of cattle.

Test duration for growth, feed intake, and feed efficiency in beef cattle using the GrowSafe System.

This study was conducted to determine the optimum test duration and the effect of missing data on accuracy of measuring feed efficiency and its 4 related traits ADG, DMI, feed conversion ratio, and residual feed intake in beef cattle using data from 456 steers with 5,397 weekly averaged feed intakes and BW repeated measurements taken over 91 d. Data were collected using the GrowSafe System at the University of Alberta Kinsella Research Station. The changes and relative changes in phenotypic residual variances and correlations (Pearson and Spearman) among data from shortened test durations (7, 14, 21, 28, 35, 42, 49, 56, 63, 70, 77, or 84 d) and a 91-d test were used to determine the optimum test duration for the 4 traits. The traits were fitted to a mixed model with repeated measures using SAS. Test durations for ADG, DMI, feed conversion ratio, and residual feed intake could be shortened to 63, 35, 42, and 63 d, respectively, without significantly reducing the accuracy of the tests when BW was measured weekly. The accuracy of the test was not compromised when up to 30% of the records were randomly removed after the first 35 d on test. These results have valuable and practical implications for performance and feed efficiency testing in beef cattle.

Relationships of feedlot feed efficiency, performance, and feeding behavior with metabolic rate, methane production, and energy partitioning in beef cattle.

Residual feed intake (RFI) is the difference between the actual and expected feed intake of an animal based on its BW and growth rate over a specified period. The biological mechanisms underlying the variation in feed efficiency in animals with similar BW and growth rate are not well understood. This study determined the relationship of feedlot feed efficiency, performance, and feeding behavior with digestion and energy partitioning of 27 steers. The steers were selected from a total of 306 animals based on their RFI following feedlot tests at the University of Alberta Kinsella Research Station. Selected steers were ranked into high RFI (RFI > 0.5 SD above the mean, n = 11), medium RFI (RFI +/- 0.5 SD above and below the mean, n = 8), and low RFI (RFI < -0.5 SD below the mean, n = 8). The respective BW +/- SD for the RFI groups were 495.6 +/- 12.7, 529.1 +/- 18.6, and 501.2 +/- 15.5 kg. Digestibility and calorimetry trials were performed on a corn-or barley-based concentrate diet in yr 1 and 2, respectively, at 2.5 x maintenance requirements. Mean DMI (g/kg of BW(0.75)) during the measurements for high-, medium-, and low-RFI groups, respectively, were 82.7 +/- 2.0, 78.8 +/- 2.6, and 81.8 +/- 2.5 and did not differ (P > 0.10). Residual feed intake was correlated with daily methane production and energy lost as methane (r = 0.44; P < 0.05). Methane production was 28 and 24% less in low-RFI animals compared with high- and medium-RFI animals, respectively. Residual feed intake tended to be associated (P < 0.10) with apparent digestibilities of DM (r = -0.33) and CP (r = -0.34). The RFI of steers was correlated with DE (r = -0.41; P < 0.05), ME (r = -0.44; P < 0.05), heat production (HP; r = 0.68; P < 0.001), and retained energy (RE; r = -0.67; P < 0.001; energy values are expressed in kcal/kg of BW(0.75)). Feedlot partial efficiency of growth was correlated (P < 0.01) with methane production (r = -0.55), DE (r = 0.46), ME (r = 0.49), HP (r = -0.50), and RE (r = 0.62). With the exception of HP (r = 0.37; P < 0.05), feed conversion ratio was unrelated to the traits considered in the study. Feeding duration was correlated (P < 0.01) with apparent digestibility of DM (r = -0.55), CP (r = -0.47), methane production (r = 0.51), DE (r = -0.52), ME (r = -0.55), and RE (r = -0.60). These results have practical implications for the selection of animals that eat less at a similar BW and growth rate and for the environmental sustainability of beef production.