Heritability of beef cow metabolizable energy for maintenance.

Most of the metabolizable energy that a cow uses during a production year is for maintenance; however, less is known about the heritability of maintenance compared to other traits that can be measured directly. Feed intake is a heritable trait in the mature cow and most of the feed consumed is used for maintenance. We hypothesized that maintenance energy was a heritable trait. Individual feed intake was measured for 84 or 85 d on 5 yr old pregnant cows (N = 887) from a pedigreed population of cattle that represent prominent breeds in the United States. Phenotypic mean (± SD) values were 654 ± 68 kg for cow body weight, 0.21 ± 0.24 kg/d for average daily gain, and 175 ± 17 d for midpoint fetal age. Dry matter intake averaged (± SD) 10.84 ± 1.41 kg/d. Metabolizable energy for maintenance was estimated by subtracting the metabolizable energy used for conceptus growth and tissue accretion from metabolizable energy intake. Metabolizable energy for maintenance averaged (± SD) 139 ± 18 ME kcal/d/BW kg0.75 and had a heritability of 0.31 ± 0.11. Cows have a moderate heritability for maintenance suggesting an opportunity for selection.

Feed is one of the greatest costs of beef production. Most of the feed used annually by a cow is to maintain her body. A study was conducted measuring individual feed intake of mature pregnant cows. We have determined that the amount of energy that a cow uses to maintain her body is heritable suggesting that cows can be selected for differences in the energy required to maintain their bodies.

Genetic and phenotypic associations of mitochondrial DNA copy number, SNP, and haplogroups with growth and carcass traits in beef cattle.

Mitochondrial DNA copy number (mtDNA CN) is heritable and easily obtained from low-pass sequencing (LPS). This study investigated the genetic correlation of mtDNA CN with growth and carcass traits in a multi-breed and crossbred beef cattle population. Blood, leucocyte, and semen samples were obtained from 2,371 animals and subjected to LPS that resulted in nuclear DNA (nuDNA) and mtDNA sequence reads. Mitochondrial DNA CN was estimated as the ratio of mtDNA to nuDNA coverages. Variant calling was performed from mtDNA, and 11 single nucleotide polymorphisms (SNP) were identified in the population. Samples were classified in taurine haplogroups. Haplogroup and mtDNA type were further classified based on the 11 segregating SNP. Growth and carcass traits were available for between 7,249 and 60,989 individuals. Associations of mtDNA CN, mtDNA haplogroups, mtDNA types, and mtDNA SNP with growth and carcass traits were estimated with univariate animal models, and genetic correlations were estimated with a bivariate animal model based on pedigree. Mitochondrial DNA CN tended (P-value ≤0.08) to be associated with birth weight and weaning weight. There was no association (P-value >0.10) between mtDNA SNP, haplogroups, or types with growth and carcass traits. Genetic correlation estimates of mtDNA CN were -0.30 ± 0.16 with birth weight, -0.31 ± 0.16 with weaning weight, -0.15 ± 0.14 with post-weaning gain, -0.11 ± 0.19 with average daily dry-matter intake, -0.04 ± 0.22 with average daily gain, -0.29 ± 0.13 with mature cow weight, -0.11 ± 0.13 with slaughter weight, -0.14 ± 0.13 with carcass weight, -0.07 ± 0.14 with carcass backfat, 0.14 ± 0.14 with carcass marbling, and -0.06 ± 0.14 with ribeye area. In conclusion, mtDNA CN was negatively correlated with most traits investigated, and the genetic correlation was stronger with growth traits than with carcass traits.

This study investigated mitochondrial DNA copy number (mtDNA CN) as a potential genetic indicator of growth and carcass traits in a composite beef cattle population. Mitochondrial DNA CN was previously shown to be under genetic control. The current study estimated the genetic relationship of mtDNA CN with growth and carcass traits. Blood, leucocyte, and semen samples were obtained from 2,371 animals and subjected to whole-genome sequencing at a low depth that resulted in nuclear DNA and mtDNA sequence reads. Mitochondrial DNA CN was estimated as the ratio of mtDNA to nuclear DNA coverages. Growth and carcass traits were available for between 7,249 and 60,989 individuals. Genetic parameters were estimated from an animal model based on pedigree. Genetic correlation estimates of mtDNA CN with growth and carcass traits were low to moderate and mostly negative. These indicate that selection for lower mtDNA would be associated with an increase in birth weight, weaning weight, post-weaning gain, average daily dry-matter intake, mature cow weight, slaughter weight, and carcass weight. Therefore, the by-product of whole-genome sequencing at a low depth could be used as an indicator trait for growth and carcass traits in genetic evaluations, but the genetic relationships are not likely strong enough to prioritize mtDNA ahead of routinely used indicator traits.

Breeding Sustainable Beef Cows: Reducing Weight and Increasing Productivity.

Programs for sustainable beef production are established, but the specific role of beef cows in these systems is not well defined. This work characterized cows for two traits related to sustainability, cow weight (CW) and cumulative weight weaned (WtW). Cow weight indicates nutrient requirements and enteric methane emissions. Cumulative weight weaned reflects reproductive performance and avoidance of premature culling for characteristics related to animal health, welfare, and worker safety. Both traits were evaluated with random regression models with records from a crossbred population representing 18 breeds that conduct US national cattle evaluations. The genomic REML analyses included additive and dominance components, with relationships among 22,776 animals constructed from genotypes of 181,286 potentially functional variants imputed from a low-pass sequence. Projected to 8 years of age, the additive heritability estimate for CW was 0.57 and 0.11 for WtW. Dominance heritability was 0.02 for CW and 0.19 for WtW. Many variants with significant associations with CW were within previously described quantitative trait loci (QTL) for growth-related production, meat, and carcass traits. Significant additive WtW variants were covered by QTL for traits related to reproduction and structural soundness. All breeds contributed to groups of cows with high and low total genetic values (additive + dominance effects) for both traits. The high WtW cows and cows above the WtW mean but below the CW mean had larger heterosis values and fewer bases in runs of homozygosity. The high additive heritability of CW and dominance effects on WtW indicate that breeding to improve beef cow sustainability should involve selection to reduce CW and mate selection to maintain heterosis and reduce runs of homozygosity.

Genetic parameters, heterosis, and breed effects for body condition score and mature cow weight in beef cattle.

Understanding the genetic relationship between mature cow weight (MWT) and body condition score (BCS) is useful to implement selection programs focused on cow efficiency. The objectives of this study were to estimate genetic parameters, heterosis, and breed effects for MWT and BCS. In total, 25,035 and 24,522 overlapping records were available for MWT and BCS on 6,138 and 6,131 cows, respectively, from the Germplasm Evaluation program, a crossbred beef population at the U.S. Meat Animal Research Center. Pedigree was available for 48,013 individuals. Univariate animal models were used to estimate heritabilities for each trait by parity. Bivariate animal models were used to estimate genetic correlations between parities within a trait and between traits within parities. Bivariate repeatability animal models were used to estimate genetic correlations between traits across parities. Estimates of heritability for different parities ranged from 0.43 ±â€…0.05 to 0.55 ±â€…0.07 for MWT and from 0.12 ±â€…0.03 to 0.25 ±â€…0.04 for BCS and were lower with the repeatability model at 0.40 ±â€…0.02 and 0.11 ±â€…0.01 for MWT and BCS, respectively. Estimates of repeatability were high for MWT (0.67 ±â€…0.005) and low for BCS (0.22 ±â€…0.006). Estimates of genetic correlation for MWT and BCS between parities were, in general, high, especially between consecutive parities. Estimates of genetic correlation between MWT and BCS were positive and moderate, ranging from 0.32 ±â€…0.09 to 0.68 ±â€…0.14. The direct heterosis estimates were 21.56 ±â€…3.53 kg (P ≤ 0.001) for MWT and 0.095 ±â€…0.034 (P ≤ 0.001) for BCS. Ordered by decreasing MWT, the breeds ranked Brahman, Charolais, Angus, Simmental, Salers, Hereford, Santa Gertrudis, Chiangus, Brangus, Red Angus, Shorthorn, Maine-Anjou, Gelbvieh, Beefmaster, Limousin, and Braunvieh. Ordered by decreasing BCS, the breeds ranked Brahman, Red Angus, Charolais, Angus, Hereford, Brangus, Beefmaster, Chiangus, Salers, Simmental, Maine-Anjou, Limousin, Santa Gertrudis, Shorthorn, Gelbvieh, and Braunvieh. Estimates of breed differences for MWT were also adjusted for BCS (AMWT), and in general, AMWT depicted smaller differences between breeds with some degree of re-ranking (r = 0.59). These results suggest that MWT and BCS are at least moderately genetically correlated and that they would respond favorably to selection. Estimates of breed differences and heterotic effects could be used to parameterize multibreed genetic evaluations for indicators of cow maintenance energy requirements.

The current study estimated the genetic relationship between mature cow weight (MWT) and body condition score (BCS), heterosis, and breed effects for these traits in a crossbred beef population. In total, 25,035 and 24,522 overlapping records were available for MWT and BCS, respectively. Pedigree was available for 48,013 individuals. Heritability and genetic correlations were estimated within a trait between parities, between traits within parities, and between traits across parities. Estimates of heritability ranged from 0.40 ±â€…0.02 to 0.55 ±â€…0.07 for MWT and from 0.11 ±â€…0.01 to 0.25 ±â€…0.04 for BCS. Genetic correlations within a trait and between parities were, in general, high. Estimates of genetic correlation between MWT and BCS were positive and moderate, ranging from 0.32 ±â€…0.09 to 0.68 ±â€…0.14. Heterosis effects were 21.56 ±â€…3.53 kg for MWT and 0.095 ±â€…0.034 for BCS. For both traits, Brahman and Braunvieh were associated with the highest and lowest breed effects, respectively. These results suggest that MWT and BCS would respond favorably to selection and are moderately genetically correlated. Breed differences and heterotic effects could be used to parameterize multibreed genetic evaluations for indicators of cow maintenance energy requirements.

Breed and heterotic effects for mature weight in beef cattle.

Cow mature weight (MWT) is heritable and affects the costs and efficiency of a breeding operation. Cow weight is also influenced by the environment, and the relationship between the size and profitability of a cow varies depending on production system. Producers, therefore, need tools to incorporate MWT in their selection of cattle breeds and herd replacements. The objective of this study was to estimate breed and heterotic effects for MWT using weight-age data on crossbred cows. Cow's MWT at 6 yr was predicted from the estimated parameter values-asymptotic weight and maturation constant (k)-from the fit of the Brody function to their individual data. Values were obtained for 5,156 crossbred cows from the U.S. Meat Animal Research Center (USMARC) Germplasm Evaluation Program using 108,957 weight records collected from approximately weaning up to 6 yr of age. The cows were produced from crosses among 18 beef breeds. A bivariate animal model was fitted to the MWT and k obtained for each cow. The fixed effects were birth year-season contemporary group and covariates of direct and maternal breed fractions, direct and maternal heterosis, and age at final weighing. The random effects were direct additive and residual. A maternal additive random effect was also fitted for k. In a separate analysis from that used to estimate breed effects and (co)variances, cow MWT was regressed on sire yearling weight (YWT) Expected Progeny Differences by its addition as a covariate to the animal model fitted for MWT. That regression coefficient was then used to adjust breed solutions for sire selection in the USMARC herd. Direct heterosis was 15.3 ± 2.6 kg for MWT and 0.000118 ± 0.000029 d-1 for k. Maternal heterosis was -5.7 ± 3.0 kg for MWT and 0.000130 ± 0.000035 d-1 for k. Direct additive heritabilities were 0.56 ± 0.03 for MWT and 0.23 ± 0.03 for k. The maternal additive heritability for k was 0.11 ± 0.02. The direct additive correlation between MWT and k was negligible (0.08 ± 0.09). Adjusted for sire sampling, Angus was heaviest at maturity of the breeds compared. Deviations from Angus ranged from -8.9 kg (Charolais) to -136.7 kg (Braunvieh). Ordered by decreasing MWT, the breeds ranked Angus, Charolais, Hereford, Brahman, Salers, Santa Gertrudis, Simmental, Maine Anjou, Limousin, Red Angus, Brangus, Chiangus, Shorthorn, Gelbvieh, Beefmaster, and Braunvieh. These breed effects for MWT can inform breeding programs where cow size is considered a key component of the overall profitability.

Comparison of different functions to describe growth from weaning to maturity in crossbred beef cattle1.

Cow mature weight (MWT) has increased in the past 30 yr. Larger cows cost more to maintain, but their efficiency-and thus profitability-depends on the production environment. Incorporating MWT effectively into selection and mating decisions requires understanding of growth to maturity. The objective of this study was to describe growth to maturity in crossbred beef cattle using Brody, spline, and quadratic functions. Parameter estimates utilized data on crossbred cows from cycle VII and continuous sampling phases of the Germplasm Evaluation Program at the U.S. Meat Animal Research Center. The MWT were estimated at 6 yr from the fitted parameters obtained from the Brody (BMWT), spline (SMWT), and quadratic (QMWT) functions. These were defined as BMWT, SMWT, and QMWT for the Brody, spline, and quadratic functions, respectively. Key parameters from the Brody function were BMWT and maturing constant. The spline was fitted as piecewise linear where the two linear functions joined at a knot. Key parameters were knot position and SMWT. For the quadratic model, the main parameter considered was QMWT. Data were scaled for fitting such that 180 d was the y-intercept with the average weight at 180 d (214.3 kg) subtracted from all weights. Weights were re-expressed by adding 214.3 kg after analysis. Once data were edited, with outliers removed, there were parameter estimates for 5,156, 5,041, and 4,905 cows for the Brody, spline, and quadratic functions, respectively. The average maturing constant (SD) was 0.0023 d-1 (0.0008 d-1). The mean MWT estimates (SD) from the Brody, spline, and quadratic functions were 650.0 kg (64.0 kg), 707.3 kg (79.8 kg), and 597.8 kg (116.7 kg), respectively. The spline function had the highest average R2 value when fit to individual cows' data. However, the Brody function produced more consistent MWT estimates regardless of the timeframe of data available and produced the fewest extreme MWT. For the spline and quadratic functions, weights through 4 and 5 yr of age, respectively, were needed before consistent estimates of MWT were obtained. Of the three functions fitted, the Brody was best suited for estimating MWT at a later age in crossbred beef cattle.

Genetic correlations among weight and cumulative productivity of crossbred beef cows.

Mature weight of beef cows in the United States has been increasing as a correlated response to selection for calf growth. Unfavorable genetic correlations between cow weight and various measures of female fertility, stayability, and lifetime production suggest declining cow productivity might also be expected as a correlated response to growth selection. National cattle evaluations, however, show increasing trends for stayability and sustained fertility. Random regression (RR) models were employed to further examine genetic relationships among cow weight and productivity, and to assess cumulative productivity traits observed throughout cows' productive lives. Records were from 13,707 females born in the Germplasm Evaluation (GPE) project and mated to calve first as 2-yr olds. Weights observed at pregnancy testing (n = 65,086) and calf production from each exposure to breeding (n = 71,583) were included in uni- and bivariate RR analyses. Production following each breeding season was added to previous production to obtain cumulative production records for each season that the female was exposed to breeding. Zero was added if the cow failed to produce after a breeding season. The number of pregnancies, calves born and calves weaned, as well as age and weight of weaned calves, were accumulated. Projected age-specific heritability (h2) estimates for cumulative production were low (<0.1) at age 2 but increased with age (0.12 to 0.26 at age 6; 0.32 to 0.48 at age 10). Estimated h2 for cow weight were high, fluctuating between 0.6 and 0.7 from ages 2 through 10. Genetic correlations (rg) were positive among all ages within each trait. Between ages 3 and 9, estimated rg were negative between cumulative weaning productivity and cow weight. The correlations were usually weak enough (<-0.2) that small correlated declines from following yearling weight trends might be overcome by culling females after their first reproductive failure. More noticeable increases might be realized by selection among sires with EBV based on productivity of several daughters. The RR EBV for cow weight and cumulative weight weaned represent major sources of variation in cow costs and income, and can be incorporated into economic selection indexes to project differences in cow profitability and value at any age. The RR approach utilizes all available records, enabling later productivity to be projected from observations on young cows.

Comparison of molecular breeding values based on within- and across-breed training in beef cattle.

BACKGROUND: Although the efficacy of genomic predictors based on within-breed training looks promising, it is necessary to develop and evaluate across-breed predictors for the technology to be fully applied in the beef industry. The efficacies of genomic predictors trained in one breed and utilized to predict genetic merit in differing breeds based on simulation studies have been reported, as have the efficacies of predictors trained using data from multiple breeds to predict the genetic merit of purebreds. However, comparable studies using beef cattle field data have not been reported. METHODS: Molecular breeding values for weaning and yearling weight were derived and evaluated using a database containing BovineSNP50 genotypes for 7294 animals from 13 breeds in the training set and 2277 animals from seven breeds (Angus, Red Angus, Hereford, Charolais, Gelbvieh, Limousin, and Simmental) in the evaluation set. Six single-breed and four across-breed genomic predictors were trained using pooled data from purebred animals. Molecular breeding values were evaluated using field data, including genotypes for 2227 animals and phenotypic records of animals born in 2008 or later. Accuracies of molecular breeding values were estimated based on the genetic correlation between the molecular breeding value and trait phenotype. RESULTS: With one exception, the estimated genetic correlations of within-breed molecular breeding values with trait phenotype were greater than 0.28 when evaluated in the breed used for training. Most estimated genetic correlations for the across-breed trained molecular breeding values were moderate (> 0.30). When molecular breeding values were evaluated in breeds that were not in the training set, estimated genetic correlations clustered around zero. CONCLUSIONS: Even for closely related breeds, within- or across-breed trained molecular breeding values have limited prediction accuracy for breeds that were not in the training set. For breeds in the training set, across- and within-breed trained molecular breeding values had similar accuracies. The benefit of adding data from other breeds to a within-breed training population is the ability to produce molecular breeding values that are more robust across breeds and these can be utilized until enough training data has been accumulated to allow for a within-breed training set.

Sparse inverse of covariance matrix of QTL effects with incomplete marker data.

Gametic models for fitting breeding values at QTL as random effects in outbred populations have become popular because they require few assumptions about the number and distribution of QTL alleles segregating. The covariance matrix of the gametic effects has an inverse that is sparse and can be constructed rapidly by a simple algorithm, provided that all individuals have marker data, but not otherwise. An equivalent model, in which the joint distribution of QTL breeding values and marker genotypes is considered, was shown to generate a covariance matrix with a sparse inverse that can be constructed rapidly with a simple algorithm. This result makes more feasible including QTL as random effects in analyses of large pedigrees for QTL detection and marker assisted selection. Such analyses often use algorithms that rely upon sparseness of the mixed model equations and require the inverse of the covariance matrix, but not the covariance matrix itself. With the proposed model, each individual has two random effects for each possible unordered marker genotype for that individual. Therefore, individuals with marker data have two random effects, just as with the gametic model. To keep the notation and the derivation simple, the method is derived under the assumptions of a single linked marker and that the pedigree does not contain loops. The algorithm could be applied, as an approximate method, to pedigrees that contain loops.