Longevity in South African Afrikaner cows as assessed through survival analysis.

The Afrikaner breed of cattle is indigenous to South Africa and, due to their hardiness, was once the most popular breed amongst South African farmers, although in recent years their numbers have decreased. The goal of this study was to assess factors affecting length of productive life, defined as the interval between production of the first and last calf, in Afrikaner cattle using survival analysis. The data spanned 40 years with an observed measure of length of life for 29,379 cows from 374 herds. Relative to similar analyses, few (n = 2964; 8.4%) cows had records that were right censored. The median length of productive life of an Afrikaner cow was just less than 6 years. Cows that were younger at their first parturition had longer productive lives than those that were older at their first calving. Cows that were born in the period from December to February had shorter productive lives than those born between March and November. The estimated animal genetic variance of 0.266 resulted in a heritability estimate for length of productive life in Afrikaner cattle of 0.225. Thus, there appeared to be sufficient additive genetic variance in Afrikaner cattle to enable genetic improvement in their length of productive life.

Variance component estimates, phenotypic characterization, and genetic evaluation of bovine congestive heart failure in commercial feeder cattle.

The increasing incidence of bovine congestive heart failure (BCHF) in feedlot cattle poses a significant challenge to the beef industry from economic loss, reduced performance, and reduced animal welfare attributed to cardiac insufficiency. Changes to cardiac morphology as well as abnormal pulmonary arterial pressure (PAP) in cattle of mostly Angus ancestry have been recently characterized. However, congestive heart failure affecting cattle late in the feeding period has been an increasing problem and tools are needed for the industry to address the rate of mortality in the feedlot for multiple breeds. At harvest, a population of 32,763 commercial fed cattle were phenotyped for cardiac morphology with associated production data collected from feedlot processing to harvest at a single feedlot and packing plant in the Pacific Northwest. A sub-population of 5,001 individuals were selected for low-pass genotyping to estimate variance components and genetic correlations between heart score and the production traits observed during the feeding period. At harvest, the incidence of a heart score of 4 or 5 in this population was approximately 4.14%, indicating a significant proportion of feeder cattle are at risk of cardiac mortality before harvest. Heart scores were also significantly and positively correlated with the percentage Angus ancestry observed by genomic breed percentage analysis. The heritability of heart score measured as a binary (scores 1 and 2 = 0, scores 4 and 5 = 1) trait was 0.356 in this population, which indicates development of a selection tool to reduce the risk of congestive heart failure as an EPD (expected progeny difference) is feasible. Genetic correlations of heart score with growth traits and feed intake were moderate and positive (0.289-0.460). Genetic correlations between heart score and backfat and marbling score were -0.120 and -0.108, respectively. Significant genetic correlation to traits of high economic importance in existing selection indexes explain the increased rate of congestive heart failure observed over time. These results indicate potential to implement heart score observed at harvest as a phenotype under selection in genetic evaluation in order to reduce feedlot mortality due to cardiac insufficiency and improve overall cardiopulmonary health in feeder cattle.

Single Nucleotide Polymorphism Effects on Lamb Fecal Egg Count Estimated Breeding Values in Progeny-Tested Katahdin Sires.

Estimated breeding values (EBV) for fecal egg counts (FEC) at 42-90 days of age (WFEC) and 91-150 days of age (PFEC) for 84 progeny-tested Katahdin sires were used to identify associations of deregressed EBV with single-nucleotide polymorphisms (SNP) using 388,000 SNP with minor-allele frequencies ≥0.10 on an Illumina high-density ovine array. Associations between markers and FEC EBV were initially quantified by single-SNP linear regression. Effects of linkage disequilibrium (LD) were minimized by assigning SNP to 2,535 consecutive 1-Mb bins and focusing on the effect of the most significant SNP in each bin. Bonferroni correction was used to define bin-based (BB) genome- and chromosome-wide significance. Six bins on chromosome 5 achieved BB genome-wide significance for PFEC EBV, and three of those SNP achieved chromosome-wide significance after Bonferroni correction based on the 14,530 total SNP on chromosome 5. These bins were nested within 12 consecutive bins between 59 and 71 Mb on chromosome 5 that reached BB chromosome-wide significance. The largest SNP effects were at 63, 67, and 70 Mb, with LD among these SNP of r 2 ≤ 0.2. Regional heritability mapping (RHM) was then used to evaluate the ability of different genomic regions to account for additive variance in FEC EBV. Chromosome-level RHM indicated that one 500-SNP window between 65.9 and 69.9 Mb accounted for significant variation in PFEC EBV. Five additional 500-SNP windows between 59.3 and 71.6 Mb reached suggestive (p < 0.10) significance for PFEC EBV. Although previous studies rarely identified markers for parasite resistance on chromosome 5, the IL12B gene at 68.5 Mb codes for the p40 subunit of both interleukins 12 and 23. Other immunoregulatory genes are also located in this region of chromosome 5, providing opportunity for additive or associative effects.

Evaluation of partial body weight for predicting body weight and average daily gain in growing beef cattle.

Information on body weight and average daily gain (ADG) of growing animals is key not only to monitoring performance, but also for use in genetic evaluations in the pursuit of achieving sustainable genetic gain. Accurate calculation of ADG, however, requires serial measures of body weight over at least 70 days. This can be resource intensive and thus alternative approaches to predicting individual animal ADG warrant investigation. One such approach is the use of continuously collected individual animal partial body weights. The objective of the present study was to determine the utility of partial body weights in predicting both body weight and ADG; a secondary objective was to deduce the appropriate length of test to determine ADG from partial body weight records. The dataset used consisted of partial body weights, predicted body weights and recorded body weights recorded for 8,972 growing cattle from a range of different breed types in 35 contemporary groups. The relationships among partial body weight, predicted body weight and recorded body weight at the beginning and end of the performance test were determined and calculated ADG per animal from each body weight measure were also compared. On average, partial body weight explained 90.7 ± 2.0% of the variation in recorded body weight at the beginning of the postweaning gain test and 87.9 ± 2.9% of the variation in recorded body weight at its end. The GrowSafe proprietary algorithm to predict body weight from the partial body weight strengthened these coefficients of determination to 95.1 ± 0.9% and 94.9 ± 0.8%, respectively. The ADG calculated from the partial body weight or from the predicted body weight were very strongly correlated (r = 0.95); correlations between these ADG values with those calculated from the recorded body weights were weaker at 0.81 and 0.78, respectively. For some applications, ADG may be measured with sufficient accuracy with a test period of 50 days using partial body weights. The intended inference space is to individual trials which have been represented in this study by contemporary groups of growing cattle from different genotypes.

Effects of management decisions on genetic evaluation of simulated calving records using random regression.

The objective of this study was to evaluate the effects of various data structures on the genetic evaluation for the binary phenotype of reproductive success. The data were simulated based on an existing pedigree and an underlying fertility phenotype with a heritability of 0.10. A data set of complete observations was generated for all cows. This data set was then modified mimicking the culling of cows when they first failed to reproduce, cows having a missing observation at either their second or fifth opportunity to reproduce as if they had been selected as donors for embryo transfer, and censoring records following the sixth opportunity to reproduce as in a cull-for-age strategy. The data were analyzed using a third-order polynomial random regression model. The EBV of interest for each animal was the sum of the age-specific EBV over the first 10 observations (reproductive success at ages 2-11). Thus, the EBV might be interpreted as the genetic expectation of number of calves produced when a female is given 10 opportunities to calve. Culling open cows resulted in the EBV for 3-yr-old cows being reduced from 8.27 ± 0.03 when open cows were retained to 7.60 ± 0.02 when they were culled. The magnitude of this effect decreased as cows grew older when they first failed to reproduce and were subsequently culled. Cows that did not fail over the 11 yr of simulated data had an EBV of 9.43 ± 0.01 and 9.35 ± 0.01 based on analyses of the complete data and the data in which cows that failed to reproduce were culled, respectively. Cows that had a missing observation for their second record had a significantly reduced EBV, but the corresponding effect at the fifth record was negligible. The current study illustrates that culling and management decisions, and particularly those that affect the beginning of the trajectory of sustained reproductive success, can influence both the magnitude and accuracy of resulting EBV.

Partitioning variation in measurements of beef carcass traits using ultrasound.

Ultrasound technology provides cattle breeders with a quick, noninvasive, and inexpensive way to measure carcass data on live animals. Ultrasound data are used as indicator traits in cattle genetic evaluations for economically relevant carcass traits. Ultrasound cattle genetic evaluations assume homogeneous additive genetic and residual variance. Thus, the objective was to partition phenotypic variance in ultrasound carcass measurements into components for additive genetic effects, technicians, contemporary groups within technicians, and residual and to examine the homogeneity of these variances among image interpretation laboratories. Records of longissimus muscle area (LMA), percentage of intramuscular fat (IMF), and subcutaneous fat depth (SFD), measured using ultrasound, were provided by the American Angus Association (n = 65,967), American Hereford Association (n = 43,182), and American Simmental Association (n = 48,298). The data also included contemporary group, technician, imaging lab, and a three-generation pedigree for each animal. Variance components for ultrasound carcass measurements were first estimated with univariate animal models for each breed and imaging laboratory using derivative-free restricted maximum likelihood. Then, treating data from each imaging laboratory as separate traits, genetic correlations between laboratories for LMA, percentage of IMF, and subcutaneous fat were estimated with trivariate animal models. The technician explained 12-27%, 5-23%, and 4-26% of the variance for IMF, SFD, and LMA, respectively, across all three breeds. Variance due to technician was often greater than variance due to additive genetic effects but almost always less than that explained by the contemporary group. Within breeds, estimates of additive genetic variance for LMA, SFD, and IMF differed (range divided by mean) among laboratories by 4.5%, 21.5%, and 39.4 % (Angus); 31.6%, 15.0%, and 49.1% (Hereford); and 19.9%, 46.6%, and 55.3% (Simmental), respectively. Likewise, estimates of residual variance for LMA, SFD, and IMF differed among laboratories by 43.4%, 22.9%, and 43.3% (Angus); 24.9%, 15.2%, and 79.2% (Hereford); and 26.4%, 32.5%, and 46.2% (Simmental), respectively. Genetic correlations between labs across breeds ranged from 0.79 to 0.95 for IMF, 0.26 to 0.94 for SFD, and 0.78 to 0.98 for LMA. The impact of the observed heterogeneity of variance between labs on genetic evaluation requires further study.

Breeding objectives of Brangus cattle in Brazil.

Our goal was to define a breeding objective for Brangus beef cattle in Brazil. Bioeconomic models were produced and used to estimate economic values (EVs). The scenarios simulated were typical full-cycle beef production systems that are used in tropical and subtropical regions. The breeding objective contained pregnancy rate (PR), warm carcass weight (WCW), mature cow weight (MCW), number of nematode eggs per gram of faeces (EPG) and tick count (TICK). Two models were used in series to estimate the EV. A deterministic model was used to simulate effects of PR, WCW and MCW on profitability with a constant parasite load. Subsequently, stochastic models were used to estimate economic values for TICK and EPG as consequences of their environmental effects on weight gains, mortality and health costs. The EV of PR, WCW, MCW, EPG and TICK, was US$1.59, US$2.11, -US$0.24, -US$5.35 and -US$20.88, respectively. Results indicate positive emphasis should be placed on PR (12.49%) and WCW (65.07%) with negative emphasis on MCW (13.92%), EPG (2.77%) and TICK (5.75%). In comparison with the indexes usually used, these results suggest a reformulation in the selection indexes of the beef production system in tropical and subtropical regions in order to obtain greater profitability.

Genetic variability and relationships in nine South African cattle breeds using microsatellite markers.

Genetic variability within and between breeds allows adaptation to a changing environment and consequently prepares producers for the future. Eleven bovine-specific microsatellite markers were used to genotype animals from each of nine South African cattle breeds: Afrikaner (N = 550), Angus (N = 550), Bonsmara (N = 550), Boran (N = 321), Brahman (N = 550), Drakensberger (N = 550), Nguni (N = 550), Simmental (N = 550), and Tuli (N = 311). These breeds were drawn from Bos taurus africanus, Bos taurus, and Bos indicus. Genetic variability estimates included unbiased heterozygosity, effective number of alleles, and inbreeding. Ranges of these parameters were 0.569-0.741, 8.818-11.455, and - 0.001-0.050, respectively. Breed private allele and breed pairwise comparison was also used to characterize the breeds. The analysis of population structure with K = 2 revealed clusters comprised of Sanga-indicine and taurine, while K = 3 included separate clusters of Sanga, indicine, and taurine, and with K = 9 showed the breeds arising from unique progenitor populations. This study broke new ground in molecular cattle genetic diversity by genotyping a large sample size per breed and using a larger number of breeds compared with similar studies that have been conducted in the recent past which have either used a smaller number of breeds or smaller sample sizes but with a larger number of marker loci. Thus, opportunities that arise to explore genetic diversity and relationships in both the livestock and wildlife industries in Southern Africa may capitalize on microsatellite marker databases which remain cost-effective and accessible due to their extensive use for parentage verification.

Management of lethal recessive alleles in beef cattle through the use of mate selection software.

BACKGROUND: Recessive loss-of-function (LOF) alleles at genes which are essential for life, can result in early embryonic mortality. Cattle producers can use the LOF carrier status of individual animals to make selection and mate allocation decisions. METHODS: Two beef cattle breeding strategies i.e. (1) selection against LOF carriers as parents and (2) simultaneous selection and mate allocation to avoid the occurrence of homozygous offspring in three scenarios, which differed in number and frequency of LOF alleles were evaluated using the mate selection program, MateSel. Scenarios included (a) seven loci with high-frequency LOF alleles, (b) 76 loci with low-frequency LOF alleles, and (c) 50 loci with random high- and low-frequency LOF alleles. In addition, any savings resulting from the information obtained by varying the percentage (0-100%) of the herd genotyped, together with segregation analysis to cover ungenotyped animals, were calculated to determine (1) which percentage optimized net profit for a fixed cost of genotyping ($30/test), and (2) the breakeven cost for genotyping. RESULTS: With full knowledge of the LOF alleles carried by selection candidates, the most profitable breeding strategy was always simultaneous selection and mate allocation to avoid homozygous affected offspring (aa) as compared to indiscriminate selection against carrier parents (Aa). The breakeven value of genotyping depended on the number of loci modeled, the LOF allele frequencies, and the mating/selection strategies used. Genotyping was most valuable when it was used to avoid otherwise high levels of embryonic mortalities. As the number of essential loci with LOF alleles increased, especially when some were present at relatively high minor allele frequencies, embryonic losses increased, and profit was maximized by genotyping 10 to 20% of a herd and using that information to reduce these losses. CONCLUSIONS: Genotyping 100% of the herd was never the most profitable outcome in any scenario; however, genotyping some proportion of the herd, together with segregation analysis to cover ungenotyped animals, maximized overall profit in scenarios with large numbers of loci with LOF alleles. As more LOF alleles are identified, such a mate selection software will likely be required to optimally select and allocate matings to balance the rate of genetic gain, embryonic losses, and inbreeding.

Evaluation of a genomic-enhanced sorting system for feeder cattle1.

This study evaluated the use of molecular breeding values (MBVs) for carcass traits to sort steers into quality grid and lean meat yield (LMY) groups. A discovery set of 2,609 animals with genotypes and carcass phenotypes was used to predict MBVs for LMY and marbling score (MBS) for 299 Angus, 181 Charolais, and 638 Kinsella Composite steers using genomic best linear unbiased prediction. Steers were sorted in silico into four MBV groups namely Quality (with MBVs greater than the mean for LMY and MBS), Lean (with MBVs greater than the mean for LMY but less than or equal to the mean for MBS), Marbling (with MBVs greater than the mean for MBS but less than or equal to the mean for LMY), and Other (with MBVs lower than the mean for LMY and MBS). Carcass phenotypes on the steers were then collected at slaughter and evaluated for consistency with the assigned MBV groups using descriptive statistics and least square analysis. Accuracy of MBV predictions was assessed by Pearson's correlation between predicted MBV and adjusted phenotype divided by the square root of trait heritability. Genomic breed compositions were predicted for all steers to correct for possible population stratification and breed effects in the test model. The number of steers that met the expected carcass outcome was counted to produce actual percentages for each MBV group. Results showed that on average, Quality and Marbling groups had greater back-fat and more marbling across the three populations while Lean group had leaner carcasses. Carcass weights were similar across MBV groups. Within MBV groups, decreases in variability were observed for most traits suggesting improvement in carcass uniformity. Greater than 70% of the steers in Quality, Lean, and Marbling groups met the Quality Grid and Y1-LMY target for Angus and Charolais but not for Kinsella composite. The accuracy of MBV prediction ranged from 0.43 to 0.59 indicating that up to 35% of the observed carcass trait variability can be predicted, which suggests utility of MBV as a marker-assisted management tool to sort feeder cattle into uniform carcass endpoint groups under similar environmental and management conditions. Further investigation is warranted to evaluate the performance of feeder cattle sorted based on MBV and managed for different carcass endpoints as well as the cost-benefit implications for feedlot operations.

Crossbreeding effects on growth and efficiency in beef cow-calf systems: evaluation of Angus, Caracu, Hereford and Nelore breed direct, maternal and heterosis effects.

The objective of this study was to determine breed additive and heterosis effects on growth curves, total milk yield (TMY), calf weaning weight (WW), predicted energy intake (EI), and cow efficiency (CE) of purebred and crossbred beef cows raised in Southern Brazil. The data were from 175 purebred and crossbred cows representing eight genetic groups: Angus (A), Hereford (H), Nelore (N), A × H (AH), H × A (HA), A × N (AN), N × A (NA), and Caracu (C) × A (CA). Growth of the cows was modeled using the nonlinear Brody function and machine milking was used to assess TMY. WW was linearly adjusted to 210 d. EI was predicted with an equation in which the independent variables were estimates of parameters of the Brody function and TMY. The ratio of WW to EI estimated CE. Taurine-indicine heterosis effects were significant for all traits, and greater than those for taurine breed crosses. In general, crossbred cows were heavier at maturity, matured earlier, produced more milk, weaned heavier calves, and were predicted to consume more energy. Thus, they were more efficient than purebred cows, despite their greater predicted feed intake. Among the purebreds, A cows matured most rapidly, weighed the least at maturity, produced the most milk, weaned the heaviest calves, were predicted to consume the least energy; and were therefore most efficient among the breeds that were evaluated. These results are useful as inputs to bioeconomic models that can be used to predict productive and economic outcomes from crossbreeding and to facilitate recommendations for beef producers of southern Brazil and other similar subtropical climatic regions.

Genome-wide association scan for heterotic quantitative trait loci in multi-breed and crossbred beef cattle.

BACKGROUND: Heterosis has been suggested to be caused by dominance effects. We performed a joint genome-wide association analysis (GWAS) using data from multi-breed and crossbred beef cattle to identify single nucleotide polymorphisms (SNPs) with significant dominance effects associated with variation in growth and carcass traits and to understand the mode of action of these associations. METHODS: Illumina BovineSNP50 genotypes and phenotypes for 11 growth and carcass traits were available for 6796 multi-breed and crossbred beef cattle. After performing quality control, 42,610 SNPs and 6794 animals were used for further analyses. A single-SNP GWAS for the joint association of additive and dominance effects was conducted in purebred, crossbred, and combined datasets using the ASReml software. Genomic breed composition predicted from admixture analyses was included in the mixed effect model to account for possible population stratification and breed effects. A threshold of 10% genome-wide false discovery rate was applied to declare associations as significant. The significant SNPs with dominance association were mapped to their corresponding genes at 100 kb. RESULTS: Seven SNPs with significant dominance associations were detected for birth weight, weaning weight, pre-weaning daily gain, yearling weight and marbling score across the three datasets at a false discovery rate of 10%. These SNPs were located on bovine chromosomes 1, 3, 4, 6 and 21 and mapped to six putative candidate genes: U6atac, AGBL4, bta-mir-2888-1, REPIN1, ICA1 and NXPH1. These genes have interesting biological functions related to the regulation of gene expression, glucose and lipid metabolism and body fat mass. For most of the identified loci, we observed over-dominance association with the studied traits, such that the heterozygous individuals at any of these loci had greater genotypic values for the trait than either of the homozygous individuals. CONCLUSIONS: Our results revealed very few regions with significant dominance genetic effects across all the traits studied in the three datasets used. Regarding the SNPs that were detected with dominance associations, further investigation is needed to determine their relevance in crossbreeding programs assuming that dominance effects are the main cause of (or contribute usefully to) heterosis.

Comparison of economic returns among genetic evaluation strategies in a 2-tiered Charolais-sired beef cattle production system.

The objective of this study was to estimate economic returns and costs associated with 4 scenarios of genetic evaluation that combine genotypes, phenotypes, and pedigree information from a vertically integrated purebred (PB) and commercial (CM) beef cattle system. Inference was to a genetic evaluation for a production system producing Charolais terminal sires for 10,000 CM cows. The first genetic evaluation scenario, denoted PB_A, modeled a genetic evaluation in which pedigree information and phenotypes are available for PB seedstock animals. Scenario PB_H contained the same information as PB_A with the addition of 25K density (GeneSeek Genomic Profiler LD) single nucleotide polymorphism (SNP) genotypes from PB animals. Scenario PBCM_A contained pedigree records and phenotypes from PB and CM cattle. Scenario PBCM_H contained phenotypes, pedigree, and genotypes from the PB and CM animals. Estimates of prediction error variance, (co)variance, and selection index parameters were used to estimate accuracy of selection candidates (rTI) and genetic gain resulting from selection on an economic index in US dollars (ΔG). Annual costs and incomes were used to determine the 30-yr cumulative net present value (CNPV) per CM calf resulting from selection in these genetic evaluation scenarios. Adding genotypes and CM production phenotypes to genetic evaluation increased the rTI of selection candidates and ΔG across all 4 scenarios. Scenario PBCM_H produced the highest annual ΔG in the PB herd at US$11.91 per head. Including CM phenotypes and parentage testing in the genetic evaluation increased the time to breakeven from 12 yr in PB_A to 19 years in PBCM_A after accounting for the cost of that information. Adding CM phenotypes and genotypes increased the breakeven time from 12 yr in PB_H to 18 yr in PBCM_H. Scenario PB_H produced the highest 30-yr CNPV per slaughtered CM calf at US$371.16. These results using field data indicate that economically relevant rTI and ΔG can be realized by adding 25K SNP genotypes and CM phenotypes to genetic evaluation, but the additional cost of that data significantly delays the economic return to the enterprise.

Direct and maternal breed additive and heterosis effects on growth traits of beef cattle raised in southern Brazil.

The objective of this study was to compare growth from birth to slaughter of different breed groups that were raised in Rio Grande do Sul, Brazil and estimate the consequent breed additive and heterosis effects. Caracu (C), Hereford (H), and Nelore (N) sires were mated with Angus (A) dams, and A sires were mated with H and N dams to produce a first generation of crossbred progeny that was contemporary with purebred A, H, and N calves. Heifers from this first generation (G1) were mated with Brangus (BN) and Braford (BO) sires to produce a second generation (G2) of progeny. Data were analyzed to estimate breed group means, individual and maternal breed additive effects, and heterosis effects on birth weight, weaning weight, preweaning average daily gain, yearling weight, postweaning average daily gain, fattening phase initial weight (around 19 mo), final weight (around 24 mo), average daily gain in the fattening phase, and age at slaughter. In general, crossbred calves outperformed purebred calves. Angus-N and CA crossbred cows weaned heavier calves. Individual taurine-indicine heterosis (Z) significantly increased weaning weight. The AN, NA, and CA steers were heaviest at yearling, whereas NA, CA, AN, and HA had the greatest final weights. However, AH steers were 1 mo older at slaughter than NA contemporaries. Taurine breed effects on postweaning traits and final weight were greater than for N. Maternal breed effects on birth weight and average daily gain in the fattening phase were greater for A and H than for N. In conclusion, heterosis effects were sufficiently large for use of N to be recommended as a component of such systems, despite their relatively low-breed additive effects compared with taurine breeds. Moreover, germplasm from the tropically adapted Bos taurus C may be particularly useful when increased milk production is desired. With the breed and heterosis effects derived in the present study, it is possible to predict the performance and infer which breed and breed crosses will perform better in crossbreeding systems designed for the subtropical conditions of southern Brazil and similar regions.

Reducing the period of data collection for intake and gain to improve response to selection for feed efficiency in beef cattle.

Shortening the period of recording individual feed intake may improve selection response for feed efficiency by increasing the number of cattle that can be recorded given facilities of fixed capacity. Individual DMI and ADG records of 3,462 steers and 2,869 heifers over the entire intake recording period (range 62 to 154 d; mean 83 d; DMI83 and ADG83, respectively), DMI and ADG for the first 42 d of the recording period (DMI42 and ADG42, respectively), and postweaning ADG based on the difference between weaning and yearling weights (PADG) were analyzed. Genetic correlations among DMI42 and DMI83, ADG42 and ADG83, ADG42 and PADG, and ADG83 and PADG were 0.995, 0.962, 0.852, and 0.822, respectively. Four objective functions [feed:gain ratio in steers (FGS) and heifers (FGH); residual gain (RG); and residual feed intake (RFI)] based on DMI83 and ADG83 were considered. Indices using DMI42 and ADG42 (I42); DMI42 and PADG (IPW); and DMI42, ADG42, and PADG (IALL) were developed. Accuracy of the 5 EBV, 4 objectives, and 12 objective × index combinations were computed for all 12,033 animals in the pedigree. Accuracies of indices (IA) were summarized for animals with accuracies for objectives (OA) of 0.25, 0.5, 0.75, and 1. For the RG objective and animals with OA of 0.75, indices I42, IPW, and IALL had IA of 0.63, 0.55, and 0.67, respectively. Differences in IA increased with increased emphasis on ADG83 in the objective. Differences in IA between I42 and IPW usually increased with OA. Relative efficiency (RE) of selection on 42-d tests compared with 83 d was computed based on differences in IA and selection intensities of 5%, 25%, 50%, and 75% under the 83-d scenario, assuming 65% more animals could be tested for 42 d. For 25% selected for the RG objective, and animals with OA of 0.75, indices I42, IPW, and IALL had RE of 1.02, 0.90, and 1.10, respectively. As % selected, OA, and emphasis on DMI increased, RE increased. Relative efficiency varied considerably according to assumptions. One-half of the scenarios considered had RE > 1.15 with a maximum of 2.02 and 77% RE > 1.0. A shorter period of recording DMI can improve selection response for feed efficiency. Selection for the efficiency objectives would not affect PADG. It will be most effective if ADG over the period coinciding with intake recording and ADG over a much longer period of time are simultaneously included in a multiple-trait genetic evaluation with DMI and used in a selection index for efficiency.

Modeling heterotic effects in beef cattle using genome-wide SNP-marker genotypes.

An objective of commercial beef cattle crossbreeding programs is to simultaneously optimize use of additive (breed differences) and non-additive (heterosis) effects. A total of 6,794 multibreed and crossbred beef cattle with phenotype and Illumina BovineSNP50 genotype data were used to predict genomic heterosis for growth and carcass traits by applying two methods assumed to be linearly proportional to heterosis. The methods were as follows: 1) retained heterozygosity predicted from genomic breed fractions (HET1) and 2) deviation of adjusted crossbred phenotype from midparent value (HET2). Comparison of methods was based on prediction accuracy from cross-validation. Here, a mutually exclusive random sampling of all crossbred animals (n = 5,327) was performed to form five groups replicated five times with approximately 1,065 animals per group. In each run within a replicate, one group was assigned as a validation set, while the remaining four groups were combined to form the reference set. The phenotype of the animals in the validation set was assumed to be unknown; thus, it resulted in every animal having heterosis values that were predicted without using its own phenotype, allowing their adjusted phenotype to be used for validation. The same approach was used to test the impact of predicted heterosis on accuracy of genomic breeding values (GBV). The results showed positive heterotic effects for growth traits but not for carcass traits that reflect the importance of heterosis for growth traits in beef cattle. Heterosis predicted by HET1 method resulted in less variable estimates that were mostly within the range of estimates generated by HET2. Prediction accuracy was greater for HET2 (0.37-0.98) than HET1 (0.34-0.43). Proper consideration of heterosis in genomic evaluation models has debatable effects on accuracy of EBV predictions. However, opportunity exists for predicting heterosis, improving accuracy of genomic selection, and consequently optimizing crossbreeding programs in beef cattle.

Putative Loci Causing Early Embryonic Mortality in Duroc Swine.

Lethal recessive alleles that act prenatally may be detected from the absence of homozygous individuals in a population. However, these alleles may be maintained at relatively low frequencies in populations as heterozygotes. In pigs, they may reduce litter size. This study aimed to detect putative lethal variants in the Duroc breed. Phenotypes for the numbers of piglets born (TNB), born live (BA), alive at 24 h (L24), stillborn (SB), and born as mummified fetuses (MM) were available from 5340 recorded litters which resulted from mating of 192 genotyped boars with sows of unknown genotype (dataset 1). An additional 50 litters were produced from parents that were both genotyped (dataset 2). Imputed genotypes of 650K SNPs for 1359 Duroc boars were used in this study. One significant SNP (Bonferroni corrected P = 5.5E-06) was located on SSC14 with 45.3 homozygous individuals expected but none observed. This SNP was significant for mummified fetuses. One hundred fifty two haplotypes were also found to potentially harbor recessive lethal mutations. Twenty-one haplotypes had a significant harmful effect on at least one trait. Two regions, located on SSC8 (144.9-145.5 Mb) and SSC9 (19-19.4 Mb) had significant effects on fertility traits in both datasets. Additionally, regions on SSC1 (82.0-82.8 Mb), SSC3 (73.3-73.7 and 87.1-87.5 Mb) and SSC12 (35.8-36.2 and 50.0-50.5 Mb) had significant deleterious effects on TNB or BA or L24 in dataset 1. Finally, a region on SSC17 (28.7-29.3 Mb) had significant effects on TNB, BA and L24 in dataset 2. A few candidate genes identified within these regions were described as being involved in spermatogenesis and male fertility (TEX14, SEP4, and HSF5), or displayed recessive lethality (CYP26B1, SCD5, and PCF11) in other species. The putative loci detected in this study provide valuable information to potentially increase Duroc litter size by avoiding carrier-by-carrier matings in breeding programs. Further study of the identified candidate genes responsible for such lethal effects may lead to new insights into functions regulating pig fertility.

Decision-making tools: stochastic simulation model accounting for the impacts of biological variation on success of bovine embryo transfer programs.

The objective of the project was to create an economic risk analysis tool for user-defined embryo transfer (ET) programs as an aid in decision-making. Distributions defining the biological uncertainty for many reproductive outcomes are estimated through extensive literature review and limited industry sources. Applying the Latin hypercube variation of Monte Carlo simulation, a sample value from the descriptive distribution associated with each stochastic variable is included in each iteration of the simulation. Through large numbers of iterations with dynamic combinations of variable values, the process culminates in a distribution of possible values for the net present value, annuity equivalent net present value, and return on investment associated with the modeled embryo production scenario. Two options for embryo production, multiple ovulation embryo transfer (MOET) and in vitro embryo production (IVP) from aspirated oocytes, are modeled. Within both MOET and IVP, the use of unsorted or sex-sorted semen is considered, as well as the exception or inclusion of follicular synchronization and/or stimulation before ovum pick-up in IVP procedures. Pretransfer embryo selection through embryo biopsy can also be accounted for when considering in vivo derived embryos. Ample opportunity exists for the commercial application of in-depth, alternative ET scenario assessment afforded through stochastic simulation methodology that the ET industry has not yet fully exploited.

Genetic diversity of Afrikaner cattle in southern Africa.

The Afrikaner is an indigenous South African breed of "Sanga" type beef cattle along with breeds such as the Drakensberger and Nguni. Six composite breeds have been developed from crosses with the Afrikaner. Additionally, Afrikaner has been the base from which exotic breeds were established in South Africa through backcrossing. The study examined genetic diversity of Afrikaner cattle by genotyping 1257 animals from 27 herds in different geographic areas of South Africa and Namibia using 11 microsatellite markers. Multiple-locus assignment, performed using the Bayesian clustering algorithm of STRUCTURE, revealed three underlying genotypic groups. These groups were not geographically localized. Across herds and markers, the proportion of unbiased heterozygosity ranged from 0.49 to 0.72 averaging 0.57; mean number of alleles per locus ranged from 3.18 to 7.09, averaging 4.81; and allelic richness ranged from 2.35 to 3.38, averaging 2.67. It is concluded that a low inbreeding level of 2.7% and a moderate to high degree of variation still persists within the Afrikaner cattle breed, despite the recent decline in numbers of animals.