Validation of SNP associations with bovine ovulation and twinning rate.

Previous work identified SNP associations with twinning rate in the US Holstein population and developed a model for genomic prediction. The current study was conducted to assess the association of these SNPs with twinning rate and ovulation rate in a genetically diverse, outbred population selected for twinning and ovulation rate. A total of 18 SNPs that were components of a prediction equation for twinning rate in Holstein cattle were genotyped on 731 animals from the USDA Meat Animal Research Center production efficiency or twinning population. These 731 individuals were sires and dams well represented in the pedigrees of animals from the twinner population, and their genotypes were used in predicting genotypes for animals in the larger population (n = 16 035). Twinning rate and ovulation rate were analyzed in a two-trait repeated records analysis with marker associations analyzed individually as fixed effects. Criteria for marker validation were effect estimate with a sign consistent with previous estimates and significance at a nominal P < 0.01. Of the 14 SNPs passing quality control assessments, only one was validated. A SNP in the 5' flanking region of the IGF1 gene, discovered previously in a positional candidate gene analysis, was significantly associated with twinning rate in the USDA twinning population (P < 0.0002). This SNP may have utility in genomic prediction of twinning rate beyond the Holstein population.

Linkage disequilibrium among commonly genotyped SNP variants detected from bull sequence.

Genomic prediction utilizing causal variants could increase selection accuracy above that achieved with SNPs genotyped by currently available arrays used for genomic selection. A number of variants detected from sequencing influential sires are likely to be causal, but noticeable improvements in prediction accuracy using imputed sequence variant genotypes have not been reported. Improvement in accuracy of predicted breeding values may be limited by the accuracy of imputed sequence variants. Using genotypes of SNPs on a high-density array and non-synonymous SNPs detected in sequence from influential sires of a multibreed population, results of this examination suggest that linkage disequilibrium between non-synonymous and array SNPs may be insufficient for accurate imputation from the array to sequence. In contrast to 75% of array SNPs being strongly correlated to another SNP on the array, less than 25% of the non-synonymous SNPs were strongly correlated to an array SNP. When correlations between non-synonymous and array SNPs were strong, distances between the SNPs were greater than separation that might be expected based on linkage disequilibrium decay. Consistently near-perfect whole-genome linkage disequilibrium between the full array and each non-synonymous SNP within the sequenced bulls suggests that whole-genome approaches to infer sequence variants might be more accurate than imputation based on local haplotypes. Opportunity for strong linkage disequilibrium between sequence and array SNPs may be limited by discrepancies in allele frequency distributions, so investigating alternate genotyping approaches and panels providing greater chances of frequency-matched SNPs strongly correlated to sequence variants is also warranted. Genotypes used for this study are available from https://www.animalgenome.org/repository/pub/;USDA2017.0519/.

Genetic variance and covariance and breed differences for feed intake and average daily gain to improve feed efficiency in growing cattle.

Feed costs are a major economic expense in finishing and developing cattle; however, collection of feed intake data is costly. Examining relationships among measures of growth and intake, including breed differences, could facilitate selection for efficient cattle. Objectives of this study were to estimate genetic parameters for growth and intake traits and compare indices for feed efficiency to accelerate selection response. On-test ADFI and on-test ADG (TESTADG) and postweaning ADG (PWADG) records for 5,606 finishing steers and growing heifers were collected at the U.S. Meat Animal Research Center in Clay Center, NE. On-test ADFI and ADG data were recorded over testing periods that ranged from 62 to 148 d. Individual quadratic regressions were fitted for BW on time, and TESTADG was predicted from the resulting equations. We included PWADG in the model to improve estimates of growth and intake parameters; PWADG was derived by dividing gain from weaning weight to yearling weight by the number of days between the weights. Genetic parameters were estimated using multiple-trait REML animal models with TESTADG, ADFI, and PWADG for both sexes as dependent variables. Fixed contemporary groups were cohorts of calves simultaneously tested, and covariates included age on test, age of dam, direct and maternal heterosis, and breed composition. Genetic correlations (SE) between steer TESTADG and ADFI, PWADG and ADFI, and TESTADG and PWADG were 0.33 (0.10), 0.59 (0.06), and 0.50 (0.09), respectively, and corresponding estimates for heifers were 0.66 (0.073), 0.77 (0.05), and 0.88 (0.05), respectively. Indices combining EBV for ADFI with EBV for ADG were developed and evaluated. Greater improvement in feed efficiency can be expected using an unrestricted index versus a restricted index. Heterosis significantly affected each trait contributing to greater ADFI and TESTADG. Breed additive effects were estimated for ADFI, TESTADG, and the efficiency indices.

Breed effects and genetic parameter estimates for calving difficulty and birth weight in a multibreed population.

Birth weight (BWT) and calving difficulty (CD) were recorded on 4,579 first-parity females from the Germplasm Evaluation Program at the U.S. Meat Animal Research Center (USMARC). Both traits were analyzed using a bivariate animal model with direct and maternal effects. Calving difficulty was transformed from the USMARC scores to corresponding -scores from the standard normal distribution based on the incidence rate of the USMARC scores. Breed fraction covariates were included to estimate breed differences. Heritability estimates (SE) for BWT direct, CD direct, BWT maternal, and CD maternal were 0.34 (0.10), 0.29 (0.10), 0.15 (0.08), and 0.13 (0.08), respectively. Calving difficulty direct breed effects deviated from Angus ranged from -0.13 to 0.77 and maternal breed effects deviated from Angus ranged from -0.27 to 0.36. Hereford-, Angus-, Gelbvieh-, and Brangus-sired calves would be the least likely to require assistance at birth, whereas Chiangus-, Charolais-, and Limousin-sired calves would be the most likely to require assistance at birth. Maternal breed effects for CD were least for Simmental and Charolais and greatest for Red Angus and Chiangus. Results showed that the diverse biological types of cattle have different effects on both BWT and CD. Furthermore, results provide a mechanism whereby beef cattle producers can compare EBV for CD direct and maternal arising from disjoined and breed-specific genetic evaluations.

A survey of polymorphisms detected from sequences of popular beef breeds.

The genome sequence was obtained from 270 sires used in the Germplasm Evaluation (GPE) project. These bulls included 154 purebred AI sires from GPE Cycle VII breeds (Hereford, Angus, Simmental, Limousin, Charolais, Gelbvieh, and Red Angus), 83 F crosses of those breeds, and 33 AI sires from 8 other breeds. The exome capture sequence targeting coding regions of the genome was obtained from 176 of these bulls. Sequence reads were mapped to the UMD 3.1 bovine genome assembly; a mean of 2.5-fold (x) coverage per bull was obtained from the genomic sequence, and the targeted exons were covered at a mean of 20.0x. Over 28.8 million biallelic sequence variants were detected where each allele was present in at least 3 different bulls. These included 22.0 million previously reported variants and 94.1% of the 774,660 autosomal and BTA X SNP on the BovineHD BeadChip assay (HD). More than 92% of the variants detected in targeted exons were also detected from the low-coverage genome sequence. Less than 1% of the variants detected from the combined genome and exome sequence occurred in annotated protein-coding sequences and 5' and 3' untranslated regions (UTR) surrounding the 19,994 annotated protein coding regions. Variation was detected in the coding sequence or UTR of 96.8% of the genes: loss-of-function variants were predicted for 3,298 genes, 14,973 contained nonsynonymous variants, 11,276 had variation in UTR, and 17,721 genes contained synonymous variants. Minor allele frequencies (MAF) were <0.05 for 47.8% of the coding sequence and UTR variants, and MAF distributions were skewed toward low MAF. In contrast, 11.1% of the HD SNP detected in these bulls had MAF < 0.05, and the distribution was skewed toward higher MAF. Genes involved in immune system processes and immune response were overrepresented among those genes containing high MAF loss-of-function and nonsynonymous polymorphisms. Detected variants were submitted to the National Center for Biotechnology Information genetic variation database (dbSNP) under the handle MARC, batch GPE_Bull_GenEx.

Genetic effects on birth weight in reciprocal Brahman-Simmental crossbred calves.

Brahman-cross calves exhibit unusual inheritance of birth weight: Brahman-sired crossbreds out of females are heavier with greater difference between sexes than calves of the reciprocal cross. The objectives of this work were to confirm that unusual inheritance and to investigate non-Mendelian genetic effects that may influence differences in Brahman × Simmental crossbred calves. Crossbred calves were produced by embryo transfer ( = 2,862) and natural service or artificial insemination ( = 2,125) from 1983 to 1991 by a private seedstock producer. Brahman-sired F embryos out of Simmental donors weighed 9.4 ± 1.1 ( < 0.001) kg more at birth than Simmental-sired F embryos out of Brahman donor cows when transferred to comparable recipients. This reciprocal difference was accompanied by sexual dimorphism: within Brahman-sired F calves, males were 5.0 ± 1.4 kg heavier than females, whereas within Simmental-sired F calves, females were 0.7 ± 0.5 kg heavier than males. Covariates were constructed from the pedigree to represent genetic effects: proportion Brahman in calves and dams (direct and maternal breed effects), direct and maternal breed heterozygosity, probability of Brahman mitochondrial origin, probability of Brahman Y chromosome, probability of Brahman X chromosome, genomic imprinting (the difference between the probabilities of Brahman in the genetic dam and in the sire), nonrandom X inactivation by breed of origin (the probability of breed heterozygosity of the X chromosomes of a female), and nonrandom X inactivation by parent of origin (the difference between probabilities of a female inheriting a paternal or maternal Brahman X chromosome). The maternal breed heterozygosity, genomic imprinting, probability of Brahman X chromosome, and genomic imprinting × sex effect covariates from the full model were significant with regression coefficients of 1.1 ± 0.5 ( < 0.05), ‒8.3 ± 2.3 ( < 0.01), ‒3.5 ± 1.3 ( < 0.01), and ‒5.3 ± 2.0 ( < 0.01), respectively. Results suggest that sex-specific genomic imprinting may be contributing to the inheritance of birth weight in crossbred calves, similar to patterns of mouse litter and placental weight in interspecific crosses.

Estimation of breed-specific heterosis effects for birth, weaning, and yearling weight in cattle.

Heterosis, assumed proportional to expected breed heterozygosity, was calculated for 6834 individuals with birth, weaning and yearling weight records from Cycle VII and advanced generations of the U.S. Meat Animal Research Center (USMARC) Germplasm Evaluation (GPE) project. Breeds represented in these data included: Angus, Hereford, Red Angus, Charolais, Gelbvieh, Simmental, Limousin and Composite MARC III. Heterosis was further estimated by proportions of British × British (B × B), British × Continental (B × C) and Continental × Continental (C × C) crosses and by breed-specific combinations. Model 1 fitted fixed covariates for heterosis within biological types while Model 2 fitted random breed-specific combinations nested within the fixed biological type covariates. Direct heritability estimates (SE) for birth, weaning ,and yearling weight for Model 1 were 0.42 (0.04), 0.22 (0.03), and 0.39 (0.05), respectively. The direct heritability estimates (SE) of birth, weaning, and yearling weight for Model 2 were the same as Model 1, except yearling weight heritability was 0.38 (0.05). The B × B, B × C, and C × C heterosis estimates for birth weight were 0.47 (0.37), 0.75 (0.32), and 0.73 (0.54) kg, respectively. The B × B, B × C, and C × C heterosis estimates for weaning weight were 6.43 (1.80), 8.65 (1.54), and 5.86 (2.57) kg, respectively. Yearling weight estimates for B × B, B × C, and C × C heterosis were 17.59(3.06), 13.88 (2.63), and 9.12 (4.34) kg, respectively. Differences did exist among estimates of breed-specific heterosis for weaning and yearling weight, although the variance component associated with breed-specific heterosis was not significant. These results illustrate that there are differences in breed-specific heterosis and exploiting these differences can lead to varying levels of heterosis among mating plans.

µ-Calpain, calpastatin, and growth hormone receptor genetic effects on preweaning performance, carcass quality traits, and residual variance of tenderness in Angus cattle selected to increase minor haplotype and allele frequencies.

Genetic marker effects and interactions are estimated with poor precision when minor marker allele frequencies are low. An Angus population was subjected to marker assisted selection for multiple years to increase divergent haplotype and minor marker allele frequencies to 1) estimate effect size and mode of inheritance for previously reported SNP on targeted beef carcass quality traits; 2) estimate effects of previously reported SNP on nontarget performance traits; and 3) evaluate tenderness SNP specific residual variance models compared to a single residual variance model for tenderness. Divergent haplotypes within µ-calpain (CAPN1), and SNP within calpastatin (CAST) and growth hormone receptor (GHR) were successfully selected to increase their frequencies. Traits evaluated were birth BW, weaning BW, final BW, fat thickness, LM area, USDA marbling score, yield grade, slice shear force (SSF), and visible and near infrared predicted slice shear force. Both CAPN1 and CAST exhibited additive (P < 0.001) modes of inheritance for SSF and neither exhibited dominance (P ≥ 0.19). Furthermore, the interaction between CAPN1 and CAST for SSF was not significant (P = 0.55). Estimated additive effects of CAPN1 (1.049 kg) and CAST (1.257 kg) on SSF were large in this study. Animals homozygous for tender alleles at both CAPN1 and CAST would have 4.61 kg lower SSF (38.6% of the mean) than animals homozygous tough for both markers. There was also an effect of CAST on yield grade (P < 0.02). The tender CAST allele was associated with more red meat yield and less trimmable fat. There were no significant effects (P ≥ 0.23) for GHR on any of the traits evaluated in this study. Furthermore, CAST specific residual variance models were found to fit significantly better (P < 0.001) than single residual variance models for SSF, with the tougher genotypes having larger residual variance. Thus, the risk of a tough steak from the undesired CAST genotype is increased through both an increase in mean and an increase in variation. This work confirms the importance of CAPN1 and CAST for tenderness in beef, provides a new effect of CAST on beef tenderness, and questions the utility of GHR as a selection marker for beef quality.

The change in differing leukocyte populations during vaccination to bovine respiratory disease and their correlations with lung scores, health records, and average daily gain.

Bovine respiratory disease (BRD) is the most economically important disease in U.S. feedlots. Infection can result in morbidity, mortality, and reduced average daily gain. Cheap and reliable genetic methods of prediction and protection from BRD would be highly advantageous to the industry. The immune response may correlate with BRD incidence. Cattle (n = 2,182) were vaccinated against common viral and bacterial pathogens of BRD. Two blood samples were collected, one during booster vaccination and one 21d later, enabling 3 phenotypes for each trait [prebooster (pre), postbooster (post), and delta (post minus pre)]. From the blood samples innate and adaptive responses [counts of white blood cells (WBC), neutrophils, lymphocytes, monocytes, eosinophils, and basophils] were measured. In addition, feedlot ADG and binary traits [health records (HR; 0 = healthy, 1 = ill) and lung scores (LS; collected at harvest; 0 = no lesions, 1 = lesions)] were also recorded. Traits ADG, HR, and LS have all been significantly correlated with infection to BRD. In this investigation we aimed to find correlations between the immune response and ADG, HR, and LS to find an easily measurable trait that would be a good predictor of BRD resistance after vaccination. The results showed an average positive delta for the innate immune response (eosinophils, basophils, neutrophils), whereas the adaptive immune response had an average negative delta (lymphocytes). Overall, we discovered that the immune responses had moderately high heritabilities (h(2); lowest: delta monocytes, 0.21 ± 0.05; greatest: pre lymphocytes: 0.5 ± 0.05), with lymphocytes having the greatest h(2) throughout the study (h(2) ≥ 0.41). All genetic correlations were calculated using bivariate REML models. Although LS did not significantly correlate with any of the immune phenotypes, both ADG (post lymphocytes, -0.24 ± 0.12) and HR (pre eosinophils, -0.67 ± 0.29; delta WBC, -0.5 ± 0.24, and delta lymphocytes, -0.67 ± 0.21) did. All the significant genetic correlations with HR were negative; resistance to BRD appears to be a function of greater delta lymphocytes and WBC. The increase in eosinophils may potentially link its role in decreasing lymphocytes. These results may enable producers to predict if revaccination, quarantine, and breeding of animals is required to reduce the incidence of BRD postvaccination. In addition, immunological phenotypes maybe used to aid genomic selection indices to select animals with greater rates of protection after BRD vaccination.

A genomewide association study identified CYP2J2 as a gene controlling serum vitamin D status in beef cattle.

Vitamin D is an important modulator of calcium homeostasis and has several effects on the immune system. The objective of the study was to estimate its heritability and to identify genomic regions associated with concentration of circulating 25-hydroxyvitamin D (25OHD) in beef cattle. Status of vitamin D was measured in crossbred animals from Cycle VII of the United States Meat Animal Research Center (USMARC) Germplasm Evaluation Project. Progeny were born from March through May in 2008 and in 2010. Heritability was estimated and a genomewide association study was conducted on the concentration of 25OHD measured in 1,432 animals at preconditioning and 1,333 animals at weaning. Genotyping of the population was done by imputing from the parental generation genotyped with a high density array (777,000 SNP) to a target population genotyped with a medium density SNP array (50,000 SNP). After imputation, 675,018 SNP were used in the genomewide association study. Heritability of concentration of circulating 25OHD in cattle at preconditioning and at weaning was 0.41 ± 0.08 and 0.32 ± 0.11, respectively. A region on chromosome 3 was associated with circulating 25OHD. The region on BTA3 had 7 SNP significantly (P < 7.4 × 10(-8)) associated at the genomewide level with serum concentrations of serum 25OHD. Genomewide significant SNP spanned the region between 84.93 and 86.65 megabases (Mb); however, 6 SNP reside between 86.64 and 86.65 Mb. The gene CYP2J2 was identified as a candidate gene associated with concentrations of serum 25OHD in cattle. This is 1 of 6 enzymes involved in metabolizing vitamin D to 25OHD. Results from the present study suggest that CYP2J2 is a gene controlling serum 25OHD concentrations in cattle. CYP2J2 should be considered a prime candidate for understanding both genetic and physiological factors affecting serum 25OHD concentrations in cattle and, therefore, vitamin D status.

The accuracies of DNA-based estimates of genetic merit derived from Angus or multibreed beef cattle training populations.

Several organizations have developed prediction models for molecular breeding values (MBV) for quantitative growth and carcass traits in beef cattle using Bovine SNP50 genotypes and phenotypic or EBV data. Molecular breeding values for Angus cattle have been developed by IGENITY, Pfizer Animal Genetics, and a collaboration between researchers from Iowa State University and the University of Missouri-Columbia (ISU/UMC). The U.S. Meat Animal Research Center (USMARC; Clay Center, NE) has also developed MBV for 16 cattle breeds using 2 multibreed populations, the Germplasm Evaluation (GPE) Program and the 2,000 Bull Project (2K(ALL)), and 2 single breed subpopulations of the 2,000 Bull Project, Angus (2K(AN)) and Hereford (2K(HH)). In this study, these MBV were assessed relative to commercial ranch EBV estimated from the progeny phenotypes of Angus bulls naturally mated in multisire breeding pastures to commercial cows: 121 for USMARC MBV, 99 for ISU/UMC MBV, and 29 for IGENITY and Pfizer MBV (selected based on number of progeny carcass records). Five traits were analyzed: weaning weight (WW), HCW, marbling score (MS), rib-eye muscle area (RE), and, for IGENITY and Pfizer only, feedlot ADG. The average accuracies of MBV across traits were 0.38 ± 0.05 for IGENITY, 0.61 ± 0.12 for Pfizer, 0.46 ± 0.12 for ISU/UMC, 0.16 ± 0.04 for GPE, 0.26 ± 0.05 for 2K(ALL), 0.24 ± 0.04 for 2K(AN), and 0.02 ± 0.12 for 2K(HH). Angus-based MBV (IGENITY, Pfizer, ISU/UMC, and 2K(AN)) explained larger proportions of genetic variance in this population than GPE, 2K(ALL), or 2K(HH) MBV for the same traits. In this data set, IGENITY, Pfizer, and ISU/UMC MBV were predictive of realized performance of progeny, and incorporation of that information into national genetic evaluations would be expected to improve EPD accuracy, particularly for young animals.

Accuracy of genomic breeding values in multibreed beef cattle populations derived from deregressed breeding values and phenotypes.

Genomic selection involves the assessment of genetic merit through prediction equations that allocate genetic variation with dense marker genotypes. It has the potential to provide accurate breeding values for selection candidates at an early age and facilitate selection for expensive or difficult to measure traits. Accurate across-breed prediction would allow genomic selection to be applied on a larger scale in the beef industry, but the limited availability of large populations for the development of prediction equations has delayed researchers from providing genomic predictions that are accurate across multiple beef breeds. In this study, the accuracy of genomic predictions for 6 growth and carcass traits were derived and evaluated using 2 multibreed beef cattle populations: 3,358 crossbred cattle of the U.S. Meat Animal Research Center Germplasm Evaluation Program (USMARC_GPE) and 1,834 high accuracy bull sires of the 2,000 Bull Project (2000_BULL) representing influential breeds in the U.S. beef cattle industry. The 2000_BULL EPD were deregressed, scaled, and weighted to adjust for between- and within-breed heterogeneous variance before use in training and validation. Molecular breeding values (MBV) trained in each multibreed population and in Angus and Hereford purebred sires of 2000_BULL were derived using the GenSel BayesCπ function (Fernando and Garrick, 2009) and cross-validated. Less than 10% of large effect loci were shared between prediction equations trained on (USMARC_GPE) relative to 2000_BULL although locus effects were moderately to highly correlated for most traits and the traits themselves were highly correlated between populations. Prediction of MBV accuracy was low and variable between populations. For growth traits, MBV accounted for up to 18% of genetic variation in a pooled, multibreed analysis and up to 28% in single breeds. For carcass traits, MBV explained up to 8% of genetic variation in a pooled, multibreed analysis and up to 42% in single breeds. Prediction equations trained in multibreed populations were more accurate for Angus and Hereford subpopulations because those were the breeds most highly represented in the training populations. Accuracies were less for prediction equations trained in a single breed due to the smaller number of records derived from a single breed in the training populations.

Birth and weaning traits in crossbred cattle from Hereford, Angus, Norwegian Red, Swedish Red and White, Wagyu, and Friesian sires.

The objective of this study was to characterize breeds representing diverse biological types for birth and weaning traits in crossbred cattle (Bos taurus). Gestation length, calving difficulty, percentage of unassisted calving, percentage of perinatal survival, percentage of survival from birth to weaning, birth weight, weaning weight, BW at 205 d, and ADG was measured in 1,370 calves born and 1,285 calves weaned. Calves were obtained by mating Hereford, Angus, and MARC III (1/4 Hereford, 1/4 Angus, 1/4 Pinzgauer, and 1/4 Red Poll) mature cows to Hereford or Angus (British breeds), Norwegian Red, Swedish Red and White, Wagyu, and Friesian sires. Calves were born during the spring of 1997 and 1998. Sire breed was significant for gestation length, birth weight, BW at 205 d, and ADG (P < 0.001). Offspring from Swedish Red and White and Friesian had the shortest gestation length (282 d), whereas offspring from Wagyu sires had the longest gestation length (286 d). Progeny from British breeds were the heaviest at birth (40.5 kg) and at 205 d (237 kg), and grew faster (0.97 kg/d) than offspring from other breeds. Offspring from Wagyu sires were the lightest at birth (36.3 kg) and at 205 d (214 kg), and had the slowest growth (0.91 kg/d). Dam breed was significant for gestation length (P < 0.001), birth weight (P = 0.009), BW at 205 d, and ADG (P < 0.001). Offspring from Hereford cows had the longest gestation length (284 d), whereas offspring from Angus cows had the shortest (282 d). Offspring from MARC III cows were the heaviest at birth (39.4 kg) when compared with offspring from Hereford (38.2 kg) and Angus (38.6 kg) cows. Progeny from Angus cows were the heaviest at 205 d (235 kg) and grew faster (0.96 kg/d), whereas offspring from Hereford cows were the lightest at 205 d (219 kg) and were the slowest in growth (0.88 kg/d). Sex was significant for gestation length (P = 0.026), birth weight, BW at 205 d, and ADG (P < 0.001). Male calves had a longer gestation length (284 d) when compared with female calves (283 d). Males were heavier than females at birth and at 205 d, and grew faster. Sire breed effects can be optimized by selection and use of appropriate crossbreeding systems.

Physiology and Endocrinology Symposium: How single nucleotide polymorphism chips will advance our knowledge of factors controlling puberty and aid in selecting replacement beef females.

The promise of genomic selection is accurate prediction of the genetic potential of animals from their genotypes. Simple DNA tests might replace low-accuracy predictions for expensive or lowly heritable measures of puberty and fertility based on performance and pedigree. Knowing with some certainty which DNA variants (e.g., SNP) affect puberty and fertility is the best way to fulfill the promise. Several SNP from the BovineSNP50 assay have tentatively been associated with reproductive traits including age at puberty, antral follicle count, and pregnancy observed on different sets of heifers. However, sample sizes are too small and SNP density is too sparse to definitively determine genomic regions harboring causal variants affecting reproductive success. Additionally, associations between individual SNP and similar phenotypes are inconsistent across data sets, and genomic predictions do not appear to be globally applicable to cattle of different breeds. Discrepancies may be a result of different QTL segregating in the sampled populations, differences in linkage disequilibrium (LD) patterns such that the same SNP are not correlated with the same QTL, and spurious correlations with phenotype. Several approaches can be used independently or in combination to improve detection of genomic factors affecting heifer puberty and fertility. Larger samples and denser SNP will increase power to detect real associations with SNP having more consistent LD with underlying QTL. Meta-analysis combining results from different studies can also be used to effectively increase sample size. High-density genotyping with heifers pooled by pregnancy status or early and late puberty can be a cost-effective means to sample large numbers. Networks of genes, implicated by associations with multiple traits correlated with puberty and fertility, could provide insight into the complex nature of these traits, especially if corroborated by functional annotation, established gene interaction pathways, and transcript expression. Example analyses are provided to demonstrate how integrating information about gene function and regulation with statistical associations from whole-genome SNP genotyping assays might enhance knowledge of genomic mechanisms affecting puberty and fertility, enabling reliable DNA tests to guide heifer selection decisions.

Factors affecting pregnancy rate to estrous synchronization and fixed-time artificial insemination in beef cattle.

Application of AI in extensive beef cattle production would be facilitated by protocols that effectively synchronize ovarian follicular development and ovulation to enable fixed-time AI (TAI). The objectives were to determine whether use of a controlled internal drug release (CIDR) device to administer progesterone in a GnRH-based estrous synchronization protocol would optimize blood progesterone concentrations, improve synchronization of follicular development and estrus, and increase pregnancy rates to TAI in beef cows. Beef cows (n = 1,240) in 6 locations within the US Meat Animal Research Center received 1 of 2 treatments: 1) an injection of GnRH [100 µg intramuscularly (i.m.)] followed by PGF(2α) (PGF; 25 mg i.m.) 7 d later (CO-Synch), or 2) CO-Synch plus a CIDR during the 7 d between GnRH and PGF injections (CO-Synch + CIDR). Cows received TAI and GnRH (100 µg i.m.) at 60 h after PGF. Progesterone was measured by RIA in blood samples collected 2 wk before and at initiation of treatment (d 0) and at PGF injection (d 7). Estrous behavior was monitored by Estrotect Heat Detectors. Pregnancy was diagnosed by ultrasonography 72 to 77 d after TAI. Plasma progesterone concentrations did not differ (P > 0.10) between synchronization protocols at first GnRH injection (d 0), but progesterone was greater (P < 0.01) at PGF injection (d 7) in cows receiving CO-Synch + CIDR vs. CO-Synch as a result of fewer CIDR-treated cows having progesterone ≤1 ng/mL at PGF (10.7 vs. 29.6%, respectively). A greater (P < 0.01) proportion of CO-Synch + CIDR vs. CO-Synch cows were detected in estrus within 60 h after PGF (66.7 vs. 57.8 ± 2.6%, respectively) and a greater (P < 0.01) proportion were pregnant to TAI (54.6 vs. 44.3 ± 2.6%, respectively). For both synchronization protocols, cows expressing estrus within 60 h before TAI had a greater pregnancy rate than cows without estrus. For cows with plasma progesterone ≤1 ng/mL at PGF injection, CO-Synch + CIDR increased pregnancy rate (65.2 ± 5.9 vs. 30.8 ± 3.4% with vs. without CIDR), whereas pregnancy rates did not differ (P > 0.10) between protocols (52.1 ± 2.1 vs. 50.0 ± 2.4%, respectively) when progesterone was >1 ng/mL (treatment × progesterone; P < 0.01). Inclusion of a CIDR in the synchronization protocol increased plasma progesterone concentration, proportion of cows detected in estrus, and pregnancy rate; however, the increase in pregnancy rate from inclusion of the CIDR was primarily in cows with decreasing or low endogenous progesterone secretion during treatment.

Partial-genome evaluation of postweaning feed intake and efficiency of crossbred beef cattle.

The effects of individual SNP and the variation explained by sets of SNP associated with DMI, metabolic midtest BW, BW gain, and feed efficiency, expressed as phenotypic and genetic residual feed intake, were estimated from BW and the individual feed intake of 1,159 steers on dry lot offered a 3.0 Mcal/kg ration for at least 119 d before slaughter. Parents of these F(1) × F(1) (F(1)(2)) steers were AI-sired F(1) progeny of Angus, Charolais, Gelbvieh, Hereford, Limousin, Red Angus, and Simmental bulls mated to US Meat Animal Research Center Angus, Hereford, and MARC III composite females. Steers were genotyped with the BovineSNP50 BeadChip assay (Illumina Inc., San Diego, CA). Effects of 44,163 SNP having minor allele frequencies >0.05 in the F(1)(2) generation were estimated with a mixed model that included genotype, breed composition, heterosis, age of dam, and slaughter date contemporary groups as fixed effects, and a random additive genetic effect with recorded pedigree relationships among animals. Variance in this population attributable to sets of SNP was estimated with models that partitioned the additive genetic effect into a polygenic component attributable to pedigree relationships and a genotypic component attributable to genotypic relationships. The sets of SNP evaluated were the full set of 44,163 SNP and subsets containing 6 to 40,000 SNP selected according to association with phenotype. Ninety SNP were strongly associated (P < 0.0001) with at least 1 efficiency or component trait; these 90 accounted for 28 to 46% of the total additive genetic variance of each trait. Trait-specific sets containing 96 SNP having the strongest associations with each trait explained 50 to 87% of additive variance for that trait. Expected accuracy of steer breeding values predicted with pedigree and genotypic relationships exceeded the accuracy of their sires predicted without genotypic information, although gains in accuracy were not sufficient to encourage that performance testing be replaced by genotyping and genomic evaluations.

Predicting breed composition using breed frequencies of 50,000 markers from the US Meat Animal Research Center 2,000 Bull Project.

Knowledge of breed composition can be useful in multiple aspects of cattle production, and can be critical for analyzing the results of whole genome-wide association studies currently being conducted around the world. We examine the feasibility and accuracy of using genotype data from the most prevalent bovine genome-wide association studies platform, the Illumina BovineSNP50 array (Illumina Inc., San Diego, CA), to estimate breed composition for individual breeds of cattle. First, allele frequencies (of Illumina-defined allele B) of SNP on the array for each of 16 beef cattle breeds were defined by genotyping a large set of more than 2,000 bulls selected in cooperation with the respective breed associations to be representative of their breed. With these breed-specific allele frequencies, the breed compositions of approximately 2,000 two-, three-, and four-way cross (of 8 breeds) cattle produced at the US Meat Animal Research Center were predicted by using a simple multiple regression technique or Mendel (http://www.genetics.ucla.edu/software/mendel) and their genotypes from the Illumina BovineSNP50 array, and were then compared with pedigree-based estimates of breed composition. The accuracy of marker-based breed composition estimates was 89% when using either estimation method for all breeds except Angus and Red Angus (averaged 79%), based on comparing estimates with pedigree-based average breed composition. Accuracy increased to approximately 88% when these 2 breeds were combined into an aggregate Angus group. Additionally, we used a subset of these markers, approximately 3,000 that populate the Illumina Bovine3K (Illumina Inc.), to see whether breed composition could be estimated with similar accuracy when using this reduced panel of SNP makers. When breed composition was estimated using only SNP in common with the Bovine 3K array, accuracy was slightly reduced to 83%. These results suggest that SNP data from these arrays could be used to estimate breed composition in most US beef cattle in situations where pedigree is not known (e.g., multiple-sire natural service matings, non-source-verified animals in feedlots or at slaughter). This approach can aid analyses that depend on knowledge of breed composition, including identification and adjustment of breed-based population stratification, when performing genome-wide association studies on populations with incomplete pedigrees. In addition, SNP-based breed composition estimates may facilitate fitting cow germplasm to the environment, managing cattle in the feedlot, and tracing disease cases back to the geographic region or farm of origin.

Birth and weaning traits in crossbred cattle from Hereford, Angus, Brahman, Boran, Tuli, and Belgian Blue sires.

The objective of this study was to characterize breeds representing diverse biological types for birth and weaning traits in crossbred cattle. Gestation length, calving difficulty, percentage of unassisted calving, percentage of perinatal survival, percentage of survival from birth to weaning, birth weight, BW at 200 d, and ADG were measured in 2,500 calves born and 2,395 calves weaned. Calves were obtained by mating Hereford, Angus, and MARC III (one-fourth Hereford, one-fourth Angus, one-fourth Pinzgauer, and one-fourth Red Poll) mature cows to Hereford or Angus (British breed), Brahman, Tuli, Boran, and Belgian Blue sires. Calves were born during the spring seasons of 1992, 1993, and 1994. Sire breed was significant for all traits (P < 0.002). Offspring from British breeds and the Belgian Blue breed had the shortest gestation length (285 d) when compared with progeny from other sire breeds (average of 291 d). Calving difficulty was greater in offspring from Brahman sires (1.24), whereas the offspring of Tuli sires had the least amount of calving difficulty (1.00). Offspring from all sire breeds had similar perinatal survival and survival from birth to weaning (average of 97.2 and 96.2%, respectively), with the exception of offspring from Brahman sires, which had less (92.8 and 90.4%, respectively). Progeny of Brahman sires were heaviest at birth (45.7 kg), followed by offspring from British breed, Boran, and Belgian Blue sires (average of 42.4 kg). The lightest offspring at birth were from Tuli sires (38.6 kg). Progeny derived from Brahman sires were the heaviest at 200 d (246 kg), and they grew faster (1.00 kg/d) than offspring from any other group. The progeny of British breeds and the Belgian Blue breed had an intermediate BW at 200 d (238 kg) and an intermediate ADG (average of 0.98 kg/d). The progeny of Boran and Tuli sires were the lightest at 200 d (227 kg) and had the least ADG (0.93 kg/d). Male calves had a longer gestation length, had a greater incidence of calving difficulty, had greater mortality to weaning, were heavier, and grew faster than female calves. Sire breed effects can be optimized by selection and use of appropriate crossbreeding systems.

Contribution of genetic influences to animal-to-animal variation in myoglobin content and beef lean color stability.

Longissimus thoracis steaks from steers (n = 464) with 0 to 50% inheritance of Angus, Charolais, Gelbvieh, Hereford, Limousin, Red Angus, and Simmental were evaluated during 6 d of display to assess genetic contributions to color stability. Color space values [CIE L* (lightness), a* (redness), b* (yellowness)], chroma, color change (DeltaE), and surface metmyoglobin (K/S 572/525) were determined on d 0 and 6 of display. Myoglobin concentration was highly heritable (0.85), but ultimate pH was weakly heritable (0.06). Day 0 L* values were moderately heritable (0.24). Variation in metmyoglobin, L*, and DeltaE on d 6 was moderately explained by genetic factors (41, 40, and 29%, respectively). Change during display was moderately heritable for a* (0.31), b* (0.23), chroma (0.35), and surface metmyoglobin (0.29). At the start of display, Angus steaks had greater (P < 0.05) L* values than those from all breeds except Charolais. On d 6, Angus steaks had greater (P < 0.05) L* (50.0) values than Gelbvieh, Hereford, and Simmental steaks (46.1, 44.0, and 44.5, respectively). Day 0 values for a*, b*, chroma, and DeltaE were not affected by breed (P > 0.05). On d 6, a* values were greater (P < 0.05) for Charolais and Limousin steaks (31.1 and 30.5) than Angus, Hereford, and Red Angus steaks (27.4, 27.7, and 26.3, respectively). Thus, a* changed less (P < 0.05) in Charolais and Limousin steaks (1.8 and 2.6, respectively) vs. steaks from other breeds. Day 6 b* values were greater (P < 0.05) in Charolais (24.5) and Limousin steaks (24.0) vs. Gelbvieh (22.2), Hereford (21.9), and Red Angus steaks (21.4). Thus, b* values changed less (P < 0.05) in Charolais and Limousin steaks (1.5 and 1.7, respectively) than in Angus, Gelbvieh, Hereford, and Red Angus steaks (4.3, 3.8, 4.4, and 5.1, respectively). After 6 d of display, Charolais and Limousin steaks had greater chroma (P < 0.05; 39.5 and 38.8, respectively) compared with Angus, Hereford, and Red Angus steaks (35.4, 35.3, and 33.9, respectively). Less (P < 0.05) change in chroma occurred for Charolais and Limousin (2.1 and 2.8, respectively) than in Angus, Gelbvieh, Hereford, and Red Angus steaks (7.1, 6.6, 7.4, and 9.0, respectively). Myoglobin concentration was less for Charolais and Limousin (P < 0.05; 2.77 and 2.72, respectively) compared with Gelbvieh, Red Angus, and Simmental steaks (3.62, 3.43, and 3.71, respectively). Breeds did not differ in pH (P > 0.05). These data suggest Charolais- and Limousin-carcasses produced steaks with greater lean color stability than Angus, Hereford, and Red Angus carcasses. Furthermore, these findings suggest that genetics contribute substantially to animal-to-animal variation in lean color, particularly in maintaining color.

Genome-wide association study of growth in crossbred beef cattle.

Chromosomal regions harboring variation affecting cattle birth weight and BW gain to 1 yr of age were identified by marker association using the highly parallel BovineSNP50 BeadChip (50K) assay composed of 54,001 individual SNP. Genotypes were obtained from progeny (F(1); 590 steers) and 2-, 3-, and 4-breed cross grandprogeny (F(1)(2) = F(1) x F(1); 1,306 steers and 707 females) of 150 AI sires representing 7 breeds (22 sires per breed; Angus, Charolais, Gelbvieh, Hereford, Limousin, Red Angus, and Simmental). Genotypes and birth, weaning, and yearling BW records were used in whole-genome association analyses to estimate effects of individual SNP on growth. Traits analyzed included growth component traits: birth weight (BWT), 205-d adjusted birth to weaning BW gain (WG), 160-d adjusted postweaning BW gain (PWG); cumulative traits: 205-d adjusted weaning weight (WW = BWT + WG) and 365-d adjusted yearling weight (YW = BWT + WG + PWG); and indexes of relative differences between postnatal growth and birth weight. Modeled fixed effects included additive effects of calf and dam SNP genotype, year-sex-management contemporary groups, and covariates for calf and dam breed composition and heterosis. Direct and maternal additive polygenic effects and maternal permanent environment effects were random. Missing genotypes, including 50K genotypes of most dams, were approximated with a single-locus BLUP procedure from pedigree relationships and known 50K genotypes. Various association criteria were applied: stringent tests to account for multiple testing but with limited power to detect associations with small effects, and relaxed nominal P that may detect SNP associated with small effects but include excessive false positive associations. Genomic locations of the 231 SNP meeting stringent criteria generally coincided with described previously QTL affecting growth traits. The 12,425 SNP satisfying relaxed tests were located throughout the genome. Most SNP associated with BWT and postnatal growth affected components in the same direction, although detection of SNP associated with one component independent of others presents a possible opportunity for SNP-assisted selection to increase postnatal growth relative to BWT.