Age-dependent intoxication by larkspur (Delphinium) in Angus steers.

The effect of age on larkspur poisoning of cattle is unknown. An experiment consisting of oral dosing of dried, ground, Delphinium barbeyi to ten Angus steers as yearlings, and again at two years was performed. There was a significant difference between the responses of yearling and two year old steers (P = 0.0015), with yearling steers being more susceptible. These results suggest that the adverse response of Angus cattle to larkspur is age-dependent.

Complete inhibition of fetal movement in the day 40 pregnant goat model by the piperidine alkaloid anabasine but not related alkaloids.

Four chemically similar alkaloids, anabasine, anabaseine, epibatidine and dimethylphenylpiperazinium (DMPP), are potent nicotinic acetylcholine receptor agonists of fetal muscle nicotinic acetylcholine receptors in human TE-671 cells. Based on results with these cells, we hypothesized that the alkaloids would completely inhibit ultrasound-monitored fetal movement in a goat model. Different, single doses of anabasine, anabaseine, epibatidine, DMPP, or saline control were administered I.V. to pregnant goats on day 40 of gestation and the number of fetal movements per 5 min sample was measured by ultrasound at times 0, 0.5, 1, 2, 4 and 8 h. The differences among does in fetal movements were more consistent at dosing and following recovery for doses of anabasine above 0.125 mg/kg compared to the other compounds and dosages. Anabasine actions were dose-dependent with an IC50 value of ∼0.1 mg/kg, and, at a dose of 0.8 mg/kg, completely inhibited fetal movement for 1.5 h after dosing. Anabaseine, epibatidine, and DMPP failed to completely inhibit fetal movement in day 40 pregnant goats at doses predicted to be effective. These results suggest that while experiments with TE-671 cells provide valuable information and predictions of the actions of plant alkaloids on fetal movement, in vivo experiments are still required in order to determine the ability of an alkaloid to inhibit fetal movement in livestock species. Moreover, other pharmacological properties such as receptor differences between mammalian species and differences in the pharmacokinetic properties of the alkaloids also are likely to weaken teratologic predictions based solely on the in vitro data.

Relationships between the genes expressed in the mesenteric adipose tissue of beef cattle and feed intake and gain.

Mesenteric fat, a depot within the visceral fat, accumulates in cattle during maturation and finishing and may be a potential source of production inefficiency. The aim of this study was to determine whether the genes expressed in the mesenteric fat of steers were associated with body weight gain and feed intake. Sixteen steers chosen by their rank of distance from the bivariate mean for gain and feed intake were used for this study. Mesenteric fat was obtained and evaluated for differences in gene expression. A total of 1831 genes were identified as differentially expressed among steers with variation in feed intake and gain. Many of these genes were involved with metabolic processes such as proteolysis, transcription and translation. In addition, the Gene Ontology annotations including transport and localization were both over-represented among the differentially expressed genes. Pathway analysis was also performed on the differentially expressed genes. The superoxide radical degradation pathway was identified as over-represented based on the differential expression of the genes GPX7, SOD2 and TYRP1, suggesting a potential role for oxidative stress or inflammatory pathways among low gain-high intake animals. GPX7 and SOD2 were in lower transcript abundance, and TYRP1 was higher in transcript abundance among the low gain-high feed intake animals. The retinoate biosynthesis pathway was also enriched due to the differential expression of the genes AKR1C3, ALDH8A1, RDH8, RDH13 and SDR9C7. These genes were all more highly expressed in the low gain-high intake animals. The glycerol degradation and granzyme A signaling pathways were both associated with gain. Three glycerol kinase genes and the GZMA gene were differentially expressed among high vs. low gain animals. Mesenteric fat is a metabolically active tissue, and in this study, genes involved in proteolysis, transcription, translation, transport immune function, glycerol degradation and oxidative stress were differentially expressed among beef steers with variation in body weight gain and feed intake.

Genome-wide copy number variation in the bovine genome detected using low coverage sequence of popular beef breeds.

Copy number variations (CNVs) are large insertions, deletions or duplications in the genome that vary between members of a species and are known to affect a wide variety of phenotypic traits. In this study, we identified CNVs in a population of bulls using low coverage next-generation sequence data. First, in order to determine a suitable strategy for CNV detection in our data, we compared the performance of three distinct CNV detection algorithms on benchmark CNV datasets and concluded that using the multiple sample read depth approach was the best method for identifying CNVs in our sequences. Using this technique, we identified a total of 1341 copy number variable regions (CNVRs) from genome sequences of 154 purebred sires used in Cycle VII of the USMARC Germplasm Evaluation Project. These bulls represented the seven most popular beef breeds in the United States: Hereford, Charolais, Angus, Red Angus, Simmental, Gelbvieh and Limousin. The CNVRs covered 6.7% of the bovine genome and spanned 2465 protein-coding genes and many known quantitative trait loci (QTL). Genes harbored in the CNVRs were further analyzed to determine their function as well as to find any breed-specific differences that may shed light on breed differences in adaptation, health and production.

Genomewide association study of liver abscess in beef cattle.

Fourteen percent of U.S. cattle slaughtered in 2011 had liver abscesses, resulting in reduced carcass weight, quality, and value. Liver abscesses can result from a common bacterial cause, , which inhabits rumen lesions caused by acidosis and subsequently escapes into the blood stream, is filtered by the liver, and causes abscesses in the liver. Our aim was to identify SNP associated with liver abscesses in beef cattle. We used lung samples as a DNA source because they have low economic value, they have abundant DNA, and we had unrestricted access to sample them. We collected 2,304 lung samples from a beef processing plant: 1,152 from animals with liver abscess and 1,152 from animals without liver abscess. Lung tissue from pairs of animals, 1 with abscesses and another without, were collected from near one another on the viscera table to ensure that pairs of phenotypically extreme animals came from the same lot. Within each phenotype (abscess or no abscess), cattle were pooled by slaughter sequence into 12 pools of 96 cattle for each phenotype for a total of 24 pools. The pools were constructed by equal volume of frozen lung tissue from each animal. The DNA needed to allelotype each pool was then extracted from pooled lung tissue and the BovineHD Bead Array (777,962 SNP) was run on all 24 pools. Total intensity (TI), an indicator of copy number variants, was the sum of intensities from red and green dyes. Pooling allele frequency (PAF) was red dye intensity divided TI. Total intensity and PAF were weighted by the inverse of their respective genomic covariance matrices computed over all SNP across the genome. A false discovery rate ≤ 5% was achieved for 15 SNP for PAF and 20 SNP for TI. Genes within 50 kbp from significant SNP were in diverse pathways including maintenance of pH homeostasis in the gastrointestinal tract, maintain immune defenses in the liver, migration of leukocytes from the blood into infected tissues, transport of glutamine into the kidney in response to acidosis to facilitate production of bicarbonate to increase pH, aggregate platelets to liver injury to facilitate liver repair, and facilitate axon guidance. Evidence from the 35 detected SNP associations combined with evidence of polygenic variation indicate that there is adequate genetic variation in incidence rate of liver abscesses, which could be exploited to select sires for reduced susceptibility to subacute acidosis and associated liver abscess.

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.

Genomewide association study of lung lesions in cattle using sample pooling.

Bovine respiratory disease complex (BRDC) is the most expensive disease in beef cattle in the United States costing the industry at least US$1 billion annually. Bovine respiratory disease complex causes damage to lung tissue resulting in persistent lung lesions observable at slaughter. Severe lung lesions at harvest have been associated with decreased preharvest ADG and increased clinical BRDC in the feedlot. Our objective was to identify SNP that are associated with severe lung lesions observed at harvest in feedlot cattle. We conducted a genomewide association study (GWAS) using a case-control design for severe lung lesions in fed cattle at slaughter using the Illumina Bovine HD array (approximately 770,000 SNP) and sample pooling. Lung samples were collected from 11,520 young cattle, a portion of which had not been treated with antibiotics (participating in a "natural" marketing program), at a large, commercial beef processing plant in central Nebraska. Lung samples with lesions (cases) and healthy lungs (controls) were collected when both phenotypes were in close proximity on the viscera (offal) table. We constructed 60 case and 60 control pools with 96 animals per pool. Pools were constructed by sampling sequence to ensure that case and control pool pairs were matched by proximity on the processing line. The Bovine HD array (770,000 SNP) was run on all pools. Fourteen SNP on BTA 2, 3, 4, 9, 11, 14, 15, 22, 24, and 25 were significant at the genomewide experiment-wise error rate of 5% ( ≤ 1.49 × 10). Eighty-five SNP on 28 chromosomes achieved a false discovery rate of 5% ( ≤ 5.38 × 10). Significant SNP were near (±100 kb) genes involved in tissue repair and regeneration, tumor suppression, cell proliferation, apoptosis, control of organ size, and immunity. Based on 85 significantly associated SNP in or near a collection of genes with diverse function on 28 chromosomes, we conclude that the genomic footprint of lung lesions is complex. A complex genomic footprint (genes and regulatory elements that affect the trait) is consistent with what is known about the cause of the disease: complex interactions among multiple viral and bacterial pathogens along with several environmental factors including dust, commingling, transportation, and stress. Characterization of sequence variation near significant SNP will enable accurate and cost effective genome-enhanced genetic evaluations for BRDC resistance in AI bulls and seed stock populations.

Evaluation of single nucleotide polymorphisms in chromosomal regions impacting pregnancy status in cattle.

Reproductive success is an important component of commercial beef cattle production, and identification of DNA markers with predictive merit for reproductive success would facilitate accurate prediction of mean daughter pregnancy rate, enabling effective selection of bulls to improve female fertility. A previous study identified SNP associated with beef cattle reproductive efficiency based on a genomewide association analysis approach using genotyping multiple-animal pools of DNA to increase the number of animals that could be genotyped with available resources. For the current study, we expand on this previous study by individually genotyping cattle from the pooling study for 89 SNP that were associated with female pregnancy rate. The aims of the study were to confirm the results of the pooling study and, more specifically, identify modes of gene action and DNA variations such as haplotypes that would not be possible with pooled genotyping. Eighty-nine SNP selected from the pooling study were evaluated using the Sequenom MassARRAY system to individually genotype animals from populations evaluated in the pooling study, including both and breeds. From this research, regions on chromosomes 5 (26.3-48.1 Mb; UMD3.1 assembly) and 9 (37,436,575 bp; UMD3.1 assembly), first identified in the previous pooling study, were shown through individual genotyping to harbor genetic variation ( < 0.05 genomewide significance) affecting reproductive efficiency in interspecific crosses ( and ) of cattle. Each of these markers exhibited additive (vs. dominant) gene action. Additionally, a haplotype block harboring an allele of origin with negative effects on reproduction was identified on chromosome 5 in interspecific composite breeds of × composites.

A genome-wide association study for the incidence of persistent bovine viral diarrhea virus infection in cattle.

Bovine viral diarrhea viruses (BVDV) comprise a diverse group of viruses that cause disease in cattle. BVDV may establish both transient and persistent infections depending on the developmental stage of the animal at exposure. The objective was to determine whether genomic regions harboring single nucleotide polymorphisms (SNPs) could be associated with the presence or absence of persistent BVDV infection. A genome-wide association approach based on 777,000 SNP markers was used. Samples of animals identified as positive (n = 1200) or negative (n = 1200) for the presence of BVDV in skin samples (n = 1200) were used. DNA samples were combined in 24 pools (100 animals per pool). One SNP, significant at the 5 percent genome-wide level (P = 9.41 × 10(-8) ), was detected on chromosome 14, located at position 80 675 176 bp. Fifteen SNPs, residing on chromosomes 1, 2, 6, 8, 10, 15 and 18, were moderately associated (P < 1 × 10(-5) ) with persistent BVDV infection. Results show that genes harboring or neighboring significant SNPs are involved in leucopenia, signal transduction, RNA splicing and DNA methylation processes.

CAPN1, CAST, and DGAT1 genetic effects on preweaning performance, carcass quality traits, and residual variance of tenderness in a beef cattle population selected for haplotype and allele equalization.

Genetic marker effects and type of inheritance are estimated with poor precision when minor marker allele frequencies are low. A stable composite population (MARC III) was subjected to marker-assisted selection for multiple years to equalize specific marker frequencies to 1) estimate effect size and mode of inheritance for previously reported SNP on targeted beef carcass quality traits (n=254), 2) estimate pleiotropic effects of previously reported SNP on nontarget performance traits (n=542 or 254), and 3) evaluate tenderness SNP specific residual variance for LM tenderness. Three haplotypes within µ-calpain (CAPN1), a SNP in calpastatin (CAST), and a dinucleotide substitution in diacylglycerol O-acyltransferase 1 (DGAT1) were successfully selected to equalize their frequencies. Traits evaluated were birth BW, weaning BW, yearling BW, final BW, dressing percent, HCW, fat thickness, LM area, USDA marbling score, yield grade, LM slice shear force (SSF), and visible and near-infrared (VISNIR)-predicted SSF. While the CAPN1 genotype effect on SSF was not significant (P=0.12), the direction and size of CAPN1 contrasts were consistent with previous research. Effects on SSF between divergent CAPN1 haplotypes (1.153 kg) and the additive effect of CAST (0.902 kg) were large, and animals homozygous for tender alleles at both CAPN1 and CAST would have 4.11 kg lower SSF (27.5% of the mean) than animals homozygous tough for both markers. Furthermore, the interaction between CAPN1 and CAST for SSF was not significant (P=0.40). There were significant effects for DGAT1 on adjusted fat thickness (P=0.02) and VISNIR-predicted SSF (P<0.001) with additive and dominance modes of inheritance (P<0.05) for both traits. Furthermore, CAST genotype specific residual variance models fit significantly better (P<0.001) than single residual variance models for SSF, with the tougher genotypes having progressively larger residual (and hence phenotypic) variances. Therefore, 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 is supportive of the importance of CAPN1 and CAST for mean tenderness in beef, confirms an effect of CAST on beef LM tenderness variation, and identifies an effect of DGAT1 on subcutaneous fat thickness.

Genomewide association study of reproductive efficiency in female cattle.

Reproductive efficiency is of economic importance in commercial beef cattle production, as failure to achieve pregnancy reduces the number of calves marketed per cow exposed. Identification of genetic markers with predictive merit for reproductive success would facilitate early selection of sires with daughters having improved reproductive rate without increasing generation intervals. To identify regions of the genome harboring variation affecting reproductive success, we applied a genomewide association study (GWAS) approach based on the >700,000 SNP marker assay, using a procedure based on genotyping multianimal pools of DNA to increase the number of animals that could be genotyped with available resources. Cows from several populations were classified according to reproductive efficiency, and DNA was pooled within population and phenotype prior to genotyping. Populations evaluated included a research population at the U.S. Meat Animal Research Center, 2 large commercial ranch populations, and a number of smaller populations (<100 head) across the United States. We detected 2 SNP with significant genomewide association (P ≤ 1.49 × 10(-7)), on BTA21 and BTA29, 3 SNP with suggestive associations (P ≤ 2.91 × 10(-6)) on BTA5, and 1 SNP with suggestive association each on BTA1 and BTA25. In addition to our novel findings, we confirmed previously published associations for SNP on BTA-X and all autosomes except 3 (BTA21, BTA22, and BTA28) encompassing substantial breed diversity including Bos indicus and Bos taurus breeds. The study identified regions of the genome associated with reproductive efficiency, which are being targeted for further analysis to develop robust marker systems, and demonstrated that DNA pooling can be used to substantially reduce the cost of GWAS in cattle.

Identifying genetic loci controlling neonatal passive transfer of immunity using a hybrid genotyping strategy.

Colostrum intake is critical to a piglet's survival and can be measured by precipitating out the γ-immunoglobulins from serum with ammonium sulfate (immunocrit). Genetic analysis of immunocrits on 5312 piglets indicated that the heritabilities (se) for direct and maternal effects were 0.13 (0.06) and 0.53 (0.08) respectively. To identify QTL for direct genetic effects, piglets with the highest and lowest immunocrits from 470 litters were selected. Six sets of DNA pools were created based on sire of the litter. These 12 DNA pools were applied to Illumina Porcine SNP60 BeadChips. Normalized X and Y values were analyzed. Three different SNP selection methods were used: deviation of the mean from high vs. low pools, the deviation adjusted for variance based on binomial theory and ANOVA. The 25 highest ranking SNPs were selected from each evaluation for further study along with 12 regions selected based on a five-SNP window approach. Selected SNPs were individually genotyped in the 988 piglets included in pools as well as in 524 piglets that had intermediate immunocrits. Association analyses were conducted fitting an animal model using the estimated genetic parameters. Nineteen SNPs were nominally associated (P < 0.01) with immunocrit values, of which nine remained significant (P < 0.05) after Bonferroni correction, located in 16 genomic regions on 13 chromosomes. In conclusion, the pooling strategy reduced the cost to scan the genome by more than 80% and identified genomic regions associated with a piglet's ability to acquire γ-immunoglobulin from colostrum. Each method to rank SNPs from the pooled analyses contributed unique validated markers, suggesting that multiple analyses will reveal more QTL than a single analysis.

Deletion on chromosome 5 associated with decreased reproductive efficiency in female cattle.

Reproductive efficiency is arguably the most economically important trait in commercial beef cattle production, as failure to achieve pregnancy reduces the number of calves marketed per cow exposed to breeding. Identification of variation in the genome with predictive merit for reproductive success would facilitate accurate prediction of daughter pregnancy rate in sires enabling effective selection of bulls producing daughters with improved fertility. Copy number variation (CNV) is one form of structural variation that results in abnormal copies of DNA in the genome. Our lab previously reported a region between 25 and 70 Mb on chromosome 5 associated with reproductive efficiency. To further evaluate this region for genomic variations such as CNV, we initially applied a genomewide association approach based on the >700,000 SNP marker assay and PennCNV analysis to 68 Bos indicus cross females from a large commercial ranch in central Florida. A genomic segment located on chromosome 5, spanning the region of approximately 58.37 to 58.44 Mb (Bovine UMD3.1 assembly) was identified as containing a deletion associated with decreased reproductive efficiency. To verify this deletion, a quantitative real-time PCR test was developed to evaluate additional females in the central Florida and U.S. Meat Animal Research Center (USMARC) populations. The frequency of the homozygous deletion was 7% (23/319) in the central Florida population (Bos indicus cross) for females with 2 consecutive failed breeding seasons and 0% in the USMARC population (predominantly Bos taurus) of low reproductive females. To date, we have not identified the deletion in Bos taurus cattle, suggesting that the deletion is specific to Bos indicus cattle. From these data, we have identified a deletion on chromosome 5 associated with reproductive efficiency in Bos indicus-influenced cattle.

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.

Breeding and Genetics Symposium: networks and pathways to guide genomic selection.

Many traits affecting profitability and sustainability of meat, milk, and fiber production are polygenic, with no single gene having an overwhelming influence on observed variation. No knowledge of the specific genes controlling these traits has been needed to make substantial improvement through selection. Significant gains have been made through phenotypic selection enhanced by pedigree relationships and continually improving statistical methodology. Genomic selection, recently enabled by assays for dense SNP located throughout the genome, promises to increase selection accuracy and accelerate genetic improvement by emphasizing the SNP most strongly correlated to phenotype although the genes and sequence variants affecting phenotype remain largely unknown. These genomic predictions theoretically rely on linkage disequilibrium (LD) between genotyped SNP and unknown functional variants, but familial linkage may increase effectiveness when predicting individuals related to those in the training data. Genomic selection with functional SNP genotypes should be less reliant on LD patterns shared by training and target populations, possibly allowing robust prediction across unrelated populations. Although the specific variants causing polygenic variation may never be known with certainty, a number of tools and resources can be used to identify those most likely to affect phenotype. Associations of dense SNP genotypes with phenotype provide a 1-dimensional approach for identifying genes affecting specific traits; in contrast, associations with multiple traits allow defining networks of genes interacting to affect correlated traits. Such networks are especially compelling when corroborated by existing functional annotation and established molecular pathways. The SNP occurring within network genes, obtained from public databases or derived from genome and transcriptome sequences, may be classified according to expected effects on gene products. As illustrated by functionally informed genomic predictions being more accurate than naive whole-genome predictions of beef tenderness, coupling evidence from livestock genotypes, phenotypes, gene expression, and genomic variants with existing knowledge of gene functions and interactions may provide greater insight into the genes and genomic mechanisms affecting polygenic traits and facilitate functional genomic selection for economically important traits.

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.

Y are you not pregnant: identification of Y chromosome segments in female cattle with decreased reproductive efficiency.

Reproductive efficiency is of economic importance in commercial beef cattle production, since failure to achieve pregnancy reduces the number of calves marketed. Identification of genetic markers with predictive merit for reproductive success would facilitate early selection of females and avoid inefficiencies associated with sub-fertile cows. To identify regions of the genome harboring variation affecting reproductive success, we applied a genome-wide association approach based on the >700,000 SNP marker assay. To include the largest number of individuals possible under the available budget, cows from several populations were assigned to extremes for reproductive efficiency, and DNA was pooled within population and phenotype before genotyping. Surprisingly, pools prepared from DNA of low reproductive cattle returned fluorescence intensity data intermediate between fertile females and males for SNP mapped to the Y chromosome (i.e., male sex chromosome). The presence of Y-associated material in low reproductive heifers or cows was confirmed by Y-directed PCR, which revealed that 21 to 29% of females in the low reproductive category were positive by a Y chromosome PCR test normally used to sex embryos. The presence of the Y chromosome anomaly was further confirmed with application of additional Y-specific PCR amplicons, indicating the likelihood of the presence of some portion of male sex chromosome in female cattle in various beef cattle herds across the U.S. Discovery of this Y anomaly in low reproductive females may make an important contribution to management of reproductive failures in beef cattle operations.

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.

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.

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.