Reply to the 'Comment on "Perturbation theory of scattering for grazing-incidence fast-atom diffraction"' by G. A. Bocan, H. Breiss, S. Szilasi, A. Momeni, E. M. S. Casagrande, E. A. Sánchez, M. S. Gravielle and H. Khemliche, Phys. Chem. Chem. Phys., 2023, 25, DOI: 10.1039/D3CP02486E.

In this Reply, we show that criticisms of perturbation theory for grazing-incidence fast-atom diffraction (GIFAD) are ill-founded. We show explicitly that our formulation (W. Allison, S. Miret-Artés and E. Pollak, Phys. Chem. Chem. Phys., 2022, 24, 15851) provides a similar precision in describing the observed phenomena as ab initio potentials. Since that is the main criterion to distinguish between methods, it seems reasonable to conclude that the perturbation approach using a Morse-type potential reproduces the essential aspects of the dynamics correctly. In addition we expand on the historical context and summarize the physical insights provided by our methods.

Genetic parameter estimates for bull prolificacy and its relationship with scrotal circumference in a commercial beef cattle population.

The commercial beef cattle industry relies heavily on the use of natural service sires. When artificial insemination is deemed difficult to implement, multisire breeding pastures are used to increase reproductive rates in large breeding herds or to safe-guard against bull injury during the breeding season. Although each bull might be given an equal opportunity to produce offspring, evidence suggest that there is substantial variation in the number of calves sired by each bull in a breeding pasture. With the use of DNA-based paternity testing, correctly assigning calves to their respective sires in multisire pastures is possible and presents an opportunity to investigate the degree to which this trait complex is under genetic control. Field data from a large commercial ranch was used to estimate genetic parameters for calf count (CC; 574 records from 443 sires) and yearling scrotal circumference (SC; n = 1961) using univariate and bivariate animal models. Calf counts averaged 12.2 ± 10.7 and SC averaged 35.4 ± 2.30 cm. Bulls had an average of 1.30 records and there were 23.9 ± 11.1 bulls per contemporary group. The model for CC included fixed effects of age during the breeding season (in years) and contemporary group (concatenation of breeding pasture and year). Random effects included additive genetic and permanent environmental effects, and a residual. The model for SC included fixed effects of age (in days) and contemporary group (concatenation of month and year of measurement). Random effects included an additive genetic effect and a residual. Univariate model heritability estimates for CC and SC were 0.178 ± 0.142 and 0.455 ± 0.072, respectively. Similarly, the bivariate model resulted in heritability estimates for CC and SC of 0.184 ± 0.142 and 0.457 ± 0.072, respectively. Repeatability estimates for CC from univariate and bivariate models were 0.315 ± 0.080 and 0.317 ± 0.080, respectively. The estimate of genetic correlation between CC and SC was 0.268 ± 0.274. Heritability estimates suggest that both CC and SC would respond favorably to selection. Moreover, CC is lowly repeatable and although favorably correlated, SC appears to be weakly associated with CC.

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.

Comparison of Bayesian models to estimate direct genomic values in multi-breed commercial beef cattle.

BACKGROUND: While several studies have examined the accuracy of direct genomic breeding values (DGV) within and across purebred cattle populations, the accuracy of DGV in crossbred or multi-breed cattle populations has been less well examined. Interest in the use of genomic tools for both selection and management has increased within the hybrid seedstock and commercial cattle sectors and research is needed to determine their efficacy. We predicted DGV for six traits using training populations of various sizes and alternative Bayesian models for a population of 3240 crossbred animals. Our objective was to compare alternate models with different assumptions regarding the distributions of single nucleotide polymorphism (SNP) effects to determine the optimal model for enhancing feasibility of multi-breed DGV prediction for the commercial beef industry. RESULTS: Realized accuracies ranged from 0.40 to 0.78. Randomly assigning 60 to 70% of animals to training (n ≈ 2000 records) yielded DGV accuracies with the smallest coefficients of variation. Mixture models (BayesB95, BayesCπ) and models that allow SNP effects to be sampled from distributions with unequal variances (BayesA, BayesB95) were advantageous for traits that appear or are known to be influenced by large-effect genes. For other traits, models differed little in prediction accuracy (~0.3 to 0.6%), suggesting that they are mainly controlled by small-effect loci. CONCLUSIONS: The proportion (60 to 70%) of data allocated to training that optimized DGV accuracy and minimized the coefficient of variation of accuracy was similar to large dairy populations. Larger effects were estimated for some SNPs using BayesA and BayesB95 models because they allow unequal SNP variances. This substantially increased DGV accuracy for Warner-Bratzler Shear Force, for which large-effect quantitative trait loci (QTL) are known, while no loss in accuracy was observed for traits that appear to follow the infinitesimal model. Large decreases in accuracy (up to 0.07) occurred when SNPs that presumably tag large-effect QTL were over-regressed towards the mean in BayesC0 analyses. The DGV accuracies achieved here indicate that genomic selection has predictive utility in the commercial beef industry and that using models that reflect the genomic architecture of the trait can have predictive advantages in multi-breed populations.

QTLs associated with dry matter intake, metabolic mid-test weight, growth and feed efficiency have little overlap across 4 beef cattle studies.

BACKGROUND: The identification of genetic markers associated with complex traits that are expensive to record such as feed intake or feed efficiency would allow these traits to be included in selection programs. To identify large-effect QTL, we performed a series of genome-wide association studies and functional analyses using 50 K and 770 K SNP genotypes scored in 5,133 animals from 4 independent beef cattle populations (Cycle VII, Angus, Hereford and Simmental×Angus) with phenotypes for average daily gain, dry matter intake, metabolic mid-test body weight and residual feed intake. RESULTS: A total of 5, 6, 11 and 10 significant QTL (defined as 1-Mb genome windows with Bonferroni-corrected P-value<0.05) were identified for average daily gain, dry matter intake, metabolic mid-test body weight and residual feed intake, respectively. The identified QTL were population-specific and had little overlap across the 4 populations. The pleiotropic or closely linked QTL on BTA 7 at 23 Mb identified in the Angus population harbours a promising candidate gene ACSL6 (acyl-CoA synthetase long-chain family member 6), and was the largest effect QTL associated with dry matter intake and mid-test body weight explaining 10.39% and 14.25% of the additive genetic variance, respectively. Pleiotropic or closely linked QTL associated with average daily gain and mid-test body weight were detected on BTA 6 at 38 Mb and BTA 7 at 93 Mb confirming previous reports. No QTL for residual feed intake explained more than 2.5% of the additive genetic variance in any population. Marker-based estimates of heritability ranged from 0.21 to 0.49 for residual feed intake across the 4 populations. CONCLUSIONS: This GWAS study, which is the largest performed for feed efficiency and its component traits in beef cattle to date, identified several large-effect QTL that cumulatively explained a significant percentage of additive genetic variance within each population. Differences in the QTL identified among the different populations may be due to differences in power to detect QTL, environmental variation, or differences in the genetic architecture of trait variation among breeds. These results enhance our understanding of the biology of growth, feed intake and utilisation in beef cattle.

Use of robust multivariate linear mixed models for estimation of genetic parameters for carcass traits in beef cattle.

Assumptions of normality of residuals for carcass evaluation may make inferences vulnerable to the presence of outliers, but heavy-tail densities are viable alternatives to normal distributions and provide robustness against unusual or outlying observations when used to model the densities of residual effects. We compare estimates of genetic parameters by fitting multivariate Normal (MN) or heavy-tail distributions (multivariate Student's t and multivariate Slash, MSt and MS) for residuals in data of hot carcass weight (HCW), longissimus muscle area (REA) and 12th to 13th rib fat (FAT) traits in beef cattle using 2475 records from 2007 to 2008 from a large commercial operation in Nebraska. Model comparisons using deviance information criteria (DIC) favoured MSt over MS and MN models, respectively. The posterior means (and 95% posterior probability intervals, PPI) of v for the MSt and MS models were 5.89 ± 0.90 (4.35, 7.86) and 2.04 ± 0.18 (1.70, 2.41), respectively. Smaller values of posterior densities of v for MSt and MS models confirm that the assumption of normally distributed residuals is not adequate for the analysis of the data set. Posterior mean (PM) and posterior median (PD) estimates of direct genetic variances were variable with MSt having the highest mean value followed by MS and MN, respectively. Posterior inferences on genetic variance were, however, comparable among the models for FAT. Posterior inference on additive heritabilities for HCW, REA and FAT using MN, MSt and MS models indicated similar and moderate heritability comparable with the literature. Posterior means of genetic correlations for carcass traits were variable but positive except for between REA and FAT, which showed an antagonistic relationship. We have demonstrated that genetic evaluation and selection strategies will be sensitive to the assumed model for residuals.

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.

Maternal influence on feeding site selection of male and female lambs.

We conducted an experiment to determine whether early-life social learning of feeding site selection in lambs was sex-specific. Sixteen ewes and their new born lambs were used in a controlled experiment. Eight ewe-lamb pairs included a male lamb and the remaining eight a female lamb. All pairs were individually exposed to an experimental arena containing a safe and unsafe artificial feeding site (SFS, UFS) each consisting of nine bowls which contained either ground Bermuda grass hay (SFS) or ground alfalfa hay (UFS). The bowls in UFS were surrounded by bright orange traffic cones (visual cues). Half the ewes were trained with controlled electric shock to avoid UFS. Thus, pairs were randomly assigned to: (1) shock aversion training (SAT) to mothers of male lambs (MS); (2) SAT to mothers of female lambs (FS); (3) no aversion training (NAT, control) to mothers of male lambs (MC); and (4) NAT (control) to mothers of female lambs (FC). None of the lambs were subjected to SAT. During training, testing, extinction, and retraining ewe-lamb pairs were exposed to the arena together. Ewes were then removed from the experiment and two additional extinction phases were conducted with weaned lambs alone. Fear conditioning elicited UFS avoidance of both the trained ewes (means±s.e.m. % times observed in UFS during testing phase: FC=95.3±1.70; MC=94.4±4.87; FS=1.6±1.63; MS=0 ±0; P<0.01) and their naïve lambs (FC=83.8±6.07%; MC=76.6±6.56%; FS=30.4±7.90%; MS=33.9±9.23%; P<0.01). UFS avoidance in lambs occurred regardless of sex and tended to persist after weaning (% times observed in UFS during 1st post-weaning extinction phase: FC=92.6±4.50%; MC=89.8±6.09%; FS=45.1±10.57%; MS=43.5±10.42%; P=0.06). Fear conditioning in mothers appeared to alter sex-related differences in mother-infant behavioral synchrony by increasing and decreasing feeding synchrony of male and female lambs, respectively (FC: r=0.52, P<0.01; MC: r=-0.02, P=0.86; FS: r=0.14, P=0.26; MS: r=0.46, P<0.01). During the extinction phase mothers of ram lambs were observed feeding more often (FC=85.0±2.33%; MC=92.7±1.45%; FS=47.3±8.81%; MS=72±5.68%; P=0.02) and standing less often than ewes with daughters (FC=7.3±2.40%; MC=2.7±0.83%; FS=39.3±9.04%; MS=18.0±5.29%; P=0.06). This study suggests that social conditioning at an early age could be a viable tool to induce learning of feeding site avoidance in female and male lambs alike.

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.

Beef cattle body temperature during climatic stress: a genome-wide association study.

Cattle are reared in diverse environments and collecting phenotypic body temperature (BT) measurements to characterize BT variation across diverse environments is difficult and expensive. To better understand the genetic basis of BT regulation, a genome-wide association study was conducted utilizing crossbred steers and heifers totaling 239 animals of unknown pedigree and breed fraction. During predicted extreme heat and cold stress events, hourly tympanic and vaginal BT devices were placed in steers and heifers, respectively. Individuals were genotyped with the BovineSNP50K_v2 assay and data analyzed using Bayesian models for area under the curve (AUC), a measure of BT over time, using hourly BT observations summed across 5-days (AUC summer 5-day (AUCS5D) and AUC winter 5-day (AUCW5D)). Posterior heritability estimates were moderate to high and were estimated to be 0.68 and 0.21 for AUCS5D and AUCW5D, respectively. Moderately positive correlations between direct genomic values for AUCS5D and AUCW5D (0.40) were found, although a small percentage of the top 5% 1-Mb windows were in common. Different sets of genes were associated with BT during winter and summer, thus simultaneous selection for animals tolerant to both heat and cold appears possible.

A simulation-based approach for evaluating and comparing the environmental footprints of beef production systems.

A methodology was developed and used to determine environmental footprints of beef cattle produced at the U.S. Meat Animal Research Center (MARC) in Clay Center, NE, with the goal of quantifying improvements achieved over the past 40 yr. Information for MARC operations was gathered and used to establish parameters representing their production system with the Integrated Farm System Model. The MARC farm, cow-calf, and feedlot operations were each simulated over recent historical weather to evaluate performance, environmental impact, and economics. The current farm operation included 841 ha of alfalfa and 1,160 ha of corn to produce feed predominately for the beef herd of 5,500 cows, 1,180 replacement cattle, and 3,724 cattle finished per year. Spring and fall cow-calf herds were fed on 9,713 ha of pastureland supplemented through the winter with hay and silage produced by the farm operation. Feedlot cattle were backgrounded for 3 mo on hay and silage with some grain and finished over 7 mo on a diet high in corn and wet distillers grain. For weather year 2011, simulated feed production and use, energy use, and production costs were within 1% of actual records. A 25-yr simulation of their current production system gave an average annual carbon footprint of 10.9±0.6 kg of CO2 equivalent units per kg BW sold, and the energy required to produce that beef (energy footprint) was 26.5±4.5 MJ/kg BW. The annual water required (water footprint) was 21,300±5,600 L/kg BW sold, and the water footprint excluding precipitation was 2,790±910 L/kg BW. The simulated annual cost of producing their beef was US$2.11±0.05/kg BW. Simulation of the production practices of 2005 indicated that the inclusion of distillers grain in animal diets has had a relatively small effect on environmental footprints except that reactive nitrogen loss has increased 10%. Compared to 1970, the carbon footprint of the beef produced has decreased 6% with no change in the energy footprint, a 3% reduction in the reactive nitrogen footprint, and a 6% reduction in the real cost of production. The water footprint, excluding precipitation, has increased 42% due to greater use of irrigated corn production. This proven methodology provides a means for developing the production data needed to support regional and national full life cycle assessments of the sustainability of beef.

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

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

Communication: Optical cooling of trans-stilbene.

Trans-stilbene in n-hexane is excited with excess vibrational energy in the range 0-7000 cm(-1). In the excited electronic state, the Raman linewidth of the ethylenic C=C stretching mode at 1570 cm(-1) is followed with ~100 fs time resolution. Upon excitation with substantial excess energy, the width of the peak is initially broad and then narrows within a few picoseconds, as observed previously by Iwata and Hamaguchi [Chem. Phys. Lett. 196, 462 (1992)]. This narrowing is understood as being caused by cooling of the initially hot molecule, by the surrounding solvent. In this Communication, we report that upon excitation without excess energy, the width is initially relatively narrow and then broadens on a picosecond time scale. The broadening is attributed to heating of the molecule by solvent collisions. It follows that the nascent population in the excited electronic state is cold as compared with the solvent. Such reduction of the initial vibrational energy may affect the rate for the subsequent photoreaction, especially in the absence of the solvent.

Application of multivariate heavy-tailed distributions to residuals in the estimation of genetic parameters of growth traits in beef cattle.

Assumptions of normality in most animal breeding applications may make inferences vulnerable to the presence of outliers. Heavy-tail densities are viable alternatives to normal distributions and provide robustness against unusual or outlying observations when used to model the densities of residual effects. Our objective is to compare estimates of genetic parameters by fitting multivariate normal (MN) or heavy-tail distributions [multivariate Student's t (MSt) and multivariate slash (MS)] for residuals in data of body birth weight (BBW), weaning (WW), and yearling (YW) weight traits in beef cattle. A total of 17,019 weight records for BBW, WW, and YW from 1998 through 2010 from a large commercial cow/calf operation in the sand hills of Nebraska were analyzed. Models included fixed effects of contemporary group and sire breed whereas animal and maternal effects were random and the degrees of freedom (v) was treated as unknown for MSt and MS. Model comparisons using deviance information criteria (DIC) favored MSt over MS and MN models, respectively. The posterior means [and 95% posterior probability intervals (PPI)] of v for the MSt and MS models were 5.28 (4.80, 5.85) and 1.88 (1.76, 2.00), respectively. Smaller values of posterior densities of v for MSt and MS models confirm that the assumption of normally distributed residuals is not adequate for the analysis of BBW, WW, and YW datasets. Posterior mean (PM) and posterior median (PD) estimates of direct and maternal genetic variances were the same and posterior densities of these parameters were found to be symmetric. The 95% PPI estimates from MN and MSt models for BBW did not overlap, which indicates significant difference between PM estimates from MN or MSt models. The observed antagonistic relationship between additive direct and additive maternal effects indicated that genetic evaluation and selection strategies will be sensitive to the assumed model for residuals.

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.

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.

Determination of the quantum contribution to the activated motion of hydrogen on a metal surface: H/Pt(111).

Measurements of the atomic-scale motion of H and D atoms on the Pt(111) surface, above the crossover temperature to deep tunneling, are presented. The results indicate that quantum effects are significant up to the highest temperature studied (250 K). The motion is shown to correspond to nearest neighbor hopping diffusion on a well defined fcc (111) lattice. The measurements provide information on the adiabatic potential of both the adsorption site and the transition state and give strong empirical support for a dissipative transition-state theory description of the quantum contribution to the motion.

Interlaboratory agreement in the monitoring of unfractionated heparin using the anti-factor Xa-correlated activated partial thromboplastin time.

BACKGROUND: In an effort to improve interlaboratory agreement in the monitoring of unfractionated heparin (UFH), the College of American Pathologists (CAP) recommends that the therapeutic range of the activated partial thromboplastin time (APTT) be defined in each laboratory through correlation with a direct measure of heparin activity such as the factor Xa inhibition assay. Whether and to what extent this approach enhances the interlaboratory agreement of UFH monitoring has not been reported. OBJECTIVES: We conducted a cross-validation study among four CAP-accredited coagulation laboratories to compare the interlaboratory agreement of the anti-FXa-correlated APTT with that of the traditional 1.5-2.5 times the midpoint of normal (1.5-2.5:control) method for defining the therapeutic APTT range. PATIENTS AND METHODS: APTT and FXa inhibition assays were performed in each laboratory on plasma samples from 44 inpatients receiving UFH. RESULTS: Using the anti-FXa-correlation method, there was agreement among all four laboratories as to whether a sample was subtherapeutic, therapeutic or supratherapeutic in seven (16%) patient samples. In contrast, consensus was achieved in 23 (52%) samples when the 1.5-2.5:control method was employed. CONCLUSIONS: The anti-FXa-correlation method does not appear to enhance interlaboratory agreement in UFH monitoring as compared with the traditional 1.5-2.5:control method. Adoption of the anti-FXa-correlation method produces considerable disparity in UFH dosing decisions among different centers, although the clinical impact of this disparity is not known.

Genetic evaluation of retail product percentage in Simmental cattle.

The objective of this study was to estimate genetic parameters required for genetic evaluation of retail product percentage (RPP) in Simmental cattle. Carcass weight (HCW), subcutaneous fat thickness (FAT), longissimus muscle area (REA) and kidney, pelvic, and heart fat (KPH) records were available to compute RPP on steers (n = 5171) and heifers (n = 1400) from the American Simmental Association database; animals were sired by 561 Simmental bulls and out of 5886 crossbred dams. Genetic parameters were estimated using residual maximal likelihood and a four trait animal model for the components of RPP including fixed harvest contemporary group effects, random animal genetic effects, and a linear covariate for age at harvest. Heritability estimates were 0.51 +/- 0.05, 0.36 +/- 0.05, 0.46 +/- 0.05, and 0.18 +/- 0.05 for HCW, FAT, REA and KPH respectively. Non-zero genetic correlations were estimated between HCW and REA (rg = 0.51 +/- 0.06) and between REA and FAT (rg = -0.43 +/- 0.08), but other genetic correlation estimates among the component traits were low. As a linear function of its components, heritability and genetic correlations involving RPP were estimated using index methods. The heritability estimate for RPP was 0.41, and genetic correlations were -0.17, -0.83, 0.67, and 0.01 with HCW, FAT, REA and KPH respectively. Therefore, RPP was strongly associated with muscle and fat deposition, but essentially independent of carcass weight and internal body cavity fat. Genetic evaluation of RPP would be straightforward using multiple trait index methods and genetic regression, although the inclusion of KPH would be of marginal value.