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Objective: To study the behavioral relevance of postural and ocular-motor deficits on daily activity and risk of falling in patients with bilateral vestibular hypofunction (BVH). Methods: Thirty patients with BVH and 30 age- and gender-matched healthy controls participated in a continuous 2-week assessment of daily activities and mobility using a body-worn inertial sensor and a 6-month prospective fall risk assessment. At inclusion, patients and controls further underwent a multi-modal clinical, score- and instrument-based assessment of general health and balance status. We analyzed the relationship between clinical, lab-, and sensor-based measures and their validity to identify those patients at a risk of general, frequent, and severe falling. Results: Patients exhibited impairments in daily activity in particular in terms of reduced ambulatory activity (p = 0.009). 43% of patients experienced falls (13% in controls, p = 0.008) and 70% of these patients reported recurrent falling (0% in controls, p = 0.001) during prospective assessment. Severe fall-related injuries that would require medical attention neither occurred in patients nor in controls. Classificatory models based on multi-modal clinical, lab-, and sensor-based measures of balance and mobility identified patients who fell with an accuracy of 93% and patients who recurrently fell with an accuracy of 89%. Conclusion: BVH is linked to particular impairments of patients' daily activities which in turn are related to patients' fall risk. Hence, off-laboratory measures of daily mobility may supplement standard clinical assessment in BVH to more adequately capture the burden of disease and to reliably identify those patients at a specific risk of falling. [ABSTRACT FROM AUTHOR]

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Summary: Identifying genes or genomic regions influencing carcass‐quality traits such as fatness (FTN) is essential to optimize the genetic selection processes in beef cattle. The aim of this study was to identify genomic regions associated with FTN in Nellore cattle as well as to elucidate the metabolic pathways related to the phenotypic expression. Ultrasound‐based measurements of FTN were collected in 11 750 animals, with 39 903 animals in the pedigree file. Additionally, 1440 animals were genotyped using the GGP‐indicus 35K SNP panel, which contained 33 623 SNPs after quality control. Twenty genes related to FTN were found on 11 chromosomes, explaining 12.96% of the total additive genetic variance. Gene ontology revealed seven genes: NR1L2, PKD2, GSK3β, EXT1, RAD51B, SORCS1 and DPH6, associated with important processes related to FTN. In addition, novel candidate genes (MAATS1, LYPD1, CDK5RAP2, RAD51B, c13H2Oorf96 and TRAPPC11) were detected and could provide further knowledge to uncover genetic regions associated to carcass fatness in beef cattle. [ABSTRACT FROM AUTHOR]

The aim of this study was to establish a comprehensive and yet parsimonious model of daily mobility activity in patients with neurological gait disorders. Patients (N = 240) with early-stage neurological (peripheral vestibular, cerebellar, hypokinetic, vascular or functional) gait disorders and healthy controls (N = 35) were clinically assessed with standardized scores related to functional mobility, balance confidence, quality of life, cognitive function, and fall history. Subsequently, daily mobility was recorded for 14 days by means of a body-worn inertial sensor (ActivPAL®). Fourteen mobility measures derived from ActivPAL recordings were submitted to principle component analysis (PCA). Group differences within each factor obtained from PCA were analyzed and hierarchical regression analysis was performed to identify predictive characteristics from clinical assessment for each factor. PCA yielded five significant orthogonal factors (i.e., mobility domains) accounting for 92.3% of the total variance from inertial-sensor-recordings: ambulatory volume (38.7%), ambulatory pattern (22.3%), postural transitions (13.3%), sedentary volume (10.8%), and sedentary pattern (7.2%). Patients' mobility performance only exhibited reduced scores in the ambulatory volume domain but near-to-normal scores in all remaining domains. Demographic characteristics, clinical scores, and fall history were differentially associated with each domain explaining 19.2–10.2% of their total variance. This study supports a low-dimensional five-domain model for daily mobility behavior in patients with neurological gait disorders that may facilitate monitoring the course of disease or therapeutic intervention effects in ecologically valid and clinically relevant contexts. Further studies are required to explore the determinants that may explain performance differences of patients within each of these domains and to examine the consequences of altered mobility behavior with respect to patients' risk of falling and quality of life. [ABSTRACT FROM AUTHOR]

Summary: Deviation from Mendelian inheritance expectations (transmission ratio distortion, TRD) has been observed in several species, including the mouse and humans. In this study, TRD was characterized in the turkey genome using both allelic (specific‐ and unspecific‐parent TRD) and genotypic (additive‐ and dominance‐TRD) parameterizations within a Bayesian framework. In this study, we evaluated TRD for 23 243 genotyped Turkeys across 56 393 autosomal SNPs. The analyses included 500 sires, 2013 dams and 11 047 offspring (trios). Three different haplotype sliding windows of 4, 10 and 20 SNPs were used across the autosomal chromosomes. Based on the genotypic parameterizations, 14 haplotypes showed additive and dominance TRD effects highlighting regions with a recessive TRD pattern. In contrast, the allelic model uncovered 12 haplotype alleles with the allelic TRD pattern which showed an underrepresentation of heterozygous offspring in addition to the absence of homozygous animals. For regions with the allelic pattern, only one particular region showed a parent‐specific TRD where the penetrance was high via the dam, but low via the sire. The gene set analysis uncovered several gene ontology functional terms, Reactome pathways and several Medical Subject Headings that showed significant enrichment of genes associated with TRD. Many of these gene ontology functional terms (e.g. mitotic spindle assembly checkpoint, DRM complex and Aneuploidy), Reactome pathways (e.g. Mismatch repair) and Medical Subject Headings (e.g. Adenosine monophosphate) are known to be related to fertility, embryo development and lethality. The results of this study revealed potential novel candidate lethal haplotypes, functional terms and pathways that may enhance breeding programs in Turkeys through reducing mortality and improving reproduction rate. [ABSTRACT FROM AUTHOR]

The application of hyperspectral image analysis for land cover classification is mainly executed in presence of manually labeled data. The ground truth represents the distribution of the actual classes and it is mostly derived from field recorded information. Its manual generation is ineffective, tedious and very time-consuming. The continuously increasing amount of proprietary and publicly available datasets makes it imperative to reduce these related costs. In addition, adequately equipped computer systems are more capable of identifying patterns and neighbourhood relationships than a human operator. Based on these facts, an unsupervised labeling approach is presented to automatically generate labeled images used during the training of a convolutional neural network (CNN) classifier. The proposed method begins with the segmentation stage where an adapted version of the simple linear iterative clustering (SLIC) algorithm for dealing with hyperspectral data is used. Consequently, the Hierarchical Agglomerative Clustering (HAC) and Fuzzy C-Means (FCM) algorithms are employed to efficiently group similar superpixels considering distances with respect to each other. The distinct utilization of these clustering techniques defines a complementary stage for overcoming class overlapping during image generation. Ultimately, a CNN classifier is trained using the computed image to pixel-wise predict classes on unseen datasets. The labeling results, obtained using two hyperspectral benchmark datasets, indicate that the current approach is able to detect objects boundaries, automatically assign class labels to the entire dataset and to classify new data with a prediction certainty of 90%. Additionally, this method is also capable of achieving better classification accuracy and visual correspondence with reality than the ground truth images. [ABSTRACT FROM AUTHOR]

Hyperspectral data recorded by future earth observation satellites will have up to hundreds of narrow bands that cover a wide range of the electromagnetic spectrum. The spatial resolution (around 30 meters) of such data, however, can impede the integration of the spatial domain for a classification due to spectrally mixed pixels and blurred edges in the data. Hence, the ability of performing a meaningful classification only relying on spectral information is important. In this study, a model for the spectral classification of hyperspectral data is derived by strategically optimizing a convolutional neural network (1D-CNN). The model is pre-trained and optimized on imagery of different nuts, beans, peas and dried fruits recorded with the Cubert ButterflEye X2 sensor. Subsequently, airborne hyperspectral datasets (Greding, Indian Pines and Pavia University) are used to evaluate the CNN's capability of transfer learning. For that, the datasets are classified with the pre-trained weights and, for comparison, with the same model architecture but trained from scratch with random weights. The results show substantial differences in classification accuracies (from 71.8% to 99.8% overall accuracy) throughout the used datasets, mainly caused by variations in the number of training samples, the spectral separability of the classes as well as the existence of mixed pixels for one dataset. For the dataset that is classified least accurately, the greatest improvement with pre-training is achieved (difference of 3.3% in overall accuracy compared to the non-pre-trained model). For the dataset that is classified with the highest accuracy, no significant transfer learning was observed. [ABSTRACT FROM AUTHOR]

Summary: High blood cholesterol concentration, mainly caused by high dietary cholesterol, is a potential risk factor for human health. Dairy products are important sources of human dietary cholesterol intake. Therefore, monitoring bovine milk cholesterol concentration is important for human health benefit. Genetic selection for improvement of cow milk cholesterol content requires understanding of the genetics of milk cholesterol. For this purpose, we performed analyses of additive and dominance effects of 126 potentially functional SNPs within 43 candidate genes with milk cholesterol content [expressed as mg of cholesterol in 100 g of fat (CHL_fat) or in 100 mg of milk (CHL_milk)]. The additive and dominance effects of SNPs rs380643365 in AGPAT1 (P = 0.04) and rs134357240 in SOAT1 (P = 0.035) genes associated significantly with CHL_fat. Moreover, five (rs109326954 and rs523413537 in DGAT1, rs109376747 in LDLR, rs42781651 in FAM198B and rs109967779 in ACAT2) and four (rs137347384 in RBM19, rs109376747 in LDLR, rs42016945 in PPARG and rs110862179 in SCAP) SNPs were significantly associated with CHL_milk (P < 0.05) based on additive and dominance effect analyses respectively. Rs109326954 and rs523413537 in DGAT1 explained a considerable portion of the phenotypic variance of CHL_milk (7.54 and 6.84% respectively), and might be useful in selection programs for reduced milk cholesterol content. Several significantly associated SNPs were in genes (such as ACAT2 and LDLR) involved in cholesterol metabolism in the liver or cholesterol transport, suggesting multiple mechanisms regulating milk cholesterol content. Nine and seven SNPs identified by additive or dominance effect analyses associated significantly with milk yield and fat yield respectively. Further analyses are required to better understand the consequences of these variants and their potential use in genomic selection of the studied traits. [ABSTRACT FROM AUTHOR]

The Canadian dairy industry has been using in vivo and in vitro assisted reproductive technologies to produce embryos. Technological improvements have helped increase the number and quality of embryos produced, but genetic and genomic tools for improving these traits have yet to be assessed for the Canadian Holstein population. Genetic parameters and a genome-wide association study were performed in Canadian Holstein for the total number of embryos (NE) and the number of viable embryos (VE). Results showed potential for genetic selection for both NE and VE, with heritability estimates (± s.e.) of approximately 0.15 ± 0.01. Genetic correlations between the number of embryos produced using different procedures (in vivo and in vitro) suggested that a similar number of embryos should be expected from a donor regardless of the procedure used. A region on chromosome 11 of the bovine genome was found to be significantly associated with the number of embryos, indicating a potential regulatory role of this region on embryo production. Overall, these findings are of interest for the Canadian dairy industry because they provide useful information for breeders that are interested in producing embryos from the elite donors in their herds or in the population using assisted reproductive technologies. [ABSTRACT FROM AUTHOR]

In the present study, different random regression models, focussed on the nature of the effect of the contemporary group, fixed or random, were compared for genetic evaluation of test-day milk yield in dairy Gir breed, whose herds are characterised by relatively reduced numbers of cows. Cows were assigned to the same contemporary group if they were tested in the same herd, year and month. In one of the evaluated models, the contemporary group was investigated as a fixed effect and a clustering procedure was adopted to group herd-year subclasses in order to, at the end of the process, all contemporary groups contained at least three cows. The models were compared by the quality of fit, the accuracy of the predicted breeding values and their estimates of genetic parameters. The clustering procedure did not significantly improve the accuracy of predicted breeding values. Moreover, the fit to the data for this model was negatively affected. Therefore, this strategy should not be further implemented. The model including the herd-calving period effect and contemporary group treated as random effect showed similar characteristics to its equivalent, where the contemporary group was modelled as a fixed effect. However, the fit to the data for this model was slightly worse. Thus, the results suggest a random regression model including the herd-calving period effect and the fixed effect of contemporary group for the genetic evaluations of production traits in dairy Gir cattle. These findings could be extended to small dairy cattle populations whose herds are small-sized. Several small populations of cattle are important genetic resources for the milk production systems, mainly in the Tropics. Obtaining accurate evaluation of the genetic merit of the animals in these populations requires consideration of some particularities. We compare alternatives to include the contemporary group in the model for genetic evaluation and our results showed that consider the contemporary group as a fixed effect without clustering herds is a better option than clustering herds to increase the size of contemporary groups. [ABSTRACT FROM AUTHOR]

The uptake of genomic selection (GS) by the swine industry is still limited by the costs of genotyping. A feasible alternative to overcome this challenge is to genotype animals using an affordable low-density (LD) single nucleotide polymorphism (SNP) chip panel followed by accurate imputation to a high-density panel. Therefore, the main objective of this study was to screen incremental densities of LD panels in order to systematically identify one that balances the tradeoffs among imputation accuracy, prediction accuracy of genomic estimated breeding values (GEBVs), and genotype density (directly associated with genotyping costs). Genotypes using the Illumina Porcine60K BeadChip were available for 1378 Duroc (DU), 2361 Landrace (LA) and 3192 Yorkshire (YO) pigs. In addition, pseudo-phenotypes (de-regressed estimated breeding values) for five economically important traits were provided for the analysis. The reference population for genotyping imputation consisted of 931 DU, 1631 LA and 2103 YO animals and the remainder individuals were included in the validation population of each breed. A LD panel of 3000 evenly spaced SNPs (LD3K) yielded high imputation accuracy rates: 93.78% (DU), 97.07% (LA) and 97.00% (YO) and high correlations (>0.97) between the predicted GEBVs using the actual 60 K SNP genotypes and the imputed 60 K SNP genotypes for all traits and breeds. The imputation accuracy was influenced by the reference population size as well as the amount of parental genotype information available in the reference population. However, parental genotype information became less important when the LD panel had at least 3000 SNPs. The correlation of the GEBVs directly increased with an increase in imputation accuracy. When genotype information for both parents was available, a panel of 300 SNPs (imputed to 60 K) yielded GEBV predictions highly correlated (⩾0.90) with genomic predictions obtained based on the true 60 K panel, for all traits and breeds. For a small reference population size with no parents on reference population, it is recommended the use of a panel at least as dense as the LD3K and, when there are two parents in the reference population, a panel as small as the LD300 might be a feasible option. These findings are of great importance for the development of LD panels for swine in order to reduce genotyping costs, increase the uptake of GS and, therefore, optimize the profitability of the swine industry. [ABSTRACT FROM AUTHOR]

Characterizing ruminal parameters in the context of sampling routine and feed efficiency is fundamental to understand the efficiency of feed utilization in the bovine. Therefore, we evaluated microbial and volatile fatty acid (VFA) profiles, rumen papillae epithelial and stratum corneum thickness and rumen pH (RpH) and temperature (RT) in feedlot cattle. In all, 48 cattle (32 steers plus 16 bulls), fed a high moisture corn and haylage-based ration, underwent a productive performance test to determine residual feed intake (RFI) using feed intake, growth, BW and composition traits. Rumen fluid was collected, then RpH and RT logger were inserted 5.5±1 days before slaughter. At slaughter, the logger was recovered and rumen fluid and rumen tissue were sampled. The relative daily time spent in specific RpH and RT ranges were determined. Polynomial regression analysis was used to characterize RpH and RT circadian patterns. Animals were divided into efficient and inefficient groups based on RFI to compare productive performance and ruminal parameters. Efficient animals consumed 1.8 kg/day less dry matter than inefficient cattle (P⩽0.05) while achieving the same productive performance (P⩾0.10). Ruminal bacteria population was higher (P⩽0.05) (7.6×1011v. 4.3×1011 copy number of 16S rRNA gene/ml rumen fluid) and methanogen population was lower (P⩽0.05) (2.3×109v. 4.9×109 copy number of 16S rRNA gene/ml rumen fluid) in efficient compared with inefficient cattle at slaughter with no differences (P⩾0.10) between samples collected on-farm. No differences (P⩾0.10) in rumen fluid VFA were also observed between feed efficiency groups either on-farm or at slaughter. However, increased (P⩽0.05) acetate, and decreased (P⩽0.05) propionate, butyrate, valerate and caproate concentrations were observed at slaughter compared with on-farm. Efficient had increased (P⩽0.05) rumen epithelium thickness (136 v. 126 µm) compared with inefficient cattle. Efficient animals also spent 318% and 93.2% more time (P⩽0.05) in acidotic (4.14% v. 1.30%) (pH⩽5.6) and optimal (5.6v. 4.42%) RpH range compared with inefficient cattle. The circadian patterns revealed lower (P⩽0.05) RpH and no differences (P⩾0.10) in RT pre-, during, and post-prandial periods in efficient compared with inefficient cattle. In essence, superior feed efficiency in cattle seems linked to rumen features consistent with improved efficiency of feed utilization. Microbial abundance, rumen epithelial histomorphology, and RpH, may serve as indicators for feed efficiency in cattle. The divergences of assessments made on-farm and at slaughter should be considered in the development of proxies for feed efficiency. [ABSTRACT FROM AUTHOR]

Summary: We aimed to investigate the performance of three deregression methods (VanRaden, VR; Wiggans, WG; and Garrick, GR) of cows’ and bulls’ breeding values to be used as pseudophenotypes in the genomic evaluation of test‐day dairy production traits. Three scenarios were considered within each deregression method: (i) including only animals with reliability of estimated breeding value (RELEBV ) higher than the average of parent reliability (RELPA ) in the training and validation populations; (ii) including only animals with RELEBV higher than 0.50 in the training and RELEBV higher than RELPA in the validation population; and (iii) including only animals with RELEBV higher than 0.50 in both training and validation populations. Individual random regression coefficients of lactation curves were predicted using the genomic best linear unbiased prediction (GBLUP), considering either unweighted or weighted residual variances based on effective records contributions. In summary, VR and WG deregression methods seemed more appropriate for genomic prediction of test‐day traits without need for weighting in the genomic analysis, unless large differences in RELEBV between training population animals exist. [ABSTRACT FROM AUTHOR]

Background The number of Standardbred racehorses admitted to the Ontario Veterinary College Teaching Hospital (Guelph, Canada) for treatment of atrial fibrillation ( AF) has been on the rise since the early 1990s. A small number of sires have been contributing to a large proportion of cases, indicating there may be a genetic predisposition to the arrhythmia in this breed. Objectives The objectives of this study were to determine the heritability of AF in Standardbred horses and whether heritability of the arrhythmia differs across gaits and/or sexes. Study design Heritability study based on retrospective review of clinical records and publicly available pedigree and racing records. Methods Standardbred horses admitted to hospital for treatment of AF that were born between 1978 and 2007 comprised the affected case population (n = 204). Five randomly selected racing contemporaries for each case, assumed to not suffer from the arrhythmia, comprised the control population (n = 1017). Racing contemporaries were identified by examining the race records of affected horses within the 6 months prior to their admission, and randomly selecting sex- and gait-matched horses from these races. Heritability was estimated from the sampled horses as a whole (n = 1221), as well as for both sexes and gaits, using a generalised linear mixed model. Results Heritability of AF on the underlying liability scale was estimated to be (±s.e.) 0.30±0.04 in the entire data set; 0.30±0.06 in males; 0.24±0.08 in females; and 0.32±0.05 in pacers. After conversion to the observed scale, heritability estimates were 0.14, 0.15, 0.09 and 0.15, respectively. Main limitations There were insufficient data to estimate heritability of AF for trotters. Conclusions Modest heritability estimates were found for AF in the Standardbred horse, particularly in males and pacers, which support the hypothesis that there is a genetic contribution to the arrhythmia in this breed. The Summary is available in Chinese - See Supporting Information. [ABSTRACT FROM AUTHOR]

Proxies have the potential to accelerate feed efficiency (residual feed intake (RFI); kg dry matter/day) improvement, assisting with the reduction of beef cattle feed costs and environmental impact. Heart rate (HR) (beats per minute (BPM)) is associated with feed efficiency and influenced by autonomic activity and peripheral metabolism, suggesting HR could be used as a proxy for feed efficiency. Objectives were to assess associations between overnight HR, lying patterns and RFI, and between acute stress HR and RFI. Heifer calves (n=107; 408±28 days of age, 341±42.2 kg) and yearling heifers (n=36; 604±92 days of age, 539±52.2 kg) were exposed to a performance test to determine productive performance. Overnight HR (electrode based) and lying patterns (accelerometer based) were monitored on a subgroup of heifer calves (n=40; 20 lowest RFI; 20 highest RFI). In the 10-min acute stress assessment, all heifers were individually exposed to the opening and closing of an umbrella and HR before (HRBEF), in response to (HRMAX), after (HRAFT) and change (HRCHG; HRAFT−HRBEF) as a result of exposure were determined. Using polynomial regression, rate of HR decrease pre-exposure (β1) and rates of HR increase (β2) and decrease (β3, β4) post-exposure were determined. Heifer calves in the overnight assessment were classified into equal RFI groups (low RFI; high RFI) and HR means were treated as repeated measures and compared using multiple regression. In the acute stress assessment, heifers were classified within cattle category into equal RFI groups (low RFI; high RFI) and means and polynomial regression parameters were compared using multiple regression. Low-RFI heifer calves had a lower overnight HR (69.2 v. 72.6 BPM), similar HR change from lying to standing intervals (8.9 v. 9.2 BPM) and similar time lying (61.1% v. 64.5%) compared with high-RFI heifer calves. Low-RFI heifer calves had a higher absolute HRMAX (162.9 v. 145.7 BPM) and β2 (−0.34 v. −0.20) than high-RFI heifer calves. Low-RFI yearling heifers had similar acute stress HR means and a lower β1 (0.003 v. 0.006) than high-RFI yearling heifers. Overnight HR and acute stress HR are potential indicators of RFI in heifer calves. However, acute stress HR results varied in yearling heifers, suggesting previous handling experience and/or age influence stress response. Pending further development (predictive ability, repeatability), the acute stress assessment could have potential for on-farm application as a feed efficiency proxy in young heifers with minimal handling experience. [ABSTRACT FROM PUBLISHER]

Genomic prediction for crossbred beef cattle has shown limited results using low- to moderate-density SNP panels. The relationship between the training and validation populations, as well as the size of the reference population, affects the prediction accuracy for genomic selection. Rotational crossbreeding systems require the usage of crossbred animals as sires and dams of future generations, so crossbred animals require accurate evaluation. Here, a novel method for grouping of purebred and crossbred animals (based exclusively on genotypes) for genomic selection was investigated. Clustering of animals to investigate the genetic similarity among different groups was performed using several genomic relationship criteria between individuals. Hierarchical clusters based on average-link criteria (computed as the mean distance between elements of each subcluster) were formed. The accuracy of genomic prediction was assessed using 1,500 bulls genotyped for 54,609 markers. Estimated breeding values based on all available phenotypic records for birth weight, weaning gain, postweaning gain, and yearling gain were calculated using BLUP methodologies and deregressed to ensure unbiased comparisons could be made across populations. A 5-fold validation technique was used to calculate direct genomic values for all genotyped bulls; the addition of unrelated animals in the reference population was also investigated. We demonstrate a decrease in genomic selection accuracy after including animals from disconnected clusters. A method to improve genomic selection for crossbred and purebred animals by clustering animals based on their genotype is suggested. Unlike traditional approaches for genomic selection with a fixed reference population, genomic prediction using clusters (GPC) chooses the best reference population for better accuracy of genomic prediction of crossbred and purebred animals using clustering methods based on genotypes. An overall average gain in accuracy of 1.30% was noted over all scenarios across all traits investigated when the GPC approach was implemented. Further investigation is required to assess this difference in accuracy when a larger genotyped population is available, especially for the comparison of groups with higher genetic dissimilarity, such as those found in industry-wide across-breed genetic evaluations. [ABSTRACT FROM AUTHOR]

The accuracy of genomic predictions can be used to assess the utility of dense marker genotypes for genetic improvement of beef efficiency traits. This study was designed to test the impact of genomic distance between training and validation populations, training population size, statistical methods, and density of genetic markers on prediction accuracy for feed efficiency traits in multibreed and crossbred beef cattle. A total of 6,794 beef cattle data collated from various projects and research herds across Canada were used. Illumina BovineSNP50 (50K) and imputed Axiom Genome-Wide BOS 1 Array (HD) genotypes were available for all animals. The traits studied were DMI, ADG, and residual feed intake (RFI). Four validation groups of 150 animals each, including Angus (AN), Charolais (CH), Angus-Hereford crosses (ANHH), and a Charolais-based composite (TX) were created by considering the genomic distance between pairs of individuals in the validation groups. Each validation group had 7 corresponding training groups of increasing sizes (n = 1,000, 1,999, 2,999, 3,999, 4,999, 5,998, and 6,644), which also represent increasing average genomic distance between pairs of individuals in the training and validations groups. Prediction of genomic estimated breeding values (GEBV) was performed using genomic best linear unbiased prediction (GBLUP) and Bayesian method C (BayesC). The accuracy of genomic predictions was defined as the Pearson's correlation between adjusted phenotype and GEBV (r), unless otherwise stated. Using 50K genotypes, the highest average r achieved in purebreds (AN, CH) was 0.41 for DMI, 0.34 for ADG, and 0.35 for RFI, whereas in crossbreds (ANHH, TX) it was 0.38 for DMI, 0.21 for ADG, and 0.25 for RFI. Similarly, when imputed HD genotypes were applied in purebreds (AN, CH), the highest average r was 0.14 for DMI, 0.15 for ADG, and 0.14 for RFI, whereas in crossbreds (ANHH, TX) it was 0.38 for DMI, 0.22 for ADG, and 0.24 for RFI. The r of GBLUP predictions were greatly reduced with increasing genomic average distance compared to those from BayesC predictions. The results indicate that 50K genotypes, used with BayesC, are more effective for predicting GEBV in purebred cattle. Imputed HD genotypes found utility when dealing with composites and crossbreds. Formulation of a fairly large training set for genomic predictions in beef cattle should consider the genomic distance between the training and target populations. [ABSTRACT FROM AUTHOR]

Mycobacterium avium ssp. paratuberculosis ( MAP) causes chronic enteritis in cattle that results in substantial financial losses to the cattle industry worldwide. Given that susceptibility to MAP infection is determined in part by genetics, marker-assisted selection may help in the breeding of animals that are more resistant to MAP infection. The toll-like receptor 4 gene ( TLR4) was selected as a potential candidate gene because of its role in innate immunity and its involvement in MAP recognition and infection. The objective of this study, therefore, was to identify associations between TLR4 polymorphisms and susceptibility to MAP infection in Canadian Holstein cows. Two biologically relevant SNPs, including c.-226G>C in the 5′-untranslated region and the non-synonymous SNP c.2021C>T in the potential TIR domain, were selected for an association analysis with MAP infection status in 409 Canadian Holsteins. The haplotype C-T from these combined SNPs yielded significant association with susceptibility to MAP infection, supporting the involvement of TLR4 in susceptibility to MAP infection. [ABSTRACT FROM AUTHOR]

In order to achieve improvements in production efficiency in livestock, herds of high sexual precocity and good fertility are needed. These traits increase the availability of animals in herd, either for sale or selection, allowing both greater selective intensity and greater genetic progress. This study aimed at estimating genetic parameters for reproductive traits measured directly in females in order to verify whether they could be used as selection criteria for genetic improvement in Nellore cows, as well as estimating the genetic relationship among these traits and scrotal circumference (SC), the traditional selection criterion for sexual precocity in cattle. In addition to SC, stayability (STAY), number of calvings at 53 months (NC53) and heifers rebreeding (HR) were studied. The (co)variances and genetic parameters were estimated using Bayesian inference. STAY, NC53 and HR were analyzed assuming a threshold model, whereas SC was analyzed with a linear model. Heritability estimated for NC53 was 0.22, and this trait was strongly and positively correlated with STAY, meaning selection for NC53 would improve productive longevity of Nellore cows. Correlations estimated between HR and STAY (≈0.97) and between HR and NC53 (≈0.99) allow an improvement on HR rates if selection was applied to traits related to longevity. Genetic correlations among SC and female reproductive traits were positive but weak, suggesting the need to use reproductive traits directly measured in females in order to obtain greater improvements in sexual precocity and longevity. [ABSTRACT FROM PUBLISHER]

The characterization of blood metabolite concentrations over the circadian period and across physiological stages is important for understanding the biological basis of feed efficiency, and may culminate in indirect methods for assessing feed efficiency. Hematological analyses for albumin, urea, creatine kinase, glutamate dehydrogenase, aspartate aminotransferase, carbon dioxide, and acetate were carried out in growing and gestating heifers. These measures were carried out in a sample of 36 Bos taurus crossed beef heifers held under the same husbandry conditions. Hourly blood samples were collected over a 24-h period on three separate sampling occasions, corresponding approximately to the yearling (and open), early-gestation and late-gestation stages. This design was used to determine variation throughout the day, effects due to physiological status and any associations with feed efficiency, as measured by residual feed intake. Blood analyte levels varied with time of day, with the most variation occurring between 0800 and 1600 h. There were also considerable differences in analyte levels across the three physiological stages; for example, creatine kinase was higher (P<0.05) in open heifers, followed by early- and late-gestation heifers. Feed efficiency was also associated with analyte abundance. In more feed-efficient open heifers, there were higher activities of creatine kinase (P<0.05) and aspartate aminotransferase (P<0.05), and lower concentrations of carbon dioxide (P<0.05). Furthermore, in late gestation, more efficient heifers had lower urea concentrations (P<0.05) and lower creatine kinase levels (P<0.05). Over the whole experimental period, carbon dioxide concentrations were numerically lower in more feed efficient heifers (P=0.079). Differences were also observed across physiological stages. For instance, open heifers had increased levels (P<0.05) of creatine kinase, aspartate aminotransferase, carbon dioxide than early and late pregnancy heifers. In essence, this study revealed relevant information about the metabolic profile in the context of feed efficiency and physiological stages. Further optimization of our approach, along with the evaluation of complementary analytes, will aid in the development of robust, indirect assessments of feed efficiency. [ABSTRACT FROM PUBLISHER]

Genotyping with lower density but lower cost panels enables more animals to be genotyped for genomic selection. Imputation enables the determination of missing SNP genotypes in animals genotyped with a low-density panel by using information from a reference population genotyped with a higher density panel, which should increase accuracy of genomic EBV. In this study, population imputation, using linkage disequilibrium among markers, was implemented using the software BEAGLE, FIMPUTE 2.2, and IMPUTE2 in a multibreed, crossbred taurine beef cattle population genotyped with the Illumina SNP50. Different combinations of reference populations and imputed animals were defined based on breed composition. Number of animals (n = 250 to 4,932) and the presence of closer relatives in the reference population (only for Angus animals) were investigated. The overall average imputation accuracy for purebred animals ranged from 94.20 to 97.93% using FIMPUTE, from 95.35 to 98.31% using IMPUTE2, and from 90.02 to 96.38% when BEAGLE software was used. Imputation accuracy of crossbred animals ranged from 54.15 to 97.53% (FIMPUTE), from 57.04 to 97.46% (IMPUTE2), and from 54.35 to 95.64% (BEAGLE). Higher imputation accuracies were obtained when closer relatives along with the breed composition of imputed animals was well represented in the reference population. Within breed imputation from 6K to 50K did not improve when an additional purebred population was added to the reference population. FIMPUTE reduced the run time by 13 to 52 times compared to BEAGLE and 51 to 108 times compared to IMPUTE2. [ABSTRACT FROM AUTHOR]

• Prediction of methane emission based on the GreenFeed system data is not explored. • Prediction models were developed for methane production, yield and intensity. • Models were developed from combinations of milk spectra and performance traits. • The prediction models can be utilized to generate largescale methane emission data. • Large scale methane data can be used to reduce methane emission from dairy cattle. Methane emission is not included in the current breeding goals for dairy cattle mainly due to the expense and difficulty in obtaining sufficient data to generate accurate estimates of the relevant traits. While several models have been developed to predict methane emission from milk spectra using reference methane data obtained by the respiration chamber, SF6 and sniffer methods, the prediction of methane emission from milk mid-infrared (MIR) spectra using reference methane data collected by the GreenFeed system has not yet been explored. Methane emission was monitored for 151 cows using the GreenFeed system. Prediction models were developed for daily and average (for the trial period of 12 or 14 days) methane production (g/d), yield (g/kg DM intake (DMI)) and intensity (g/kg of fat- and protein-corrected milk) using partial least squares regression. The predictions were evaluated in 100 repeated validation cycles, where animals were randomly partitioned into training (80%) and testing (20%) populations for each cycle. The best performing model was observed for average methane intensity using MIR, parity and DMI with validation coefficient of determination ( R 2 val ) and RMSE of prediction of 0.66 and 4.7 g/kg of fat- and protein-corrected milk, respectively. The accuracy of the best models for average methane production and average methane yield were poor (R 2 val = 0.28 and 0.12, respectively). A lower accuracy of prediction was observed for methane intensity and production (R 2 val = 0.42 and 0.17) when daily records were used while prediction for methane yield was comparable to that for average methane yield (R 2 val = 0.16). Our results suggest the potential to predict methane intensity with moderate accuracy. In this case, prediction models for average methane values were generally better than for daily measures when using the GreenFeed system to obtain reference methane emission measurements. [ABSTRACT FROM AUTHOR]

In beef cattle, phenotypic data that are difficult and/or costly to measure, such as feed effi-ciency, and DNA marker genotypes are usually avail-able on a small number of animals of different breeds or populations. To achieve a maximal accuracy of genomic prediction using the phenotype and genotype data, strategies for forming a training population to predict genomic breeding values (GEBV) of the selec-tion candidates need to be evaluated. In this study, we examined the accuracy of predicting GEBV for residual feed intake (RFI) based on 522 Angus and 395 Charo-lais steers genotyped on SNP with the Illumina Bovine SNP50 Beadchip for 3 training population forming strategies: within breed, across breed, and by pooling data from the 2 breeds (i.e., combined). Two other sce-narios with the training and validation data split by birth year and by sire family within a breed were also inves-tigated to assess the impact of genetic relationships on the accuracy of genomic prediction. Three statistical methods including the best linear unbiased prediction with the relationship matrix defined based on the pedi-gree (PBLUP), based on the SNP genotypes (GBLUP), and a Bayesian method (BayesB) were used to predict the GEBV. The results showed that the accuracy of the GEBV prediction was the highest when the prediction was within breed and when the validation population had greater genetic relationships with the training pop-ulation, with a maximum of 0.58 for Angus and 0.64 for Charolais. The within-breed prediction accuracies dropped to 0.29 and 0.38, respectively, when the vali-dation populations had a minimal pedigree link with the training population. When the training population of a different breed was used to predict the GEBV of the validation population, that is, across-breed genomic prediction, the accuracies were further reduced to 0.10 to 0.22, depending on the prediction method used. Pool-ing data from the 2 breeds to form the training popula-tion resulted in accuracies increased to 0.31 and 0.43, respectively, for the Angus and Charolais validation populations. The results suggested that the genetic rela-tionship of selection candidates with the training popu-lation has a greater impact on the accuracy of GEBV using the Illumina Bovine SNP50 Beadchip. Pooling data from different breeds to form the training popula-tion will improve the accuracy of across breed genomic prediction for RFI in beef cattle. [ABSTRACT FROM AUTHOR]

Genetic improvement of exotic and indig-enous pigs in tropical developing countries is desired. Implementations of traditional selection methods on trop-ical pig populations are limited by lack of data recording and analysis infrastructure. Genome-wide selection (GS) provides an approach for achieving faster genetic prog-ress without developing a pedigree recording system. The implications of GS on long-term gain and inbreeding should be studied before actual implementation, especial-ly where low linkage disequilibrium (LD) is anticipated in the target population. A simulation case study of this option was performed on the basis of the available 60,000 SNP panel for porcine genome. Computer simulation was used to explore the effects of various selection meth- ods, trait heritability, and different breeding programs when applying GS. Genomic predictions were based on the ridge regression method. Genome-wide selection performed better than BLUP and phenotypic selection methods by increasing genetic gain and maintaining genetic variation while lowering inbreeding, especially for traits with low heritability. Indigenous pig populations with low LD can be improved by using GS if high-den-sity marker panels are available. The combination of GS with repeated backcrossing of crossbreds to exotic pigs in developing countries promises to rapidly improve the genetic merit of the commercial population. Application of this novel method on a real population will need to be performed to validate these results. [ABSTRACT FROM AUTHOR]

The objectives of this study were to analyze the trend of within-breed genetic diversity and identify major causes leading to loss of genetic diversity in Guernsey breed in three countries. Pedigree files of Canadian (GCN), South African (GSA) and American (GUS) Guernsey populations containing 130 927, 18 593 and 1 851 624 records, respectively, were analyzed. Several parameters derived from the in-depth pedigree analyses were used to measure trends and current levels of genetic diversity. Pedigree completeness index of GCN, GSA and GUS populations, in the most recent year (2007), was 97%, 74% and 79%, respectively, considering four generations back in the analysis. The rate of inbreeding in each population was 0.19%, 0.16% and 0.17% between 2002 and 2007, respectively. For the same period, the estimated effective population size for GCN, GSA and GUS was 46, 57 and 46, respectively. The estimated percentage of genetic diversity lost within each population over the last four decades was 8%, 3% and 5%, respectively. The relative proportion of genetic diversity lost due to random genetic drift in the three populations was 93%, 91% and 86%, respectively. In conclusion, the results suggested that GCN and GUS have lost more genetic diversity than GSA over the past four decades, and this loss is gaining momentum due to increasing rates of inbreeding. Therefore, strategies such as optimum contribution selection and migration of genetic material are advised to increase effective population size, particularly in GCN and GUS. [ABSTRACT FROM PUBLISHER]

Summary [ABSTRACT FROM AUTHOR]

A better understanding of the factors regulating feed efficiency and their potential as predictors of feed efficiency in cattle is needed. Therefore, the potential of three classes of traits, namely, feeding behavior characteristics: daily time at feeder (TF; min/day), time per meal (TM; min), meal size (MS; g DM), eating rate (ER; g DM/min), number of daily meals (NM) and daily visits to the feeder (VF); infrared (IR) thermography traits (°C): eye (EY), cheek (CK), snout (SN), ribs (RB) and hind area (HA); and glucocorticoid levels: fecal cortisol metabolites (FCM; ng/g) and plasma cortisol (PC; ng/ml) as predictors of efficiency were evaluated in 91 steers (436±37 kg) over 2 years (Y1=46; Y2=45). Additionally, the individual traits of each of these three classes were combined to define three single traits. Individual daily feed intake of a corn silage and high-moisture corn-based diet was measured using an automated feeding system. Body weight and thermographs were taken every 28 days over a period of 140 days. Four productive performance traits were calculated: daily dry matter intake (DMI), average daily gain (ADG), feed to gain ratio (F : G) and residual feed intake (RFI). Steers were also classified into three RFI categories (low-, medium- and high-RFI). Among the feeding behavior characteristics, MS and ER were correlated with all efficiency traits (range: 0.26 to 0.75). Low-RFI (more efficient steers) had smaller MS, lower ER and fewer VF in comparison to high-RFI steers. Less efficient steers (high-RFI) performed more VF during the nocturnal period than more efficient steers. More efficient steers had lower CK and SN temperatures than less efficient steers (28.1°C v. 29.2°C and 30.0°C v. 31.2°C), indicating greater energetic efficiency for low-RFI steers. In terms of glucocorticoids, PC was not correlated with efficiency traits. In contrast, more efficient steers had higher FCM in comparison to less efficient steers (51.1 v. 31.2 ng/g), indicating that a higher cortisol baseline is related to better feed efficiency. The overall evaluation of the three classes of traits revealed that feeding behavior, IR thermography and glucocorticoids accounted for 18%, 59% and 7% of the total variation associated with RFI, respectively. These classes of traits have usefulness in the indirect assessment of feed efficiency in cattle. Among them, IR thermography was the most promising alternative to screen cattle for this feed efficiency. These findings might have application in selection programs and in the better understanding of the biological basis associated with productive performance. [ABSTRACT FROM AUTHOR]

The aim of this study was to identify the presence of SNPs in the chemokine genes CCL2 and IL8 and the chemokine receptor genes IL8RA and CCR2, and assess their potential contribution to variation in estimated breeding values (EBVs) for somatic cell score (SCS) and four other traits in Canadian Holstein bulls. Pools of DNA for bulls with high (H) and low (L) EBVs for SCS were used for identification of 11 SNPs. Two unreported SNPs were found in the CCL2 gene and one SNP was found in the CCR2 gene. Previously reported SNPs (three in the IL8 gene and five in the IL8RA chemokine receptor) were also identified. Two SNPs in CCL2, three in IL8, one in IL8RA and one in CCR2 were genotyped in Canadian Holstein bulls ( n = 338) using tetra primer ARMS-PCR. We investigated associations of these seven polymorphisms with three production traits (milk yield, fat yield and protein yield) and one conformation trait related to mastitis (udder depth). The allele substitution effect for the CCL2 rs41255713:T>C SNP was significant at an experimental-wise level for milk yield (247.5 ± 79.9 kg) and protein yield (7.4 ± 2.3 kg) EBVs ( P ≤ 0.05). The associations of the SNPs with SCS EBVs were not significant at an experimental-wise level. However, the allele substitution effect of the CCR2 rs41257559:C>T SNP on SCS was significant at the comparison-wise level (−0.04 ± 0.02, P = 0.05), which might indicate a possible association in support of other published studies. Lastly, we assigned CCR2 to BTA22q24, where a previously QTL for SCS was identified. [ABSTRACT FROM AUTHOR]

Calpastatin (CAST) is a naturally occurring protein that inhibits the normal tenderization of meat as it ages postmortem. A SNP was identified in the CAST gene (a G to C substitution) and genotyped on crossbred commercially fed heifers (n = 163), steers (n = 226), and bulls (n = 61) from beef feedlots, and steers (n = 178) from a University of Guelph feeding trial. The association of the CAST SNP with carcass and meat quality traits was studied. Carcass traits included fat, lean, and bone yield; grade fat; LM area; and HCW. Meat quality traits included marbling grade; i.m. fat content of LM; tenderness evaluation of LM (Warner-Bratzler shear force) at 2, 7, 14, and 21 d of postmortem aging; and tenderness evaluation of semitendinosus muscle at 7 d of postmortem aging. The mixed model used in the analyses included fixed effects of CAST genotype, sex, slaughter group, and breed composition (linear covariate); sire was a random effect. For the analysis of shear force, i.m. fat content of LM was also included in the model as a linear covariate. Shear force measures were analyzed within days of postmortem aging and by repeated measures analysis. The CAST SNP allele C was more frequent (63%) in the crossbred population than allele G. The CAST SNP was associated with shear force across days of postmortem aging (P = 0.005); genotype CC yielded beef that was more tender than GG (-0.32 kg ± 0.13), and CG had intermediate tenderness. The corresponding average allele substitution effect (G to C substitution) was also highly significant (-0.15 ± 0.05 kg, P = 0.002). A lower percentage of unacceptably tough steaks (shear force >5.7 kg) at 2 and 7 d postmortem was associated with an increasing number of C alleles (P ≤ 0.05). At 7 d postmortem, the percentage of unacceptably tough steaks decreased by 24 and 35%, respectively, for animals carrying 1 and 2 copies of the C allele relative to animals with no C alleles. However, genotype CC had a greater fat yield (+1.44 ± 0.56%; P = 0.037) than genotype GG, with a corresponding allele substitution effect of 0.67 ± 0.27% (P = 0.015). Therefore, the CAST SNP allele C was associated with increased LM tenderness across days of postmortem aging and, importantly for the beef industry, had a significant reduction in the percentage of steaks rated unacceptably tough by consumers based on an assumed threshold level. [ABSTRACT FROM AUTHOR]

Studies with different populations arc required to properly characterize the robustness of associations of polymorphisms in candidate genes with economically important traits across beef cattle populations before this sort of genetic information can be used efficiently in breeding and management decisions. The objective of this study was to evaluate the association of previously reported SNP in the bovine leptin gene with carcass and meat quality traits from a large sample of crossbred beef cattle. Five SNP (UASMSI UASMS2, UASMS3, E2JW, and E2FB) were genotyped on 1,111 crossbred bulls, heifers, and steers. The measured traits included fat, lean, and bone yield (%) by partial rib dissection, grade fat, LM area, HCW, quality grade, LM i.m. fat, and tenderness evaluation of LM and semitendinosus muscle. Only four SNP were analyzed (UASMS1, UASMS2, E2JW, and E2FB), because UASMS1 and UASMS3 were completely linked. A univariate mixed-inheritance animal model was used to evaluate the association of either genotypes or haplotypes with the traits. The two leptin exon 2 SNP were associated with fat and lean yield and grade fat (E2JW, P < 0.01, E2FB, P < 0.05), and they interacted in their effect on LM tenderness (P < 0.01). The leptin promoter SNP were either not associated with any of the traits (UASMS2) or with fat yield only (UASMS1). Three haplotypes (TCAC, CCAT, TTAC) were at high frequency in the population (88%) and had similar effects on all the traits. Compared with the common haplotypes, one haplotype (CCTT) showed a significantly different effect on fat and lean yield and grade fat (P < 0.01), and one haplotype (TTTT) had a different effect on LM tenderness (P < 0.03). Therefore, important associations between SNP within the leptin gene with lean yield, fatness (fat yield and subcutaneous fat), and tenderness were detected. Results confirm some of the previously reported associations, but diverge with respect to others, showing that further efforts are required to validate some prospective associations. [ABSTRACT FROM AUTHOR]

(Co)variance components, direct and maternal breed additive, dominance, and epistatic loss effects on preweaning weight gain of beef cattle were estimated. Data were from 478,466 animals in Ontario, Canada, from 1986 to 1999, including records of both purebred and crossbred animals from Angus, Blonde d'Aquitaine, Charolais, Gelbvieh, Hereford, Limousin, Maine-Anjou, Salers, Shorthorn, and Simmental breeds. The genetic model included fixed direct and maternal breed additive, dominance, and epistatic loss effects, fixed environmental effects of age of the calf, contemporary group, and age of the dam × sex of the calf, random additive direct and maternal genetic effects, and random maternal permanent environment effects. Estimates of direct and maternal additive genetic, maternal permanent environmental and residual variances, expressed as proportions of the phenotypic variance, were 0.32, 0.20, 0.12, and 0.52, respectively. Correlation between direct and maternal additive genetic effects was -0.63. Breed ranking was similar to previous studies, but estimates showed large SE. The favorable effects of direct and maternal dominance (P <0.05) on preweaning gain were equivalent to 1.3 and 2.3% of the phenotypic mean of purebred calves, respectively. The same features for direct and maternal epistatic loss effects were -2.2% (P < 0.05) and -0.1% (P > 0.05). The large SE of breed effects were likely due to multicollinearity among predictor variables and deficiencies in the dataset to separate direct and maternal effects and may result in a less reliable ranking of the animals for across breed comparisons. Further research to identify the causes of the instability of estimates of breed additive, dominance, and epistatic loss genetic effects, and application of alternative statistical methods is recommended. [ABSTRACT FROM AUTHOR]

In spring 1992 in Jordan 70 flocks of sheep and goats were investigated coproscopically. 838 of altogether 882 small ruminants (=95.01%) harboured endoparasites. In three different parts of the country - in the vicinities of Ma'an, Kerak and Amman - the results were similar ( Dictyocaulus, Nematodirus, Moniezia) or they differed (protostrongylids, Marshallagia and other trichostrongylids, Eimeria). In connection with the established parasite status remarks concerning the therapy, including the problems involved as well as remarks concerning the time of treatment in the investigated area will be made. Finally, suggestions will be made for important and specialized follow-up studies regarding improvement of the situation in this country. [ABSTRACT FROM AUTHOR]

The aim of this study was to identify genomic regions associated with the total amount of saturated (SFA), monounsaturated (MUFA), and polyunsaturated (PUFA) fatty acids in the beef of Nellore cattle. The investigated dataset contained records from 963 Nellore bulls, about two years old, finished in feedlot (90 days). Meat samples of Longissimus dorsi muscle, between the 12th and 13th ribs of the left half-carcasses, were taken to measure the fatty acids (FAs). FAs were quantified by gas chromatography (GC-2010 Plus - Shimadzu AOC 20i autoinjector) using SP-2560 capillary column (100 m × 0.25 mm diameter with 0.02 mm thickness; Supelco, Bellefonte, PA). The animals were genotyped using the high-density SNP panel (BovineHD BeadChip assay 777k, Illumina Inc., San Diego, CA). Those SNP markers with minor allele frequency less than 0.05, call rate less than 90%, monomorphic, located on sex chromosomes, and those with unknown position were removed from the analysis. After genomic quality control, 470,007 SNPs and 868 animals were available for the analyses. Missing genotypes were imputed using FImpute software. Genotypes were phased to haplotypes using fastPHASE software and then haplotype blocks were defined based on linkage disequilibrium using HaploView software. Genome-wide association analyses were performed considering one haplotype at a time. The model included fixed effects of contemporary group (92 levels), haplotype (linear regression on number of copies), and age at slaughter as a linear covariate. Bonferroni correction was applied at 5% significance to adjust for multiple tests. A total of 83,883 haplotypes were included in the genome-wide association analyses. From those haplotypes, 292, 17, and 31 were significantly associated (P < 0.05) with SFA, MUFA, and PUFA, respectively. Most associations were found on BTA17, BTA3, BTA1, BTA8, BTA25, and BTA2. These significant regions harbor genes such as GALNT12, SLC6A7, CAMK2A, SYTL3, EPAS1, PRKCB, EPHA6, MPZL1, UHMK1, KIRREL, FYN, LTBP1, PRKCE, SIK2, TOM1L1, NF1, DNAJA3, SH2B2, AFAP1L2, and AGAP1. These genes are involved in lipid metabolism, reproductive hormone receptors, transport and use of fatty acids and cholesterol, phospholipid and membrane hydrolysis and biosynthesis, energy metabolism, and protein kinase synthesis. Thus, the identification of these associated haplotypes may contribute to further studies to validate these regions and prospect candidate genes that would be useful for breeding programs to improve the beef quality of Nellore cattle. [ABSTRACT FROM AUTHOR]

Dairy products are rich in cholesterol (CHL); therefore, monitoring CHL levels in cow milk may become an important factor. This study aimed to (a) determine the factors that influence milk CHL content, (b) estimate (co) variances and heritability for milk cholesterol, and (c) estimate genetic correlations between milk CHL and other production traits. Milk samples were collected from 2,907 cows from 38 commercial herds in Quebec. Milk CHL content was determined by gas chromatography and expressed as mg of CHL in 100 g of total fat (CHL_fat) or in 100 mg of milk (CHL_milk). Test-day milk (Milk), fat (Fat) and protein (Prot) yields, fat (Fat%) and protein (Prot%) percentages, and somatic cell counts (SCC) were also determined. A total of 2,418 cows were retained for analysis after editing for registration status, cow, sire/dam identification, breed, age at calving, and stage of lactation. Linear mixed models with fixed effects of test date, parity, age at calving, and stage of lactation and random effects of herd-year-season of calving and residual were run to test the significance of fixed effects on CHL. Univariate models were used to estimate (co) variances and heritability; meanwhile bivariate models were used to compute phenotypic and genetic correlations. The mean values of CHL_fat and CHL_milk were 274.60 ± 74.66 mg and 11.27 ± 0.74 mg, respectively. Cholesterol content was significantly affected by stage of lactation but not by parity and age at calving, regardless of the scale of expression (P < 0.05). Heritability estimates for CHL_fat and CHL_milk were 0.09 ± 0.04 and 0.18 ± 0.05, respectively. Phenotypic and genetic correlations between CHL_fat and CHL_milk were 0.85 ± 0.01 and 0.33 ± 0.17, respectively. CHL_fat had no significant genetic correlations with Milk, Fat, and Prot% (-0.17 to -0.37) and close to zero genetic correlation with Prot and Fat%. CHL_milk also had low nonsignificant genetic correlations with Fat (0.33) and Prot (-0.39) but moderate and significant genetic correlations with Milk (0.58) and Prot% (0.47) and high genetic correlation with Fat% (0.81). CHL_fat and CHL_milk also had no significant genetic correlations with SCC. This is the first study to estimate genetic parameters for milk CHL content. Further studies on response to selection and genomics are required to assess the possibility of genetically selecting cows with desired CHL content. [ABSTRACT FROM AUTHOR]

Background: Ketosis in dairy cattle has been shown to cause a high morbidity in the farm and substantial financial losses to dairy farmers. Ketosis symptoms, however, are difficult to identify, therefore, the amount of ketone bodies (mainly β-hydroxybutyric acid, BHB) is used as an indicator of subclinical ketosis in cows. It has also been shown that milk BHB concentrations have a strong correlation with ketosis in dairy cattle. Mid-infrared spectroscopy (MIR) has recently became a fast, cheap and high-throughput method for analyzing milk components. The aim of this study was to perform a genome-wide association study (GWAS) on the MIR-predicted milk BHB to identify genomic regions, genes and pathways potentially affecting subclinical ketosis in North American Holstein dairy cattle. Results: Several significant regions were identified associated with MIR-predicted milk BHB concentrations (indicator of subclinical ketosis) in the first lactation (SCK1) and second and later lactations (SCK2) in Holstein dairy cows. The strongest association was located on BTA6 for SCK1 and BTA14 on SCK2. Several SNPs on BTA6 were identified in regions and variants reported previously to be associated with susceptibility to ketosis and clinical mastitis in Jersey and Holstein dairy cattle, respectively. One highly significant SNP on BTA14 was found within the DGAT1 gene with known functions on fat metabolism and inflammatory response in dairy cattle. A region on BTA6 and three SNPs on BTA20 were found to overlap between SCK1 and SCK2. However, a novel region on BTA20 (55–63 Mb) for SCK2 was also identified, which was not reported in previous association studies. Enrichment analysis of the list of candidate genes within the identified regions for MIR-predicted milk BHB concentrations yielded molecular functions and biological processes that may be involved in the inflammatory response and lipid metabolism in dairy cattle. Conclusions: The results of this study confirmed several SNPs and genes identified in previous studies as associated with ketosis susceptibility and immune response, and also found a novel region that can be used for further analysis to identify causal variations and key regulatory genes that affect clinical/ subclinical ketosis. [ABSTRACT FROM AUTHOR]

Transmission ratio distortion (TRD) is the deviation from the expected Mendelian inheritance of alleles from heterozygous parents. This phenomenon has been reported in a broad range of organisms and can be caused by various biological mechanisms including meiotic drive, embryo or fetal failure, germline selection, gametic competition, imprint resetting error and differential survival of offspring. Within this context, we investigated TRD in cattle aiming to identify genomic regions showing altered deviations in segregation that could contain potential causal mutations directly affecting economically important traits, such as reproduction. A Bayesian approach was implemented in order to uncover TRD across the whole genome using SNP-by-SNP and haplotypes of 2-SNP sliding windows using 79,238 genotyped trios of Holstein. From a total of 44,369 autosomal SNP, 942 were significantly detected with TRD that exceeded a Bayes factor (BF) ≥ 10 (strong evidence) and 408 with BF ≥ 100 (decisive evidence) from SNP-by-SNP analyses. The number of SNP with parent-unspecific TRD were 270 whereas 393 and 271 SNP were detected as either sire- or dam-TRD, respectively. By using the approximate empirical null distribution of TRD, results potentially generated by chance were discarded, resulting in 555, 307 and 92 SNP significantly detected with a probability of error of 5%, 1% and 0.1%, respectively. From the SNP-by-SNP approach, regions with moderate-to-high |TRD| (≥ 0.15) were less polymorphic (minor allele frequency, MAF < 0.027), providing evidence of TRD selection and unravelling rare variants as candidate lethal alleles. In contrast, slightly more polymorphic regions with moderate-to-high |TRD| were identified by the haplotype approach (MAF ~ 0.045). The number of regions identified by haplotype approach after correction (at 0.1% probability of error) were 1,047, 421 and 683 for overall, sire- and dam-TRD, respectively. The preliminary functional analysis of detected regions with TRD identified positional genes associated with regulation of embryonic development. Moreover, the identification of alleles with TRD in chromosomal regions around haplotypes well known to be associated with recessive disorders in Holstein or affecting fertility traits in other cattle breeds highlighted important biological implications of TRD. In conclusion, the prevalence of TRD was extended across the whole genome and an in-depth deeper study of these candidate regions and alleles will be further investigated to better understand this phenomenon in cattle. [ABSTRACT FROM AUTHOR]

In this paper, we present a bottom-up approach to designing and constructing a high-speed electrochemical scanning tunneling microscope (EC-STM). Using finite element analysis (FEA) calculations of the frequency response of the whole mechanical loop of the STM, we analyzed several geometries to find the most stable one that could facilitate fast scanning. To test the FEA results, we conducted measurements of the vibration amplitudes using a prototype STM setup. Based on the FEA analysis and the measurement results, we identified the potentially most disturbing vibration modes that could impair fast scanning. By modifying the design of some parts of the EC-STM, we reduced the amplitudes as well as increased the resonance frequencies of these modes. Additionally, we designed and constructed an electrochemical flow-cell that allows STM imaging in a flowing electrolyte, and built a bi-potentiostat to achieve electrochemical potential control during the measurements. Finally, we present STM images acquired during high-speed imaging in air as well as in an electrochemical environment using our newly-developed EC-STM. [ABSTRACT FROM AUTHOR]