Identification of copy number variations in the genome of Dairy Gir cattle.

Studying structural variants that can control complex traits is relevant for dairy cattle production, especially for animals that are tolerant to breeding conditions in the tropics, such as the Dairy Gir cattle. This study identified and characterized high confidence copy number variation regions (CNVR) in the Gir breed genome. A total of 38 animals were whole-genome sequenced, and 566 individuals were genotyped with a high-density SNP panel, among which 36 animals had both sequencing and SNP genotyping data available. Two sets of high confidence CNVR were established: one based on common CNV identified in the studied population (CNVR_POP), and another with CNV identified in sires with both sequence and SNP genotyping data available (CNVR_ANI). We found 10 CNVR_POP and 45 CNVR_ANI, which covered 1.05 Mb and 4.4 Mb of the bovine genome, respectively. Merging these CNV sets for functional analysis resulted in 48 unique high confidence CNVR. The overlapping genes were previously related to embryonic mortality, environmental adaptation, evolutionary process, immune response, longevity, mammary gland, resistance to gastrointestinal parasites, and stimuli recognition, among others. Our results contribute to a better understanding of the Gir breed genome. Moreover, the CNV identified in this study can potentially affect genes related to complex traits, such as production, health, and reproduction.

Classification Performance of Machine Learning Methods for Identifying Resistance, Resilience, and Susceptibility to Haemonchus contortus Infections in Sheep.

This study investigated the feasibility of using easy-to-measure phenotypic traits to predict sheep resistant, resilient, and susceptible to gastrointestinal nematodes, compared the classification performance of multinomial logistic regression (MLR), linear discriminant analysis (LDA), random forest (RF), and artificial neural network (ANN) methods, and evaluated the applicability of the best classification model on each farm. The database comprised 3654 records of 1250 Santa Inês sheep from 6 farms. The animals were classified into resistant (2605 records), resilient (939 records), and susceptible (110 records) according to fecal egg count and packed cell volume. A random oversampling method was performed to balance the dataset. The classification methods were fitted using the information of age class, the month of record, farm, sex, Famacha© degree, body weight, and body condition score as predictors, and the resistance, resilience, and susceptibility to gastrointestinal nematodes as the target classes to be predicted considering data from all farms randomly. An additional leave-one-farm-out cross-validation technique was used to assess prediction quality across farms. The MLR and LDA models presented good performances in predicting susceptible and resistant animals. The results suggest that the use of readily available records and easily measurable traits may provide useful information for supporting management decisions at the farm level.

Integrating genome-wide association study and pathway analysis reveals physiological aspects affecting heifer early calving defined at different ages in Nelore cattle.

Heifer early calving (HC) plays a key role in beef cattle herds' economic sustainability and profitability by reducing production costs and generation intervals. However, the genetic basis of HC in Nelore heifers at different ages remains to be well understood. In this study, we aimed to perform a multi-trait weighted single-step genome-wide association (MT w-ssGWAS) to uncover the genetic mechanism involved in HC at 24 (HC24), 26 (HC26), 28 (HC28), and 30 (HC30) months of age in Nelore heifers. The MT w-ssGWAS pointed out four shared windows regions for HC24, HC26, HC28, and HC30 on BTA 5, 6, 14, and 16, explaining a larger proportion of genetic variation from 9.2% for HC30 to 10.6% for HC28. The shared regions harbored candidate genes related with the major gatekeeper for early puberty onset by controlling metabolic aspects related to homeostasis, reproductive, and growth (IGF1, PARPBP, PMCH, GNRHR, LYN, TMEM68, PLAG1, CHCHD7, KISS1, GOLT1A, and PPP1R15B). The MT w-ssGWAS and pathway analysis highlighted differences in physiological processes that support complex interactions between the gonadotropic axes, growth aspects, and sexual precocity in Nelore heifers, providing useful information for genetic improvement and management strategies.

Strategy to Predict High and Low Frequency Behaviors Using Triaxial Accelerometers in Grazing of Beef Cattle.

Knowledge of animal behavior can be indicative of the well-being, health, productivity, and reproduction of animals. The use of accelerometers to classify and predict animal behavior can be a tool for continuous animal monitoring. Therefore, the aim of this study was to provide strategies for predicting more and less frequent beef cattle grazing behaviors. The behavior activities observed were grazing, ruminating, idle, water consumption frequency (WCF), feeding (supplementation) and walking. Three Machine Learning algorithms: Random Forest (RF), Support Vector Machine (SVM) and Naïve Bayes Classifier (NBC) and two resample methods: under and over-sampling, were tested. Overall accuracy was higher for RF models trained with the over-sampled dataset. The greatest sensitivity (0.808) for the less frequent behavior (WCF) was observed in the RF algorithm trained with the under-sampled data. The SVM models only performed efficiently when classifying the most frequent behavior (idle). The greatest predictor in the NBC algorithm was for ruminating behavior, with the over-sampled training dataset. The results showed that the behaviors of the studied animals were classified with high accuracy and specificity when the RF algorithm trained with the resampling methods was used. Resampling training datasets is a strategy to be considered, especially when less frequent behaviors are of interest.

Application of the principal component analysis, cluster analysis, and partial least square regression on crossbreed Angus-Nellore bulls feedlot finished.

Principal component analysis (PCA) and the non-hierarchical clustering analysis (K-means) were used to characterize the most important variables from carcass and meat quality traits of crossbred cattle. Additionally, partial least square (PLS) regression analysis was applied between the carcass measurements and meat quality traits on the classes defined by the cluster analysis. Ninety-seven non-castrated F1 Angus-Nellore bulls feedlot finished were used. After slaughter, hot carcass weight, carcass yield, cold carcass weight, carcass weight losses, pH, and backfat thickness (BFT) were measured. Subsequently, samples of the longissimus thoracis were collected to analyze shear force (SF), cooking loss (CL), meat color (L*, chroma, and hue), intramuscular fat, protein, collagen, moisture, and ashes. Principal component 1 (PC1) was correlated with colorimetric variables, while PC2 was correlated with carcass weights. Afterwards, three clusters (k = 3) were formed and projected in the gradient defined by PC1 and PC2 and allowed distinguishing groups with divergent values for collagen, protein, moisture, CL, SF, and BFT. Animals from high chroma group presented meat with more attractive colors and tenderness (SF = 1.97 to 4.84 kg). Subsequently, the PLS regression on the three chroma groups revealed a good fitness and the coefficients are used to predict the chroma variable from the explanatory variables, which may have practical importance in attempts to predict meat color from carcass and meat quality traits. Thus, PCA, K-means, and PLS regression confirmed the relationship between meat color and tenderness.

Genetic parameters for performance and carcass traits in a paternal 1 lineage of broiler.

The objective of this study was to estimate variance components for performance and carcass traits in a paternal broiler line. The (co)variance components were estimated by the restricted maximum likelihood method applied to the animal model, including the fixed effect of group (sex and hatch) and additive genetic and residual as random effects. Estimated heritability for performance traits ranged from 0.09 to 0.42. The genetic correlations between traits ranged from -0.50 to 0.97. The heritability estimates of feed intake, weight gain, and feed conversion from 35 to 41 days of age were of low magnitude. The genetic correlations among them were favorable to genetic selection. These results suggest that moderate genetic gain can be obtained to the feed intake and weight gain when the selection criterion is the body weight and prime cuts traits. The feed conversion that had low heritability estimation and low genetic correlation with the body weight and prime cut traits needs to pay greater attention due to the economic importance in the high-meat production lineage breeding programs.

Contribution of astrocytes and macrophage migration inhibitory factor to immune-mediated canine encephalitis caused by the distemper virus.

Macrophage migration inhibitory factor (MIF) is a pleiotropic cytokine that is produced by many cell types in situations of homeostasis or disease. One of its functions is to act as a proinflammatory molecule. In humans, several studies have shown that MIF levels become elevated in the serum, urine, cerebrospinal fluid and tissues of patients with chronic inflammatory diseases (systemic lupus erythematosus, rheumatoid arthritis, multiple sclerosis, sepsis, atheromas, diabetes and cancer). In dogs, distemper is a viral infectious condition that may lead to demyelination and inflammation in the central nervous system (CNS). In addition to the action of the virus, the inflammatory process may give rise to lesions in the white matter. Therefore, the objectives of the present study were to evaluate the role of MIF in the encephalitis that the canine distemper virus causes and to compare this with immunodetection of major histocompatibility complex-II (MHC-II), CD3 T lymphocytes, MMP-9 and glial fibrillary acidic protein (GFAP; astrocytes) in demyelinated areas of the encephalon, in order to ascertain whether these findings might be related to the severity of the encephalic lesions. To this end, a retrospective study on archived paraffinized blocks was conducted, in which 21 encephala from dogs that had been naturally infected with the canine distemper virus (infected group) and five from dogs that had been free from systemic or CNS-affecting diseases (control group) were used. In the immunohistochemical analysis on the samples, the degree of marking by GFAP, MHC-II, MMP-9 and MIF was greater in the demyelinated areas and in the adjacent neuropil, and this was seen particularly in astrocytes. Detection of CD3 was limited to perivascular cuffs. In areas of liquefactive necrosis, Gitter cells were positive for MMP-9, MIF and MHC-II. Hence, it was concluded that activated astrocytes influenced the afflux of T lymphocytes to the encephalon (encephalitis). In the more advanced phases, activated phagocytes in the areas of liquefactive necrosis (Gitter cells) continued to produce inflammatory mediators even after the astrocytes in these localities had died, thereby worsening the encephalic lesions. Distemper virus-activated astrocytes and microglia produce MIF that results in proinflammatory stimulus on glial cells and brain-infiltrating leukocytes. Therefore, the effect of the inflammatory response is potentiated on the neuropil, resulting in neurological clinical signs.

Isolated perfused udder model for transcriptome analysis in response to Streptococcus agalactiae.

This study aimed to evaluate the transcriptional changes occurring in isolated perfused mammary alveolar tissue in response to inoculation with S. agalactiae and to identify the most affected biological functions and pathways after 3 h. Four udders taken at slaughter from cows with healthy mammary gland were perfused ex situ with warmed and gassed Tyrode's solution. Mammary alveolar tissue samples were taken from the left fore and rear quarters (IQ-inoculated quarters) before inoculation (hour 0) and at 3 h post inoculation (hpi) and at the same times from control right fore and rear quarters (not inoculated: NIQ). A total of 1756 differentially expressed genes (DEGs) were identified between IQ and NIQ at 3 hpi using edgeR package. Within this set of DEGs, 952 were up regulated and mainly involved with innate immune response and inflammatory response, e.g., CD14, CCL5, TLR2, IL-8, SAA3, as well as in transcriptional regulation such as FOS, STAT3 and NFKBIA. Genes down-regulated (804) included those involved with lipid synthesis e.g., APOC2, SCD, FABP3 and FABP4. The most affected pathways were chemokine signaling, Wnt signaling and complement and coagulation cascades, which likely reflects the early stage response of mammary tissue to S. agalactiae infection. No significant gene expression changes were detected by RNA-Seq in the others contrasts. Real time-PCR confirmed the increase in mRNA abundance of immune-related genes: TLR2, TLR4, IL-1ß, and IL-10 at 3 hpi between IQ and NIQ. The expression profiles of Casp1 and Bax for any contrasts were unaffected whereas Bcl2 was increased in IQ, which suggests no induction of apoptosis during the first hours after infection. Results provided novel information regarding the early functional pathways and gene network that orchestrate innate immune responses to S. agalactiae infection. This knowledge could contribute to new strategies to enhance resistance to this disease, such as genomic selection.

Genome-wide association study and functional analysis of feet and leg conformation traits in Nellore cattle.

Feet and leg conformation is evaluated as a subset of conformational structure traits in dairy and beef cattle and is related to the feet and leg quality that can compromise the animals' productive performance and longevity. The aim of this study was to perform a genome-wide association study (GWAS) of two traits related to feet and leg conformation in Nellore cattle to identify chromosomal regions related to the expression of these traits. Phenotypic and pedigree data from 104,725 animals and genotypes from 1,435 animals and 407,730 SNPs were used. Feet and leg structure was evaluated as a binary trait (FL1) to identify yearling animals with feet and leg problems or as categorical score (FL2) to assess the overall quality of their feet and leg. The top ten 1-Mb windows that explained the largest proportion of the total genetic variance were identified and functional enrichment analyses were performed. The 10 windows with large effects obtained for FL1 are located on chromosomes 1, 2, 6, 7, 8, 10, and 14, and together explained 8.96% of the additive genetic variance. For FL2, these windows are located on chromosomes 1, 7, 10, 11, 18, 20, 22, 28, and 29, explaining 8.98% of the additive genetic variance. Several candidate genes were identified, including DLX2 which is associated with osteogenic differentiation, IL-1ß and IL-1A associated with some properties of articular cartilage, PiT1 which plays an important role in bone physiology, and CTSL associated with rheumatoid arthritis. The results presented here should contribute to a better understanding of the genetic and physiologic mechanisms regulating both traits, and identifies candidate genes for future investigation of causal mutations.

Genotype imputation in a tropical crossbred dairy cattle population.

The objective of this study was to investigate different strategies for genotype imputation in a population of crossbred Girolando (Gyr × Holstein) dairy cattle. The data set consisted of 478 Girolando, 583 Gyr, and 1,198 Holstein sires genotyped at high density with the Illumina BovineHD (Illumina, San Diego, CA) panel, which includes ∼777K markers. The accuracy of imputation from low (20K) and medium densities (50K and 70K) to the HD panel density and from low to 50K density were investigated. Seven scenarios using different reference populations (RPop) considering Girolando, Gyr, and Holstein breeds separately or combinations of animals of these breeds were tested for imputing genotypes of 166 randomly chosen Girolando animals. The population genotype imputation were performed using FImpute. Imputation accuracy was measured as the correlation between observed and imputed genotypes (CORR) and also as the proportion of genotypes that were imputed correctly (CR). This is the first paper on imputation accuracy in a Girolando population. The sample-specific imputation accuracies ranged from 0.38 to 0.97 (CORR) and from 0.49 to 0.96 (CR) imputing from low and medium densities to HD, and 0.41 to 0.95 (CORR) and from 0.50 to 0.94 (CR) for imputation from 20K to 50K. The CORRanim exceeded 0.96 (for 50K and 70K panels) when only Girolando animals were included in RPop (S1). We found smaller CORRanim when Gyr (S2) was used instead of Holstein (S3) as RPop. The same behavior was observed between S4 (Gyr + Girolando) and S5 (Holstein + Girolando) because the target animals were more related to the Holstein population than to the Gyr population. The highest imputation accuracies were observed for scenarios including Girolando animals in the reference population, whereas using only Gyr animals resulted in low imputation accuracies, suggesting that the haplotypes segregating in the Girolando population had a greater effect on accuracy than the purebred haplotypes. All chromosomes had similar imputation accuracies (CORRsnp) within each scenario. Crossbred animals (Girolando) must be included in the reference population to provide the best imputation accuracies.

Genome-Enabled Prediction of Breeding Values for Feedlot Average Daily Weight Gain in Nelore Cattle.

Nelore is the most economically important cattle breed in Brazil, and the use of genetically improved animals has contributed to increased beef production efficiency. The Brazilian beef feedlot industry has grown considerably in the last decade, so the selection of animals with higher growth rates on feedlot has become quite important. Genomic selection (GS) could be used to reduce generation intervals and improve the rate of genetic gains. The aim of this study was to evaluate the prediction of genomic-estimated breeding values (GEBV) for average daily weight gain (ADG) in 718 feedlot-finished Nelore steers. Analyses of three Bayesian model specifications [Bayesian GBLUP (BGBLUP), BayesA, and BayesCπ] were performed with four genotype panels [Illumina BovineHD BeadChip, TagSNPs, and GeneSeek High- and Low-density indicus (HDi and LDi, respectively)]. Estimates of Pearson correlations, regression coefficients, and mean squared errors were used to assess accuracy and bias of predictions. Overall, the BayesCπ model resulted in less biased predictions. Accuracies ranged from 0.18 to 0.27, which are reasonable values given the heritability estimates (from 0.40 to 0.44) and sample size (568 animals in the training population). Furthermore, results from Bos taurus indicus panels were as informative as those from Illumina BovineHD, indicating that they could be used to implement GS at lower costs.

Strategies for genotype imputation in composite beef cattle.

BACKGROUND: Genotype imputation has been used to increase genomic information, allow more animals in genome-wide analyses, and reduce genotyping costs. In Brazilian beef cattle production, many animals are resulting from crossbreeding and such an event may alter linkage disequilibrium patterns. Thus, the challenge is to obtain accurately imputed genotypes in crossbred animals. The objective of this study was to evaluate the best fitting and most accurate imputation strategy on the MA genetic group (the progeny of a Charolais sire mated with crossbred Canchim X Zebu cows) and Canchim cattle. The data set contained 400 animals (born between 1999 and 2005) genotyped with the Illumina BovineHD panel. Imputation accuracy of genotypes from the Illumina-Bovine3K (3K), Illumina-BovineLD (6K), GeneSeek-Genomic-Profiler (GGP) BeefLD (GGP9K), GGP-IndicusLD (GGP20Ki), Illumina-BovineSNP50 (50K), GGP-IndicusHD (GGP75Ki), and GGP-BeefHD (GGP80K) to Illumina-BovineHD (HD) SNP panels were investigated. Seven scenarios for reference and target populations were tested; the animals were grouped according with birth year (S1), genetic groups (S2 and S3), genetic groups and birth year (S4 and S5), gender (S6), and gender and birth year (S7). Analyses were performed using FImpute and BEAGLE software and computation run-time was recorded. Genotype imputation accuracy was measured by concordance rate (CR) and allelic R square (R(2)). RESULTS: The highest imputation accuracy scenario consisted of a reference population with males and females and a target population with young females. Among the SNP panels in the tested scenarios, from the 50K, GGP75Ki and GGP80K were the most adequate to impute to HD in Canchim cattle. FImpute reduced computation run-time to impute genotypes from 20 to 100 times when compared to BEAGLE. CONCLUSION: The genotyping panels possessing at least 50 thousands markers are suitable for genotype imputation to HD with acceptable accuracy. The FImpute algorithm demonstrated a higher efficiency of imputed markers, especially in lower density panels. These considerations may assist to increase genotypic information, reduce genotyping costs, and aid in genomic selection evaluations in crossbred animals.

CD4+FOXP3+ cells produce IL-10 in the spleens of dogs with visceral leishmaniasis.

Visceral Leishmaniasis (VL) is caused by intracellular parasites of the genus Leishmania that affect humans and several animal species. Dogs are one of the main urban reservoirs of the parasite and play a central role in the transmission cycle to humans via sandflies. Studies concerning the immune response in dogs with VL have demonstrated that protective immunity is associated with cellular immune response, while disease progression is associated with humoral response and IL-10 and TGF-ß production. The study aimed to evaluate IL-10 and TGF-ß production by regulatory T (Treg) cells in the blood and spleen of dogs naturally infected by Leishmania spp. and correlate this with parasite load. Five healthy dogs and 29 dogs with proven infection were selected for the study group. Real-time PCR was used to quantify parasite load and confirm infection by Leishmania spp. Treg cells producing IL-10 and TGF-ß were quantified using flow cytometry. An increase in IL-10 production by Treg cells was verified in the spleen of dogs naturally infected by Leishmania spp. Concurrently, a decrease in the total number of T cells in these dogs was verified compared with healthy dogs. No association was determined between parasite load and the percentage of spleen Treg cells producing IL-10 and TGF-ß. These findings suggest that Treg cells are an important source of IL-10 in the spleen, participating in immune response modulation, while the reduced percentage of these cells in infected dogs could be attributed to persistent immune activation.

Genome-wide association for growth traits in Canchim beef cattle.

Studies are being conducted on the applicability of genomic data to improve the accuracy of the selection process in livestock, and genome-wide association studies (GWAS) provide valuable information to enhance the understanding on the genetics of complex traits. The aim of this study was to identify genomic regions and genes that play roles in birth weight (BW), weaning weight adjusted for 210 days of age (WW), and long-yearling weight adjusted for 420 days of age (LYW) in Canchim cattle. GWAS were performed by means of the Generalized Quasi-Likelihood Score (GQLS) method using genotypes from the BovineHD BeadChip and estimated breeding values for BW, WW, and LYW. Data consisted of 285 animals from the Canchim breed and 114 from the MA genetic group (derived from crossings between Charolais sires and ½ Canchim + ½ Zebu dams). After applying a false discovery rate correction at a 10% significance level, a total of 4, 12, and 10 SNPs were significantly associated with BW, WW, and LYW, respectively. These SNPs were surveyed to their corresponding genes or to surrounding genes within a distance of 250 kb. The genes DPP6 (dipeptidyl-peptidase 6) and CLEC3B (C-type lectin domain family 3 member B) were highlighted, considering its functions on the development of the brain and skeletal system, respectively. The GQLS method identified regions on chromosome associated with birth weight, weaning weight, and long-yearling weight in Canchim and MA animals. New candidate regions for body weight traits were detected and some of them have interesting biological functions, of which most have not been previously reported. The observation of QTL reports for body weight traits, covering areas surrounding the genes (SNPs) herein identified provides more evidence for these associations. Future studies targeting these areas could provide further knowledge to uncover the genetic architecture underlying growth traits in Canchim cattle.