Explore the vast range of titles available.

In this study, we explored the gene expression patterns of the pituitary gland and hypothalamus of Angus cows at different growth and developmental stages by deep sequencing and we identified genes that affect bovine reproductive performance to provide new ideas for improving bovine fertility in production practice. We selected three 6-month-old (weaning period), three 18-month-old (first mating period), and three 30-month-old (early postpartum) Angus cattle. The physiological status of the cows in each group was the same, and their body conformations were similar. After quality control of the sequencing, the transcriptome analyses of 18 samples yielded 129.18 GB of clean data. We detected 13,280 and 13,318 expressed genes in the pituitary gland and hypothalamus, respectively, and screened 35 and 50 differentially expressed genes (DEGs) for each, respectively. The differentially expressed genes in both tissues were mainly engaged in metabolism, lipid synthesis, and immune-related pathways in the 18-month-old cows as compared with the 6-month-old cows. The 30-month-old cows presented more regulated reproductive behavior, and pituitary CAMK4 was the main factor regulating the reproductive behavior during this period via the pathways for calcium signaling, longevity, oxytocin, and aldosterone synthesis and secretion. A variant calling analysis also was performed. The SNP inversions and conversions in each sample were counted according to the different base substitution methods. In all samples, most base substitutions were represented by substitutions between bases A and G, and the probability of base conversion exceeded 70%, far exceeding the transversion. Heterozygous SNP sites exceeded 37.68%.

Background Single-step genomic best linear unbiased prediction (SSGBLUP) is a comprehensive method for genomic prediction. Point estimates of marker effects from SSGBLUP are often used for genome-wide association studies (GWAS) without a formal framework of hypothesis testing. Our objective was to implement p-values for single-marker GWAS studies within the single-step GWAS (SSGWAS) framework by deriving computational algorithms and procedures, and by applying these to a large beef cattle population. Methods P-values were obtained based on the prediction error (co)variances for single nucleotide polymorphisms (SNPs), which were obtained from the prediction error (co)variances of genomic predictions based on the inverse of the coefficient matrix and formulas to estimate SNP effects. Results Computation of p-values took a negligible time for a dataset with almost 2 million animals in the pedigree and 1424 genotyped sires, and no inflation of statistics was observed. The SNPs that passed the Bonferroni threshold of 10 −5.9 were the same as those that explained the highest proportion of additive genetic variance, but even at the same significance levels and effects, some of them explained less genetic variance due to lower allele frequency. Conclusions The use of a p-value for SSGWAS is a very general and efficient strategy to identify quantitative trait loci (QTL). It can be used for complex datasets such as those used in animal breeding, where only a proportion of the pedigreed animals are genotyped.

In modern nature conservation and rewilding there is a need for controlling the movements of large grazers in extensively managed areas. The inflexibility of physical fencing can be a limitation in nature management, and the physical boundaries created by physical fencing can have detrimental effects on wildlife. Virtual fencing systems provide boundaries without physical structures. These systems utilise collars with GPS technology to track animals and deliver auditory or electric cues to encourage the animals to stay within the predefined boundaries. This study aims to assess the use of virtual fencing (Nofence©) to keep twelve Angus cows (Bos taurus) within a virtual enclosure without compromising their welfare. As such, the study examines inter-individual differences between the cows as well as their herd behaviour, when reacting and learning to respond appropriately to virtual fencing. Moreover, the activity of the cows was used as an indicator of welfare. The virtual fencing was successful in keeping the herd within the designated area. Moreover, the cattle learned to avoid the virtual border and respond to auditory cues, where the cows received significantly more auditory warning and electric impulses per week throughout the first 14 days than the remaining 125 days (p < 0.001). The cows were found to express both inter-individual differences (p < 0.001) and herd behaviour. The cattle did not express any significant changes in their activity upon receiving an electrical impulse from the collar. Thus, indicating that there were little to no acute welfare implications associated with the use of virtual fencing in this study. This study clearly supports the potential for virtual fencing as a viable alternative to physical electric fencing. However, it also shows that both individual differences in personality and herd structure should be considered when selecting individuals for virtual fencing.

Although the concept of genomic selection relies on linkage disequilibrium (LD) between quantitative trait loci and markers, reliability of genomic predictions is strongly influenced by family relationships. In this study, we investigated the effects of LD and family relationships on reliability of genomic predictions and the potential of deterministic formulas to predict reliability using population parameters in populations with complex family structures. Five groups of selection candidates were simulated by taking different information sources from the reference population into account: (1) allele frequencies, (2) LD pattern, (3) haplotypes, (4) haploid chromosomes, and (5) individuals from the reference population, thereby having real family relationships with reference individuals. Reliabilities were predicted using genomic relationships among 529 reference individuals and their relationships with selection candidates and with a deterministic formula where the number of effective chromosome segments (Me) was estimated based on genomic and additive relationship matrices for each scenario. At a heritability of 0.6, reliabilities based on genomic relationships were 0.002 ± 0.0001 (allele frequencies), 0.022 ± 0.001 (LD pattern), 0.018 ± 0.001 (haplotypes), 0.100 ± 0.008 (haploid chromosomes), and 0.318 ± 0.077 (family relationships). At a heritability of 0.1, relative differences among groups were similar. For all scenarios, reliabilities were similar to predictions with a deterministic formula using estimated Me. So, reliabilities can be predicted accurately using empirically estimated Me and level of relationship with reference individuals has a much higher effect on the reliability than linkage disequilibrium per se. Furthermore, accumulated length of shared haplotypes is more important in determining the reliability of genomic prediction than the individual shared haplotype length.

The average daily gain (ADG) is a critical index for evaluating growth rates in cattle and is closely linked to the economic benefits of the cattle industry. Heredity is one of the factors affecting the daily gain of cattle. However, the molecular mechanisms regulating ADG remain incompletely understood. This study aimed to systematically unravel the molecular mechanisms underlying the divergence in ADG between high average daily gain (HADG) and low average daily gain (LADG) Angus cattle through integrated multi-omics analyses (microbiome, metabolome, and transcriptome), hypothesizing that the gut microbiota–host gene–metabolism axis is a key regulatory network driving ADG divergence. Thirty Angus cattle were classified according to their HADG and LADG. Fecal and serum samples were collected for 16S, fecal metabolome, and blood transcriptome analysis. The results showed that compared with the LADG group, the abundance of Firmicutes increased in the HADG group, while the abundance of Bacteroidetes and Proteobacteria decreased. Metabolomics and transcriptomic analysis revealed that KEGG pathways associated with differentially expressed genes (DEGs) and differentially abundant metabolites (DAMs) were enriched in bile acid metabolism. Spearman correlation analysis showed that Oscillospira was positively correlated with ZBTB20 and negatively correlated with RADIL. ZBTB20 was negatively correlated with dgA-11_gut_group. This study analyzed the regulatory mechanism of average daily gain of beef cattle from genetic, metabolic, and microbial levels, providing a theoretical basis for analyzing the mechanism of differential daily gain of beef cattle, and has important significance for improving the production performance of beef cattle. The multi-omics network provides biomarker foundations for machine learning-based ADG prediction models, offering potential applications in precision breeding. While these biomarkers show promise for precision breeding, their causal roles require further validation. The conclusions are derived from a single breed (Angus) and gender (castrated males). Future studies should include females and diverse breeds to assess generalizability.

Improvement in feed conversion efficiency can improve the sustainability of beef cattle production, but genomic selection for feed efficiency affects many underlying molecular networks and physiological traits. This study describes the differences between steer progeny of two influential Angus bulls with divergent genomic predictions for residual feed intake (RFI). Eight steer progeny of each sire were phenotyped for growth and feed intake from 8 mo. of age (average BW 254 kg, with a mean difference between sire groups of 4.8 kg) until slaughter at 14-16 mo. of age (average BW 534 kg, sire group difference of 28.8 kg). Terminal samples from pituitary gland, skeletal muscle, liver, adipose, and duodenum were collected from each steer for transcriptome sequencing. Gene expression networks were derived using partial correlation and information theory (PCIT), including differentially expressed (DE) genes, tissue specific (TS) genes, transcription factors (TF), and genes associated with RFI from a genome-wide association study (GWAS). Relative to progeny of the high RFI sire, progeny of the low RFI sire had -0.56 kg/d finishing period RFI (P = 0.05), -1.08 finishing period feed conversion ratio (P = 0.01), +3.3 kg^0.75 finishing period metabolic mid-weight (MMW; P = 0.04), +28.8 kg final body weight (P = 0.01), -12.9 feed bunk visits per day (P = 0.02) with +0.60 min/visit duration (P = 0.01), and +0.0045 carcass specific gravity (weight in air/weight in air-weight in water, a predictor of carcass fat content; P = 0.03). RNA-seq identified 633 DE genes between sire groups among 17,016 expressed genes. PCIT analysis identified >115,000 significant co-expression correlations between genes and 25 TF hubs, i.e. controllers of clusters of DE, TS, and GWAS SNP genes. Pathway analysis suggests low RFI bull progeny possess heightened gut inflammation and reduced fat deposition. This multi-omics analysis shows how differences in RFI genomic breeding values can impact other traits and gene co-expression networks.

Agricultural industries rely on physical fences to manage livestock. However, these present practical, financial, and ecological challenges, which may be solved using virtual fencing. This study aimed to identify how experienced cattle through social facilitation and the introduction method influence inexperienced cattle. Based on three stocks held in Fanø, Denmark, containing 12, 17 and 13 Angus (Bos taurus), we examined the virtual fence learning in three case studies using one gradual introduction with zero experienced cattle (A) and two different instant introductions with one (B) and ten (C) experienced cattle. Gradual introduction had the virtual fence moved 20 m every other day for eleven days, and in the two instant introductions, the physical fence was removed in one day. Warnings and impulses were recorded during an 11-day learning period and a 26-day post-learning period, using the impulses per warning to quantify if the cattle adapted. Case studies A and B showed a significant reduction in the warnings and impulses, but only A showed a significant reduction in the impulses per warning when comparing the learning period to the post-learning period. Due to the non-standardised experiments, it was not possible to conclude if the number of experienced cattle or the introduction method had an effect on the results.

Functional and enduring mammary structure is pivotal for producer profitability, and animal health and welfare in beef production. Genetic evaluations for teat and udder score in Canadian Angus cattle have previously been developed. The aim of this study was to identify genomic regions associated with teat and udder structure in Canadian Angus cows thereby enhancing knowledge of the biological architecture of these traits. Thus, we performed a weighted single-step genome wide association study (WssGWAS) to identify candidate genes for teat and udder score in 1,582 Canadian Angus cows typed with the GeneSeek.sup.® Genomic Profiler Bovine 130K SNP array. Genomically enhanced estimated breeding values (GEBVs) were converted to SNP marker effects using unequal variances for markers to calculate weights for each SNP over three iterations. At the genome wide level, we detected windows of 20 consecutive SNPs that explained more than 0.5% of the variance observed in these traits. A total of 35 and 28 windows were identified for teat and udder score, respectively, with two SNP windows in common for both traits. Using Ensembl, the SNP windows were used to search for candidate genes and quantitative trait loci (QTL). A total of 94 and 71 characterized genes were identified in the regions for teat and udder score, respectively. Of these, 7 genes were common for both traits. Gene network and enrichment analysis, using Ingenuity Pathway Analysis (IPA), signified key pathways unique to each trait. Genes of interest were associated with immune response and wound healing, adipose tissue development and morphology, and epithelial and vascular development and morphology. Genetic architecture from this GWAS confirms that teat and udder score are distinct, polygenic traits involving varying and complex biological pathways, and that genetic selection for improved teat and udder score is possible.

Background If unmanaged, high rates of inbreeding in livestock populations adversely impact their reproductive fitness. In beef cattle, historical selection strategies have increased the frequency of several segregating fatal autosomal recessive polymorphisms. Selective breeding has also decreased the extent of haplotypic diversity genome-wide. By identifying haplotypes for which homozygotes are not observed but would be expected based on their frequency, candidates for developmentally lethal recessive loci can be localized. This analysis comes without the need for observation of the loss-associated phenotype (e.g., failure to implant, first trimester abortion, deformity at birth). In this study, haplotypes were estimated for 3961 registered Angus individuals using 52,545 SNP loci using findhap v2, which exploited the complex pedigree among the individuals in this population. Results Seven loci were detected to possess haplotypes that were not observed in homozygous form despite a sufficiently high frequency and pedigree-based expectation of homozygote occurrence. These haplotypes were identified as candidates for harboring autosomal recessive lethal alleles. Of the genotyped individuals, 109 were resequenced to an average 27X depth of coverage to identify putative loss-of-function alleles genome-wide and had variants called using a custom in-house developed pipeline. For the candidate lethal-harboring haplotypes present in these bulls, sequence-called genotypes were used to identify concordant variants. In addition, whole-genome sequence imputation of variants was performed into the set of 3961 genotyped animals using the 109 resequenced animals to identify candidate lethal recessive variants at the seven loci. Following the imputation, no variants were identified that were fully concordant with the marker-based diplotypes. Conclusions Selective breeding programs could utilize the predicted lethal haplotypes associated with SNP genotypes. Sequencing and other methods for identifying the causal variants underlying these haplotypes can allow for more efficient methods of management such as gene editing. These two methods in total will reduce the negative impacts of inbreeding on fertility and maximize overall genetic gains.

Previous studies have indicated that cattle with more excitable temperaments exhibit an increased stress response. The objective of this study was to investigate the relationship between temperament traits, handling, and stress-induced hyperthermia (SIH) in beef cattle. Rectal temperatures (TREC, °C) of 60 purebred Angus cattle (30 heifers, 30 steers; 235.2 ± 5.11 kg) were recorded at 20 s intervals from 30 min prior to handling until two hours post handling. All cattle were exposed to a standardized handling procedure consisting of (i) being restrained in a weighing box for 30 s; (ii) being held within the crush for 30 s; and then (iii) being restrained in a head bail for 60 s. Cattle temperaments were evaluated via three traits: (1) agitometer score (AG); (2) crush score (CS); and (3) flight speed (FS) during the handling procedure. Agitometer scores and FS measures were used to describe an AG category (AGCAT) and an FS category (FSCAT) that were used to classify animals into three temperament categories: 1, calm; 2, intermediate; and 3, temperamental. Pearson’s correlation coefficients were used to evaluate the associations between (i) AG, CS, FS, and TREC 30 min prior to entry into the weighing box (T-30) and then at 1 min intervals between time of entry into the weighing box (T0) until 10 min post-weighing (T10); and (ii) the relationship between AG, CS, and FS. The relationship between TREC and temperament traits over the 2.5 h were modeled by using a first-order autoregressive repeated measures model. Flight speed had strong to moderate associations with TREC at T-30 (r ≥ 0.37; p ≤ 0.006) and between T0 and T10 (r ≥ 0.36; p ≤ 0.01). There were moderate associations amongst TREC between T0 and T10 and CS (r ≥ 0.31; p ≤ 0.01). A weak relationship existed with CS (r = 0.16; p = 0.16). There were no associations between AG and TREC at T-30 (r ≥ −0.15; p = 0.84) or between T0 and T10 (r ≤ 0.04; p ≥ 0.4). Rectal temperature, irrespective of sex and temperament traits, was influenced by time (p < 0.0001), and maximum TREC (39.3 ± 0.04 °C) occurred between 4 and 5.7 min after entry into the weighing box. In addition, CS (p = 0.007) influenced TREC in these cattle. There were also time × temperament trait × sex interactions with the CS (p = 0.0003) and FSCAT (p = 0.043) categories; however, time × temperament trait interactions were not statistically significant. Results from this study suggest that cattle with excitable temperaments, as evaluated by FS and CS, have a greater increase in TREC. In addition, these results suggest that a relationship exists between basal TREC and FS and CS. Together, these results highlight that temperament, as assessed by FS and CS, influences both basal TREC and the peak temperature recorded following handling but does not influence the magnitude of change in TREC post handling.