Search Results (20)

Genomic selection (GS) is a new landmark method in modern animal breeding programs, and it has become a tool for routine genetic evaluation regarding dual-purpose cattle breeding. In this study, we employed data on milk-production, reproduction, and growth measurements of dual-purpose Simmental cows during the period 1987–2022 from two large-scale farms in Northwest China. For this purpose, we used a single-trait model based on the A-array PBLUP and H-array ssGBLUP to perform genetic evaluation of milk-production, reproduction, and growth traits by applying the restricted maximum likelihood (REML) methods. The results revealed that the heritability based on the additive genetic correlation matrix was approximately 0.09–0.31 for milk-production traits, 0.03–0.43 for reproduction traits, and 0.13–0.43 for growth traits. In addition, the heritability based on the genome–pedigree association matrix was similarly 0.09–0.32 for milk-production traits, 0.04–0.44 for reproductive traits, and 0.14–0.43 for growth traits. In the entire population, the reliability of genomic estimated breeding values (GEBVs) increased by 0.6–3.2%, 0.2–2.4%, and 0.5–1.5% for milk-production, reproductive traits, and growth traits, respectively. In the genotyped population, the reliability of GEBV for milk-production and reproduction traits increased by 1.6–4.0% and 0.4–3.6%, respectively, whereas the reliability of GEBV for growth traits decreased by 12.0–17.0%. These results suggest that the construction of an H-matrix with ssGBLUP could improve the heritability and reliability of breeding values for milk-production and reproduction traits. However, the advantage was not evident for growth traits in smaller populations. The present results thus provide a basis for future application of genomic genetic evaluation of dual-purpose Simmental cattle, providing data support for the selection and marketing of excellent breeding bulls, thereby helping to establish a basis for their independently bred breeding bull. Full article

This study aims to elucidate the population structure and genetic diversity of Xinjiang brown cattle (XJBC) and Chinese Simmental cattle (CSC) while conducting genome-wide selective signatures analyses to identify selected genes associated with milk production traits in both breeds. Based on whole-genome resequencing technology, whole-genome single nucleotide polymorphisms (SNPs) of 83 Xinjiang brown cattle and 80 Chinese Simmental cattle were detected to resolve the genetic diversity and genetic structure of the two populations, whole-genome selective elimination analysis was performed for the two breeds of cattle using the fixation index (F_st) and nucleotide diversity (θπ ratio), and enrichment analysis was performed to explore their biological functions further. Both breeds exhibited relatively rich genetic diversity, with the Chinese Simmental cattle demonstrating higher genetic diversity than Xinjiang brown cattle. The IBS and G matrix results indicated that most individuals in the two populations were farther apart from each other. The PCA and neighbor-joining tree revealed no hybridization between the two breeds, but there was a certain degree of genetic differences among the individuals in the two breeds. Population structure analysis revealed that the optimal number of ancestors was three when K = 3. This resulted in clear genetic differentiation between the two populations, with only a few individuals having one ancestor and the majority having two or three common ancestors. A combined analysis of F_st and θπ was used to screen 112 candidate genes related to milk production traits in Xinjiang brown cattle and Chinese Simmental cattle. This study used genome-wide SNP markers to reveal the genetic diversity, population structure, and selection characteristics of two breeds. This study also screened candidate genes related to milk production traits, providing a theoretical basis for conserving genetic resources and improving genetic selection for milk production traits in Xinjiang brown cattle and Chinese Simmental cattle. Full article

In livestock production, deeply understanding the molecular mechanisms of growth and metabolic differences in different breeds of cattle is of great significance for optimizing breeding strategies, improving meat quality, and promoting sustainable development. This study aims to comprehensively reveal the molecular-level differences between Chinese domestic cattle and Simmental crossbred cattle through multi-omics analysis, and further provide a theoretical basis for the efficient development of the beef cattle industry. The domestic cattle in China are a unique genetic breed resource. They have characteristics like small size, strong adaptability, and distinctive meat quality. There are significant differences in the growth rate and meat production between these domestic cattle and Simmental hybrid cattle. However, the specific molecular-level differences between them are still unclear. This study conducted a comprehensive comparison between the domestic cattle in China and Simmental crossbred cattle, focusing on microbiology, short-chain fatty acids, blood metabolome, and transcriptome. The results revealed notable differences in the microbial Simpson index between the domestic and Simmental crossbred cattle. The differential strain Akkermansia was found to be highly negatively correlated with the differential short-chain fatty acid isocaproic acid, suggesting that Akkermansia may play a key role in the differences observed in isocaproic acid levels or phenotypes. Furthermore, the transcriptional metabolomics analysis indicated that the differentially expressed genes and metabolites were co-enriched in pathways related to insulin secretion, thyroid hormone synthesis, bile secretion, aldosterone synthesis and secretion, and Cyclic Adenosine Monophosphate (cAMP) signaling pathways. Key genes such as ADCY8 and 1-oleoyl-sn-glycero-3-phosphocholine emerged as crucial regulators of growth and metabolism in beef cattle. Full article

Blood is an important component for maintaining animal lives and synthesizing sugars, lipids, and proteins in organs. Revealing the relationship between genes and metabolite expression and milk somatic cell count (SCC), milk fat percentage, milk protein percentage, and lactose percentage in blood is helpful for understanding the molecular regulation mechanism of milk formation. Therefore, we separated the buffy coat and plasma from the blood of Xinjiang Brown cattle (XJBC) and Chinese Simmental cattle (CSC), which exhibit high and low SCC/milk fat percentage/milk protein percentage/lactose percentages, respectively. The expression of genes in blood and the metabolites in plasma was detected via RNA-Seq and LC-MS/MS, respectively. Based on the weighted gene coexpression network analysis (WGCNA) and functional enrichment analysis of differentially expressed genes (DEGs), we further found that the expression of genes in the blood mainly affected the SCC and milk fat percentage. Immune or inflammatory-response-related pathways were involved in the regulation of SCC, milk fat percentage, milk protein percentage, and lactose percentage. The joint analysis of the metabolome and transcriptome further indicated that, in blood, the metabolism pathways of purine, glutathione, glycerophospholipid, glycine, arginine, and proline are also associated with SCC, while lipid metabolism and amino-acid-related metabolism pathways are associated with milk fat percentage and milk protein percentage, respectively. Finally, related SCC, milk fat percentage, and milk protein percentage DEGs and DEMs were mainly identified in the blood. Full article

The aim of this experiment was to investigate the differences in metabolites in perirenal fat (PF) between Chinese Simmental cattle and Angus cattle. Six healthy 18-month-old male Angus cattle and Chinese Simmental cattle were selected, and the perirenal adipose tissue was collected after slaughtering. HE staining, a triglyceride assay kit, and liquid chromatography–tandem mass spectrometry (LC-MS/MS) technology were used to compare and analyze the differences in the cell morphology, lipid accumulation, and metabolites of the two types of PF. The results showed that the PF of Angus cattle had a larger cell area and stronger lipid deposition ability than that of Simmental cattle. A total of 567 metabolites were detected by LC-MS/MS technology, of which 119 were significantly upregulated in Angus cattle PF and 129 were significantly upregulated in Simmental cattle PF. Differential metabolites were enriched in pathways such as fatty acid biosynthesis, polyunsaturated fatty acid biosynthesis, regulation of adipocyte lipolysis, and oxidative phosphorylation. Finally, 12 metabolites that may cause phenotypic differences between the two types of perirenal adipose tissue were screened out from these pathways. This study has preliminarily screened out biomarkers that may affect lipid metabolism in PF, providing basic data for the further exploration of the metabolic characteristics of PF. Full article

Stearoyl-CoA desaturase-1 (SCD1) is a key enzyme in the biosynthesis of monounsaturated fatty acids and is considered a candidate gene for improving milk and meat quality traits. Sanger sequencing was employed to investigate the genetic polymorphism of the fifth exon and intron of bovine SCD1, revealing four SNPs, g.21272246 A>G, g.21272306 T>C, g.21272422 C>T, and g.21272529 A>G. Further variance analysis and multiple comparisons were conducted to examine the relationship between variation sites and economic traits in Chinese Simmental cattle, as well as milk production traits in Holstein cows. The findings revealed these four loci exhibited significant associations with carcass traits (carcass weight, carcass length, backfat thickness, and waist meat thickness), meat quality (pH value, rib eye area, and marbling score), adipogenic traits (fat score and carcass fat coverage rate), and fatty acid composition (linoleic acid and α-linolenic acid). Furthermore, these loci were additionally found to be significantly associated with average milk yield and milk fat content in cows. In addition, a haplotype analysis of combinations of SNPs showed that H2H3 has a significant association with adipogenic traits and H2H2 was associated with higher levels of linoleic acid and α-linolenic acid than the other combinations. These results suggest that the four SNPs are expected to be prospective genetic markers for the above economic traits. In addition, the function of SNPs in exon 5 of SCD1 on gene expression and protein structure needs to be explored in the future. Full article

Intramuscular fat content (IMF), one of the most important carcass traits in beef cattle, is controlled by complex regulatory factors. At present, molecular mechanisms involved in regulating IMF and fat metabolism in beef cattle are not well understood. Our objective was to integrate comparative transcriptomic and competing endogenous RNA (ceRNA) network analyses to identify candidate messenger RNAs (mRNAs) and regulatory RNAs involved in molecular regulation of longissimus dorsi muscle (LDM) tissue for IMF and fat metabolism of 5 beef cattle breeds (Angus, Chinese Simmental, Luxi, Nanyang, and Shandong Black). In total, 34 circRNAs, 57 lncRNAs, 15 miRNAs, and 374 mRNAs were identified by integrating gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Furthermore, 7 key subnets with 16 circRNAs, 43 lncRNAs, 7 miRNAs, and 237 mRNAs were detected through clustering analyses, whereas GO enrichment analysis of identified RNAs revealed 48, 13, and 28 significantly enriched GO terms related to IMF in biological process, molecular function, and cellular component categories, respectively. The main metabolic-signaling pathways associated with IMF and fat metabolism that were enriched included metabolic, calcium, cGMP-PKG, thyroid hormone, and oxytocin signaling pathways. Moreover, MCU, CYB5R1, and BAG3 genes were common among the 10 comparative groups defined as important candidate marker genes for fat metabolism in beef cattle. Contributions of transcriptome profiles from various beef breeds and a competing endogenous RNA (ceRNA) regulatory network underlying phenotypic differences in IMF provided novel insights into molecular mechanisms associated with meat quality. Full article

Depending on excellent prediction ability, machine learning has been considered the most powerful implement to analyze high-throughput sequencing genome data. However, the sophisticated process of tuning hyperparameters tremendously impedes the wider application of machine learning in animal and plant breeding programs. Therefore, we integrated an automatic tuning hyperparameters algorithm, tree-structured Parzen estimator (TPE), with machine learning to simplify the process of using machine learning for genomic prediction. In this study, we applied TPE to optimize the hyperparameters of Kernel ridge regression (KRR) and support vector regression (SVR). To evaluate the performance of TPE, we compared the prediction accuracy of KRR-TPE and SVR-TPE with the genomic best linear unbiased prediction (GBLUP) and KRR-RS, KRR-Grid, SVR-RS, and SVR-Grid, which tuned the hyperparameters of KRR and SVR by using random search (RS) and grid search (Gird) in a simulation dataset and the real datasets. The results indicated that KRR-TPE achieved the most powerful prediction ability considering all populations and was the most convenient. Especially for the Chinese Simmental beef cattle and Loblolly pine populations, the prediction accuracy of KRR-TPE had an 8.73% and 6.08% average improvement compared with GBLUP, respectively. Our study will greatly promote the application of machine learning in GP and further accelerate breeding progress. Full article

Beef calf production is a source of sustainable development for the beef cattle industry. However, no comparative studies have reported on the technical efficiency of different beef calf production systems and their influencing factors. Based on data from 218 Chinese farmers and 12 governments, in the present study, we constructed data envelopment analysis (DEA) models and conducted a comparative analysis of the technical efficiency of the main three beef calf production systems: the Simmental calf intensive production system (CIPS), Simmental calf semi-intensive production system (SCIPS) and Holstein bull calf intensive production system (BCIPS). Using Tobit models, we analyzed the effects of various factors. The results show that: (1) The technical efficiency of the production system of Simmental calf is higher than that of Holstein bull calf, and the efficiency of SCIPS is higher than that of CIPS. The technical efficiency (TE), pure technical efficiency (PTE) and scale efficiency (SE) of different systems are significantly different. (2) Policy on the environment positively affected (p < 0.01) the TE, TPE and SE of CIPS, but negatively affected the PTE of SCIPS. Therefore, appropriate environmental regulations have a positive effect on production efficiency, which means that measures should be taken according to the reality and characteristics of the production system, and policies applicable to other systems or regions may not be applicable in a given case. (3) The management level and technology training had positive effects on the TE, TPE and SE of the three systems, while the number of years of production had a negative or no significant effect. Producers are not the “perfectly rational economic man”, and the more knowledge they have, the more productive they will be. However, the “knowledge” referred to here is that which is adapted to production, not that which is traditional. The knowledge possessed by the producer should be updated continuously with the changes over time and the development of the industry, while outdated information is not considered as “knowledge” here. Therefore, to achieve sustainability, the government should fully consider the characteristics of the local breeding mode and, more importantly, the expected effects of policies to be implemented. Full article

Both waxy corn stover after fresh- (CF) and ripe-corn (CR) harvested are important byproducts of corn cropping system and have 20 d difference in harvest time. The study aimed to investigate the effects of prolonging harvest time on the nutritive value of corn stover silage by comparing CF with CR silages. In vitro ruminal experiment was firstly performed to investigate substrate degradation and fermentation of CF and CR silages. The CR diet was formulated by replacing 50% forage of CF silage with CR silage on a dry matter (DM) basis. Fourteen crossbred steers (Simmental × Limousin × local Chinese) aged 13 months with an average weight of 318.1 ± 37.1 kg were selected and randomly allocated into two dietary treatment groups. Although the CR silage had greater DM and fiber contents than CF silage, it did not alter in vitro degradation (p > 0.05), but with lower molar percentage of propionate and acetate to propionate ratio (p < 0.05). The cattle fed CR diet had a higher DM intake and lower fiber digestibility with reduction in 18S rRNA gene copies of protozoa and fungi and 16S rRNA gene copies of Fibrobacter succinogenes (p < 0.05). Further 16S rRNA gene amplicon analysis indicated a similar diversity of bacteria community between CR and CF treatments (p > 0.05). Few differences were observed in the abundance of genera larger than 1% (p > 0.05), except for the reduction in abundance of genera Ruminococcaceae_NK4A214_group in CR treatment (p < 0.05). In summary, prolonging 20 d harvest time of corn stover silage increases the forage fiber and DM content, which promotes feed intake with decreased fiber degradation, although rumen fermentation and growth performance are not changed in growing beef cattle. Full article

Visual identification of cattle in the wild provides an essential way for real-time cattle monitoring applicable to precision livestock farming. Chinese Simmental exhibit a yellow or brown coat with individually characteristic white stripes or spots, which makes a biometric identifier for identification possible. This work employed the observable biometric characteristics to perform cattle identification with an image from any viewpoint. We propose multi-center agent loss to jointly supervise the learning of DCNNs by SoftMax with multiple centers and the agent triplet. We reformulated SoftMax with multiple centers to reduce intra-class variance by offering more centers for feature clustering. Then, we utilized the agent triplet, which consisted of the features and the agents, to enforce separation among different classes. As there are no datasets for the identification of cattle with multi-view images, we created CNSID100, consisting of 11,635 images from 100 Chinese Simmental identities. Our proposed loss was comprehensively compared with several well-known losses on CNSID100 and OpenCows2020 and analyzed in an engineering application in the farming environment. It was encouraging to find that our approach outperformed the state-of-the-art models on the datasets above. The engineering application demonstrated that our pipeline with detection and recognition is promising for continuous cattle identification in real livestock farming scenarios. Full article

Body weight (BW) is an important longitudinal trait that directly described the growth gain of bovine in production. However, previous genome-wide association study (GWAS) mainly focused on the single-record traits, with less attention paid to longitudinal traits. Compared with traditional GWAS models, the association studies based on the random regression model (GWAS-RRM) have better performance in the control of the false positive rate through considering time-stage effects. In this study, the BW trait data were collected from 808 Chinese Simmental beef cattle aged 0, 6, 12, and 18 months, then we performed a GWAS-RRM to fit the time-varied SNP effect. The results showed a total of 37 significant SNPs were associated with BW. Gene functional annotation and enrichment analysis indicated FGF4, ANGPT4, PLA2G4A, and ITGA5 were promising candidate genes for BW. Moreover, these genes were significantly enriched in the signaling transduction pathway and lipid metabolism. These findings will provide prior molecular information for bovine gene-based selection, as well as facilitate the extensive application of GWAS-RRM in domestic animals. Full article

Chinese Simmental beef cattle play a key role in the Chinese beef industry due to their great adaptability and marketability. To achieve efficient genetic gain at a low breeding cost, it is crucial to develop a customized cost-effective low-density SNP panel for this cattle population. Thirteen growth, carcass, and meat quality traits and a BovineHD Beadchip genotyping of 1346 individuals were used to select trait-associated variants and variants contributing to great genetic variance. In addition, highly informative SNPs with high MAF in each 500 kb sliding window and in each genic region were also included separately. A low-density SNP panel consisting of 30,684 SNPs was developed, with an imputation accuracy of 97.4% when imputed to the 770 K level. Among 13 traits, the average prediction accuracy levels evaluated by genomic best linear unbiased prediction (GBLUP) and BayesA/B/Cπ were 0.22–0.47 and 0.18–0.60 for the ~30 K array and BovineHD Beadchip, respectively. Generally, the predictive performance of the ~30 K array was trait-dependent, with reduced prediction accuracies for seven traits. While differences in terms of prediction accuracy were observed among the 13 traits, the low-density SNP panel achieved moderate to high accuracies for most of the traits and even improved the accuracies for some traits. Full article

The objective of the present study was to perform a genome-wide association study (GWAS) for growth curve parameters using nonlinear models that fit original weight–age records. In this study, data from 808 Chinese Simmental beef cattle that were weighed at 0, 6, 12, and 18 months of age were used to fit the growth curve. The Gompertz model showed the highest coefficient of determination (R² = 0.954). The parameters’ mature body weight (A), time-scale parameter (b), and maturity rate (K) were treated as phenotypes for single-trait GWAS and multi-trait GWAS. In total, 9, 49, and 7 significant SNPs associated with A, b, and K were identified by single-trait GWAS; 22 significant single nucleotide polymorphisms (SNPs) were identified by multi-trait GWAS. Among them, we observed several candidate genes, including PLIN3, KCNS3, TMCO1, PRKAG3, ANGPTL2, IGF-1, SHISA9, and STK3, which were previously reported to associate with growth and development. Further research for these candidate genes may be useful for exploring the full genetic architecture underlying growth and development traits in livestock. Full article

The beef aging process is essential for compliance with certain major requisites, such as sensory characteristics for cooking and meat processing. Meat quality analysis of Yunling cattle, a new hybrid beef cattle bred by Chinese researchers, during the aging process, represents a major research gap. To explore Yunling beef initially, indicators associated with meat quality during the aging process of Yunling, Simmental, and Wenshan cattle were measured. In addition, some important economic traits were detected in the three breeds, including growth performance and carcass characteristics. The results showed that the growth performance, carcass traits, pH, and water holding capacity of Yunling and Simmental cattle were basically the same and better, respectively, than those of Wenshan cattle. The proportions of individual fatty acids in Yunling beef were healthier than in the other two breeds. Aging time did not affect the fatty acid profiles of the beef (p > 0.05). The contents of certain fatty acids in the three beef types displayed some differences in terms of days of aging (p < 0.05). The tenderness and meat color were better in the Yunling beef as the aging time increased, indicating that Yunling beef aged for 7 days was more suitable for cooking, exhibiting better sensory characteristics. Thus, a 7-day short-term aging process is very effective in improving the quality of Yunling beef. Our study attempted to fill a gap in the Yunling beef quality analysis during aging, providing further evidence for Yunling beef improvement. Full article