Transcriptome Characterization of Short Distance Transport Stress in Beef Cattle Blood

Characterization of feed efficiency-related key signatures molecular in different cattle breeds

Feed efficiency is a major constraint in the beef industry and has a significant negative correlation with residual feed intake (RFI). RFI is widely used as a measure of feed efficiency in beef cattle and is independent of economic traits such as body weight and average daily gain. However, key traits with commonality or specificity among beef cattle breeds at the same level of RFI have not been reported. Accordingly, the present study hypothesized that signatures associated with feed efficiency would have commonality or specificity in the liver of cattle breeds at the same RFI level. By comparing and integrating liver transcriptome data, we investigated the critical signatures closely associated with RFI in beef cattle using weighted co-expression network analysis, consensus module analysis, functional enrichment analysis and protein network interaction analysis. The results showed that the consensus modules in Angus and Charolais cattle were negatively correlated, and four (turquoise, red, tan, yellow) were significantly positively correlated in Angus liver, while (turquoise, red) were significantly negatively correlated in Charolais liver. These consensus modules were found to be primarily involved in biological processes such as substance metabolism, energy metabolism and gene transcription, which may be one of the possible explanations for the difference in feed efficiency between the two beef breeds. This research also identified five key candidate genes, PLA2G12B, LCAT, MTTP, LCAT, ABCA1 and FADS1, which are closely associated with hepatic lipid metabolism. The present study has identified some modules, genes and pathways that may be the major contributors to the variation in feed efficiency among different cattle breeds, providing a new perspective on the molecular mechanisms of feed efficiency in beef cattle and a research basis for investigating molecular markers associated with feed efficiency in beef cattle.

Dietary Supplementation of Tannic Acid Promotes Performance of Beef Cattle via Alleviating Liver Lipid Peroxidation and Improving Glucose Metabolism and Rumen Fermentation

This study aimed to investigate the effects of dietary tannic acid (TAN) on the gas production, growth performance, antioxidant capacity, rumen microflora, and fermentation function of beef cattle through in vitro and in vivo experiments. TAN was evaluated at 0.15% (dry matter basis, DM) in the in vitro experiment and 0.20% (DM basis) in the animal feeding experiment. The in vitro results revealed that compared with control (CON, basal diet without TAN), the addition of TAN significantly increased the cumulative gas production and asymptotic gas production per 0.20 g dry matter substrate (p < 0.01), with a tendency to reduce methane concentration after 96 h of fermentation (p = 0.10). Furthermore, TAN supplementation significantly suppressed the relative abundance of Methanosphaera and Methanobacteriaceae in the fermentation fluid (LDA > 2.50, p < 0.05). The in vivo experiment showed that compared with CON, the dietary TAN significantly improved average daily gain (+0.15 kg/d), dressing percent (+1.30%), net meat percentage (+1.60%), and serum glucose concentration (+23.35%) of beef cattle (p < 0.05), while it also significantly reduced hepatic malondialdehyde contents by 25.69% (p = 0.02). Moreover, the TAN group showed significantly higher alpha diversity (p < 0.05) and increased relative abundance of Ruminococcus and Saccharomonas (LDA > 2.50, p < 0.05), while the relative abundance of Prevotellaceae in rumen microbial community was significantly decreased (p < 0.05) as compared to that of the CON group. In conclusion, the dietary supplementation of TAN could improve the growth and slaughter performance and health status of beef cattle, and these favorable effects might be attributed to its ability to alleviate liver lipid peroxidation, enhance glucose metabolism, and promote a balanced rumen microbiota for optimal fermentation.

Recent advances in feed and nutrition of beef cattle in China - A review

The beef cattle industry in China has advanced remarkably since its reform and opening up; consequently, China has become the world's third-largest beef cattle producer. China is also one of the countries with the most substantial research input and output in the field of beef cattle feed and nutrition. The progress and innovation by China in the research field of beef cattle feed and nutrition have undoubtedly promoted the development of the domestic beef cattle industry. This review summarizes recent advances in feed resource development, nutrient requirements, and nutritional regulation of beef cattle in China. Limitations in current research and perspectives on future work are also discussed.

Candidate Genes and Gene Networks Change with Age in Japanese Black Cattle by Blood Transcriptome Analysis

Age is an important physiological factor that affects the metabolism and immune function of beef cattle. While there have been many studies using the blood transcriptome to study the effects of age on gene expression, few have been reported on beef cattle. To this end, we used the blood transcriptomes of Japanese black cattle at different ages as the study subjects and screened 1055, 345, and 1058 differential expressed genes (DEGs) in the calf vs. adult, adult vs. old, and calf vs. old comparison groups, respectively. The weighted co-expression network consisted of 1731 genes. Finally, blue, brown, and yellow age-specific modules were obtained, in which genes were enriched in signaling pathways related to growth and development and immune metabolic dysfunction, respectively. Protein-protein interaction (PPI) analysis showed gene interactions in each specific module, and 20 of the highest connectivity genes were chosen as potential hub genes. Finally, we identified 495, 244, and 1007 genes by exon-wide selection signature (EWSS) analysis of different comparison groups. Combining the results of hub genes, we found that VWF, PARVB, PRKCA, and TGFB1I1 could be used as candidate genes for growth and development stages of beef cattle. CORO2B and SDK1 could be used as candidate marker genes associated with aging. In conclusion, by comparing the blood transcriptome of calves, adult cattle, and old cattle, the candidate genes related to immunity and metabolism affected by age were identified, and the gene co-expression network of different age stages was constructed. It provides a data basis for exploring the growth, development, and aging of beef cattle.

Ferroptosis-related genes are involved in asthma and regulate the immune microenvironment

Background: Asthma was a chronic inflammatory illness driven by complicated genetic regulation and environmental exposure. The complex pathophysiology of asthma has not been fully understood. Ferroptosis was involved in inflammation and infection. However, the effect of ferroptosis on asthma was still unclear. The study was designed to identify ferroptosis-related genes in asthma, providing potential therapeutic targets. Methods: We conducted a comprehensive analysis combined with WGCNA, PPI, GO, KEGG, and CIBERSORT methods to identify ferroptosis-related genes that were associated with asthma and regulated the immune microenvironment in GSE147878 from the GEO. The results of this study were validated in GSE143303 and GSE27066, and the hub genes related to ferroptosis were further verified by immunofluorescence and RT-qPCR in the OVA asthma model. Results: 60 asthmatics and 13 healthy controls were extracted for WGCNA. We found that genes in the black module (r = -0.47, p < 0.05) and magenta module (r = 0.51, p < 0.05) were associated with asthma. CAMKK2 and CISD1 were discovered to be ferroptosis-related hub genes in the black and magenta module, separately. We found that CAMKK2 and CISD1 were mainly involved in the CAMKK-AMPK signaling cascade, the adipocytokine signaling pathway, the metal cluster binding, iron-sulfur cluster binding, and 2 iron, 2 sulfur cluster binding in the enrichment analysis, which was strongly correlated with the development of ferroptosis. We found more infiltration of M2 macrophages and less Tregs infiltration in the asthma group compared to healthy controls. In addition, the expression levels of CISD1 and Tregs were negatively correlated. Through validation, we found that CAMKK2 and CISD1 expression were upregulated in the asthma group compared to the control group and would inhibit the occurrence of ferroptosis. Conclusion: CAMKK2 and CISD1 might inhibit ferroptosis and specifically regulate asthma. Moreover, CISD1 might be tied to the immunological microenvironment. Our results could be useful to provide potential immunotherapy targets and prognostic markers for asthma.

Differential gene expression analysis using RNA-seq in the blood of goats exposed to transportation stress

Transportation stress causes significant changes in physiological responses in goats; however, studies exploring the transcriptome of stress are very limited. The objective of this study was to determine the differential gene expressions and related pathways in the blood samples using RNA-seq procedure in Spanish goats subjected to different durations of transportation stress. Fifty-four male Spanish goats (8-mo old; BW = 29.7 ± 2.03 kg) were randomly subjected to one of three treatments (TRT; n = 18 goats/treatment): (1) transported for 180 min, (2) transported for 30 min, or (3) held in pens (control). Blood samples were collected before and after treatment for stress hormone, metabolite, and transcriptomic analysis. RNA-seq technology was used to obtain the transcriptome profiles of blood. Analysis of physiological data using SAS showed that plasma cortisol concentrations were higher (P < 0.01) in 180 min and 30 min groups compared to the control group. Enrichment analysis of DEGs related to transportation stress through Gene Ontology and KEGG databases revealed that the differentially expressed genes related to inflammatory pathways, caspases, and apoptosis such as IL1R2, CASP14, CD14, TLR4, and MAPK14 were highly enriched in the transported group of goats compared to non-transported goats. Stress in goats leads to a sequence of events at cellular and molecular levels that causes inflammation and apoptosis.

Genome-wide scan for selective sweeps identifies novel loci associated with resistance to mastitis in German Holstein cattle

Domestication and selection significantly changed phenotypic and behavioural traits in modern domestic animals. In this study, to identify the genomic regions associated with mastitis, genomic data of German Holstein dairy cattle were analysed. The samples were genotyped using the Bovine 50 K SNP chip. For each defined healthy and sick group, 133 samples from 13,276 genotyped dairy cows were selected based on mastitis random residual effects. Grouping was done to infer selection signatures based on XP-EHH statistic. The results revealed that for the top 0.01 percentile of the obtained XP-EHH values, five genomic regions on chromosomes 8, 11, 12, 14 and 26 of the control group, and four regions on chromosomes 3, 4 (two regions) and 22 of the case group, have been under selection. Also, consideration of the top 0.1 percentile of the XP-EHH values, clarified 21 and 15 selective sweeps in the control and case group, respectively. This study identified some genomic regions containing potential candidate genes associated with resistance and susceptibility to mastitis, immune system and inflammation, milk traits, udder morphology and different types of cancers. In addition, these regions overlap with some quantitative trait loci linked to clinical mastitis, immunoglobulin levels, somatic cell score, udder traits, milk fat and protein, milk yield, milking speed and veterinary treatments. It is noteworthy that we found two regions in the healthy group (on chromosomes 12 and 14) with strong signals, which were not described previously. It is likely that future research could link these identified genomic regions to mastitis. The results of the current study contribute to the identification of causal mutations, genomic regions and genes affecting mastitis incidence in dairy cows.

Multi-transcriptomics reveals RLMF axis-mediated signaling molecules associated with bovine feed efficiency

The regulatory axis plays a vital role in interpreting the information exchange and interactions among mammal organs. In this study on feed efficiency, it was hypothesized that a rumen-liver-muscle-fat (RLMF) regulatory axis exists and scrutinized the flow of energy along the RLMF axis employing consensus network analysis from a spatial transcriptomic standpoint. Based on enrichment analysis and protein-protein interaction analysis of the consensus network and tissue-specific genes, it was discovered that carbohydrate metabolism, energy metabolism, immune and inflammatory responses were likely to be the biological processes that contribute most to feed efficiency variation on the RLMF regulatory axis. In addition, clusters of genes related to the electron respiratory chain, including ND (2,3,4,4L,5,6), NDUF (A13, A7, S6, B3, B6), COX (1,3), CYTB, UQCR11, ATP (6,8), clusters of genes related to fatty acid metabolism including APO (A1, A2, A4, B, C3), ALB, FG (A, G), as well as clusters of the ribosomal-related gene including RPL (8,18A,18,15,13, P1), the RPS (23,27A,3A,4X), and the PSM (A1-A7, B6, C1, C3, D2-D4, D8 D9, E1) could be the primary effector genes responsible for feed efficiency variation. The findings demonstrate that high feed efficiency cattle, through the synergistic action of the regulatory axis RLMF, may improve the efficiency of biological processes (carbohydrate metabolism, protein ubiquitination, and energy metabolism). Meanwhile, high feed efficiency cattle might enhance the ability to respond to immunity and inflammation, allowing nutrients to be efficiently distributed across these organs associated with digestion and absorption, energy-producing, and energy-storing organs. Elucidating the distribution of nutrients on the RLMF regulatory axis could facilitate an understanding of feed efficiency variation and achieve the study on its molecular regulation.

Tannic acid supplementation in the diet of Holstein bulls: Impacts on production performance, physiological and immunological characteristics, and ruminal microbiota

This study was conducted to evaluate the influences of supplementing tannic acid (TA) at different doses on the production performance, physiological and immunological characteristics, and rumen bacterial microbiome of cattle. Forty-eight Holstein bulls were randomly allocated to four dietary treatments: the control (CON, basal diet), the low-dose TA treatment [TAL, 0.3% dry matter (DM)], the mid-dose TA treatment (TAM, 0.9% DM), and the high-dose TA treatment (TAH, 2.7% DM). This trial consisted of 7 days for adaptation and 90 days for data and sample collection, and samples of blood and rumen fluid were collected on 37, 67, and 97 d, respectively. The average daily gain was unaffected (P > 0.05), whilst the ruminal NH3-N was significantly decreased (P < 0.01) by TA supplementation. The 0.3% TA addition lowered (P < 0.05) the levels of ruminal isobutyrate, valerate, and tumor necrosis factor alpha (TNF-α), and tended to (P < 0.1) increase the gain to feed ratio. The digestibility of DM, organic matter (OM), and crude protein, and percentages of butyrate, isobutyrate, and valerate were lower (P < 0.05), while the acetate proportion and acetate to propionate ratio in both TAM and TAH were higher (P < 0.05) than the CON. Besides, the 0.9% TA inclusion lessened (P < 0.05) the concentrations of glucagon and TNF-α, but enhanced (P < 0.05) the interferon gamma (IFN-γ) level and Simpson index of ruminal bacteria. The 2.7% TA supplementation reduced (P < 0.05) the intake of DM and OM, and levels of malondialdehyde and thyroxine, while elevated (P < 0.05) the Shannon index of the rumen bacterial populations. Moreover, the relative abundances of the phyla Fibrobacteres and Lentisphaerae, the genera Fibrobacter and Bradyrhizobium, and the species Bradyrhizobium sp., Lachnospiraceae bacterium RM29, and Lachnospiraceae bacterium CG57 were highly significantly (q < 0.01) or significantly (q < 0.05) raised by adding 2.7% TA. Results suggested that the TA addition at 0.3% is more suitable for the cattle, based on the general comparison on the impacts of supplementing TA at different doses on all the measured parameters.

Improved biomarker discovery through a plot twist in transcriptomic data analysis

Background

Transcriptomic analysis is crucial for understanding the functional elements of the genome, with the classic method consisting of screening transcriptomics datasets for differentially expressed genes (DEGs). Additionally, since 2005, weighted gene co-expression network analysis (WGCNA) has emerged as a powerful method to explore relationships between genes. However, an approach combining both methods, i.e., filtering the transcriptome dataset by DEGs or other criteria, followed by WGCNA (DEGs + WGCNA), has become common. This is of concern because such approach can affect the resulting underlying architecture of the network under analysis and lead to wrong conclusions. Here, we explore a plot twist to transcriptome data analysis: applying WGCNA to exploit entire datasets without affecting the topology of the network, followed with the strength and relative simplicity of DEG analysis (WGCNA + DEGs). We tested WGCNA + DEGs against DEGs + WGCNA to publicly available transcriptomics data in one of the most transcriptomically complex tissues and delicate processes: vertebrate gonads undergoing sex differentiation. We further validate the general applicability of our approach through analysis of datasets from three distinct model systems: European sea bass, mouse, and human.

Results

In all cases, WGCNA + DEGs clearly outperformed DEGs + WGCNA. First, the network model fit and node connectivity measures and other network statistics improved. The gene lists filtered by each method were different, the number of modules associated with the trait of interest and key genes retained increased, and GO terms of biological processes provided a more nuanced representation of the biological question under consideration. Lastly, WGCNA + DEGs facilitated biomarker discovery.

Conclusions

We propose that building a co-expression network from an entire dataset, and only thereafter filtering by DEGs, should be the method to use in transcriptomic studies, regardless of biological system, species, or question being considered.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12915-022-01398-w.

Construction of Severe Eosinophilic Asthma Related Competing Endogenous RNA Network by Weighted Gene Co-Expression Network Analysis

Background: Currently, disease control in patients with severe eosinophilic asthma is not optimistic. Competing endogenous RNA (ceRNA) networks have been found to play a key role in asthma in recent years. However, it is unclear whether ceRNA networks play an important part in severe eosinophilic asthma. Methods: Firstly, gene expression profiles related to severe eosinophilic asthma were downloaded from the Gene Expression Omnibus (GEO) database. Secondly, the key modules were identified by the weighted gene co-expression network analysis (WGCNA). Thirdly, genes in modules highly associated with severe eosinophilic asthma were selected for further construction of the ceRNA network. Fourthly, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed on hub genes. Finally, the results of this study were validated on the GSE143303, GSE137268, and GSE147878 datasets. Results: 22 severe eosinophilic asthmatics and 13 healthy controls were extracted for WGCNA. We found that the genes in the black module (r = -0.75, p < 0.05) and yellow module (r = 0.65, p < 0.05) were highly associated with severe eosinophilic asthma. EP300 was discovered to serve the key connecting function in the ceRNA network. Surprisingly, lncRNAs seem to eliminate the role of EP300 in the black module and we discovered that CCT8 and miRNA-mRNA formed a circRNA-miRNA-mRNA network in the yellow module. We found that EP300 and FOXO3 in the black module were regulated by steroid hormones in the enrichment analysis, which were related to the medication used by the patient. Through validation of other datasets, we found that the hub genes in the yellow module were the key genes in the treatment of severe eosinophilic asthma. In particular, RPL17 and HNRNPK might specifically regulate severe eosinophilic asthma. Conclusion: RPL17 and HNRNPK might particularly regulate severe eosinophilic asthma. Our results could be useful to provide potential immunotherapy targets and prognostic markers for severe eosinophilic asthma.

Genes and regulatory mechanisms associated with experimentally-induced bovine respiratory disease identified using supervised machine learning methodology

Bovine respiratory disease (BRD) is a multifactorial disease involving complex host immune interactions shaped by pathogenic agents and environmental factors. Advancements in RNA sequencing and associated analytical methods are improving our understanding of host response related to BRD pathophysiology. Supervised machine learning (ML) approaches present one such method for analyzing new and previously published transcriptome data to identify novel disease-associated genes and mechanisms. Our objective was to apply ML models to lung and immunological tissue datasets acquired from previous clinical BRD experiments to identify genes that classify disease with high accuracy. Raw mRNA sequencing reads from 151 bovine datasets (n = 123 BRD, n = 28 control) were downloaded from NCBI-GEO. Quality filtered reads were assembled in a HISAT2/Stringtie2 pipeline. Raw gene counts for ML analysis were normalized, transformed, and analyzed with MLSeq, utilizing six ML models. Cross-validation parameters (fivefold, repeated 10 times) were applied to 70% of the compiled datasets for ML model training and parameter tuning; optimized ML models were tested with the remaining 30%. Downstream analysis of significant genes identified by the top ML models, based on classification accuracy for each etiological association, was performed within WebGestalt and Reactome (FDR ≤ 0.05). Nearest shrunken centroid and Poisson linear discriminant analysis with power transformation models identified 154 and 195 significant genes for IBR and BRSV, respectively; from these genes, the two ML models discriminated IBR and BRSV with 100% accuracy compared to sham controls. Significant genes classified by the top ML models in IBR (154) and BRSV (195), but not BVDV (74), were related to type I interferon production and IL-8 secretion, specifically in lymphoid tissue and not homogenized lung tissue. Genes identified in Mannheimia haemolytica infections (97) were involved in activating classical and alternative pathways of complement. Novel findings, including expression of genes related to reduced mitochondrial oxygenation and ATP synthesis in consolidated lung tissue, were discovered. Genes identified in each analysis represent distinct genomic events relevant to understanding and predicting clinical BRD. Our analysis demonstrates the utility of ML with published datasets for discovering functional information to support the prediction and understanding of clinical BRD.

Metagenomics Reveals That Proper Placement After Long-Distance Transportation Significantly Affects Calf Nasopharyngeal Microbiota and Is Critical for the Prevention of Respiratory Diseases

Transportation is an inevitable phase for the cattle industry, and its effect on the respiratory system of transported cattle remains controversial. To reveal cattle’s nasopharyngeal microbiota dynamics, we tracked a batch of beef calves purchased from an auction market, transported to a farm by vehicle within 3 days, and adaptively fed for 7 days. Before and after the transport and after the placement, a total of 18 nasopharyngeal mucosal samples were collected, and microbial profiles were obtained using a metagenomic shotgun sequencing approach. The diversity, composition, structure, and function of the microbiota were collected at each time point, and their difference was analyzed. The results showed that, before the transportation, there were a great abundance of potential bovine respiratory disease (BRD)-related pathogens, and the transportation did not significantly change their abundance. After the transportation, 7 days of placement significantly decreased the risk of BRD by decreasing the abundance of potential BRD-related pathogens even if the diversity was decreased. We also discussed the controversial results of transportation’s effect in previous works and the decrease in diversity induced by placement. Our work provided more accurate information about the effect of transportation and the followed placement on the calf nasopharyngeal microbial community, indicated the importance of adaptive placement after long-distance transport, and is helpful to prevent BRD induced by transportation stress.

Small RNA-Seq Analysis Reveals miRNA Expression of Short Distance Transportation Stress in Beef Cattle Blood

Simple Summary

In this study, three miRNA modules were identified in a cattle short-distance transportation stress model, and the turquoise module showed key miRNA sets according to their correlation with hub genes. Further, hub miRNAs were identified based on their targeting relationship with hub genes in our previous study. This finding provides the potential utility for predicting and treatment of short-distance transportation stress in beef cattle.

Abstract

Transportation is a crucial phase in the beef cattle industry, and the annual losses caused by beef cattle transport stress are substantial. Because of its huge economic losses, such as lower growth rate and even death, long-distance transportation stress has attracted more attention from beef production practitioners because of its huge economic losses. Compared with the long-distance transportation stress, the short-distance transportation stress was ignored for the reason of no obvious symptoms in cattle. Our previous study showed that the disorder of B cell function could be a potential health risk after short-distance transportation. However, the transcriptome details of the changes in the cattle blood after short-distance transportation and the molecular mechanisms for the regulation of the developmental process are not clearly known. In this study, a total of 10 Qinchuan cattle were used to compare the molecular characteristics of blood before and after short-distance transportation. The miRNA-seq showed that 114 differentially expressed miRNAs (DEMs) were found (40 upregulated and 74 downregulated) between two groups before and after transportation. Furthermore, more than 90% of the miRNAs with counts of more than 10 were used to construct a co-expression network by weighted correlation network analysis (WGCNA), and four independent modules were identified. According to their relationship with 30 hub genes, the turquoise module was the key module in this study. The regulator network of hub genes and miRNAs in the turquoise module was constructed by miRNAs targeting genes predicting, and the miRNAs had targeting sites within hub genes that could be identified as hub-miRNAs. Further, it showed that CD40 and ITPKB had the same targeting miRNAs (miR-339a/b), and the newly discovered hub miRNAs filled the gaps in our previous study about the relationship between hub genes in short-distance transportation stress and provided the potential utility for predicting and treatment of short-distance transportation stress in beef cattle.