Transcriptome Characterization of Short Distance Transport Stress in Beef Cattle Blood

Zhao, Hailin; Tang, Xiaoqin; Wu, Mingli; Li, Qi; Yi, Xiaohua; Liu, Shirong; Jiang, Junyi; Wang, Shuhui; Sun, Xiuzhu

doi:10.3389/fgene.2021.616388

Cited by 16 publications

(17 citation statements)

References 49 publications

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“…Over the past several years, RNA-Seq analysis has been utilized in bovine disease research to evaluate gene expression related to risk of BRD development, stress response, and viral lesion development 30,31,32,33,34,35,73,74 . Primarily, studies that generate RNA-Seq data utilize statistical platforms and techniques for the detection of differentially expressed genes and subsequent construction of functional networks or modules.…”

Section: Discussionmentioning

confidence: 99%

Genes and Mechanisms Associated With Experimentally Induced Bovine Respiratory Disease Identified With Supervised Machine Learning Methodology on Integrated Transcriptomic Datasets

Scott¹,

Woolums²,

Swiderski³

et al. 2021

Preprint

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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 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 (5-fold, repeated 10 times) were applied in a 70:30 training/testing ratio. Downstream analysis of genes identified by the top sparse classifiers for each etiological association was performed within WebGestalt and Reactome (FDR < 0.05). Support vector machines was routinely the top non-sparse classifier for predicting etiological disease versus sham control. Nearest shrunken centroid and Poisson linear discriminant analysis with power transformation could reliably classify IBR and BRSV with 100% accuracy. Genes identified in IBR and BRSV, but not BVDV, were related to type I interferon production and IL-8 secretion, specifically in lymphoid tissue and not lung. Genes identified in Mannheimia haemolytica infections 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. The few genes shared across analyses may be reliably associated with clinical BRD. Our analysis demonstrates the utility of ML with published datasets for discovering functional information to support prediction and understanding BRD acquisition.

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Section: Discussionmentioning

confidence: 99%

Genes and Mechanisms Associated With Experimentally Induced Bovine Respiratory Disease Identified With Supervised Machine Learning Methodology on Integrated Transcriptomic Datasets

Scott¹,

Woolums²,

Swiderski³

et al. 2021

Preprint

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“…The transportation distance was 70 km, and the vehicle was a singlelayer Foton cart with a maximum speed of 60 km/h and an average speed of 30 km/h. The interval time between the two blood samples collection was 6-8 h. The temperature ranged from 26~32 • C, and the humidity was 70% [11].…”

Section: Animal Model Of Short-distance Transport Stressmentioning

confidence: 99%

“…WGCNA parameters were as follows: power = 6, minModuleSize = 30, networkType = "signed", corType = "Pearson", TOMType = "signed", mergeCutHeight = 0.25. The relationship between hub genes [11] in the turquoise module and different modules of miRNA was constructed by correlation analysis. The relationship between hub genes and their targeting miRNA in key miRNA module was constructed by miranda.…”

Section: Small Rna-seq Analysis and Statisticsmentioning

confidence: 99%

“…The mechanism of short-distance transportation was still poorly understood compared with long-distance transportation. Our previous study showed that the disorder of B cell differentiation, proliferation, survival, and apoptosis were the potential molecular mechanisms in short-distance transportation stress [11]. It suggested that beef cattle are susceptible to the attack of pathogenic bacteria after short-distance transportation.…”

Section: Introductionmentioning

confidence: 99%

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

Tang

Raza

et al. 2021

Animals

Self Cite

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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.

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“…In China and North America, long-distance transport was an inevitable phase for the cattle industry ( Cirone et al, 2019 ). Besides affecting the nervous, endocrine, immune, and energy supply systems ( Van Engen and Coetzee, 2018 ), the latest research found that transportation also affected cattle’s blood transcriptome, indicating that transport affected B cells’ activity ( Zhao et al, 2021 ). It is not surprising that transport was widely considered an intense BRD trigger ( Earley et al, 2017 ; Zeineldin et al, 2019 ).…”

Section: Introductionmentioning

confidence: 99%

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

Cui

Cai

et al. 2021

Front. Microbiol.

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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.

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Transcriptome Characterization of Short Distance Transport Stress in Beef Cattle Blood

Cited by 16 publications

References 49 publications

Genes and Mechanisms Associated With Experimentally Induced Bovine Respiratory Disease Identified With Supervised Machine Learning Methodology on Integrated Transcriptomic Datasets

Genes and Mechanisms Associated With Experimentally Induced Bovine Respiratory Disease Identified With Supervised Machine Learning Methodology on Integrated Transcriptomic Datasets

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

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

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