AUTHOR=Zhao Haidong , Tang Xiaoqin , Wu Mingli , Li Qi , Yi Xiaohua , Liu Shirong , Jiang Junyi , Wang Shuhui , Sun Xiuzhu TITLE=Transcriptome Characterization of Short Distance Transport Stress in Beef Cattle Blood JOURNAL=Frontiers in Genetics VOLUME=12 YEAR=2021 URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2021.616388 DOI=10.3389/fgene.2021.616388 ISSN=1664-8021 ABSTRACT=
The transportation is a crucial phase in beef cattle industry, and the annual losses caused by beef cattle transport stress are substantial. Several studies have described the effect of long distance transportation stress on animal health, such as disorder in nervous, endocrine, immune, and metabolic system. However, molecular mechanisms underlying short distance transportation stress is still poorly understood. Present study aims to investigate the effect of short distance transportation by measuring the hematological indices and transcriptomic analysis. In this study, a total 10 Qinchuan cattle were used to compare the molecular characteristics of blood before and after transportation. We have found that a stress-related marker “white blood cell count (WBC)” increased significantly after transportation. The decrease in triglyceride (TG), cholestenone (CHO), high-density lipoprotein (HDL), and low-density lipoprotein (LDL) showed that energy expenditure was increased after transportation, but not enough to activate fatty decomposition. Intriguingly, the decrease of malondialdehyde (MDA) showed that cattle were more resilience to oxidative stress. The RNA-seq showed that 1,092 differentially expressed genes (DEGs) were found (329 up-regulated and 763 down-regulated) between group before and group after. The GO and KEGG enrichment showed that the metabolic pathway and B cell function related pathways were enriched. Furthermore, median absolute deviation (MAD) top 5,000 genes were used to construct a co-expression network by weighted correlation network analysis (WGCNA), and 11 independent modules were identified. Combing with protein-protein interaction (PPI) analysis, the verification of quantitative real-time PCR (qPCR) and the correlation of B cell function,