GSE123808
Changes of metabolic genes expression in lungs of bleomycin-treated mice
Purpose: Explore whether bleomycin treatment will induce changes of metabolic genes expression via next-generation sequencing (NGS) in mouse lung tissues. Methods: Four groups of wild type mice were intratracheally injected with 25 µl PBS or bleomycin (15 mg/kg) after anesthetization. 10 days after bleomycin treatment, lung tissues were removed for RNA collection. Three samples per group were mixed to one sample and used for next RNA purification. RNA samples were then used for high-throughput sequencing according to standard operation based on RNA BGISEQ-500. Results: Using an optimized data analysis workflow, we mapped about 21.9 million sequence reads per sample to the mouse genome (build mm10) and identified 1024 upregulated and 936 downregulated genes in lungs of bleomycin-treated mice. RNA-seq data had a linear relationship with qRT–PCR for more than four orders of magnitude. Altered expression of 20 genes was confirmed with qRT–PCR, demonstrating the high degree of sensitivity of the RNA-seq method. Hierarchical clustering of differentially expressed genes uncovered metabolic changes of many carbohydrates, amino acid and fatty acid. Data analysis with BWA and TopHat workflows revealed a significant overlap yet provided complementary insights in metabolism profiling. Conclusions: Our study represents the first detailed analysis of metabolic changes in lungs of bleomycin-treated mice with biologic replicates, generated by RNA-seq technology. The optimized data analysis workflows reported here should provide a framework for comparative investigations of expression profiles. We conclude that RNA-seq based metabolic genes characterization would expedite genetic network analyses and permit the dissection of complex biologic functions. Overall design: mRNA profiles of metabolic genes expression in bleomycin-treated or untreated mice were generated by deep sequencing, in triplicate, using BGISEQ-500.