Pluto Bioinformatics

GSE154798: Hispidulin attenuates cardiac hypertrophy by improving mitochondrial dysfunction

Bulk RNA sequencing

Purpose:RNA-Seq analysis was performed on mouse hearts with or without hispidulin treatment 4 weeks after arotic banding or sham surgery to determining the effect of hispidulin on pressure overload induced cardiac hypertrophy.; Methods: the mRNA profiles of mouse hearts underwent sham or arotic banding surgery with treatment of hispidulin or DMSO were generated by RNA-seq analysis in triplicate. The expression level of gene was calculated by RSEM(v.1.2.12). Differential expression analysis was performed using the DESeq2(V 1.4.5).; Results: RNA isolation, library construction, and sequencing were performed on a BGISEQ-500 (Beijing Genomic Institution, www.genomics.org.cn, BGI). For the gene expression analysis, the fold changes were also estimated according to the fragments per kilobase of exon per million fragments mapped (FPKM) in each sample. The significance of different gene expression was defined by the following filter criteria: false discovery rate (FDR) 0.001 and log2-ratio 1. After comparing of DMSO+AB group and hispidulin+AB group, we found that 113 genes were significantly differentially expressed. Gene ontology and cluster analysis indicated that alternated genes were enriched in fatty acid oxidation, glucose metabolism, TCA cycle, oxidative phosphorylation, hypertrophic cardiomyopathy, ECM organism, oxidative stress and unfolded protein binding. This result indicated that hispidulin improved mitochondrial function.; Conclusions: Our study represents the first detailed analysis of heart transcriptomes, 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. Our results show that NGS offers a comprehensive and more accurate quantitative and qualitative evaluation of mRNA content within a cell or tissue. We conclude that RNA-seq based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions. SOURCE: Chen Liu (liuch75@mail.sysu.edu.cn) - The First Affiliated Hospital of Sun Yat-sen University