Description
The knowledge of an expression network signature in end-stage heart failure (HF) diseased hearts may offer important insights into the complex pathogenesis of advanced cardiac failure, as well as it may provide potential targets for therapeutic intervention. In this study, the NGS sequencing of RNA (RNA-Seq) method was employed to obtain the whole transcriptome of cardiac tissues from transplant recipients with advanced stage of HF. The analysis of RNA-Seq data presents novel challenges and many methods have been developed for the purpose of mapping reads to genomic features and quantifying gene expression. The main goal of this work was to identify, characterize and catalogue all the transcripts expressed within cardiac tissue and to quantify the differential expression of transcripts in both physio- and pathological conditions through whole transcriptome analyses. Expression levels, differential splicing, allele-specific expression, RNA editing and fusion transcripts constitute important information when comparing samples for disease related studies. Analysis methods for RNA-Seq data are continuing to evolve. Thus, in order to find the best solution for filter generated list of differentially expressed genes, an informatic approach of NOISeq BIO method has been applied in this RNA-Seq analysis. Most of the genes obtained by filtering differentially expressed gene list, have been experimentally validated by Real time RT-PCR. Noteworthy, these findings provide valuable resources for further studies of the molecular mechanisms involved in heart ischemic response thus leading to potential novel biomarkers and targets for therapeutic intervention in the onset and progression of cardiomyopathies. Overall design: Heart biopsies from candidates for solid organ transplantation were collected and their RNA samples were used for high-throughput sequencing purposes. Libraries were sequenced on the Illumina HiSeq2000 NGS platform.