New Methods in Cardiovascular Biology Analysis of Transcriptome Complexity Through RNA Sequencing in Normal and Failing Murine Hearts

Rationale: Accurate and comprehensive de novo transcriptome profiling in heart is a central issue to better understand cardiac physiology and diseases. Although significant progress has been made in genome-wide profiling for quantitative changes in cardiac gene expression, current knowledge offers limited insights to the total complexity in cardiac transcriptome at individual exon level. Objective: To develop more robust bioinformatic approaches to analyze high-throughput RNA sequencing (RNA-Seq) data, with the focus on the investigation of transcriptome complexity at individual exon and transcript levels. Methods and Results: In addition to overall gene expression analysis, the methods developed in this study were used to analyze RNA-Seq data with respect to individual transcript isoforms, novel spliced exons, novel alternative terminal exons, novel transcript clusters (ie, novel genes), and long noncoding RNA genes. We applied these approaches to RNA-Seq data obtained from mouse hearts after pressure-overload–induced by transaortic constriction. Based on experimental validations, analyses of the features of the identified exons/transcripts, and expression analyses including previously published RNA-Seq data, we demonstrate that the methods are highly effective in detecting and quantifying individual exons and transcripts. Novel insights inferred from the examined aspects of the cardiac transcriptome open ways to further experimental investigations. Conclusions: Our work provided a comprehensive set of methods to analyze mouse cardiac transcriptome complexity at individual exon and transcript levels. Applications of the methods may infer important new insights to gene regulation in normal and disease hearts in terms of exon utilization and potential involvement of novel components of cardiac transcriptome. R egulation of gene expression has a critical role in normal cardiac function and pathogenesis of heart failure. A global change in cardiac transcriptome from normal to one with characteristics of " fetal-like " profile is a major part of the pathological remodeling in failing hearts. 1–3 Although much insight has been learnt from transcriptome profiling studies using microarray technologies, limitations in coverage and sensitivity still leave a significant part of the cardiac transcriptome landscape unexplored, especially concerning expression and variation at single exon resolution. Recent advances in high-throughput sequencing technologies are enabling a new way to study transcriptomes: massively parallel sequencing of short reads derived from mRNAs (RNA-Seq). 4,5 Compared with microarray technologies, RNA-Seq was shown to enable more accurate quantification of gene expression levels. 6,7 More importantly, RNA-Seq does not require a priori annotation of gene and transcript structures. It allows not only in-depth studies of expression changes in …