Transcriptome analysis in heart failure

Purpose of review Genome-wide analysis of RNA abundances (transcriptome analysis) offers great potential to identify biomarkers of disease and to gain insight into mechanisms underlying the development of heart failure. I will discuss key factors in generating and evaluating transcriptome data, and recent studies that have contributed to the understanding of cardiac disease in humans and animal models. Recent findings Thorough assessments of RNA-sequencing performance performed across multiple laboratories have demonstrated its primacy in measuring differential RNA abundances, due in part to its wide dynamic range and accuracy. In combination with network and pathway analysis tools, this enables greater understanding of heart failure mechanisms than previously possible, and renders possible current and future investigations into the role of RNA alternative splicing. Summary Current and future acquisition of accurate, unbiased, and comprehensive transcriptome data will continue to inform the understanding of heart failure, enabling hypothesis testing as well as hypothesis generation. Transcriptome data represent a vital bridge between genomic and epigenomic variation and proteomic output; progressive integration of data from these and other domains will fully realize the potential inherent in transcriptome analyses.