Deep mRNA Sequencing for In Vivo Functional Analysis of Cardiac Transcriptional Regulators Application to Gαq

Rationale: Transcriptional profiling can detect subclinical heart disease and provide insight into disease etiology and functional status. Current microarray-based methods are expensive and subject to artifact. Objective: To develop RNA sequencing methodologies using next generation massively parallel platforms for high throughput comprehensive analysis of individual mouse cardiac transcriptomes. To compare the results of sequencing- and array-based transcriptional profiling in the well-characterized G alpha q transgenic mouse hypertrophy/cardiomyopathy model. Methods and Results: The techniques for preparation of individually bar-coded mouse heart RNA libraries for Illumina Genome Analyzer II resequencing are described. RNA sequencing showed that 234 high-abundance transcripts (>60 copies/cell) comprised 55% of total cardiac mRNA. Parallel transcriptional profiling of G alpha q transgenic and nontransgenic hearts by Illumina RNA sequencing and Affymetrix Mouse Gene 1.0 ST arrays revealed superior dynamic range for mRNA expression and enhanced specificity for reporting low-abundance transcripts by RNA sequencing. Differential mRNA expression in G alpha q and nontransgenic hearts correlated well between microarrays and RNA sequencing for highly abundant transcripts. RNA sequencing was superior to arrays for accurately quantifying lower-abundance genes, which represented the majority of the regulated genes in the G alpha q transgenic model. Conclusions: RNA sequencing is rapid, accurate, and sensitive for identifying both abundant and rare cardiac transcripts, and has significant advantages in time-and cost-efficiencies over microarray analysis. (Circ Res. 2010; 106:1459-1467.)