Transcriptome characterization through comparative genome-wide analysis of nuclear RNA and RNAPII association in erythroid cells

Current evidence suggests that more than half of the mammalian genome is transcribed, yet how this vast transcriptome is regulated in vivo remains poorly understood. We demonstrate here an integrated, straightforward and widely applicable approach to characterize cell type-specific transcriptional programs and regulatory mechanisms by generating two genome-wide data sets. We used deep sequencing of nuclear RNA (nucRNA-Seq) to comprehensively describe the nuclear transcriptome in ex vivo murine erythroid cells. In parallel, we generated a profile of active RNA polymerase II (RNAPII) binding by chromatin-immunoprecipitation (ChIP-Seq), allowing us to explore the relationship between RNAPII occupancy and transcriptional output in erythroid cells on a genome-wide scale. Comparative analysis of both data sets enables us to not only measure primary transcriptional output and identify genes associated with more efficient polymerase usage, but also to identify putative regulatory elements such as enhancers and novel non-coding transcripts. Application of this method to different cell types allows for the characterization of important aspects of gene regulation in a cell type-specific manner. Our findings demonstrate the complex ways in which RNAPII is associated with the genome and how this affects transcription of target genes, highlighting the importance of approaching transcriptome characterization from multiple angles.

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