bioRxivGenomicsPreprint
Stereoscopic RNA Analysis of Transcriptional and Post-transcriptional Regulation
Abstract
Regulation of gene expression takes place at multiple stages of RNA synthesis, processing, and decay. The dynamics of RNA processing is an essential layer of RNA regulation, required for a deeper understanding of gene expression. Here, we present a streamlined analysis combining nascent RNA sequencing and poly(A) tail length sequencing methods, named Stereoscopic Analysis of Transcriptome (STOAT). Using this analysis, we were able to redefine known and unknown transcripts with high precision, and quantitatively assess RNA expression and stability. We also investigated poly(A) tail processing and their linkage to post-transcriptional features in different cell lines and identified the diversity of microRNA networks in RNA stability and opposing effects of HuR-TTP on poly(A) processing among human cell lines. This method can effectively measure promoter activity, RNA synthesis, poly(A) processing, stability, and decay, providing a comprehensive perspective of the dynamic transcriptome as well as discovering diverse transcript isoforms. MOTIVATIONRNA sequencing (RNA-seq) enables transcriptome-wide mapping and quantitative analysis, but it only provides a static view of the transcriptome. Also, due to its lack of standardization between sequencing platforms and read depth, it compromises reproducibility, and the cost remains prohibitive. To improve these limitations, we are presenting the minimal combination of two methods, nascent RNA sequencing and poly(A) tail length sequencing, which can effectively measure promoter activity, RNA synthesis, abundance, poly(A) processing, stability, and decay, and can discover diverse undefined transcript isoforms. This streamlined analysis of transcription rate and polyadenylation status will provide a comprehensive perspective of the dynamic transcriptome.
- organism: human
- assay: bulk RNA-seq
- research focus: gene regulatory network inference
- research focus: differential expression
- research focus: trajectory inference
- research focus: dimensionality reduction
- approach: statistical model
- approach: experimental assay
- Citations
- 0
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