RPASuite

RPASuite analyzes RNA-seq read profiles to identify differential and coherent RNA processing events across annotated and unannotated genomic loci, enabling transcriptome-wide detection of short RNAs (including ~24 nt and ~17 nt species) and microRNA arm switching.

Key Features:

• Differential Processing Analysis: Detects differential processing events including microRNA arm switching and has identified both previously known and novel differentially processed miRNAs in nine ENCODE cell lines.
• Coherent Processing Detection: Identifies coherent processing events across annotated and unannotated regions, with annotated loci enriched for ~24 nt short RNAs and unannotated loci enriched for ~17 nt short RNAs.
• Read Profile Pattern Analysis: Examines RNA-seq read profile patterns to distinguish processing signatures and classify loci as annotated or unannotated.
• Overlap with Transcriptional Features: Reports significant overlaps of short RNAs with transcription start sites and DNase I hypersensitive sites, consistent with transcription initiation RNAs.
• Statistical Significance: Applies statistical testing to assess significance of findings, reporting overlaps with key transcriptional features at p < 0.01.

Scientific Applications:

• Post-transcriptional processing studies: Enables transcriptome-wide identification of processing events and short RNA species involved in post-transcriptional regulation.
• MicroRNA biology: Facilitates detection of microRNA arm switching and discovery of novel differentially processed miRNAs across tissues or cell lines.
• Transcription initiation RNA mapping: Supports mapping of short RNAs that overlap transcription start sites and DNase I hypersensitive sites to investigate transcription initiation RNAs.

Methodology:

The pipeline processes high-throughput RNA-seq data by analyzing read profile patterns to identify genomic loci exhibiting differential or coherent processing and to distinguish annotated versus unannotated regions.