csRNA-seq
csRNA-seq identifies transcription start sites (TSSs) of stable and unstable RNAs at single-nucleotide resolution from total RNA to map transcription initiation and regulatory elements across eukaryotes.
Key Features:
- Single-Nucleotide Resolution: Detects TSSs with single-nucleotide precision.
- Sensitivity to Transcriptional Changes: Highly sensitive to acute changes in transcription, identifying more regulated transcripts than traditional RNA sequencing methods.
- Detection of Unstable Transcripts: Captures unstable transcripts including enhancer RNAs, primary microRNAs (pri-miRNAs), antisense transcripts, and promoter upstream transcripts.
- Broad Eukaryotic Applicability: Applicable across eukaryotes, including multicellular animals, plants, and fungi.
- Integration with Epigenomic Data: Facilitates integration with epigenomic data and reveals histone modification patterns such as histone H3 trimethylation (H3K4me3) enrichment at TSSs of stable transcripts and H3K27ac marking nucleosomes downstream of active TSSs.
- Capture of 5' Cap-Protected RNAs: Sequences the 5' ends of cap-protected RNAs from total RNA to capture both stable and unstable transcripts for TSS mapping.
- Dynamic Quantification: Enables identification and dynamic quantification of regulatory elements from total RNA.
Scientific Applications:
- Regulatory Element Identification: Enables identification and dynamic quantification of regulatory elements within total RNA to study transcriptional regulation.
- Evolutionary Insights: Provides comparative insights into conserved mechanisms of transcription initiation spanning 1.6 billion years of eukaryotic evolutionary history.
- Histone Modification Roles: Aids elucidation of the roles of posttranslational histone modifications in transcription regulation, indicating ancient and fundamental functions.
Methodology:
Sequences the 5' ends of cap-protected RNAs from total RNA to capture stable and unstable transcripts and identify TSSs at single-nucleotide resolution.
Topics
Details
- Tool Type:
- command-line tool
- Programming Languages:
- Perl
- Added:
- 1/9/2020
- Last Updated:
- 12/17/2020
Operations
Publications
Duttke SH, Chang MW, Heinz S, Benner C. Identification and dynamic quantification of regulatory elements using total RNA. Genome Research. 2019;29(11):1836-1846. doi:10.1101/gr.253492.119. PMID:31649059. PMCID:PMC6836739.