SMS-seq
SMS-seq profiles RNA secondary and tertiary structure at single-molecule resolution by combining enzymatic or chemical probing with native RNA sequencing to capture non-amplified structural profiles and reveal structural heterogeneity.
Key Features:
- Single-molecule resolution: Enables interrogation of individual RNA molecules to reveal structural heterogeneity and intra-molecular dependencies.
- Comprehensive structural profiling: Employs enzymatic or chemical probing across numerous bases to map secondary structure throughout transcripts.
- Detection of tertiary interactions and dynamics: Captures tertiary interactions relevant to riboswitch ligand binding and complex three-dimensional RNA configurations, including mRNA features.
- Novel analysis methods: Applies mutual information–based analysis to detect dependencies and heterogeneity in single-molecule structural data.
Scientific Applications:
- Transcriptome-wide structural mapping: Produces per-molecule structural profiles for transcriptome-scale studies of RNA structure and function.
- Study of structural heterogeneity: Enables analysis of variation in secondary and tertiary structure across molecules within a population.
- Investigation of riboswitches and ligand interactions: Captures dynamics of riboswitch ligand binding and other ligand-dependent tertiary interactions.
- Exploration of mRNA structural features: Characterizes mRNA structural motifs implicated in post-transcriptional regulation.
Methodology:
Computational analysis of single-molecule native RNA sequencing and probing data using mutual information to interpret dependencies and structural heterogeneity.
Topics
Details
- License:
- Not licensed
- Cost:
- Free of charge
- Tool Type:
- command-line tool
- Operating Systems:
- Mac, Linux, Windows
- Programming Languages:
- Python, Shell
- Added:
- 10/30/2022
- Last Updated:
- 11/24/2024
Operations
Publications
Bizuayehu TT, Labun K, Jakubec M, Jefimov K, Niazi AM, Valen E. Long-read single-molecule RNA structure sequencing using nanopore. Nucleic Acids Research. 2022;50(20):e120-e120. doi:10.1093/nar/gkac775. PMID:36166000. PMCID:PMC9723614.
DOI: 10.1093/nar/gkac775
PMID: 36166000
PMCID: PMC9723614
Funding: - Norwegian Research Council: 250049