SeqFold

SeqFold predicts RNA secondary structures at genome scale by integrating high-throughput RNA structure profiling data with computational ensemble sampling and classification to reconstruct transcriptome-wide RNA secondary structure.


Key Features:

  • Integration of High-Throughput Data: Incorporates PARS, SHAPE-Seq, FragSeq (fragmentation sequencing), deep sequencing data, and conventional SHAPE data for structure probing inputs.
  • Structure Preference Profile (SPP): Transforms experimental RNA structure information into a Structure Preference Profile (SPP) used to represent ensemble-informed structure preferences.
  • High-Dimensional Classification Framework: Uses a high-dimensional classification framework to match an SPP to the most likely cluster of structures sampled from a Boltzmann-weighted ensemble.
  • Performance and Robustness: Benchmarked against known structures of mRNAs and noncoding RNAs, showing comparable or superior accuracy and robustness to noisy data.
  • Adaptability: Supports incorporation of new types of high-throughput RNA structure profiling data as they become available.

Scientific Applications:

  • Structurome reconstruction: Reconstructs RNA secondary structures across entire transcriptomes to generate transcriptome-wide structuromes.
  • Gene regulation analysis: Enables analysis of how RNA secondary structure influences translation efficiency, transcription initiation, and protein–RNA interactions.
  • Yeast transcriptome studies: Applied to the yeast transcriptome to uncover diverse impacts of RNA secondary structure on translation, transcription initiation, and protein–RNA interactions.

Methodology:

Integrates PARS, SHAPE-Seq, FragSeq, deep sequencing and conventional SHAPE data into a Structure Preference Profile (SPP), samples structures from a Boltzmann-weighted ensemble, clusters sampled structures, applies a high-dimensional classification framework to match SPPs to structure clusters and selects stable structure candidates, and benchmarks predictions against known mRNA and noncoding RNA structures.

Topics

Details

Tool Type:
command-line tool
Operating Systems:
Linux, Windows
Programming Languages:
Python
Added:
12/18/2017
Last Updated:
11/25/2024

Operations

Publications

Ouyang Z, Snyder MP, Chang HY. SeqFold: Genome-scale reconstruction of RNA secondary structure integrating high-throughput sequencing data. Genome Research. 2012;23(2):377-387. doi:10.1101/gr.138545.112. PMID:23064747. PMCID:PMC3561878.

Documentation

Links