RNAprofile

RNAprofile identifies conserved sequence-and-structure motifs within sets of unaligned RNA sequences to detect functional elements in mRNA and non-coding RNA.

Key Features:

• Motif Identification: Extracts regions of highest conservation from collections of unaligned RNA sequences using a similarity measure that incorporates nucleotide sequence and secondary-structure potential.
• Secondary Structure Consideration: Integrates base-pairing and thermodynamic principles to predict optimal secondary structures of candidate motifs, enabling detection of conserved elements such as hairpins.
• Parameterization: Requires a single input parameter specifying the number of distinct hairpins the motif must contain, without constraining the size, number, or position of individual motif elements.
• Efficient Search Strategy: Employs a greedy heuristic to reduce computational complexity and avoid exhaustive enumeration of candidate regions.
• Robustness to Data Variability: Operates when motifs are absent from some input sequences and can handle corrupted datasets while identifying more complex motifs in non-coding RNA.

Scientific Applications:

• Iron responsive element (IRE): Characterization of IRE stem-loop regulatory motifs in mRNA.
• Selenocysteine insertion sequence (SECIS): Detection and characterization of SECIS stem-loop structures.
• Functional element exploration: Investigation of conserved sequence-and-structure functional elements across mRNA and non-coding RNA.

Methodology:

Extract candidate regions from each input sequence whose predicted secondary structure contains the specified number of hairpins; compare extracted regions with a similarity measure combining nucleotide sequence and secondary-structure potential to identify groups of most similar regions including one region per sequence; employ a greedy heuristic to limit search and avoid exhaustive enumeration.