LocARNA

LocARNA performs structure-based multiple alignment and clustering of RNA sequences to identify and classify conserved RNA secondary structures, including noncoding RNAs and regulatory RNA signals.

Key Features:

• Structure-based clustering: Aligns and clusters RNAs based on predicted secondary structure rather than primary sequence similarity to reveal structurally conserved ncRNAs and regulatory signals.
• Robustness to false positives: Filters unstructured or nonconserved sequences to reduce false positive clusters in noisy datasets.
• Scalability: Uses an algorithmic variant optimized for speed and robustness to handle large datasets comprising several thousand candidate RNA sequences.
• Detection of known and novel RNA families: Recovers known families such as tRNAs, microRNAs, and snoRNAs and can suggest putative novel ncRNA classes from genome-wide surveys.

Scientific Applications:

• Noncoding RNA research: Classifies ncRNAs into functional classes based on structural conservation to support studies of RNA function and regulation.
• Comparative genomics and transcriptomics: Supports high-throughput analyses to detect stabilizing selection on RNA secondary structures and annotate novel RNA elements.
• Genome-wide structured RNA surveys: Extracts putative RNA classes from extensive sets of hypothetical RNAs in large-scale genomic screens.

Methodology:

Implements a variant of the Sankoff algorithm tailored for local alignment, optimized for speed and robustness to process large-scale datasets of several thousand RNA sequences.