Specific alignment of structured RNA: stochastic grammars and sequence annealing

Area of Science:

• Bioinformatics
• Computational Biology
• Genomics

Background:

• Eukaryotic genomes are rich in non-coding RNAs (ncRNAs).
• Accurate multiple RNA sequence alignment is essential for comparative genomics.
• Existing methods often lack specificity, aligning non-homologous sequences.

Purpose of the Study:

• To develop a novel, accurate, and specific method for multiple RNA sequence alignment.
• To introduce the Stemloc-AMA software for RNA alignment.

Main Methods:

• Coupling a generative probabilistic model of RNA sequence and structure.
• Employing an efficient sequence annealing approach for alignment space exploration.
• Developing the Stemloc-AMA software package.

Main Results:

• Stemloc-AMA demonstrates comparable sensitivity and superior specificity to existing methods on benchmark datasets (BRalibase II, BRalibase 2.1).
• A large-scale experiment confirmed Stemloc-AMA's ability to align only homologous sequences, unlike other programs.
• Unrelated sequences are left unaligned by Stemloc-AMA, ensuring alignment integrity.

Conclusions:

• Stemloc-AMA provides accurate and specific multiple RNA alignments.
• This specificity is crucial for reliable comparative genomics analyses, including phylogenetic inference and substitution rate estimation.
• Stemloc-AMA is available as part of the dart software package.