Evolutionary Analyses of Base-Pairing Interactions in DNA and RNA Secondary Structures

Area of Science:

• Computational Biology
• Bioinformatics
• Molecular Biology

Background:

• Nucleic acid secondary structures are crucial for biological function.
• Coevolution of nucleotide pairs suggests functional base-pairing.
• Existing models often require known secondary structures.

Purpose of the Study:

• Introduce MESSI (Modeling the Evolution of Secondary Structure Interactions), a novel sequence evolution model.
• Infer coevolution at base-paired sites in DNA/RNA alignments, even with unknown secondary structures.
• Enhance computational speed using GPU parallelism.

Main Methods:

• Developed MESSI, a sequence evolution model for inferring coevolution.
• Applied MESSI to noncoding RNA and viral RNA/DNA alignments.
• Validated MESSI's coevolution estimates against experimental data (SHAPE-MaP) and structural rankings.

Main Results:

• MESSI successfully inferred coevolution in various nucleic acid alignments.
• GU pair coevolution was higher in RNA than GT pair coevolution in DNA, suggesting differential stability.
• MESSI's coevolution estimates correlated better with experimental pairing scores than non-evolutionary measures.
• MESSI ranked substructures by coevolution, highlighting known and novel functional elements.

Conclusions:

• MESSI is an effective tool for inferring coevolution and identifying functional nucleic acid structures.
• The model provides insights into the biophysical basis of base-pairing stability.
• MESSI aids in prioritizing functionally relevant RNA/DNA substructures for further research.