Secondary structure prediction for RNA sequences including N⁶-methyladenosine

Area of Science:

• Molecular Biology
• Bioinformatics
• RNA Biology

Background:

• Growing interest in the functional roles of covalently modified nucleotides in RNA.
• Lack of software and thermodynamic data hinders the accurate prediction of RNA secondary structures with modifications.
• N6-methyladenosine (m6A) is a prevalent RNA modification with significant biological implications.

Purpose of the Study:

• To develop computational tools and thermodynamic parameters for predicting RNA secondary structures incorporating N6-methyladenosine (m6A).
• To enable secondary structure prediction for an expanded nucleotide alphabet including m6A.
• To investigate the impact of m6A on RNA folding stability and its functional consequences.

Main Methods:

• Development of a user-defined nucleotide alphabet feature in RNAstructure software.
• Experimental determination of nearest-neighbor thermodynamic parameters for helices and loops containing m6A.
• Application of the enhanced software and parameters to predict m6A effects on RNA structure and function.

Main Results:

• RNAstructure software now supports user-defined nucleotide alphabets, including m6A.
• New thermodynamic parameters reveal that m6A decreases helix stability, has minimal effect at helix ends, and increases stability for unpaired adenosines stacked on helices.
• Predictions demonstrate m6A's role in activating a protein recognition site on MALAT1 and its transcriptome-wide impact on adenosine burial in helices.

Conclusions:

• The developed software and parameters provide a robust solution for predicting RNA secondary structures with m6A modifications.
• N6-methylation significantly influences RNA folding stability in a context-dependent manner.
• These findings enhance our understanding of m6A's regulatory roles in RNA structure, protein binding, and gene expression.