Secondary structure prediction for RNA sequences including N6-methyladenosine

David H Mathews,Scott D Kennedy,Elzbieta Kierzek,Ryszard Kierzek,Marta Szabat,Richard M Watson,Xiaoju Zhang

doi:10.1038/s41467-022-28817-4

David H Mathews, Scott D Kennedy + Show 5 more

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https://doi.org/10.1038/s41467-022-28817-4

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Abstract

There is increasing interest in the roles of covalently modified nucleotides in RNA. There has been, however, an inability to account for modifications in secondary structure prediction because of a lack of software and thermodynamic parameters. We report the solution for these issues for N6-methyladenosine (m6A), allowing secondary structure prediction for an alphabet of A, C, G, U, and m6A. The RNAstructure software now works with user-defined nucleotide alphabets of any size. We also report a set of nearest neighbor parameters for helices and loops containing m6A, using experiments. Interestingly, N6-methylation decreases folding stability for adenosines in the middle of a helix, has little effect on folding stability for adenosines at the ends of helices, and increases folding stability for unpaired adenosines stacked on a helix. We demonstrate predictions for an N6-methylation-activated protein recognition site from MALAT1 and human transcriptome-wide effects of N6-methylation on the probability of adenosine being buried in a helix.

Highlights

There is increasing interest in the roles of covalently modified nucleotides in RNA
N6-methyladenosine (m6A) is considered the most prevalent modification in mRNA, and m6A is widespread in lncRNAs15,16
We provide a model for the change in protein binding affinity caused by N6-methylation of the long non-coding RNAs (lncRNAs) metastasisassociated lung adenocarcinoma transcript (MALAT1)

Summary

Introduction

There is increasing interest in the roles of covalently modified nucleotides in RNA. There has been, an inability to account for modifications in secondary structure prediction because of a lack of software and thermodynamic parameters. Secondary structure prediction has been used to identify microRNA binding sites[27], design siRNAs28,29, identify protein binding sites[30], and discover functional RNA structures[31,32] These types of calculations have not been able to account for modifications without extensive user intervention because a set of nearest neighbor parameters are needed for estimating the folding stability of structures that include modifications[26,33]. We developed a full set of nearest neighbor parameters for a folding alphabet of m6A, A, C, G, and U nucleotides These parameters account for helix and loop formation, and they are based on optical melting experiments for 32 helices with m6A-U base pairs and 13 oligonucleotides with m6A in loop motifs. We modified the RNAstructure software package to accept user-defined folding alphabets and to read and utilize thermodynamic parameters for these extended alphabets[40] Together, these advances allow the prediction of RNA secondary structures for sequences with m6A. We provide a model for the change in protein binding affinity caused by N6-methylation of the lncRNA metastasisassociated lung adenocarcinoma transcript (MALAT1)

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