Identification and comparison of m6A modifications in glioblastoma non-coding RNAs with MeRIP-seq and Nanopore dRNA-seq

ABSTRACT

The most prominent RNA modification – N6-methyladenosine (m6A) – affects gene regulation and cancer progression. The extent and effect of m6A on long non-coding RNAs (lncRNAs) is, however, still not clear. The most established method for m6A detection is methylated RNA immunoprecipitation and sequencing (MeRIP-seq). However, Oxford Nanopore Technologies recently developed direct RNA-seq (dRNA-seq) method, allowing m6A identification at higher resolution and in its native form. We performed whole transcriptome sequencing of the glioblastoma cell line U87-MG with both MeRIP-seq and dRNA-seq. For MeRIP-seq, m6A peaks were identified using nf-core/chipseq, and for dRNA-seq – EpiNano pipeline. MeRIP-seq analysis revealed 5086 lncRNAs transcripts, while dRNA-seq identified 336 lncRNAs transcripts from which 556 and 198 were found to be m6A modified, respectively. While 24 lncRNAs with m6A overlapped between two methods. Gliovis database analysis revealed that the expression of the major part of identified overlapping lncRNAs was associated with glioma grade or patient survival prognosis. We found that the frequency of m6A occurrence in lncRNAs varied more than 9-fold throughout the provided list of 24 modified lncRNAs. The highest m6A frequency was detected in MIR1915HG, THAP9-AS1, MALAT1, NORAD1, and NEAT1 (49–88nt), while MIR99AHG, SNHG3, LOXL1-AS1, ILF3-DT showed the lowest m6A frequency (445–261nt). Taken together, (1) we provide a high accuracy list of 24 m6A modified lncRNAs of U87-MG cells; (2) we conclude that MeRIP-seq is more suitable for an initial m6A screening study, due to its higher lncRNA coverage, whereas dRNA-seq is most useful when more in-depth analysis of m6A quantity and precise location is of interest.

Abbreviations: (dRNA-seq) direct RNA-seq, (GBM) glioblastoma, (LGG) low-grade glioma, (lncRNAs) long non-coding RNAs, (m6A) N6-methyladenosine, (MeRIP-seq) methylated RNA immunoprecipitation and sequencing, (ncRNA) non-coding RNA, (ONT) Oxford Nanopore Technologi; Lietuvos Mokslo Taryba

KEYWORDS:

• lncRNA
• m6A
• epi-transcriptome
• glioblastoma
• MeRIP-seq
• nanopore dRNA-seq

Acknowledgments

Part of the computing for this project was performed on the GenomeDK cluster. We would like to thank GenomeDK and Aarhus University for providing computational resources and support that contributed to these research results. In addition, we are grateful to Brian Vendelbo Hansen from Copenhagen University Hospital Rigshospitalet, Department of Growth and Reproduction for all the help during the preparation of Nanopore sequencing. Finally, we appreciate the help from Indre Valiulyte and Rugile Dragunaite in substantial assistance in culturing of cell lines.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Author contributions

PV: GS generated an idea, and planned experiments. RK isolated RNA from cell lines. GS, RK performed poly A enrichment and immunoprecipitation of m6A RNA. RS, KA performed sequencing experiments and bioinformatic analysis. GS, RS analyzed processed MeRIP-seq and nanopore dRNA-seq data. RK, PV, GS prepared the manuscript.

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/15592294.2022.2163365

Data Availability Statement

The datasets generated and analysed during the current study are available in the Sequence Read Archive SRA repository, https://dataview.ncbi.nlm.nih.gov/object/PRJNA917040?reviewer=r52jnkdi9kh2e653p9p7bi20qe

Additional information

Funding

This project was funded by the Research Council of Lithuania, Lietuvos Mokslo Taryba [S-MIP-20-51]