Identification of differential RNA modifications from nanopore direct RNA sequencing with xPore

RNA modifications, such as N 6 -methyladenosine (m 6 A), modulate functions of cellular RNA species. However, quantifying differences in RNA modifications has been challenging. Here we develop a computational method, xPore, to identify differential RNA modifications from nanopore direct RNA sequenci...

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Bibliographic Details
Published in:	Nature biotechnology Vol. 39; no. 11; pp. 1394 - 1402
Main Authors:	Pratanwanich, Ploy N., Yao, Fei, Chen, Ying, Koh, Casslynn W. Q., Wan, Yuk Kei, Hendra, Christopher, Poon, Polly, Goh, Yeek Teck, Yap, Phoebe M. L., Chooi, Jing Yuan, Chng, Wee Joo, Ng, Sarah B., Thiery, Alexandre, Goh, W. S. Sho, Göke, Jonathan
Format:	Journal Article
Language:	English
Published:	New York Nature Publishing Group US 01-11-2021 Nature Publishing Group
Subjects:	631/114/1314 631/114/2415 631/114/2785 631/114/794 631/45/500 Agriculture Analysis Bioinformatics Biomedical and Life Sciences Biomedical Engineering/Biotechnology Biomedicine Biotechnology Cancer Computer applications Enzymes Gene sequencing Identification Identification and classification Life Sciences Medical research Methods Multiple myeloma N6-methyladenosine Properties Ribonucleic acid RNA RNA sequencing Structure Transcriptomes Tumor cell lines China Singapore
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Summary:	RNA modifications, such as N 6 -methyladenosine (m 6 A), modulate functions of cellular RNA species. However, quantifying differences in RNA modifications has been challenging. Here we develop a computational method, xPore, to identify differential RNA modifications from nanopore direct RNA sequencing (RNA-seq) data. We evaluate our method on transcriptome-wide m 6 A profiling data, demonstrating that xPore identifies positions of m 6 A sites at single-base resolution, estimates the fraction of modified RNA species in the cell and quantifies the differential modification rate across conditions. We apply xPore to direct RNA-seq data from six cell lines and multiple myeloma patient samples without a matched control sample and find that many m 6 A sites are preserved across cell types, whereas a subset exhibit significant differences in their modification rates. Our results show that RNA modifications can be identified from direct RNA-seq data with high accuracy, enabling analysis of differential modifications and expression from a single high-throughput experiment. m 6 A RNA modifications are quantified in cancer patient samples and cell lines using nanopore sequencing.
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23
ISSN:	1087-0156 1546-1696
DOI:	10.1038/s41587-021-00949-w