RT Journal Article
SR Electronic
T1 Detection of differential RNA modifications from direct RNA sequencing of human cell lines
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2020.06.18.160010
DO 10.1101/2020.06.18.160010
A1 Ploy N. Pratanwanich
A1 Fei Yao
A1 Ying Chen
A1 Casslynn W.Q. Koh
A1 Christopher Hendra
A1 Polly Poon
A1 Yeek Teck Goh
A1 Phoebe M. L. Yap
A1 Choi Jing Yuan
A1 Wee Joo Chng
A1 Sarah Ng
A1 Alexandre Thiery
A1 W.S. Sho Goh
A1 Jonathan Göke
YR 2020
UL http://biorxiv.org/content/early/2020/06/20/2020.06.18.160010.abstract
AB Differences in RNA expression can provide insights into the molecular identity of a cell, pathways involved in human diseases, and variation in RNA levels across patients associated with clinical phenotypes. RNA modifications such as m6A have been found to contribute to molecular functions of RNAs. However, quantification of differences in RNA modifications has been challenging. Here we develop a computational method (xPore) to identify differential RNA modifications from direct RNA sequencing data. We evaluate our method on transcriptome-wide m6A profiling data, demonstrating that xPore identifies positions of m6A sites at single base resolution, estimates the fraction of modified RNAs in the cell, and quantifies the differential modification rate across conditions. We apply the method to direct RNA-Sequencing data from 6 cell lines and find that many m6A sites are preserved, while a subset of m6A sites show significant differences in their modification rates across cell types. Together, we show that RNA modifications can be identified from direct RNA-sequencing with high accuracy, enabling the analysis of differential modifications and expression from a single high throughput experiment.Availability xPore is available as open source software (https://github.com/GoekeLab/xpore)Competing Interest StatementThe authors have declared no competing interest.