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Semi-quantitative detection of pseudouridine modifications and type I/II hypermodifications in human mRNAs using direct long-read sequencing

Sepideh Tavakoli, Mohammad Nabizadeh, Amr Makhamreh, Howard Gamper, Caroline A. McCormick, Neda K. Rezapour, Ya-Ming Hou, Meni Wanunu and Sara H. Rouhanifard ()
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Sepideh Tavakoli: Northeastern University
Mohammad Nabizadeh: Northeastern University
Amr Makhamreh: Northeastern University
Howard Gamper: Thomas Jefferson University
Caroline A. McCormick: Northeastern University
Neda K. Rezapour: Northeastern University
Ya-Ming Hou: Thomas Jefferson University
Meni Wanunu: Northeastern University
Sara H. Rouhanifard: Northeastern University

Nature Communications, 2023, vol. 14, issue 1, 1-12

Abstract: Abstract Here, we develop and apply a semi-quantitative method for the high-confidence identification of pseudouridylated sites on mammalian mRNAs via direct long-read nanopore sequencing. A comparative analysis of a modification-free transcriptome reveals that the depth of coverage and specific k-mer sequences are critical parameters for accurate basecalling. By adjusting these parameters for high-confidence U-to-C basecalling errors, we identify many known sites of pseudouridylation and uncover previously unreported uridine-modified sites, many of which fall in k-mers that are known targets of pseudouridine synthases. Identified sites are validated using 1000-mer synthetic RNA controls bearing a single pseudouridine in the center position, demonstrating systematic under-calling using our approach. We identify mRNAs with up to 7 unique modification sites. Our workflow allows direct detection of low-, medium-, and high-occupancy pseudouridine modifications on native RNA molecules from nanopore sequencing data and multiple modifications on the same strand.

Date: 2023
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DOI: 10.1038/s41467-023-35858-w

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