bioRxivGeneticsPreprint
Decoding the Epitranscriptional Landscape from Native RNA Sequences
Thidathip WongsurawatiD, Piroon JenjaroenpuniD, Trudy M. WassenaariD, Taylor D. Wadley, Visanu WanchaiiD, Nisreen S. AkeliD, Aime T. FrancoiD, Michael L. JenningsiD, David Wayne UsseryiD, Intawat NookaewiD
Abstract
Sequencing of native RNA and corresponding cDNA was performed using Oxford Nanopore Technology. The % Error of Specific Bases (%ESB) was higher for native RNA than for cDNA, which enabled detection of ribonucleotide modification sites. Based on %ESB differences of the two templates, a bioinformatic tool ELIGOS was developed and applied to rRNAs of E. coli, yeast and human cells. ELIGOS captured 91%, 95%, [~]75%, respectively, of the known variety of RNA methylation sites in these rRNAs. Yeast transcriptomes from different growth conditions were also compared, which identified an association between metabolic adaptation and inferred RNA modifications. ELIGOS was further applied to human transcriptome datasets, which identified the well-known DRACH motif containing N6-methyadenine being located close to 3-untranslated regions of mRNA. Moreover, the RNA G-quadruplex motif was uncovered by ELIGOS. In summary, we have developed an experimental method coupled with bioinformatic software to uncover native RNA modifications and secondary-structures within transcripts.
- organism: E. coli
- organism: yeast
- organism: human
- assay: long-read sequencing
- research focus: gene regulatory network inference
- research focus: differential expression
- research focus: database / resource
- approach: statistical model
- approach: experimental assay
- Citations
- 21
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