Journal
SCIENCE ADVANCES
Volume 7, Issue 32, Pages -Publisher
AMER ASSOC ADVANCEMENT SCIENCE
DOI: 10.1126/sciadv.abd2605
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Funding
- RNA Biology Center at the Cancer Science Institute of Singapore, NUS, Singapore Ministry of Education's AcRF Tier 3 grants [MOE2014-T3-1-006]
- National Research Foundation Singapore
- Singapore Ministry of Education under its Research Centres of Excellence initiative
- PhRMA Foundation Pre-Doctoral Fellowship in Informatics
- Lee Kuan Yew Postdoctoral Fellowship
- Singapore Ministry of Education's AcRF Tier 1 grant
- STaR Investigator Award
- NIH (USA) [R35CA197697, P01HL131477]
- NSCC
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Studying RNA modifications in large clinical cohorts can provide insights into the relationship between the epitranscriptome and human diseases, with ModTect offering a way to identify known and unknown types of mRNA modifications. This tool can help discover associations between RNA modifications and clinical outcomes in patient cohorts.
The study of RNA modifications in large clinical cohorts can reveal relationships between the epitranscriptome and human diseases, although this is especially challenging. We developed ModTect (https://github.com/ktan8/ModTect), a statistical framework to identify RNA modifications de novo by standard RNA-sequencing with deletion and mis-incorporation signals. We show that ModTect can identify both known (N-1-methyladenosine) and previously unknown types of mRNA modifications (N-2,N-2-dimethylguanosine) at nucleotide-resolution. Applying ModTect to 11,371 patient samples and 934 cell lines across 33 cancer types, we show that the epitranscriptome was dysregulated in patients across multiple cancer types and was additionally associated with cancer progression and survival outcomes. Some types of RNA modification were also more disrupted than others in patients with cancer. Moreover, RNA modifications contribute to multiple types of RNA-DNA sequence differences, which unexpectedly escape detection by Sanger sequencing. ModTect can thus be used to discover associations between RNA modifications and clinical outcomes in patient cohorts.
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