Identification of protein-protected mRNA fragments and structured excisedintron RNAs in human plasma by TGIRT-seq peak calling
Abstract
Human plasma contains >40,000 different coding and non-coding RNAs that are potential biomarkers for human diseases. Here, we used thermostable group II intron reverse transcriptase sequencing (TGIRT-seq) combined with peak calling to simultaneously profile all RNA biotypes in apheresis-prepared human plasma pooled from healthy individuals. Extending previous TGIRT-seq analysis, we found that human plasma contains largely fragmented mRNAs from >19,000 protein-coding genes, abundant full-length, mature tRNAs and other structured small non-coding RNAs, and less abundant tRNA fragments and mature and pre-miRNAs. Many of the mRNA fragments identified by peak calling correspond to annotated protein-binding sites and/or have stable predicted secondary structures that could afford protection from plasma nucleases. Peak calling also identified novel repeat RNAs, miRNA-sized RNAs, and putatively structured intron RNAs of potential biological, evolutionary, and biomarker significance, including a family of full-length excised introns RNAs, subsets of which correspond to mirtron pre-miRNAs or agotrons.
Data availability
Code availability: All scripts used for data processing are deposited in GitHub: https://github.com/wckdouglas/cfNADate deposition: The TGIRT-seq datasets in this manuscript are listed in the Supplementary File and have been deposited in the National Center for Biotechnology Information Sequence Read Archive (accession number: PRJNA640428).
Article and author information
Author details
Funding
National Institute of General Medical Sciences (R01 GM37949)
- Alan M Lambowitz
National Institute of General Medical Sciences (R35 GM136216)
- Alan M Lambowitz
Welch Foundation (F-1607)
- Alan M Lambowitz
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2020, Yao et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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