ABSTRACT
Traditional epitranscriptomics relies on capturing a single RNA modification by antibody or chemical treatment, combined with short-read sequencing to identify its transcriptomic location. This approach is labor-intensive and may introduce experimental artifacts. Direct sequencing of native RNA using Oxford Nanopore Technologies (ONT) can allow for directly detecting the RNA base modifications, although these modifications might appear as sequencing errors. The percent Error of Specific Bases (%ESB) was higher for native RNA than unmodified RNA, which enabled the detection of ribonucleotide modification sites. Based on the %ESB differences, we developed a bioinformatic tool, epitranscriptional landscape inferring from glitches of ONT signals (ELIGOS), that is based on various types of synthetic modified RNA and applied to rRNA and mRNA. ELIGOS is able to accurately predict known classes of RNA methylation sites (AUC > 0.93) in rRNAs from Escherichiacoli, yeast, and human cells, using either unmodified in vitro transcription RNA or a background error model, which mimics the systematic error of direct RNA sequencing as the reference. The well-known DRACH/RRACH motif was localized and identified, consistent with previous studies, using differential analysis of ELIGOS to study the impact of RNA m6A methyltransferase by comparing wild type and knockouts in yeast and mouse cells. Lastly, the DRACH motif could also be identified in the mRNA of three human cell lines. The mRNA modification identified by ELIGOS is at the level of individual base resolution. In summary, we have developed a bioinformatic software package to uncover native RNA modifications.
Subject(s)
Computational Biology/methods , High-Throughput Nucleotide Sequencing , RNA Processing, Post-Transcriptional , RNA-Seq , Scientific Experimental Error , Software , Adenine/analogs & derivatives , Adenine/analysis , Animals , Cell Line , Escherichia coli/genetics , Humans , Meiosis , Methyltransferases/deficiency , Methyltransferases/metabolism , Mice , Mice, Knockout , Nucleotide Motifs , RNA, Bacterial/genetics , RNA, Fungal/genetics , RNA, Messenger/genetics , RNA, Ribosomal/genetics , ROC Curve , Saccharomyces cerevisiae/genetics , Sequence Analysis, DNA , Templates, Genetic , Transcription, GeneticABSTRACT
Escherichia coli ATCC 11775 is a strain that was identified in 1941 and is now considered a type strain for the species. We present here the complete genome sequence for E. coli ATCC 11775. The genome was sequenced using Oxford Nanopore Technologies products and had 4,903,501 and 131,333 nucleotides of sequence length of the individual chromosome and plasmid, respectively.
ABSTRACT
Long-read nanopore sequencing by a MinION device offers the unique possibility to directly sequence native RNA. We combined an enzymatic poly-A tailing reaction with the native RNA sequencing to (i) sequence complex population of single-stranded (ss)RNA viruses in parallel, (ii) detect genome, subgenomic mRNA/mRNA simultaneously, (iii) detect a complex transcriptomic architecture without the need for assembly, (iv) enable real-time detection. Using this protocol, positive-ssRNA, negative-ssRNA, with/without a poly(A)-tail, segmented/non-segmented genomes were mixed and sequenced in parallel. Mapping of the generated sequences on the reference genomes showed 100% length recovery with up to 97% identity. This work provides a proof of principle and the validity of this strategy, opening up a wide range of applications to study RNA viruses.
