scholarly journals Exploring prokaryotic transcription, operon structures, rRNA maturation and modifications using Nanopore-based native RNA sequencing

Author(s):  
Felix Grünberger ◽  
Robert Knüppel ◽  
Michael Jüttner ◽  
Martin Fenk ◽  
Andreas Borst ◽  
...  

AbstractThe prokaryotic transcriptome is shaped by transcriptional and posttranscriptional events that define the characteristics of an RNA, including transcript boundaries, the base modification status, and processing pathways to yield mature RNAs. Currently, a combination of several specialised short-read sequencing approaches and additional biochemical experiments are required to describe all transcriptomic features. In this study, we present native RNA sequencing of bacterial (E. coli) and archaeal (H. volcanii, P. furiosus) transcriptomes employing the Oxford Nanopore sequencing technology. Based on this approach, we could address multiple transcriptomic characteristics simultaneously with single-molecule resolution. Taking advantage of long RNA reads provided by the Nanopore platform, we could (re-)annotate large transcriptional units and boundaries. Our analysis of transcription termination sites suggests that diverse termination mechanisms are in place in archaea. Moreover, we shed additional light on the poorly understood rRNA processing pathway in Archaea. One of the key features of native RNA sequencing is that RNA modifications are retained. We could confirm this ability by analysing the well-known KsgA-dependent methylation sites and mapping of N4-acetylcytosines modifications in rRNAs. Notably, we were able to follow the relative timely order of the installation of these modifications in the rRNA processing pathway.

2021 ◽  
Author(s):  
Doaa Hassan ◽  
Daniel Acevedo ◽  
Swapna Vidhur Daulatabad ◽  
Quoseena Mir ◽  
Sarath Chandra Janga

AbstractPseudouridine is one of the most abundant RNA modifications, occurring when uridines are catalyzed by Pseudouridine synthase proteins. It plays an important role in many biological processes and also has an importance in drug development. Recently, the single-molecule sequencing techniques such as the direct RNA sequencing platform offered by Oxford Nanopore technologies enable direct detection of RNA modifications on the molecule that is being sequenced, but to our knowledge this technology has not been used to identify RNA Pseudouridine sites. To this end, in this paper, we address this limitation by introducing a tool called Penguin that integrates several developed machine learning (ML) models (i.e., predictors) to identify RNA Pseudouridine sites in Nanopore direct RNA sequencing reads. Penguin extracts a set of features from the raw signal measured by the Oxford Nanopore and the corresponding basecalled k-mer. Those features are used to train the predictors included in Penguin, which in turn, is able to predict whether the signal is modified by the presence of Pseudouridine sites. We have included various predictors in Penguin including Support vector machine (SVM), Random Forest (RF), and Neural network (NN). The results on the two benchmark data sets show that Penguin is able to identify Pseudouridine sites with a high accuracy of 93.38% and 92.61% using SVM in random split testing and independent validation testing respectively. Thus, Penguin outperforms the existing Pseudouridine predictors in the literature that achieved an accuracy of 76.0 at most with an independent validation testing. A GitHub of the tool is accessible at https://github.com/Janga-Lab/Penguin.


2019 ◽  
Author(s):  
Adrien Leger ◽  
Paulo P. Amaral ◽  
Luca Pandolfini ◽  
Charlotte Capitanchik ◽  
Federica Capraro ◽  
...  

AbstractRNA molecules undergo a vast array of chemical post-transcriptional modifications (PTMs) that can affect their structure and interaction properties. To date, over 150 naturally occurring PTMs have been identified, however the overwhelming majority of their functions remain elusive. In recent years, a small number of PTMs have been successfully mapped to the transcriptome using experimental approaches relying on high-throughput sequencing. Oxford Nanopore direct-RNA sequencing (DRS) technology has been shown to be sensitive to RNA modifications. We developed and validated Nanocompore, a robust analytical framework to evaluate the presence of modifications in DRS data. To do so, we compare an RNA sample of interest against a non-modified control sample. Our strategy does not require a training set and allows the use of replicates to model biological variability. Here, we demonstrate the ability of Nanocompore to detect RNA modifications at single-molecule resolution in human polyA+ RNAs, as well as in targeted non-coding RNAs. Our results correlate well with orthogonal methods, confirm previous observations on the distribution of N6-methyladenosine sites and provide novel insights into the distribution of RNA modifications in the coding and non-coding transcriptomes. The latest version of Nanocompore can be obtained at https://github.com/tleonardi/nanocompore.


2018 ◽  
Author(s):  
Thidathip Wongsurawat ◽  
Piroon Jenjaroenpun ◽  
Trudy M. Wassenaar ◽  
Taylor D Wadley ◽  
Visanu Wanchai ◽  
...  

AbstractSequencing 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.


2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Madiha Sultan ◽  
Anastassia Kanavarioti

Abstract Protein and solid-state nanopores are used for DNA/RNA sequencing as well as for single molecule analysis. We proposed that selective labeling/tagging may improve base-to-base resolution of nucleic acids via nanopores. We have explored one specific tag, the Osmium tetroxide 2,2′-bipyridine (OsBp), which conjugates to pyrimidines and leaves purines intact. Earlier reports using OsBp-tagged oligodeoxyribonucleotides demonstrated proof-of-principle during unassisted voltage-driven translocation via either alpha-Hemolysin or a solid-state nanopore. Here we extend this work to RNA oligos and a third nanopore by employing the MinION, a commercially available device from Oxford Nanopore Technologies (ONT). Conductance measurements demonstrate that the MinION visibly discriminates oligoriboadenylates with sequence A15PyA15, where Py is an OsBp-tagged pyrimidine. Such resolution rivals traditional chromatography, suggesting that nanopore devices could be exploited for the characterization of RNA oligos and microRNAs enhanced by selective labeling. The data also reveal marked discrimination between a single pyrimidine and two consecutive pyrimidines in OsBp-tagged AnPyAn and AnPyPyAn. This observation leads to the conjecture that the MinION/OsBp platform senses a 2-nucleotide sequence, in contrast to the reported 5-nucleotide sequence with native nucleic acids. Such improvement in sensing, enabled by the presence of OsBp, may enhance base-calling accuracy in enzyme-assisted DNA/RNA sequencing.


2021 ◽  
Author(s):  
Matthew T Parker ◽  
Geoffrey J Barton ◽  
Gordon G Simpson

Yanocomp is a tool for predicting the positions and stoichiometries of RNA modifications in Nanopore direct RNA sequencing data. It uses general mixture models to identify differentially modified sites between two conditions, with good support for replicates. Yanocomp models across adjacent kmers and uses a uniform component to account for outliers, improving the accuracy of single molecule predictions. Consequently, Yanocomp can be used to measure modification stoichiometry, and correlate modifications with other RNA processing events. Yanocomp is available under an MIT license at www.github.com/bartongroup/yanocomp.


2019 ◽  
Author(s):  
Luca Cozzuto ◽  
Huanle Liu ◽  
Leszek P. Pryszcz ◽  
Toni Hermoso Pulido ◽  
Julia Ponomarenko ◽  
...  

ABSTRACTThe direct RNA sequencing platform offered by Oxford Nanopore Technologies allows for direct measurement of RNA molecules without the need of conversion to complementary DNA, fragmentation or amplification. As such, it is virtually capable of detecting any given RNA modification present in the molecule that is being sequenced, as well as provide polyA tail length estimations at the level of individual RNA molecules. Although this technology has been publicly available since 2017, the complexity of the raw Nanopore data, together with the lack of systematic and reproducible pipelines, have greatly hindered the access of this technology to the general user. Here we address this problem by providing a fully benchmarked workflow for the analysis of direct RNA sequencing reads, termed MasterOfPores. The pipeline converts raw current intensities into multiple types of processed data, providing metrics of the quality of the run, quality-filtering, base-calling and mapping. The output of the pipeline can in turn be used to compute per-gene counts, RNA modifications, and prediction of polyA tail length and RNA isoforms. The software is written using the NextFlow framework for parallelization and portability, and relies on Linux containers such as Docker and Singularity for achieving better reproducibility. The MasterOfPores workflow can be executed on any Unix-compatible OS on a computer, cluster or cloud without the need of installing any additional software or dependencies, and is freely available in Github (https://github.com/biocorecrg/master_of_pores). This workflow will significantly simplify the analysis of nanopore direct RNA sequencing data by non-bioinformatics experts, thus boosting the understanding of the (epi)transcriptome with single molecule resolution.


RNA ◽  
2021 ◽  
pp. rna.078937.121
Author(s):  
Felix Grünberger ◽  
Sébastien Ferreira-Cerca ◽  
Dina Grohmann

High-throughput sequencing dramatically changed our view of transcriptome architectures and allowed for ground-breaking discoveries in RNA biology. Recently, sequencing of full-length transcripts based on the single-molecule sequencing platform from Oxford Nanopore Technologies (ONT) was introduced and is widely employed to sequence eukaryotic and viral RNAs. However, experimental approaches implementing this technique for prokaryotic transcriptomes remain scarce. Here, we present an experimental and bioinformatic workflow for ONT RNA-seq in the bacterial model organism Escherichia coli, which can be applied to any microorganism. Our study highlights critical steps of library preparation and computational analysis and compares the results to gold standards in the field. Furthermore, we comprehensively evaluate the applicability and advantages of different ONT-based RNA sequencing protocols, including direct RNA, direct cDNA, and PCR-cDNA. We find that (PCR)-cDNA-seq offers improved yield and accuracy compared to direct RNA sequencing. Notably, (PCR)-cDNA-seq is suitable for quantitative measurements and can be readily used for simultaneous and accurate detection of transcript 5'and 3' boundaries, analysis of transcriptional units and transcriptional heterogeneity. In summary, based on our comprehensive study, we show that Nanopore RNA-seq to be a ready-to-use tool allowing rapid, cost-effective, and accurate annotation of multiple transcriptomic features. Thereby Nanopore RNA-seq holds the potential to become a valuable alternative method for RNA analysis in prokaryotes.


2021 ◽  
Author(s):  
Felix Gruenberger ◽  
Sebastien Ferreira-Cerca ◽  
Dina Grohmann

High-throughput sequencing dramatically changed our view of transcriptome architectures and allowed for ground-breaking discoveries in RNA biology. Recently, sequencing of full-length transcripts based on the single-molecule sequencing platform from Oxford Nanopore Technologies (ONT) was introduced and is widely employed to sequence eukaryotic and viral RNAs. However, experimental approaches implementing this technique for prokaryotic transcriptomes remain scarce. Here, we present an experimental and bioinformatic workflow for ONT RNA-seq in the bacterial model organism Escherichia coli, which can be applied to any microorganism. Our study highlights critical steps of library preparation and computational analysis and compares the results to gold standards in the field. Furthermore, we comprehensively evaluate the applicability and advantages of different ONT-based RNA sequencing protocols, including direct RNA, direct cDNA, and PCR-cDNA. We find that cDNA-seq offers improved yield and accuracy without bias in quantification compared to direct RNA sequencing. Notably, cDNA-seq can be readily used for simultaneous transcript quantification, accurate detection of transcript 5 ′ and 3′ boundaries, analysis of transcriptional units and transcriptional heterogeneity. In summary, we establish Nanopore RNA-seq to be a ready-to-use tool allowing rapid, cost-effective, and accurate annotation of multiple transcriptomic features thereby advancing it to become a standard method for RNA analysis in prokaryotes.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Adrien Leger ◽  
Paulo P. Amaral ◽  
Luca Pandolfini ◽  
Charlotte Capitanchik ◽  
Federica Capraro ◽  
...  

AbstractRNA molecules undergo a vast array of chemical post-transcriptional modifications (PTMs) that can affect their structure and interaction properties. In recent years, a growing number of PTMs have been successfully mapped to the transcriptome using experimental approaches relying on high-throughput sequencing. Oxford Nanopore direct-RNA sequencing has been shown to be sensitive to RNA modifications. We developed and validated Nanocompore, a robust analytical framework that identifies modifications from these data. Our strategy compares an RNA sample of interest against a non-modified control sample, not requiring a training set and allowing the use of replicates. We show that Nanocompore can detect different RNA modifications with position accuracy in vitro, and we apply it to profile m6A in vivo in yeast and human RNAs, as well as in targeted non-coding RNAs. We confirm our results with orthogonal methods and provide novel insights on the co-occurrence of multiple modified residues on individual RNA molecules.


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