Submitted Successfully!
To reward your contribution, here is a gift for you: A free trial for our video production service.
Thank you for your contribution! You can also upload a video entry or images related to this topic.
Version Summary Created by Modification Content Size Created at Operation
1
Yuri MOTORIN
 + 1381 word(s) 1381 2021-03-23 12:36:30 |
2 format change
Lily Guo
 Meta information modification 1381 2021-03-31 10:22:12 |

Video Upload Options

Do you have a full video?
Send video materials Upload full video

Confirm

Are you sure to Delete?
Yes No
Cite
If you have any further questions, please contact Encyclopedia Editorial Office.
Motorin, Y. Post-transcriptional RNA Modifications. Encyclopedia. Available online: https://encyclopedia.pub/entry/8238 (accessed on 07 July 2024).
Motorin Y. Post-transcriptional RNA Modifications. Encyclopedia. Available at: https://encyclopedia.pub/entry/8238. Accessed July 07, 2024.
Motorin, Yuri. "Post-transcriptional RNA Modifications" Encyclopedia, https://encyclopedia.pub/entry/8238 (accessed July 07, 2024).
Motorin, Y. (2021, March 24). Post-transcriptional RNA Modifications. In Encyclopedia. https://encyclopedia.pub/entry/8238
Motorin, Yuri. "Post-transcriptional RNA Modifications." Encyclopedia. Web. 24 March, 2021.
Post-transcriptional RNA Modifications
Edit
This entry is adapted from the peer-reviewed paper 10.3390/genes12020278

Post-transcriptional RNA modifications (also called “Epitranscriptomics”) can be detected in RNA while using various methods and approaches exploiting the chemical and physico-chemical properties of these non-canonical RNA nucleotides. 

RNA modification

1. Introduction

Post-transcriptional RNA modifications (also called “Epitranscriptomics”) can be detected in RNA while using various methods and approaches exploiting the chemical and physico-chemical properties of these non-canonical RNA nucleotides. In addition to classical RNA techniques, such as 5’/3’ and specific internal labeling as well as nucleoside/RNA oligonucleotide analysis by Liquid Chromatography coupled to Mass Spectrometry (LC-MS) or tandem Mass Spectrometry (LC-MS/MS), methods that are based on second- (abbreviated as NGS for Next Generation Sequencing) and third- (NNGS, for Next-Next Generation Sequencing) generation sequencing become increasingly popular. These approaches aim to provide single-nucleotide resolution for the identification of the modified RNA position, but they may be less accurate in the exact nature of the modified residue due to a rather generic treatment used during the library preparation step. The most popular and reliable methods using NGS analysis rely on various specific chemical treatments that are applied to specifically alter RNA-modified residues to make them detectable either as RT-stop or as a mis-incorporation of nucleotides into cDNA. Actually, NNGS approaches mostly use ion-current profiles through the nanopore or kinetics of deoxynucleotide triphosphates (dNTP) incorporation in PacBio chips to deduce the presence of unusually modified nucleotides.

However, in both NGS (cluster sequencing) and NNGS (single-molecule sequencing) the nature of the signal may be only indirectly related to the chemical nature of the RNA modification, thus mis-identifications are not only possible, but actually rather frequent. In addition, if the analysis is performed at the whole-transcriptome scale (→106–107 nucleotides), even methods with an extremely good False Discovery Rate (FDR )<0.001 will still provide thousands of false positive hits. Thus, extreme care should be taken in the interpretation of large transcriptome-wide datasets claiming the presence of hundreds, or even thousands, of detected RNA modified nucleotides (as discussed in [1]).

The mapping of RNA modifications by NGS approaches is mainly based on: (1) altered base pairing during a reverse transcriptase (RT)-driven primer extension step, (2) altered chemical reactivity of the base due to a specific reagent (3) associated cleavage of the ribose-phosphate chain, and (4) a differential recognition of modified RNA nucleotides by specific antibodies (Ab) or proteins. In some instances, an enzymatic treatment or in vivo metabolic labeling can be used to exacerbate the chemical reactivity of a given modified nucleotide. Altered base-pairing is typically exploited for RNA modifications bearing extra chemical groups at the Watson–Crick (WC) edge of the base (so-called direct RT-signature) or for ‘RT-silent’ modifications after chemical derivatization affecting their WC edge. Methods that are based on the specific cleavage of the phosphodiester bond either rely on altered recognition by a specific enzyme or on the formation of an RNA abasic site, followed by a specific (and highly selective) ligation step. Antibody (protein enrichment) protocols exploit differential noncovalent or covalent binding to the modified site using UltraViolet light (UV) or chemical cross-linking steps.

Current approaches using NNGS (single-molecule sequencing) are mostly based on the use of direct nanopore RNA sequencing. Indeed, the profile of ion current registered for modified nucleotides passing through the nanopore is substantially altered when compared to the unmodified counterparts. While the experimental setup is generally rather straightforward and the RNA treatment is not different from classical RNA-Seq analysis, the extraction and analysis of raw nanopore sequencing data require complex and time-consuming bioinformatics treatment. Because of these limitations, NNGS methods are only at the emerging stage and cannot be considered to be an alternative to replace established NGS protocols. This will certainly evolve in the nearest future, and experience that accumulated in now-routine NGS analysis will be extremely helpful in the development of NNGS single-molecule analysis.

2. Analysis of RNA Modifications by NGS

Different principles are currently employed for the detection of RNA modifications in the epitranscriptome using NGS and NNGS. We classify them in: (1) an analysis of RNA signatures that are visible in sequencing profiles (natural/enhanced or chemically induced), (2) the treatment-induced cleavage of the RNA phosphodiester chain followed by a selective ligation of sequencing adapters, and 3) affinity-based enrichment protocols exploiting the specificity of polyclonal or monoclonal antibodies and specific enzymes installing modifications in RNA. In many instances, the developed protocols use a combination of different principles (such as Ab-driven enrichment, followed by specific chemical treatment).

3. Analysis of RNA Modifications by NNGS (Single-Molecule Sequencing)

The use of single-molecule sequencing approaches (NNGS or third-generation deep sequencing) is an attractive alternative to classical cluster sequencing protocols. Indeed, cluster sequencing involves an amplification step, providing only an average picture of modifications in a population of RNA molecules. Single-molecule analysis should be performed to obtain information regarding the exact combinations of modifications in a given RNA chain (individual modification pattern) [2].

The proof of principle for the analysis of RNA modifications (namely, m6A) by single-molecule sequencing was established seven years ago by using the PacBio single-molecule, real-time (SMRT) technology. HIV-1 and AMV RT were loaded to a zero-mode waveguide (ZMW) chip and the extension of DNA primer on the RNA template was monitored [3]. Even if the precision of the RNA sequencing remains limited, the analysis of the RT kinetics can be used to identify the RNA base modifications. This work was not pursued further, most probably because HIV-1 RT containing ZMW chips for PacBio machines is not commercially available.

More recent examples of single-molecule RNA sequencing for the detection of RNA modifications concern direct RNA sequencing by nanopores (Oxford Nanopores). Using direct RNA sequencing, it was demonstrated that m6A RNA modifications can be detected with a high accuracy in the form of systematic errors and decreased base-calling qualities [4]. With appropriate training datasets containing m6A-modified and -unmodified synthetic sequences, the prediction of m6A RNA modifications can be achieved with ~90% accuracy. The analysis of ion current profiles for the direct MinION nanopore sequencing of full-length 16S rRNA revealed conserved and aminoglycoside antibiotic resistance-related 7-methylguanosines (m7G) as well as pseudouridine modifications [5].

It is clear that the major challenge in the field of direct RNA sequencing and RNA modification mapping by nanopores consists of the use of appropriate data analysis software and algorithms. Analysis can be either conducted by standard base calling and the identification of “sequencing signatures” or by the extremely laborious, but direct, analysis of ion current traces. The first solution is implemented in the software MINES (m6A Identification using Nanopore Sequencing), which assigns m6A methylation status to more than 13,000 previously unannotated DRACH (D = A/G/U, R = A/G, H = A/C/U) sites in endogenous HEK293T transcripts and identifies more than 40,000 sites with isoform-level resolution in a human mammary epithelial cell line [6].

The direct analysis of nanopore ion current profiles is extremely computationally heavy, but it certainly provides more valuable information. The bioinformatic tool, called Epitranscriptional Landscape Inferring from Glitches of ONT signals (ELIGOS), was trained on various types of synthetic modified RNA and applied to rRNA and mRNA sequencing. ELIGOS is able to accurately predict known classes of RNA methylation sites (AUC > 0.93) in rRNAs from E. coli, yeast, and human cells [7]. Model-based base calling from ionic current signal levels is certainly required for reliable analysis [8]. Another intermediate solution, a workflow for the analysis of direct RNA sequencing reads, termed MasterOfPores, converts raw current intensities into multiple types of processed data, including FASTQ and BAM, providing metrics of the quality of the run, quality filtering, demultiplexing, base calling, and mapping. In a second step, the pipeline performs downstream analyses of the mapped reads, including the prediction of RNA modifications and the estimation of polyA tail lengths [9].

In the context of the COVID-19 pandemic, the direct RNA nanopore sequencing of full-length coronavirus genomic RNA allowed for us to predict multiple sites of m5C modification in SARS-Cov-2 [10]. However, the existence of these modifications in SARS-Cov-2 is still controversial, since another study utilizing nanopore sequencing with more rigorous controls did not confirm their presence [11].

In conclusion, direct RNA modification analysis by nanopore sequencing is rapidly developing and improving in reliability, but it has still not reached maturity for routine application in RNA epitranscriptomics. Thus, classical approaches are still widely used in the routine analysis of RNA modifications, and the use of nanopores is only envisaged as an alternative validation technique.

References

  1. Wiener, D.; Schwartz, S. The Epitranscriptome beyond m6A. Nat. Rev. Genet. 2020, 1–13.
  2. Xu, L.; Seki, M. Recent Advances in the Detection of Base Modifications Using the Nanopore Sequencer. J. Hum. Genet. 2020, 65, 25–33.
  3. Vilfan, I.D.; Tsai, Y.-C.; A Clark, T.; Wegener, J.; Dai, Q.; Yi, C.; Pan, T.; Turner, S.W.; Korlach, J. Analysis of RNA Base Modification and Structural Rearrangement by Single-Molecule Real-Time Detection of Reverse Transcription. J. Nanobiotechnol. 2013, 11, 8.
  4. Liu, H.; Begik, O.; Lucas, M.C.; Ramirez, J.M.; Mason, C.E.; Wiener, D.; Schwartz, S.; Mattick, J.S.; Smith, M.A.; Novoa, E.M. Accurate Detection of m6A RNA Modifications in Native RNA Sequences. Nat. Commun. 2019, 10, 1–9.
  5. Smith, A.M.; Jain, M.; Mulroney, L.; Garalde, D.R.; Akeson, M. Reading Canonical and Modified Nucleobases in 16S Ribosomal RNA Using Nanopore Native RNA Sequencing. PLoS ONE 2019, 14, e0216709.
  6. Lorenz, D.A.; Sathe, S.; Einstein, J.M.; Yeo, G.W. Direct RNA Sequencing Enables m6A Detection in Endogenous Transcript Isoforms at Base-Specific Resolution. RNA 2020, 26, 19–28.
  7. Jenjaroenpun, P.; Wongsurawat, T.; Wadley, T.D.; Wassenaar, T.M.; Liu, J.; Dai, Q.; Wanchai, V.; Akel, N.S.; Jamshidi-Parsian, A.; Franco, A.T.; et al. Decoding the Epitranscriptional Landscape from Native RNA Sequences. Nucleic Acids Res. 2021, 49, e7.
  8. Ding, H.; Bailey, A.D.; Jain, M.; Olsen, H.; Paten, B. Gaussian Mixture Model-Based Unsupervised Nucleotide Modification Number Detection Using Nanopore-Sequencing Readouts. Bioinformatics 2020, 36, 4928–4934.
  9. Cozzuto, L.; Liu, H.; Pryszcz, L.P.; Pulido, T.H.; Delgado-Tejedor, A.; Ponomarenko, J.; Novoa, E.M. MasterOfPores: A Workflow for the Analysis of Oxford Nanopore Direct RNA Sequencing Datasets. Front. Genet. 2020, 11, 211.
  10. Viehweger, A.; Krautwurst, S.; Lamkiewicz, K.; Madhugiri, R.; Ziebuhr, J.; Hölzer, M.; Marz, M. Direct RNA Nanopore Sequencing of Full-Length Coronavirus Genomes Provides Novel Insights into Structural Variants and Enables Modification Analysis. Genome Res. 2019, 29, 1545–1554.
  11. Kim, D.; Lee, J.-Y.; Yang, J.-S.; Kim, J.W.; Kim, V.N.; Chang, H. The Architecture of SARS-CoV-2 Transcriptome. Cell 2020, 181, 914–921.e10.
More
© Text is available under the terms and conditions of the Creative Commons Attribution (CC BY) license; additional terms may apply. By using this site, you agree to the Terms and Conditions and Privacy Policy.
Upload a video for this entry
Information
Subjects: Cell Biology
Contributor MDPI registered users' name will be linked to their SciProfiles pages. To register with us, please refer to https://encyclopedia.pub/register :
Yuri MOTORIN
View Times: 510
Revisions: 2 times (View History)
Update Date: 31 Mar 2021
Table of Contents
    1000/1000
    Hot Most Recent
    Video Production Service
    Feedback