RNA modifications play a crucial role in the regulation of various cellular processes, contributing to the complexity and diversity of RNA functions. Among these modifications, 2'-O-methylation (2'-O-Me) stands out as one of the most common and intriguing modifications found in different types of cellular RNAs.
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Unraveling the Complexity of RNA 2'-O-Methylation
2'-O-methylation is a prevalent modification observed in diverse cellular RNAs, including transfer RNAs (tRNAs), ribosomal RNAs (rRNAs), small nuclear/small nucleolar RNAs (snRNAs/snoRNAs), microRNAs (miRNAs), Piwi-interacting RNAs (piRNAs), and some messenger RNAs (mRNAs). This modification is catalyzed by a complex enzymatic machinery, involving both stand-alone protein enzymes and small nucleolar ribonucleoprotein (snoRNP) complexes. The significance of RNA 2'-O-methylation lies in its ability to confer distinct physico-chemical properties and reactivity to RNA molecules, impacting various biological functions.
Fig 1. Chemical and enzymatic properties of 2'-O-methylated RNA chains (Motorin Y., Marchand V. 2018).
Classical Methods for 2'-O-Methylation Detection
2'-O-Methylation, a common RNA modification, is detected and quantified using various methods in RNA biochemistry. General analytical techniques involve total RNA hydrolysis with perchloric acid followed by methanol measurement for quantification. Other methods employ partial hydrolysis coupled with oligonucleotide analysis or chromatography and mass spectrometry, allowing detection and sometimes quantification of 2'-O-methylated nucleotides.
Historically, two-dimensional thin layer chromatography (2D TLC) and RNA fingerprinting were used for RNA analysis. Modern techniques combine high-performance liquid chromatography with mass spectrometry for precise quantification. These methods show strong correlation with RiboMethSeq protocols, indicating their reliability.
Specific detection strategies exploit unique chemical properties of 2'-O-methylated nucleotides. These include resistance to alkaline or enzymatic hydrolysis, exploited in site-specific detection approaches using RNase H or DNAzymes. Reverse transcriptase (RT) pauses at 2'-O-Me residues under low deoxynucleotide triphosphate (dNTP) conditions, enabling specific detection. Quantification can be achieved using quantitative RT-PCR.
Additionally, 2'-O-Me affects enzymatic activity at RNA 3'-termini, inhibiting RNA ligase activity and reducing ligation efficiency. This property is utilized in ligation-based approaches for RNA modification analysis. Moreover, 2'-O-Me at 3'-termini reduces miRNA polyadenylation efficiency, facilitating direct measurement of miRNA and piRNA 3'-terminal 2'-O-methylation.
Limitations of Classical Detection Methods
While classical methods have been valuable, they come with limitations. Many require substantial amounts of input RNA, making analysis feasible only for highly abundant RNAs. Additionally, these methods can be laborious, time-consuming, and lack high-throughput capabilities. Furthermore, they may generate false-positive and false-negative signals, particularly in detecting partial methylation.
Deep Sequencing-based Approaches
Deep sequencing-based approaches have been developed to enhance the detection and quantification of RNA 2'-O-methylation, leveraging distinct properties of this modification. Three main methods have been proposed, each targeting different aspects of 2'-O-methylations.
RiboMethSeq
This approach relies on deep sequencing to measure the protection induced by 2'-O-methylation at the 3'-adjacent phosphodiester RNA bond against alkaline cleavage. After alkaline hydrolysis and optional fragment enrichment, RNA fragments are converted into a sequencing library. Sequencing reads are then mapped to the reference sequence, allowing precise determination of fragment ends. The resulting coverage profiles are used to calculate methylation scores, enabling detection and quantification of 2'-O-methylation levels. Various versions of RiboMethSeq have been developed, with differences in library preparation and bioinformatics analysis, affecting minor discrepancies.
2'-OMe-Seq
This method involves deep sequencing mapping of reverse transcriptase (RT) stops generated by primer extension at low deoxynucleotide triphosphate (dNTP) concentrations. The resulting cDNA chains are converted into a sequencing library, and the 3'-ends of cDNA fragments are determined by mapping to the reference sequence. Comparison with normal RT extension profiles allows exclusion of false-positive hits.
RibOxi-Seq and Nm-Seq
These protocols exploit the resistance of 2'-O-methylated 3'-terminal riboses to periodate oxidation. RNA is first randomly fragmented, leaving 5'-phosphates and 3'-OH extremities. These fragments are then subjected to periodate oxidation, which destroys unmodified cis-diol riboses but leaves 2'-O-methylated termini intact. The resulting library is enriched for 2'-O-methylated extremities in the sequencing reads. However, the fragmentation step is biased, requiring multiple cycles of oxidation and treatment, leading to substantial RNA loss. Additionally, the presence of 2'-O-methyl groups reduces the efficiency of 3'-adapter ligation, further impacting library yield and representativity.
Specific Features of Deep Sequencing Methods
Deep sequencing methods have emerged as powerful tools for analyzing RNA 2'-O-methylation, offering diverse applications across different physiological conditions. Among these methods, RiboMethSeq stands out for its widespread use in profiling 2'-O-methylations in eukaryotic rRNAs, owing to the abundance of rRNA in cells. This approach allows for direct analysis of total RNA without the need for fractionation or enrichment, making it cost-effective and accessible. Additionally, it facilitates the study of rRNA 2'-O-methylation dynamics in various physiological contexts and biomedical applications.
While rRNAs are the primary targets for RiboMethSeq, tRNAs from all organisms also present suitable candidates due to their known 2'-O-methylation sites, albeit with more complex analysis requirements. Despite the popularity of RiboMethSeq, alternative methods like 2'-OMe-Seq, RibOxi-Seq, and Nm-Seq are less widespread due to their higher RNA input requirements, limiting their applicability in biomedical research.
Assessing the performance of these methods for detecting modified residues is challenging due to variations in model RNAs, cell lines, and cultivation conditions. Sensitivity and specificity metrics vary, complicating direct comparisons. Moreover, the amount of input RNA varies significantly between methods, posing challenges, particularly for biomedical projects with limited biological material.
RiboMethSeq offers high sensitivity with relatively low input RNA requirements, making it suitable for many biomedical applications. However, it necessitates substantial sequencing depth for reliable analysis due to the irregular cleavage patterns in highly structured rRNA regions. Despite differences in methodologies, sequencing depth requirements for other methods like 2'-OMe-Seq, RibOxi-Seq, and Nm-Seq are comparable.
Quantification of methylation levels is most precise with RiboMethSeq, enabling the analysis of modification dynamics. Relative quantification is feasible with 2'-OMeSeq, but methods based on enrichments of methylated RNA 3'-ends lack quantitative information. Sequencing platforms and bioinformatics processes vary across methods but generally involve trimming, alignment, and read counting steps.
In summary, deep sequencing methods offer powerful tools for RNA 2'-O-methylation analysis, each with its unique features and applications, catering to diverse research needs across basic and biomedical sciences.
Conclusion
The combination of traditional and deep sequencing-based approaches has revolutionized the detection and quantification of RNA 2'-O-methylation. These advancements enable comprehensive identification of modified sites in diverse cellular RNAs and facilitate investigations into RNA 2'-O-methylation dynamics in various physiological and pathological contexts.
References
- Marchand V., et al. Next-generation sequencing-based RiboMethSeq protocol for analysis of tRNA 2'-O-methylation. Biomolecules. 2017, 7(1): 13.
- Motorin Y., Marchand V. Detection and analysis of RNA ribose 2'-O-methylations: challenges and solutions. Genes. 2018, 9(12): 642.
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