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, 44 (16), e135

Illumina-based RiboMethSeq Approach for Mapping of 2'-O-Me Residues in RNA

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Illumina-based RiboMethSeq Approach for Mapping of 2'-O-Me Residues in RNA

Virginie Marchand et al. Nucleic Acids Res.

Abstract

RNA 2'-O-methylation is one of the ubiquitous nucleotide modifications found in many RNA types from Bacteria, Archaea and Eukarya. RNAs bearing 2'-O-methylations show increased resistance to degradation and enhanced stability in helices. While the exact role of each 2'-O-Me residue remained elusive, the catalytic protein Fibrillarin (Nop1 in yeast) responsible for 2'-O-methylation in eukaryotes, is associated with human pathologies. Therefore, there is an urgent need to precisely map and quantify hundreds of 2'-O-Me residues in RNA using high-throughput technologies. Here, we develop a reliable protocol using alkaline fragmentation of total RNA coupled to a commonly used ligation approach, and Illumina sequencing. We describe a methodology to detect 2'-O-methylations with high sensitivity and reproducibility even with limited amount of starting material (1 ng of total RNA). The method provides a quantification of the 2'-O-methylation occupancy of a given site, allowing to detect relatively small changes (>10%) in 2'-O-methylation profiles. Altogether this technique unlocks a technological barrier since it will be applicable for routine parallel treatment of biological and clinical samples to decipher the functions of 2'-O-methylations in pathologies.

Figures

Figure 1.
Figure 1.
General overview of the RiboMethSeq protocol. RNA containing 2′-O-Me residues is randomly fragmented, 5′- and 3′-ends are repaired and adapters are ligated to both extremities. After amplification and barcoding, amplicons are subjected to Illumina sequencing. MiSeq sequencing (left) generally provides paired-end reads, while HiSeq sequencing is generally performed in a single-read mode (right). Orientations and mapping of reads are indicated. The 2′-O-Me residues protect the 3′-adjacent phosphodiester bond from cleavage, generating a typical gap in 5′-/3′-ends coverage profile.
Figure 2.
Figure 2.
2′-O-Methylation analysis using RNA fragmentation with MgCl2, alkaline bicarbonate buffer (OH) and ZnCl2. Panel (A) Typical fragmentation profiles for regions of yeast 18S and 25S rRNA are shown. Arrows indicate the +1 positions for 2′-O-Me residues. 18S rRNA contains another RNA modification, ac4C, which is present nearby, but does not generate a signal (shown in gray). Panel (B) Performance of each method was compared by calculation of score MAX to detect known 2′-O-methylations followed by construction of Receiver Operating Characteristic (ROC) curves (blue). Matthews Correlation Coefficient (MCC) is traced in red on the same graph.
Figure 3.
Figure 3.
Biological variability of MethScore observed between wild type (WT) and four yeast strains with chromosomal deletions of genes encoding different tRNA-specific methyltransferases. Panel (A) The MethScore values for each modified position in 18S and 25S rRNA. For each strain MethScore values were calculated position by position and used for calculation of the mean values as well as standard deviation (SD). Graph shows the values of MethScore, error bars represent SD for each position. Methylation level for positions Cm2197 and Am2220 (boxed) was verified by LC–MS/MS (see panel C). Panel (B) Graph showing the dispersion of the observed MethScore values for 18S rRNA (gray) and 25S rRNA (black) and their corresponding SD values. Positions with a lower MethScore show a higher variability, as attested by higher SD values. Panel (C) Experimental workflow for isolation of 25S rRNA fragment followed by LC–MS/MS analysis (left). Methylation levels for positions Cm2197 and Am2220 measured by LC–MS/MS (right). Error bars are calculated for technical triplicate.
Figure 4.
Figure 4.
RiboMethSeq analysis performed with a reduced amount of input RNA. The results of MethScore values were calculated for all modified positions in yeast 18S and 25S rRNA for 1 ng and for 250 ng of input total RNA. Mean values obtained with their SD values are traced on the graph, 18S data are in gray, 25S data are in black, respectively.
Figure 5.
Figure 5.
Validation of the RiboMethSeq approach using yeast deleted strains deficient in 2′-O-methylation residue at certain positions in 25S rRNA. Two yeast strains with deletions of snR24 and snR38, together with the corresponding WT strain, were subjected to RiboMethSeq. Variations of MethScore values are observed upon deletion of snR38, responsible for modification of position Gm2815 (left) and snR24, implicated for modification of positions Cm1437, Am1449 and Cm1450 (right). Two neighboring positions around of the affected modification site(s) are also shown for comparison. In gray, values obtained for WT yeast strain, in white, values for corresponding snoRNA-deleted mutant.
Figure 6.
Figure 6.
Analysis of 2′-O-methylation rate using synthetic modified and unmodified RNA oligonucleotides. Panel (A) Superposition of 5′-end coverage profiles obtained for modified oligonucleotide, its unmodified counterpart, as well as for mixtures 25:75, 50:50 and 75:25 of both. The 2′-O-Me signal appears at position 11 (modified Nm10 in RNA oligonucleotide). Panel (B) representative traces of MethScore values for different modified nucleotides in the same environment (contexts AmA, CmA, GmA and UmA are shown) in relation to the proportion of modified RNA oligonucleotide in the mixture.

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