Tag Archives: m6A

Patterns of RNA methylation 2

In a recent post I discussed the extent of adenosine methylation in RNAs. Meyer et al. found that m6A was found in many mRNAs and showed a bias in its distribution towards the end of coding sequence, stop codons, and the proximal section of 3’UTRs. The main chemically modified base of DNA is 5-methylcytosine. Squires et al. have surveyed the presence of m5C in human RNAs, and find that this modification is also common in tRNAs, rRNAs, mRNAs and ncRNAs.

The principal method for detecting methylated cytosines in nucleic acids is bisulphite sequencing. Bisulphite converts cytosine residues to uracil, but modified cytosines are left unchanged. Hence, when sequenced, C reads as T, and m5C reads as C. When compared to a reference sequence the status of cytosine methylation can be deduced. Squires et al. used bisulphite conversion of RNAs, followed by reverse transcription and high throughput sequencing. A number of other modified forms of cytosine known to be present in some rRNAs, such as N4-methylcytidine (m4C) and N4,2’-O-dimethylcytidine (m4Cm), may also be resistant to bisulphite treatment. With this in mind, Squires et al. termed their detected modified cytosines m5C candidate sites.

Surveying RNAs from HeLa cells, Squires et al discovered 255 modified Cs in tRNAs. This confirmed a number of known sites and identified many new candidate sites, which however generally fitted into a known pattern of modification of residues in specific secondary structural regions – the variable region and the anticodon loop. Modifications in these areas are important in stabilising secondary structure and affect aminoacylation and codon recognition.

Most interestingly, the researchers discovered 10, 275 m5C candidate sites in mRNAs and ncRNAs. Their data covered 10.6% of the total cytosine residues in the transcriptome. m5C seems to be enriched in some classes of ncRNA, but relatively depleted in mRNAs. The majority (83%) however, of their candidate sites were found in mRNAs. Within these transcripts m5C appears to be depleted within protein coding sequences but enriched in 5’ and 3’ UTRs. Further computational analysis showed an association between mRNA m5C sites and binding regions for Argonaute proteins (the proteins that small regulatory RNA molecules complex with to effect post-transcriptional regulation).

Two different methyltransferases are known to catalyse the m5C modification in eukaryotic RNAs, NSUN2 and TRDMT1. Previously these two enzymes had only been shown to methylate a few specific positions in various tRNAs. Squires et al. used RNAi to knockdown NSUN2 and TRDMT1 in HeLa cells and assayed the methylation status of a selected subset of cytosine residues. This showed that a number of m5C sites in mRNAs and ncRNAs are dependent on NSUN2, suggesting that this could be the primary enzyme responsible for cytosine methylation in these classes of RNAs. NSUN2 has been shown to be cell-cycle regulated and a target for the oncogene MYC. Mouse knockouts are small, and have revealed a role in balancing stem cell renewal and differentiation. A recent paper (Khan et al. 2012) has linked mutations in NSUN2 to autosomal-recessive intellectual disability syndrome in humans. It will be interesting to investigate the extent of this enzyme’s role in RNA methylation, and dissect what component of it’s function is responsible for the mouse and human phenotypes.

As with the investigation into m6A, m5C is commonly found in RNAs of many categories, and as with the previous study it is not yet obvious just how important RNA methylation truly is. The phenotypes associated with loss of methyltransferases or demethylases are not that extensive, but neither are they negligible. Some observations are shared between Meyer et al and Squires et al; the enrichments in 3’ UTRs and the correlation between RNA methylation and microRNA/argonaute binding sites (although there were differences in the details of these associations. This investigation by Squires et al into m5C is not on the same level as Meyer et al’s study, in that it lacked the developmental component and wasn’t on the same global scale. On the other hand bisulphite sequencing does pinpoint the exact modified residues, whereas m6A cannot as yet be detected to the same level of accuracy. The methodology used by Squires et al. can be scaled up, and so more global studies of m5C will no doubt appear in the near future. I also look forward to more detailed understanding of the enzymatic pathways involved, and a dissection of their roles in development.

Squires JE, Patel HR, Nousch M, Sibbritt T, Humphreys DT, Parker BJ, Suter CM, & Preiss T (2012). Widespread occurrence of 5-methylcytosine in human coding and non-coding RNA. Nucleic acids research, 40 (11), 5023-33 PMID: 22344696

Khan MA, Rafiq MA, Noor A, Hussain S, Flores JV, Rupp V, Vincent AK, Malli R, Ali G, Khan FS, Ishak GE, Doherty D, Weksberg R, Ayub M, Windpassinger C, Ibrahim S, Frye M, Ansar M, & Vincent JB (2012). Mutation in NSUN2, which encodes an RNA methyltransferase, causes autosomal-recessive intellectual disability. American journal of human genetics, 90 (5), 856-63 PMID: 22541562

Meyer KD, Saletore Y, Zumbo P, Elemento O, Mason CE, & Jaffrey SR (2012). Comprehensive Analysis of mRNA Methylation Reveals Enrichment in 3′ UTRs and near Stop Codons. Cell, 149 (7), 1635-46 PMID: 22608085

Patterns of RNA methylation

A new paper in Cell provides a transcriptome-wide survey of the methylation of adenosine residues in RNAs. Meyer et al find that this epitranscriptomic post-transcriptional modification is widespread and dynamically regulated, and likely to play important roles in cellular regulation.

Methylation of the N6 position of adenosine residues (m6A) has been known to be a post-transcriptional modification of RNAs for many years. Research in the 1960’s and 70’s demonstrated that m6A is present in tRNAs, rRNAs and viral RNAs, and made up between 0.1% and 0.4% or total adenosines in cellular RNA. However as m6A was not easily detectable by commonly available methods, research on this modified base foundered. A recent spur to experimentation on m6A has come from the analysis of a gene linked to obesity. FTO (fat mass and obesity associated) is a major regulator of metabolism and energy utilisation. It appears that the major catalytic function of FTO is the demethylation of N6-methyladensosine (m6A), suggesting that m6A has important physiological roles in humans and other mammals.

As m6A is not detectable by sequencing or hybridisation based techniques, nor susceptible to chemical modification, Meyer et al. based their experiments on the use of an anti-m6A antibody (ά-m6A). They first showed that m6A was present in RNA from a wide selection of different mouse tissues and cell lines. It was especially enriched in liver, kidney, and brain, and showed a dramatic increase in adult neural tissue as opposed to embryonic. m6A was found to be present in RNAs of all sizes, and was enriched in the polyadenylated fraction (ie. mRNAs), but not present in the poly(A) tails themselves.

To look in more detail at the distribution of m6A throughout the transcriptome, Meyer et al. developed a high throughput technique called MeRIP-Seq. Cellular RNA is fragmented into ~100nt fragments, and then m6A containing fragments are immunoprecipitated using ά-m6A. The RNA fragments are then deep sequenced. m6A residues should be detected on multiple RNA fragment sequence reads, allowing the detection of m6A peaks, that can be assigned to their approximate position on RNA molecules. Using adult mouse brain RNA in multiple MeRIP-Seq experiments, Meyer et al. identified 41, 072 distinct peaks in the RNAs of 8,843 genes. However they used a smaller, highly reproducible, subset of 13, 471 peaks in 4, 654 genes for their further analyses.

94.5% of the m6A peaks occurred in mRNAs, but more than 3% were found within long non-coding RNAs, showing that ncRNAs are also targets for adenosine methylation. mRNAs from a wide variety of genes were found to contain methylated adenosines, including many involved in cellular regulation, and genes linked to neurodevelopmental and neurological disorders.

The largest proportion of m6A containing mRNAs exhibited a single m6A peak (46%) (equating to either a single m6A residue or a cluster of adjacent m6As), whilst 48.5% contained two or three peaks. However, mRNAs can contain more than 15 peaks along their lengths. Although MeRIP-Seq doesn’t allow one to say exactly which adenosines are methylated, it does give one a good idea of their positions on RNAs. m6A levels are low in the 5’ ends of mRNAs. They increase steadily throughout the coding sequence, peak in the vicinity of the stop codon, remain high in the first portion of the 3’ UTR and then rapidly decline. This linkage between the region of the translational stop codon and m6A is the most important finding of the paper.

Meyer et al. went on to show that regions of m6A occurrence are more likely to be conserved in vertebrates. They also found a correlation between m6A in 3’UTRs and the presence of microRNA binding sites.

Adenosine methylation has therefore been shown to be a widespread and dynamically regulated post-transcriptional modification of mRNAs and lncRNAs in mammals. Its functional significance however, is still difficult to gauge. So far, the pathways responsible for adenosine methylation of RNAs are not characterised. It is also unclear as to whether FTO is the primary enzyme responsible for adenosine demethylation. FTO knockout mice survive, but display postnatal growth retardation and decreased locomotor activity. The linkages between m6A, stop codons and miRNA binding await mechanistic study, but are suggestive of important regulatory roles for RNA methylation. With MerIP-Seq, Meyer et al. have invented a useful technique for the analysis of this important modification.

Meyer, K., Saletore, Y., Zumbo, P., Elemento, O., Mason, C., & Jaffrey, S. (2012). Comprehensive Analysis of mRNA Methylation Reveals Enrichment in 3′ UTRs and near Stop Codons Cell DOI: 10.1016/j.cell.2012.05.003

A follow-up to this post on 5-methylcytosine in RNAs: Patterns of RNA methylation 2