N 6 -methyladenosine regulates RNA abundance of SARS-CoV-2

The worldwide pandemic of COVID-19 is caused by a novel β -coronavirus SARS-CoV-2, an enveloped RNA virus with a positive-sense, single-stranded RNA genome of ~30 kb 1,2 , which raises a key unresolved issue about its transcriptomic and epitranscriptomic architectures. The complete viral genomic RNA sequence contains six major open-reading frames (ORFs), including two large poly-proteins ORF1a and ORF1b that can form nonstructural proteins through proteolytically cleaving upon cell entry. Other subgenomic mRNAs (sgRNAs) encoding structural proteins including spike protein (S), envelope protein (E), membrane protein (M), nucleocapsid protein (N), and accessory proteins (3a, 6, 7a, 7b, and 8), generated through a mechanism termed discontinuous extension of minus strands. All the viral transcripts contain a 5 ′ cap, a common 5 ′ leader sequence of around 70 nt, a common 3 ′ untrans-lated region (3 ′ UTR),

All the viral transcripts contain a 5′ cap, a common 5′ leader sequence of around 70 nt, a common 3′ untranslated region (3′UTR), and a 3′ poly(A) tail 3 . Moreover, the formation of sgRNAs is based on the discontinuous transcription leading to the leader-body fusion controlled by the RNA-dependent RNA polymerase and transcriptionregulatory sequences (TRSs). TRSs, located at the 3′ end of the leader sequence (TRS-L) and preceding each viral gene (TRS-B), contain a conserved 6-7 nt core sequence and variable 5′ and 3′ flanking sequences 4 .
RNA chemical modifications are involved in physiology and pathology processes through regulating RNA metabolism. N 6 -methyladenosine (m 6 A) as the most abundant methylation type in mRNA has been shown to regulate the viral life cycles and the cellular response to viral infection 5,6 . Recently, dozens of RNA modification sites have been identified through nanopore direct RNA sequencing 7,8 , while the intrinsic nature and the detailed functions of the RNA modifications remain obscure. Here, we conducted m 6 A MeRIP-seq (methylated RNA immunoprecipitation sequencing) using RNAs from SARS-CoV-2-infected Vero cells, and identified 13 m 6 Amodified peaks on viral transcripts (11 peaks with the conserved eukaryotic motif RRACH (R = A/G; H = A/C/ U)). We found that m 6 A might regulate abundance of SARS-CoV-2 through a mechanism of 3′UTR with or without RRACH.
We first performed strand-specific MeRIP-and RNA-seq for both positive-sense (SARS-CoV-2 RNA, +) and negative-sense RNA (SARS-CoV-2 RNA, −) to profile the m 6 A landscape along SARS-CoV-2 transcriptome. The results showed that more than 99.4% reads aligned to SARS-CoV-2 derived from positive-sense RNA and that only less than 0.6% from negative-sense RNA in both immunoprecipitated (IP) and input samples (Supplementary Fig. S1a). As the reads were predominantly aligned to the positive-sense RNA, and the number of reads for negative-sense RNA was not sufficient for identifying m 6 A peak, we only chose the reads aligned to the viral positivesense RNA for subsequent analysis. To sensitively identify the m 6 A modifications in the viral RNA, the DAMS (Differential expressed window-based Analysis for MeRIP-Seq) algorithm was designed based on the analysis model reported in previous study 9 (Supplementary Fig. S1b). To validate the sensitivity and specificity of DAMS in m 6 A peak

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We next performed DAMS on the viral transcriptome and finally identified 13 m 6 A peaks along the viral positive-sense RNA (Fig. 1a, b; Supplementary Table S1), which were all validated by MeRIP-qPCR ( Supplementary Fig. S1f). Intriguingly, 9 of the m 6 A peaks (69.2%) were located in the CDS segments of ORF1ab (Fig. 1b), a much longer coding region than other parts of the genome sequence ( Supplementary  Fig. S1g). After normalization by the length, the segment of 3′UTR presented much higher m 6 A enrichment than ORF1ab (Fig. 1c), suggesting a potential regulatory role of m 6 A in post-transcriptional regulation of SARS-CoV-2. Moreover, we found 11 of 13 m 6 A peaks containing RRACH (Fig. 1d). To validate this result, we simulated the m 6 A pools by randomly shuffling peak locations for 1000 times and found that over 90% simulated pools (926 in 1000) contained less than 11 peaks with RRACH (Fig. 1e).
To investigate the regulatory role of m 6 A in the viral lifecycle, we first knocked down the METTL3, a key m 6 A methyltransferase subunit, in Vero cells infected with SARS-CoV-2 ( Supplementary Fig. S2a), and performed whole transcriptome sequencing. Intriguingly, we found that the proportion of SARS-CoV-2 RNA in library was increased in METTL3-depleted Vero cells (Fig. 1f) and the increased abundance of viral RNA was validated by qPCR ( Supplementary Fig. S2b), suggesting a suppressive effect of m 6 A on viral abundance. To quantify the absolute viral RNA in normal and METTL3 knockdown cells, we added ERCC (External RNA Controls Consortium) as an internal artificial reference for normalization during library construction ( Supplementary Fig. S2c). The normalized results still showed an obvious increase in the viral RNA amounts in Vero cells upon METTL3 depletion (Fig. 1g).
As m 6 A has been reported to regulate RNA stability 10 , we next quantified the expression levels of all sgRNAs to further investigate the functional role of m 6 A in viral abundance. However, since the library only captured fragmented RNA and different viral sgRNAs with shared common regions, we can only count the spanning-junction reads harboring both leader sequence and CDS sequence for sgRNA quantification except ORF1ab. We first compared the counts of spanning-junction reads between two biological replicates and found that they are well conserved in both normal and METTL3-depleted Vero cells (Supplementary Fig. S2d). Besides, in both samples, the predominant proportion was spanning-junction sgRNA reads (with leader sequence and CDS) rather than other spanning-junction reads (non-defined). Nevertheless, we did not observe any significant changes in proportions of different categories of sgRNAs between normal and METTL3-depleted Vero cells (Supplementary Fig. S2d). Collectively, these results suggest a global increase in viral RNAs instead of increase in some specific sgRNAs.
We further investigated the 5′ and 3′ selections for each spanning-junction read. As expected, TRS-L and TRS-B were significantly enriched in 5′ and 3′ selections, respectively ( Supplementary Fig. S3a, b). Besides, we also found a large amount of spanning-junction reads related to 3′UTR ( Supplementary Fig. S3a, b). Based on our previous findings that m 6 A tends to be enriched in 3′UTR, we speculate that m 6 A may be involved in the regulation of 3′UTR spanningjunction. We then profiled the global pattern of spanning junctions and found a decreased signal around 3′ termini upon METTL3 depletion (Fig. 1h). Referring to a recent study by Kim et al. 7 , we defined the spanning-junctions into four groups ( Fig. 1i; TRS-L-dependent, canonical; Random 3′ acceptor; Random 5′ donor; Random inner junction) and found that the proportion of random inner junctions was decreased by almost 8% (Fig. 1j). Through comparing the relative expression level of all spanning-junctions between control and METTL3-depleted Vero cells, we found that most 3′UTR inner junctions were decreased upon METTL3 depletion (Fig. 1k). Then, we performed MeRIP-seq in METTL3-depleted Vero cells, and found that the methylation levels of 3 m 6 A peaks near the 3′ termini (two located in sgRNA N, and one in 3′UTR) were significantly decreased upon METTL3 knockdown, while others kept a similar level of enrichment after depleting METTL3 ( Fig. 1l; Supplementary Fig. S3c-e). We further mapped the RRACH motif in m 6 A peaks along SARS-CoV-2 genomic 3′UTR and found that most inner junctions locate in the vicinity of RRACH suggesting the possibility of RRACH "cut-off" in 3′ UTR (shorter 3′UTR) (Supplementary Fig. S3f). Most regular 3′UTRs of viral RNA contain m 6 A-modified RRACH, which might promote the degradation of viral transcripts.
In summary, our work analyzed the m 6 A methylome of SARS-CoV-2 and suggests a potential regulatory role of m 6 A in SARS-CoV-2 RNA abundance, through shorter 3′ UTR formation to evade the degradation of viral RNA. Erasing m 6 A through knocking down the host m 6 A methyltransferase METTL3 might decrease the diversity of 3′UTR as less spanning-junctions were identified. Thus, we propose that there might be two types of viral 3′UTR, with (shorter 3′UTR) or without random inner junction (regular 3′UTR). In normal cells, viral sgRNAs with regular 3′UTR can be methylated by the host METTL3, which likely stimulates the cellular degradation program to clear away the viral RNA. On the other hand, to resist the m 6 A-dependent degradation, SARS-CoV-2 might acquire diverse 3′UTR by depleting m 6 A-modified RRACH motifs ( Supplementary  Fig. S4). However, these perspectives need further investigations by using in vitro cell system and further in vivo animal models with an intact interferon system.