Male C57BL/6J mice were purchased from GemPharmatech Co., Ltd. (Nanjing, China). Mice were housed in the animal facility and had free access to water and standard rodent chow. All animals care and surgical procedures were approved by the Animal Ethics Committee at The Third Affiliated Hospital of Sun Yat-sen University.

Fetal (E12.5, E15.5, and E18.5) and postnatal (1, 2, and 8 weeks) hind limb muscles were isolated for RNA and protein extraction.

For mouse muscle injury and regeneration experiment, tibialis anterior (TA) muscles of 6-week-old male mice were injected with 25 μl of 10 μM cardiotoxin (CTX, Merck Millipore, 217503), 0.9% normal saline (Saline) were used as control. The regenerated muscles were collected at day 1, 3, 5, and 10 post-injection. TA muscles were isolated for Hematoxylin and eosin staining or frozen in liquid nitrogen for RNA and protein extraction.

MuSCs were FACS-sorted from hind limb muscles of postnatal 1-week mice as previously described (Xie et al., 2018). Briefly, mechanical and enzymatic dissociation of cells, released resident mononucleated cells, then followed by antibody CD45 (PE/Cy7-CD45, eBioscience, 25-0451-82), CD31 (FITC-CD31, BioLegend, 102506), Sca1 (V450-Sca1, BD, 560653) and VCAM1 (efluor660-VCAM1, eBioscience, 50-1061-80) staining and FACS isolation. Collection of the cells those were positive for VCAM1 expression and negative for CD31, CD45, and Sca1.

HEK-293T and mouse skeletal muscle C2C12 cells were purchased from the Cellular Library of the National Collection of Authenticated Cell Cultures (Shanghai, China) and cultured in growth medium (GM), which consisted of Dulbecco’s Modified Eagle’s Medium (DMEM, Gibco) supplemented with 10% fetal bovine serum (FBS, Life Technology), 100 U/ml penicillin, and 100 μg/ml streptomycin (1 × penicillin–streptomycin). The sorted MuSCs were cultured in GM supplemented with 2.5 ng/mL bFGF (Life Technology). When MuSCs or C2C12 cells grow up to about 90% confluency, the GM was subsequently replaced with differentiation medium (DM), which was DMEM containing 2% horse serum (HyClone).

To inhibit the activity of the ERK signaling pathway, C2C12 cells were treated with 10 or 20 μM PD0325901 (PD, Sigma-Aldrich), respectively, and DMSO (Sigma-Aldrich) was used as the negative control.

Cells or homogenized tissue were lysed in ice-cold RIPA buffer containing 1 × protease inhibitor cocktail and phosphatase inhibitor (Roche). Equivalent total protein extracts were separated by SDS-PAGE and transferred to nitrocellulose membrane (GE Healthcare Life science, Germany). After that, membranes were blocked with 5% bovine serum albumin (BSA) for 1 h at room temperature. Primary antibodies were incubated and a horseradish peroxidase-conjugated secondary antibody was followed. The following antibodies were used in this study: antibodies for MEF2C (#5030), p-ERK (#9101S), ERK (#9102S), p-AKT (Thr308, #13038), p-AKT (Ser473, #4060) and GAPDH (#2118) were obtained from Cell Signaling Technology. Antibodies for MyoD (sc-760), WTAP (sc-374280) and MNK2 (sc-271559) were obtained from SantaCruz. Antibodies for METTL3 (#15073-1-AP) and Vinculin (#26520-1-AP) were obtained from Proteintech. Antibodies for ALKBH5 (ab174124) and Ki67 (ab15580) was obtained from Abcam. Antibodies for MHC (MAB4470), METTL14 (HPA038002), FTO (#597-FTO) and GFP (AE012) were obtained from R&D, Sigma, PhosphoSoklutions and ABclonal, respectively. Horseradish peroxidase-conjugated secondary antibodies were used to detect the primary antibodies. Immunoreactivities were determined using the ECL method (Advansta). The gray value of each protein band was quantified using ImageJ software.

cDNAs of mouse METTL3 and METTL14 were subcloned to pKD-CMV-MCS-EF1-PURO (pKD) vector by Gibson Assembly, pKD-GFP were subcloned as negative control. The gRNAs downstream transcription start sites used to guide the fusion of inactive Cas9 (dCas9) to the Krüppel-associated box (KRAB) repressor. The shRNA oligonucleotides were annealed and cloned into pLKO.1-TRC plasmid. Cignal 45-pathway reporter arrays, the ERK pathway reporter which measure the activity of the EKR pathways were purchased from Qiagen (Qiagen, Hilden, Germany). To generate stable cells, lentivirus were produced in 293T cells by transfecting these lentiviral vetors respectively with psPAX.2 and pMD2.G. Forty eight hours later, lentiviruses were collected, filtered, and infected target cell lines. Stable cells were selected by puromycin antibiotic.

All primers for cloning were listed in Supplementary Table 1.

Small interfering RNA (siRNA) targeting YTH family (si-YTHDF1, si-YTHDF2, si-YTHDF3, and si-YTHDC1), and corresponding negative control siRNA (si-NC) were obtained from GenePharma Co., Ltd. (Suzhou, China). The cells were reverse transfected using Lipofectamine 2000 according to the manufacturer’s protocol. A final concentration of 100 nM siRNAs was used for each transfection.

The sequences of the siRNAs were listed in Supplementary Table 2.

Total RNA was extracted from cells or tissues with TRIzol reagent (Invitrogen). First-strand cDNA for PCR analyses was synthesized with a PrimeScript RT reagent kit (Takara), quantitative real-time PCR was performed using 2 × ChamQ Universal SYBR qPCR Master Mix (Vazyme). GAPDH gene was used as endogenous control. Expression values of RNA were calculated using the comparative Ct method. Results were presented as Mean ± SD.

All primers for qPCR were listed in Supplementary Table 1.

m⁶A methylated RNA immunoprecipitation was performed as we previously described (Diao et al., 2021a). Briefly, 200 μg total RNA were incubated with 8 μg m⁶A antibody (#202003, Synaptic Systems, Germany) for 2 h on a rotating wheel at 4°C. Then, 50 μL protein A/G magnetic beads were added to reaction mixtures for 2 h on a rotating wheel at 4°C. After washed three times, beads were incubated with DNase I at 37°C for 30 min and were then digested by Proteinase K for about 2 h at 37°C with rotation. MicroElute RNA CleanUp Kit (Omega) was used for RNA purification. Purified RNA was reverse transcribed and was quantified by real-time RT-PCR.

Dot blot was performed as previously described with minor modification (Chen et al., 2015). Briefly, appropriate number of cells was and harvested avoiding RNA degradation, then purified by Dynabeads mRNA purification kit (Invitrogen, #61012). RNA samples were quantified and denatured at 95°C for 3 min, then cooled down on ice for 2 min. Samples were spotted on the membrane (Amersham Hybond-N⁺, GE) and air dry for 5 min, followed by UV-crosslink (2 auto-crosslink, 150 mJ/cm² UV Stratalinker, STRATAGENE). Membranes were washed in TBST and dyed in Methylene-blue (Sigma-Aldrich) as quantitative control. Then blocked in 5% non-fat dry milk in TBST for 2 h at room temperature, incubated with m⁶A antibodies (1:1,000, Synaptic Systems, 202-003) for overnight at 4°C. After 3 time washes, membranes were incubated with HRP linked secondary anti-rabbit IgG antibody (1:5,000, CST, #7074) for 1 h at room temperature. Signals were detected with ECL Plus Western Blotting Reagent Pack (GE Healthcare). The dots were quantified by Image J.

Cells were fixed in 4% formaldehyde for 30 min at room temperature prior to cell permeabilization with 0.1% Triton X-100 at 4°C for 10 min. Then, cells were blocked with 2.5% BSA in PBS (Beyotime) for 2.5 h. After blocking, cells were incubated with an anti-MHC antibody overnight at 4°C. The cells were washed 3 times with PBS for 10 min and then incubated with an Alexa Fluor 594-conjugated (Invitrogen) secondary antibody for 1 h. Nuclei were labeled with Hoechst (Invitrogen) for 10 min at a concentration of 0.5 μg/mL, and fluorescence signals were acquired and analyzed by laser scanning confocal microscopy (Zeiss).

For analysis of the Cignal finder pathway reporter arrays, transient transfections were performed in C2C12 cells stably overexpressed GFP or METTL3/14 as previously reported (Diao et al., 2021b). 50 ng of Cignal pathway reporter and standard negative control were transfected using lipofectamine 2000 reagent (Invitrogen) according to the manufacturer’s protocol. Firefly and Renilla luciferase activities were consecutively measured at 48 h after transfection using the Dual-Luciferase Reporter Assay kit (Promega).

Total RNA was isolated and purified using TRIzol reagent (Invitrogen) following the manufacturer’s procedure. The RNA amount and purity of each sample was quantified using NanoDrop ND-1000 (NanoDrop). The RNA integrity was assessed by Bioanalyzer 2100 (Agilent) with RIN number > 7.0, and confirmed by electrophoresis with denaturing agarose gel. Poly (A) RNA is purified from 50 μg total RNA using Dynabeads Oligo (dT) 25-61005 (Thermo Fisher Scientific). Then the poly (A) RNA was fragmented into small pieces using Magnesium RNA Fragmentation Module (NEB). Then the cleaved RNA fragments were incubated with m⁶A-specific antibody (#202003, Synaptic Systems, Germany). Then the IP RNA was reverse-transcribed to create the cDNA by SuperScript^TM II Reverse Transcriptase (Invitrogen, cat. 1896649), and fowling to synthesize U-labeled second-stranded DNAs. Then ligation with the adapter to the A-tailed fragmented DNA, the ligated products are amplified with PCR and performed the 2 × 150 bp paired-end sequencing (PE150) on an Illumina NovaSeq^TM 6000 (LC-Bio Technology Co., Ltd., Hangzhou, China) following the vendor’s recommended protocol.

For meRIP-seq, Fastp software¹ was used to remove the reads that contained adaptor contamination, low quality bases and undetermined bases with default parameter. Then sequence quality of IP and Input samples were also verified using fastp. We used HISAT2² to map reads to the reference genome (GRCm38, Ensembl) and kept unique mapped reads via samtools based on mapping quality larger than 30. Mapped reads of IP and input libraries were provided for R package exomePeak,³ which identifies significant m⁶A peaks and differential peaks, FDR ≤ 0.05 was considered significant. Bigwig format was produced via deeptools, as to be used for visualization on the IGV software.⁴ HOMER⁵ was used for de novo motif discovery based on top 1k most-enrichment peaks. Called peaks were annotated by intersecting with gene architecture using bedtools and custom python script. m⁶A metagene plot was plotted using Guitar package.

For mRNA-seq, clean fastq reads were aligned to mouse genome (Ensembl GRCm38) using hisat2 software. Raw gene read counts were calculated using featureCounts software based on Ensembl gene annotation (version 102), then values were normalized as RPKM (Reads per kilobase of exon per million reads mapped) using fpkm function in DESeq2 package. The differentially expressed genes were identified using DESeq2 package, genes with FDR (false discovery rate) ≤ 0.05 were considered statistically significant. GO and KEGG analyses were analyzed using clusterProfiler, p ≤ 0.05 were considered statistically significant. Heatmap was plotted using pheatmap package. Circos plot was plotted using Circos software.

Data are presented as the mean ± SD for three independent experiments unless otherwise noted in the figure legends. The statistical significance of difference between two means was calculated with the Student’s t-test (^∗p < 0.05, ^∗∗p < 0.01, ^****p < 0.001, ^****p < 0.0001), using Prism 9.0 (GraphPad Software).

To examine skeletal muscle differentiation, mouse C2C12 myoblasts were used to study myogenesis in vitro. We expanded C2C12 myoblasts in the presence of serum and initiated differentiation by serum withdrawal. The cell phenotype changed greatly, as described in our previous reports (Xie et al., 2018; Tan et al., 2021; Figure 1A). The differentiation of these cells was confirmed by the myogenic markers MHC, MEF2C and MyoD (Figure 1B). RNA dot blot assay was performed to investigate the dynamics of m⁶A RNA modification during myogenesis. We found that the levels of m⁶A marks were decreased during C2C12 cell differentiation. A significant downregulation of m⁶A levels was observed after serum withdrawal (Figure 1C and Supplementary Figure 1A). These results indicated that m⁶A methylation was reduced during skeletal muscle differentiation. Next, we wondered whether the decrease in m⁶A RNA modification was due to the altered expression of writers or erasers. We profiled the core components of m⁶A methyltransferases and demethylases. Interestingly, RNA and protein expression of METTL3/14 and WTAP were all significantly downregulated (Figure 1D and Supplementary Figure 1B) and negatively correlated with MHC and MEF2C expression (Figure 1B). And similar protein expression of these genes were shown in primary mouse skeletal muscle cells (Supplementary Figure 1C). While, the demethylases FTO and ALKBH5 had opposite changes during C2C12 differentiation (Supplementary Figure 1D), and the upregulation of FTO is consistent with previous report (Wang et al., 2017). To confirm the changes in the core m⁶A components during skeletal muscle development in vivo, we further profiled the expression of these genes in the hind limb muscle of developing mouse embryos. Consistent with the C2C12 cell mimic skeletal muscle differentiation results, METTL3/14 and WTAP protein levels were drastically downregulated (Figure 1E). The real-time PCR results also showed that all m⁶A modification methyltransferase genes were downregulated during mouse skeletal muscle development (Supplementary Figure 1E). These results implied that the downregulation of m⁶A was mainly due to the downregulation of its core methyltransferases, METTL3/14.

Given the robust functional roles of METTL3 and METTL14 methyltransferases in m⁶A RNA modification, as well as the equivocal METTL3 and METTL14 function in skeletal muscle homeostasis (Gheller et al., 2020; Zhang X. et al., 2020), we overexpressed METTL3 or METTL14 in C2C12 cells, and GFP-overexpressing cells were used as negative controls. The real-time PCR and western blot results validated the overexpression of METTL3/14 (Figures 1F,G). When METTL3 or METTL14 was overexpressed, the formation of myotubes was suppressed, which was confirmed by myosin immunofluorescence staining (Figure 1H). The western blot assays clearly showed that the expression of the differentiation marker MHC and that of the muscle-specific transcription factor MEF2C were decreased upon overexpression of METTL3/14 (Figures 1I,J and Supplementary Figures 2A,B). The suppression of MHC and MEF2C by overexpressed METTL3/14 was further confirmed by real-time PCR assays (Supplementary Figures 2C,D).

To complement loss-of-function experiments, we designed two gRNAs downstream of transcription start sites and used them to guide the fusion of inactive Cas9 (dCas9) to the Krüppel-associated box (KRAB) repressor to inhibit the transcription of METTL3 or METTL14 in C2C12 cells. As shown in Figure 1K, the mRNA levels of Mettl3 or Mettl14 were greatly reduced compared to those of the control gRNA. Correspondingly, the protein levels of METTL3 and METTL14 were decreased (Figures 1L,M). Four days after the cell growth medium (GM) was switched to differentiation medium (DM), the protein levels of the differentiation marker MHC were clearly upregulated when METTL3 or METTL14 was knocked down (Figures 1L,M), validating the finding showing that METTL3 or METTL14 could inhibit the differentiation of C2C12 cells. Taken together, all these results suggested that down-expression of Mettl3 and Mettl14 are required for skeletal muscle development.

To confirm the anti-differentiation functions METTL3 and METTL14, we isolated MuSC primary mouse skeletal muscle cells and infected them with lentiviruses encoding METTL3 or METTL14. Real-time PCR and western blot assays validated the success of METTL3/14 overexpression (Figures 2A,B). As determined by western blot assay, the MHC protein levels were clearly decreased when METTL3 or METTL14 was overexpressed (Figures 2C,D). The decrease in the differentiation markers MHC and MEF2C was also confirmed by real-time PCR assays (Supplementary Figure 3). These results suggested that METTL3/14 could repress the differentiation of primary mouse skeletal muscle cells.

To confirm our loss-of-function study, we knocked down METTL3 or METTL14 in MuSC primary mouse skeletal muscle cells. METTL3 and METTL14 were successfully knocked down, as shown by the significant decreases in mRNA and protein levels (Figures 2E,F). Via real-time PCR, we found that the mRNA levels of MHC and MEF2C were significantly upregulated (Figure 2G), validating the finding showing that METTL3/14 could repress the differentiation of mouse primary skeletal muscle cells. Thus, knocking down METTL3/14 promoted the differentiation of C2C12 and primary mouse skeletal muscle cells.

Taken together, our findings revealed that METTL3/14 inhibited muscle differentiation. Considering our results with those of previous studies (Gheller et al., 2020), we clarified that the m⁶A methyltransferases METTL3 and METTL14 have a common myogenetic suppressor function during skeletal muscle differentiation.

To delineate the molecular implications of m⁶A methylation during skeletal muscle differentiation, we profiled genome-wide gene expression using RNA-seq when METTL3 or METTL14 was overexpressed in C2C12 cells (Supplementary Table 3).

First, we analyzed the RNA-seq data of METTL3- or METTL14-overexpressing cells compared with those of the GFP negative control group, and the results are shown in Figures 3A,B. A panel of genes was significantly differential expressed when METTL3 or METTL14 was overexpressed (Supplementary Tables 4, 5). Furthermore, there was a perfectly positive correlation between the overall expression profile of these two groups (R = 0.98, p < 2.2e-16). These data verified the consistency of the METTL3 and METTL14 functions (Figure 3C). Next, we performed gene ontology analysis of the differentially expressed genes, and a KEGG pathway analysis revealed that the MAPK signaling pathway was the main significant signaling pathway, as indicated in both the METTL3 and METTL14 overexpression data (Figures 3D,E and Supplementary Tables 6, 7).

Many genes participate in the signal transduction of the MAPK cascade, and the ERK/MAPK signaling pathway has been reported to be involved in promoting the proliferation and inhibited differentiation of skeletal muscle (Michailovici et al., 2014; Yohe et al., 2018). We profiled ERK/MAPK signaling activity during the differentiation of C2C12 cells by detecting the phosphorylation of ERK via western blotting. As shown in Figure 3F, the ERK phosphorylation levels were downregulated when the growth medium of the C2C12 cells was switched to differentiation medium, suggesting that the activity of ERK signaling decreased during the differentiation of C2C12 cells. We chose AKT signaling as a negative control pathway and then tested the two phosphorylated forms of AKT, p-ATK at Thr308 and p-ATK at Ser473. As expected, the expression of these two phosphorylated forms of AKT did not change during muscle differentiation (Supplementary Figure 4A). To assess the role of ERK signaling in C2C12 cell differentiation, we treated C2Cl2 cells with the ERK-specific inhibitor PD0325901. ERK signaling activity was clearly inhibited, as indicated by ERK phosphorylation levels, while C2C12 cell differentiation was induced, elevating the expression of the myogenic markers MHC and MEF2C (Figure 3G and Supplementary Figure 5), indicating that ERK signaling could repress the differentiation of C2C12 cells. Interestingly, overexpression of METTL3 or METTL14 increased ERK phosphorylation levels and activated ERK signaling (Figures 3H,I), while knockdown of METTL3 or METTL14 showed the opposite effects (Figure 3J), suggesting that METTL3 or METTL14 may repress the differentiation of C2C12 cells by promoting ERK signaling activity. In the negative control pathway, the phosphorylated AKT proteins did not change when METTL3 or METTL14 expression was altered (Supplementary Figures 4B,C).

Given the recent observations that METTL3/14 regulates target function via m⁶A RNA modification, we performed MeRIP-seq to decode the underlying m⁶A-RNA mechanisms in C2C12 cells. Two representative stages were selected: GM, in which myoblasts were cultured in growth medium corresponding to an undifferentiated state, and D4, in which cells were first grown to about 90% confluency and then replaced differentiation medium for 4 days, at which time the cells differentiated into obvious myotubes. We obtained over 20 thousand unique peaks from each MeRIP-seq sequencing library (FDR ≤ 0.05, Supplementary Tables 8–10). The de novo motif predicted by HOMER showed that the m⁶A sites of all the samples were highly concordant within the typical m⁶A motif “RRACH” (Figure 4A). The stability of m⁶A-tagged transcripts showed non-significant difference between the GM and D4 groups (Supplementary Figure 6A). Consistent with previous studies (Meyer et al., 2012), m⁶A modifications were not randomly distributed in mRNA sequences but were mainly enriched in the 3′UTR (Figure 4B and Supplementary Figures 6B,C). Furthermore, we analyzed the m⁶A peaks in the whole transcriptome, and the results showed 1848 unique peaks with increased m⁶A modification and 3501 unique peaks with reduced m⁶A modification (Figure 4C and Supplementary Table 11). This result indicated lower methylation in DM4 peaks. These data were consistent with the dot blot results of C2C12 mimic differentiation.

To determine which m⁶A gene cascades are involved in the skeletal muscle differentiation process, we analyzed the differentially expressed m⁶A peaks. The KEGG analysis showed that the MAPK signaling pathway was the major signaling pathway. As shown in Figure 4D, 69 of 1257 genes were enriched in the MAPK pathway (Supplementary Table 12).

To investigate the effects of altered m⁶A modification on RNA expression, we analyzed the RNA-seq data together with the MeRIP-seq data. Among 4059 significant changed m⁶A-hyper and m⁶A-hypo genes, 531 genes showed increased RNA levels (Hypo-up plus Hyper-up), and 561 genes showed reduced RNA levels (Hypo-down plus Hyper-down). Interestingly, 2967 genes showed negligible changes in RNA levels (None) (Figure 4E). These results indicated that the more than half (2,967 out of 4,059) genes contain m⁶A marks were not affect their RNA expression significantly in our study model. Thus, we checked the 69 significantly m⁶A-modified MAPK factors in the RNA-seq data, and 45 out of 69 m⁶A-modified MAPK factors were found to be significantly expression in the D4 stage vs. the GM stage RNA-seq data, and to our surprise, 27 genes showed no change in corresponding RNA expression, as shown in Figure 4E. One of the highly m⁶A-enriched transcripts, MNK2, was of particular interest, as it has been reported to play an essential role in MAPK signaling and is a well-known regulator of ERK signaling (Waskiewicz et al., 1997; Ueda et al., 2010). The findings prompted us to analyze the m⁶A target MNK2 in the MAPK subgroup. Our MeRIP-seq data revealed one clear m⁶A peak around the 3′UTR of MNK2 mRNA (Figure 4F). To confirm that MNK2 was enriched in m⁶A marks, we used an antibody against m⁶A and performed RNA immunoprecipitation followed by real-time PCR. As shown in Figure 4G, compared to that in the IgG control, MNK2 RNA was significantly enriched in the m⁶A group, indicating that the MNK2 transcript was m⁶A enriched. Taken together, our data showed that a large number of RNAs which modified by m⁶A with slightly change in their RNA expression levels, and within that MNK2 is an m⁶A-enriched transcript involved in skeletal muscle differentiation.

To test whether MNK2 is a functional target of METTL3 and METTL14, we detected the expression of MNK2 when METTL3 or METTL14 expression was changed. As shown in Figures 5A,B, the mRNA levels of MNK2 were not changed, while the protein levels of MNK2 were greatly upregulated when METTL3 or METTL14 was overexpressed. Accordingly, MNK2 protein levels were downregulated, while its mRNA was not affected, when METTL3 and METTL14 were knocked down (Figures 5C,D), suggesting that MNK2 protein levels were regulated by METTL3/METTL14. To assay the functional importance of MNK2, we used CRISPR inhibition to knock down MNK2 in C2C12 cells. Real-time PCR results showed that MNK2 mRNA was significantly inhibited (Figure 5E). Western blot results also confirmed that MNK2 protein expression was greatly repressed (Figure 5F). Interestingly, knocking down MNK2 decreased ERK phosphorylation levels and increased MHC protein levels (Figures 5G,H), suggesting that MNK2 could be a functional downstream target of METTL3 and METTL14 and that it inhibited C2C12 differentiation probably via ERK signaling.

METTL3 and METTL14 are known as “writers” and are critical for m⁶A deposition. Some specific RNA-binding proteins, including YTHDF1/2/3 and YTHDC1, known as “readers,” can bind m⁶A motifs to regulate corresponding RNA functions and thus induce the acquisition of specific phenotypic outcomes. To identify potential m⁶A readers for MNK2, we knocked down YTHDF1/2/3 and YTHDC1 using siRNAs and then detected the expression level of MNK2. The potential readers were successfully knocked down, as indicated by the significant decrease in their mRNA levels (Figure 5I), which did not affect MNK2 mRNA expression (Figure 5J). MNK2 protein levels were decreased only when YTHDF1 expression was knocked down, while knocking down YTHDF2/3 and YTHDC1 had no effect on MNK2 protein levels (Figure 5K), suggesting that YTHDF1 is an important reader of MNK2. The mRNA levels of MHC and MEF2C were significantly upregulated when YTHDF1 expression was knocked down (Figure 5L), indicating that YTHDF1 can repress the differentiation of C2C12 cells and is a phenotypically relevant reader for MNK2.

To further explore in vivo functions of METTL3/14, we examined the expression profiles and function of METTL3/14 in acute skeletal muscle regeneration after cardiotoxin (CTX) injection. Adult muscle regeneration is sustained by infiltrating macrophages and the consequent activation of MuSCs. During the reparative process, immune cells, especially the macrophages, infiltrate damaged skeletal muscles to release cytokines, chemokines and growth factors into the localized area that alter the micro-environment to clear cellular debris and support the regeneration through MuSCs activation (Saini et al., 2016; Shang et al., 2020). We treated mice with CTX and collected tissues at different time points (Figure 6A). As determined by hematoxylin and eosin staining of muscle, extensive necrosis post-CTX treatment was observed, and the mouse muscle was markedly regenerated 5 days after the injection, suggesting that the injury and regeneration model was successfully established (Figure 6B). At early time points after injury (day1 and day3), MyoD were upregulated, indicating that MuSCs were actively proliferating and starting differentiation. Interestingly, METTL3 and METTL4 expression, along with that of their downstream target MNK2 and p-ERK were markedly upregulated on these time points (Figures 6C,D), suggesting that METTL3/14-MNK2 may be involved in the early stage of muscle regeneration and enhance the activation and proliferation of these MuSCs.