Ythdf2 facilitates precursor miR-378/miR-378-5p maturation to support myogenic differentiation

Kaiping Deng; Yalong Su; Zhipeng Liu; Silu Hu; Caifang Ren; Wurilege Wei; Yixuan Fan; Yanli Zhang; Feng Wang

doi:10.1007/s00018-024-05456-0

. 2024 Nov 6;81(1):445. doi: 10.1007/s00018-024-05456-0

Ythdf2 facilitates precursor miR-378/miR-378-5p maturation to support myogenic differentiation

Kaiping Deng ^1,², Yalong Su ^1,², Zhipeng Liu ^1,², Silu Hu ³, Caifang Ren ⁴, Wurilege Wei ^2,⁵, Yixuan Fan ^1,², Yanli Zhang ^1,², Feng Wang ^1,^2,^✉

PMCID: PMC11541164 PMID: 39503763

Abstract

Ythdf2 is known to mediate mRNA degradation in an m⁶A-dependent manner, and it has been shown to play a role in skeletal muscle differentiation. Recently, Ythdf2 was also found to bind to m⁶A-modified precursor miRNAs and regulate their maturation. However, it remains unknown whether this mechanism is related to the regulation of myogenesis by Ythdf2. Here, we observed that Ythdf2 knockdown significantly suppressed myotube formation and impacted miRNAs expression during myogenic differentiation. Through integrated analysis of miRNA and mRNA sequencing data, miR-378 and miR-378-5p were identified as important targets of Ythdf2 in myogenesis. Mechanically, Ythdf2 was found to interact with core components of the pre-miRNA processor complex, namely DICER1 and TARBP2, thereby facilitating the maturation of pre-miR-378/miR-378-5p in an m⁶A-dependent manner and resulting in an increase in the expression levels of mature miR-378 and miR-378-5p. Moreover, the downregulation of either miR-378 or miR-378-5p significantly inhibited myotube formation, while the forced expression of miR-378 or miR-378-5p could partially rescued Ythdf2 knockdown-induced suppression of myogenic differentiation by activating the mTOR pathway. Collectively, our results for the first time suggest that Ythdf2 regulates myogenic differentiation via mediating pre-miR-378/miR-378-5p maturation, which might provide new insights into the molecular mechanisms underlying m⁶A modification in the regulation of myogenesis.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00018-024-05456-0.

Keywords: Ythdf2, pre-miRNA processing, miR-378, miR-378-5p, Skeletal muscle development

Introduction

Skeletal muscle development is a precisely orchestrated process controlled by an elaborated transcriptional regulatory network of myogenic transcription factors [1]. In addition to these transcriptional regulation, various post-transcriptional regulatory pathways also are critical for skeletal muscle development, including RNA modification, DNA methylation, histone modifications, RNA-binding proteins, and non-coding RNAs [2, 3]. MicroRNAs (miRNAs) are short non-coding RNAs that can regulate the expression of up to 60% of mammalian cellular mRNAs by binding to complementary sequences on target mRNA transcripts, thereby inducing mRNA degradation or translational repression [4]. Over the past decade, numerous studies have extensively characterized the intricate expression patterns and critical regulatory roles of miRNAs during mammalian skeletal muscle development [5, 6]. Muscle-specific miRNAs, such as miR-1, miR-133a, miR-133b and miR-206, have been demonstrated to regulate key myogenic transcription factors and processes involved in skeletal muscle differentiation [7, 8]. However, the precise mechanism underlying the regulation of muscle-specific miRNA biogenesis during skeletal muscle development remains unclear.

miRNAs are typically generated from the primary transcripts of miRNA (pri-miRNA) through a two-step cleavage process. Initially, the nuclear enzyme drosha ribonuclease type III (DROSHA) cleaves the pri-miRNA to release the hairpin-shaped pre-miRNA [9]. Subsequently, the pre-miRNA is exported from the nucleus to the cytoplasm by exportin-5 (XPO5), where it is further cleaved by endoribonuclease dicer (DICER) to generate double-stranded miRNA duplexes [10, 11]. Finally, these double-stranded miRNA duplexes are incorporated into Argonaute RISC catalytic component (Ago) proteins, leading to the unwinding of the duplex and the retention of the single-stranded miRNA by Ago [12]. To precisely modulate gene expression throughout mammalian development and differentiation, the production of mature miRNA is tightly regulated at multiple levels. Recent studies have shown that epigenetic modifications, including DNA methylation, chromatin/histone modifications, and RNA modifications, play significant roles in regulating miRNA biogenesis [13, 14]. N6-methyladenosine (m⁶A) is the most abundant internal mRNA methylation and is dynamically regulated by methyltransferases (such as methyltransferase-like 3 (Mettl3), methyltransferase-like 14 (Mettl14), and Wilms tumor 1-associated protein (WTAP)) and demethylases (Fat mass and obesity-associated protein (FTO) and AlkB homolog 5 (ALKBH5)). It plays critical roles in modulating the mRNA processing and metabolism [15, 16]. Interestingly, m⁶A modifications are not only found in mRNA but also in non-coding RNAs, including miRNAs. Prior research has shown that pri-miRNAs containing m⁶A modifications can be readily recognized and bound by DGCR8, which facilitating the processing of miRNAs [17, 18]. In research focusing on cardiac hypertrophy and adipogenesis, the m⁶A methyltransferase Mettl3 and demethylase FTO were found to regulate some specific pri-miRNA maturation in an m⁶A-dependent manner [19–21]. Additionally, a recent study indicated that Mettl3 post-transcriptionally regulates the expression of certain muscle-specific miRNAs during C2C12 differentiation [22], suggesting that m⁶A modifications may influence miRNA biogenesis in skeletal muscle development. YTH domain proteins 2 (Ythdf2), a prototypical m⁶A “reader”, plays a crucial role in facilitating the degradation of target mRNAs [23]. Recent studies have demonstrated that Ythdf2 is involved in the processing of certain miRNAs during pathological processes [24, 25]. While Ythdf2 has been identified as an essential for skeletal muscle myogenesis [26], it remains unclear whether its impact on skeletal muscle development is mediated through the regulation of miRNA biogenesis.

In the present research, we explore the potential role of Ythdf2 in miRNA biogenesis during myogenic differentiation and discover that knockdown of Ythdf2 alters the expression of certain miRNAs involved in myogenesis. Furthermore, our findings indicate that Ythdf2 regulates the expression of miR-378 and miR-378-5p by promoting the maturation of precursor miR-378/miR-378-5p (pre-miR-378/miR-378-5p) in an m⁶A dependent manner. Importantly, we also investigate the molecular mechanism by which Ythdf2 regulates the processing of pre-miR-378/miR-378-5p. Our findings demonstrate that Ythdf2 interacts with DICER1 and TARBP2, facilitating the maturation of pre-miR-378/miR-378-5p and driving myogenesis.

Materials and methods

All experimental procedures were approved and carried out in accordance with relevant guidelines of the Ethic Committee of Nanjing Agricultural University, China (SYXK2022–0031).

Animal samples

All goats used in this study were sourced from Haimen goat breeding farm, in Nantong, China. Twelve male Haimen goats from the same sire were randomly selected, comprising three fetal goat (75-days-gestational age); three newborn goats (1-days-old), three goats aged 12 months, and three goats aged 24 months 12-months-old goats. All selected goats were sacrificed to obtain longissimus muscle samples, which were rapidly frozen in liquid nitrogen for subsequent RNA isolation.

Cell culture and myogenic differentiation

Goat primary myoblasts (GPMs) were isolated from the hindlimb muscles and subsequently purified using the protocol described in reference [27]. In brief, fetal goat muscle tissue was minced and digested with 1% collagenase I (Sigma-Aldrich, St. Louis, MO, USA) for 50 min at 37 °C, followed by digestion with 0.25% trypsin at the same temperature for 15 min. After passing the cell suspension through a 70-mm filter, the cells were harvested by centrifugation at 500 × g and resuspended in growth medium, which consisted of 20% fetal bovine serum (FBS, GIBCO, NY, USA), 10% horse serum (GIBCO), 1% penicillin/streptomycin (GIBCO), and 69% Dulbecco's Modified Eagle Medium (DMEM, Thermo Fisher Scientific). The differential adhesion method was then employed to obtain pure GPMs. Once the GPMs reached approximately 80% confluence in the growth medium, they were induced to differentiate by transitioning to a differentiation medium composed of 2% horse serum, 1% penicillin/streptomycin, and a 97% DMEM.

Plasmid construction, small interfering RNA (siRNA), miRNA mimics and inhibitor, and cell transfection

The coding sequence of goat Ythdf2 and Mettl3, each tagged with a FLAG sequence, were synthesized and subsequently cloned into the PEX3 plasmid (Genepharma, Shanghai, China) to create overexpression plasmids. The sequence for goat pre-miR-378/miR-378-5p (5′-gcagccagtgggtgacagagccacccagggCTCCTGACTCCAGGTCC TGTGTgttacctcgaaatagcACTGGACTTGGAGTCAGAAGGCctgagtggaatcgccttccc-3′) was also synthesized and cloned into a pGCMV-miR vector obtained from Genepharma, resulting in the generation of the pGCMV-pre-miR-378/miR-378-5p plasmid. All siRNAs, miRNA mimics, and inhibitor used in this study were purchased from Shanghai GenePharma, with their sequences provided in Supplementary Table S1. Cell transfections were performed using Lipofectamine 3000 transfection reagent (Thermo Fisher Scientific, MA, USA) according to the manufacturer’s instructions.

Immunofluorescence

The cells were fixed with 4% paraformaldehyde and then permeabilized with 0.25% Triton X-100. Subsequently, the cells were blocked with 3% bovine serum albumin and incubated overnight at 4 ℃ with the specific antibodies, including Anti- YTHDF2 antibody (1:500 dilution; Proteintech, 24,744–1-AP, Wuhan, China) and Anti-Slow Skeletal myosin heavy chain antibody (1:1000 dilution; Abcam, ab11083, Cambridge, UK). After washing with Phosphate-Buffered Saline, the cells were incubated with a secondary antibody solution containing either 488-conjugated donkey anti-rabbit antibody (1:800 dilution; Abcam, ab150073, Cambridge, UK) or 594- conjugated donkey anti-mouse antibody (1:800 dilution; Abcam, ab150108, Cambridge, UK) for one hour. The final step involved staining the cells with 4',6'-diamidino-2-phenylindole (DAPI). The immunofluorescence staining results were visualized using a Zeiss LSM710 META fluorescence microscope (Jena, Germany).

RNA isolation and library preparation for RNA sequencing

After transfection with either siCtrl or siYthdf2 for 24 h, GPMs were induced to undergo myogenic differentiation for 3 days. Cell samples were collected at the onset of differentiation (GM) and after 3 days (DM) for further experiments. Total RNA was extracted from the cell samples using TRIzol reagent (Thermo Fisher Scientific). Following assessment of the RNA sample’s quality and integrity, 1.0 μg of RNA from each sample was utilized to construct cDNA library using the NEBNext^® Ultra™ Directional RNALibrary Prep Kit for Illumina^® (NEB), following the manufacturer's instructions. Additionally, miRNA libraries were generated using the TruSeq Small RNA Sample Library Prepare Kit (Illumina) in accordance with the manufacturer's guidelines.

mRNA sequencing (mRNA-seq) and data analysis

mRNA sequencing was conducted using an Illumina NovaSeqTM 6000 sequencer (LC-Bio Technology CO., Ltd., Hangzhou, China). Sequencing reads that passed quality control were mapped to the reference genome of Capra hircus (GCF_001704415.1 assembly) using StringTie (version 1.3.4d) with default settings. Gene expression levels were normalized to fragments per kilobase of exon model per million mapped fragments (FPKM). Differential expression analysis was performed using the R packages DESeq2. Genes were identified as differentially expressed when they exhibited an absolute value of the |log2(fold change)|≥ 1 and q value < 0.05. Additionally, Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses of differentially expressed genes (DEGs) were separately performed using the clusterProfiler R package (v3.12.0).

miRNA sequencing (miRNA-seq) and data analysis

The miRNA libraries were sequenced on an Illumina HiSeq 2500 platform. Raw reads were processed using an in-house program, ACGT101-miR (LC Sciences, Houston, Texas, USA), to eliminate low-quality raw reads. The remaining clean and unique reads, rang from 18 to 26 nucleotides in length, were mapped to the specific species precursors in miRBase 22.1 through a BLAST search to identify known miRNAs and novel 3p- and 5p-derived miRNAs. Unique sequences mapping to specific species mature miRNAs in hairpin arms were identified as known miRNAs. Unmapped sequences were BLASTed against the specific genomes, and hairpin RNA structures containing the sequences were predicted from the flanking 80 nt sequences using RNAfold software (http://rna.tbi.univie.ac.at/cgi-bin/RNAfold.cgi). Differentially expressed miRNAs (DEMs) were identified using a student′s t-test with a p value < 0.05 [28]. To predict the target genes by differentially expressed miRNAs, we employed two computational target prediction algorithms (TargetScan, v5.0 and Miranda, v3.3a) to identify miRNA binding sites. The results from both algorithms were combined, and overlapping target genes were calculated. These overlapping target genes identified by both tools were selected for further GO and KEGG enrichment analyses.

Co-analysis of miR-seq and mRNA-seq

For an integrated analysis of RNA-seq and miRNA-seq data, the predicted target genes were then intersected with differential mRNA data to analyze miRNA-mRNA pairs with negative regulatory relationships. Subsequently, KEGG and GO databases were used for pathway annotation of miRNA-mRNA pairs with negative regulatory relationships.

Quantitative real-time PCR (qRT-PCR) for gene expression

The cDNA for qRT-PCR was synthesized using reverse transcription reagent kits (Vazyme, Nanjing, China), and the complementary DNA of mature miRNA was synthesized using the miRNA 1st Strand cDNA Synthesis Kit (by stem-loop, Vazyme). qRT-PCR was conducted on the ABI Step- One Plus Real- Time PCR System (Applied Biosystems) using ChamQ Universal SYBR qPCR Master Mix (Vazyme), following the manufacturer's protocol. The analysis of pre-miRNAs was performed using established methods as detailed in previous publications [29]. Briefly, two pairs of primers were designed: one pair targeted a region unique to pre-miRNA, and the other targeted a region common to both pri-miRNA and pre-miRNA. Pre-miRNA expression was calculated based on qRT-PCR results from both primer pairs. All primers used for the targeted genes are listed in Supplementary Table S2. U6 snRNA, 18S, and GAPDH were utilized as endogenous control genes.

Western blotting analysis

Cells were lysed in RIPA lysis buffer containing a protease/phosphatase inhibitor cocktail (Beyotime Biotech, Shanghai, China). After incubation for 15 min on ice, the samples were centrifugation at 12,000 × g for 10 min at 4 ℃ to extract and collect the total protein. The protein samples were then separated by 12% SDS-PAGE and transferred to PVDF membranes. The membranes were blocked with 5% skim milk for 1 h at room temperature and incubated overnight at 4 °C with primary antibodies. Following washed with Tris-buffered saline containing Tween-20, secondary antibodies were applied for 1 h at room temperature. Immunoblots were visualized using the ECL kit (Biosharp, Hefei, China), and band intensities were analyzed with ImageJ software (NIH, MD, USA). The primary antibodies used are listed in Supplementary Table S3.

m⁶A dot blot assay

Dot blot assay was conducted to detect the global m⁶A RNA methylation, following previously described method [30]. Briefly, purified mRNA was quantified and diluted to a concentration of 100–200 ng/μL. After denaturing at 95 ℃ for 3 min, the RNA samples were placed immediately on ice. Either 400 ng or 200 ng of total mRNA was then spotted onto a Hybond-N + membrane (Beyotime Biotech, Shanghai, China), UV-crosslinked, and blocked with 5% nonfat milk. The membranes were incubated overnight at 4 ℃ with an anti-m⁶A antibody (1:1000 dilution, Synaptic Systems, SySy_202003, Germany). After washing with Tris-buffered saline containing Tween-20 (TBST), the membranes were incubated with Goat anti-Rabbit IgG (H + L) Secondary Antibody, HRP (1:10,000 dilution, Invitrogen, 31,460, Carlsbad, USA) for 1 h at room temperature. The membranes were visualized using the Western Bright ECL kit (Biosharp, Hefei, China), and dots intensities were quantified with ImageJ software (NIH, MD, USA). Additionally, the membranes were stained with 0.02% methylene blue for 30 min to verify equal RNA loading.

Quantification of m⁶A modifications

The extracted RNA was purified using the GenElute mRNA Miniprep (MRN10; Sigma-Aldrich) following the manufacturer’s instructions. After purification, RNA quality was assessed using a NanoDrop. Global m⁶A RNA methylation was then quantified with the EpiQuik m⁶A RNA Methylation Quantification Kit (P-9005–48; Epigentek) according to the manufacturer's guidelines.

SELECT qRT-PCR

The quantification of m⁶A modifications in pre-miR-378/miR-378-5p was performed using SELECT qRT-PCR with primers detailed in Supplementary Table S4. The SELECT qRT-PCR method was based on a previously established protocol with slight modifications [31, 32]. Briefly, 1.5 µg of total RNA was combined with 40 nM up and down primers and 5 µM dNTP in 17 µL of 1 × CutSmart buffer. The mixture was subjected to sequential incubation at 90 °C, 80 °C, 70 °C, 60 °C, and 50 °C for 1 min each, followed by 6 min at 40 °C. The annealing product was mixed with 3 µL of an enzyme mixture (0.01 U Bst 2.0 DNA polymerase, 0.5 U SplintR ligase, 10 nmol ATP) and incubated at 40 °C for 20 min, followed by denaturation at 80 °C for 20 min. Finally, 2 µL of the resulting product was used for qRT-PCR. The cycle threshold (Ct) values obtained from qRT-PCR represent the SELECT results for detecting m⁶A levels.

RNA immunoprecipitation (RIP) combined with quantitative real-time PCR (RIP-qRT-PCR)

The RIP assay was conducted using the Imprint RNA Immunoprecipitation Kit (Sigma-Aldrich, RIP-12RXN, Saint Louis, MO, USA) as previously described [33]. Briefly, GPMs were transfected with the Ythdf2-FLAG plasmid, followed by lysis in RIP lysis buffer. The FLAG antibody (1:25 dilution; Abcam, ab205606, Cambridge, UK) or rabbit IgG (1:30 dilution; Abcam, ab313801, Cambridge, UK) was incubated with 50 μL of Dynabeads Protein A Magnetic Beads suspension in 100 μL of lysis buffer for 30 min at room temperature, followed by washing with RIP wash buffer. The supernatant from the cell lysates, along with IP buffer (containing RIP wash buffer, a protease inhibitor cocktail, and RNase inhibitor), was added to the antibody-conjugated magnetic beads and rotated overnight at 4℃. After washing with RIP wash buffer, the immunoprecipitated RNA was extracted using TRIzol reagent (Thermo Fisher Scientific) and subsequently analyzed using qRT-PCR.

Protein–protein docking analysis

Protein–protein docking analysis was performed to predict interactions between Ythdf2 and DICER1, as well as between Ythdf2 and TARBP2. The models for the Ythdf2, DICER1, and TARBP2 proteins were generated using the AlphaFold2 program [34], and their three-dimensional structures are depicted in Supplementary Figure S1. Subsequently, specialized HDCOK programs were employed for the docking analysis [35, 36]. Structures with the highest docking scores were selected as the standard results for further interaction analysis. The interconnection score was calculated using either the ITScorePP or ITScorePR iterative scoring function, where a more negative docking score suggests a higher likelihood of a stronger binding interaction. Given that docking scores for protein–protein complexes in the PDB typically range around -200 or higher, we established a confidence score based on docking scores to represent the likelihood of binding. The confidence score was calculated using the following formula: Confidence_score = 1.0/[1.0 + e0.02*(Docking_Score + 150)]. In general, a confidence score above 0.7 indicates a high probability of binding, scores between 0.5 and 0.7 suggest that binding is likely, and scores below 0.5 imply a lower likelihood of interaction between the two molecules.

Co-immunoprecipitation (Co-IP) assay

The Co-IP assay was conducted using a Co-IP Kit (Proteintech, Wuhan, China) following the manufacturer's instructions. GPMs were transfected with the Ythdf2-FLAG plasmid. After transfection, the GPMs were lysed with IP lysis solution supplemented with protease inhibitors. The lysate was then centrifuged to obtain the supernatant. This supernatant was incubated with 30 μL of rProteinA/G beads, which had been pre-coated with either a FLAG-specific antibody (1:30 dilution, Abcam, ab205606, Cambridge, UK) or a control IgG antibody (1:100 dilution, Proteintech, 30,000–0-AP). After washing the beads with IP buffer, the bound proteins were eluted and prepared for analysis by western blot.

Statistical analysis

All experiments were performed with at least three biological replicates. The results are expressed as the mean ± standard error of the mean (SEM). Statistical analyses were performed using SPSS software (version 24.0) with either Student’s t-test or ANOVA followed by Tukey’s test. P < 0.05 was considered statistically significant.

Results

Ythdf2 influences miRNAs expression during myogenic differentiation

To investigate the potential role of Ythdf2 in miRNA biogenesis during myogenesis, we assessed the impact of Ythdf2 knockdown on miRNAs expression profiles during myogenic differentiation using miRNA-seq. After transfection with either siCtrl or siYthdf2 for 24 h, GPMs were transferred into differentiation media and harvested at day 0 (GM) and day 3 (DM) to construct miRNA libraries (Fig. 1A). The libraries were categorized into four groups: siCtrl_GM, siYthdf2_GM, siYthdf2_DM, and siYthdf2_DM (Fig. 1A). It was found that depletion of Ythdf2 with siRNA significantly inhibited myogenic differentiation (Fig. 1B and C). Moreover, immunofluorescence analysis revealed reduced myotube formation in Ythdf2-knockdown GPMs compared to control cells (Fig. 1D), corroborating previous findings that Ythdf2 deficiency impedes myogenic differentiation [26]. Next, we compared the miRNA expression profiles of the siCtrl_GM group and siYthdf2_GM group and identified 169 DEMs between the two groups (Fig. 1D). Among these, 95 miRNAs were downregulated, and 74 miRNAs were upregulated (Fig. 1E and F). GO enrichment analysis indicated that the target genes of the DEMs were primarily associated with transcription, protein transport, and cell proliferation and differentiation (Fig. 1G). Furthermore, KEGG pathway analysis revealed that target genes were significantly enriched in signaling pathways related to skeletal muscle development, including the MAPK, FOXO, Hippo, and Notch signaling pathways (Fig. 1H).

Fig. 1 — miRNA-seq analysis of Ythdf2-knockdown GPMs at pre-differentiation A GPMs were transfected with either siCtrl or siYthdf2 for 24 h and then induced to undergo myogenic differentiation for 3 days. Cell samples were harvested at day 0 (GM) and day 3 (DM) of differentiation. B The mRNA expression level of Ythdf2 in cells were detected by qRT-PCR. C Phase contrast microscopy images of GPMs at day 0 (GM) and day 3 (D3) of differentiation. D Representative images of immunofluorescence blot for Ythdf2 and MyHC protein in differentiated siCtrl and siYthdf2 cells. Scale bars represent 100 μm. E A volcano plot shows DEMs between the siCtrl_GM and siYthdf2_GM group. F Heatmap shows hierarchical clustering of DEMs in the siCtrl_GM and siYthdf2_GM group. GO enrichment analysis G and KEGG enrichment analysis H of predicted target genes for the DEMs

Next, the miRNA expression profile of the siYthdf2_DM group was compared with that of the siCtrl_DM group. We obtained 394 DEMs in both groups, with 166 upregulated DEMs and 228 downregulated DEMs (Fig. 2A). These DEMs were shown in the heat map (Fig. 2B). Through the utilization of GO enrichment and KEGG pathway analysis, the target genes of these DEMs were found to be significantly enriched in several biological process terms, including transcription, signal transduction, protein transport, cell division, and cell differentiation (Fig. 2C). Additionally, they were found to be enriched in signaling pathways related with skeletal muscle development, such as the MAPK, FOXO, Notch, and insulin signaling pathways (Fig. 2D). These results indicate that Ythdf2 may regulate the expression of miRNAs involved in myogenesis during myogenic differentiation.

Fig. 2 — miRNA-seq analysis of differentiated Ythdf2-knockdown GPMs. GPMs were transfected with either siCtrl or siYthdf2 for 24 h and induced to undergo myogenic differentiation for 3 days before harvest. A A volcano plot shows DEMs between the siCtrl_DM group and siYthdf2_DM group. B Heatmap shows hierarchical clustering of DEMs in the siCtrl_DM group and siYthdf2_DM group. GO enrichment analysis C and KEGG enrichment analysis D of predicted target genes for the DEMs

Identification of potential miRNAs involved in Ythdf2-mediated myogenesis

To identify potential miRNAs involved in Ythdf2-mediated myogenesis, integrative genomic analyses were performed to evaluate the correlation between DEMs and DEGs in siCtrl cells and siYthdf2 cells at GM and D3 of myogenic differentiation. First, pairwise comparisons among the four groups revealed 50 miRNAs that were commonly differentially expressed in the following comparisons: siCtrl_DM vs siCtrl_GM, siYthdf2_DM vs siYthdf2_GM, siYthdf2_GM vs siCtrl_GM, and siYthdf2_DM vs siCtrl_DM (Fig. 3A and Supplementary Figure S2A). Among these 50 DEMs, 30 miRNAs were upregulated, while 20 were downregulated during myogenic differentiation (Fig. 3B). Notably, after Ythdf2 knockdown, the expression of these miRNAs exhibited an inverse trend compared to control cells. Specifically, miRNAs that were upregulated during differentiation in control cells were downregulated upon Ythdf2 knockdown, and those that were downregulated in control cells became upregulated (Fig. 3B). Given the regulatory role of Ythdf2 in goat myogenic differentiation through m⁶A modifications [26], we speculated that miRNAs bearing m⁶A modifications are key regulators in Ythdf2-mediated myogenesis. Interestingly, 17 of these commonly identified DEMs were found to contain m⁶A modification sites in their precursors, as predicted using the online m⁶A site prediction tool SRAMP (Supplementary table S5). Among these miRNAs, 13 miRNAs (bta-miR-31_R + 2, bta-miR-378, bta-miR-455-3p_L + 2R-1, bta-miR-503-5p_R + 3, chi-miR-125b-3p_R + 1, chi-miR-133a-5p, chi-miR-155-3p, chi-miR-378-5p, hsa-miR-4454_L-2, oar-miR-133_L + 1R-2, oar-miR-152, PC-3p-4008_1227, and ssc-mir-503-p5_1ss2CA) exhibited high or moderate scores for m⁶A modification (Supplementary table S5).

Fig. 3 — Identification of miRNAs involved in Ythdf2-mediated myogenesis. A Venn diagram depicting the common DEMs in siCtrl and siYthdf2 cells at GM and D3 of differentiation. B Heatmap of common DEMs across the different groups. C miRNA–mRNA network established from the DEMs and DEGs in siCtrl and siYthdf2 cells during the GM phase. D miRNA–mRNA network established from the DEMs and DEGs in siCtrl and siYthdf2 cells during the DM phase. Red represents upregulated miRNAs or mRNAs, while purple denotes downregulated one; Δ represents miRNA, and ○ represents mRNA. E Correlation of expression between Ythdf2 and selected DEMs during myogenic differentiation. F The locations of caprine miR-378 and miR-378-5p within the intron of the *PPARGC1β* gene. G Conservation analysis of miR-378 and miR-378-5p among different species. H Expression levels of miR-378 and miR-378-5p in longissimus muscle of goat at different ages, determined by qRT-PCR. The values are expressed as mean ± SEM; *p < 0.05, **p < 0.01

Subsequently, we performed transcriptome analyses and identified a total of 402 DEGs in the comparison between siYthdf2_GM and siCtrl_GM, and 2164 DEGs in the comparison between siYthdf2_DM and siCtrl_DM (Supplementary Figure S2B and Supplementary table S6). Since miRNAs primarily function to negatively regulate mRNA expression [37], we constructed negative interaction networks involving 13 identified miRNAs and their target genes during myogenic differentiation. In the pre-differentiation, 12 potential DEMs were found to negatively regulate 84 target DEGs. Among them, 7 downregulated miRNAs were negatively correlated with 23 upregulated target genes, while 5 upregulated miRNAs were negatively correlated with 61 downregulated target genes (Fig. 3C). During the myogenic differentiation stage, the 13 potential DEMs were found to negatively regulate 491 target DEGs. Here, 7 downregulated miRNAs were negatively correlated with 154 upregulated target genes, and 5 upregulated miRNAs were negatively correlated with 337 downregulated target genes (Fig. 3D). Furthermore, the miRNA–mRNA networks were found to be mainly linked to signaling pathways related with skeletal muscle development, including the MAPK, calcium, insulin and PI3K-Akt signaling pathways (Supplementary Figure S2C and S2D). These findings suggest that Ythdf2 may modulate these signaling pathways by regulating the expression of these potential miRNAs, thereby influencing myogenesis.

Analysis of expression profiles of 13 DEMs during myogenic differentiation revealed that 9 miRNAs were upregulated (bta-miR-378, bta-miR-503-5p_R + 3, chi-miR-133a-5p, chi-miR-378-5p, oar-miR-133_L + 1R-2, oar-miR-152, PC-3p-4008_1227, and ssc-mir-503-p5_1ss2CA), while 2 miRNAs were downregulated (chi-miR-155-3p and hsa-miR-4454_L-2) (Supplementary table S7). Given that Ythdf2 depletion inhibits myogenic differentiation, these DEMs, whose expression patterns during normal differentiation contrasted with those observed after Ythdf2 knockdown are more likely to participate in Ythdf2-mediated myogenesis. Notably, a positive correlation was observed between expression of several DEMs (including bta-miR-378, bta-miR-503-5p_R + 3, chi-miR-133a-5p, chi-miR-378-5p, oar-miR-133_L + 1R-2, PC-3p-4008_1227, and ssc-mir-503-p5_1ss2CA) and Ythdf2 expression during myogenic differentiation (Fig. 3E). In contrast, the expression of chi-miR-155-3p displayed a negative correlation with Ythdf2 expression (Fig. 3E). Additionally, qRT-PCR analysis corroborated the observed correlations between the expression of these specified microRNAs and Ythdf2 levels (Figure S2E), suggesting that the identified miRNAs may play important roles in Ythdf2-mediated myogenesis. Among these miRNAs, miR-378 and miR-378-5p were found to be derived from the intron of the peroxisome proliferator-activated receptor gamma, coactivator 1 beta (PPARGC1β) gene in goats (Fig. 3F) and were highly conserved (Fig. 3G). Furthermore, the expression of miR-378 and miR-378-5p was found to be upregulated during goat skeletal muscle development (Fig. 3H). Since miR-378 has been previously identified as a regulator of myogenesis [38], and given the increased expression of miR-378/miR-378-5p during muscle development, miR-378/miR-378-5p could serve as crucial regulators in Ythdf2-mediated myogenesis.

Ythdf2 regulates the expression of miR-378 and miR-378-5p in an m⁶A-dependent manner

To determine whether miR-378 and miR-378-5p are m⁶A-modified downstream targets of Ythdf2, we first assessed the impact of m⁶A modifications on their expression levels. As expected, m⁶A levels decreased in Mettl3-depleted cells and were upregulated in cells overexpressing Mettl3 (Fig. 4A-E). Using the SRAMP software, we identified a high-confidence m⁶A site within the precursor sequences of miR-378/miR-378-5p (Fig. 4F). Knockdown of Mettl3 resulted in an obvious reduction of m⁶A methylation at this specific site (A74) in the pre-miR-378/miR-378-5p sequence (Fig. 4G). Moreover, Mettl3 knockdown led to a significant decrease in the expression of both miR-378 and miR-378-5p, accompanied by an increase in the level of pre-miR-378/miR-378-5p (Fig. 4H). Conversely, overexpression of Mettl3 led to a substantial increase in the expression of both miR-378 and miR-378-5p, while reducing the level of pre-miR-378/miR-378-5p (Fig. 4I). Subsequently, we performed an RNA stability assay to examine the effect of m⁶A on the mRNA stability of pre-miR-378/miR-378-5p. The results revealed that Mettl3 knockdown did not significantly affect the mRNA stability of pre-miR-378/miR-378-5p (Fig. 4J). This suggests that m⁶A modification may influence the expression of miR-378 and miR-378-5p by modulating their processing from precursors to mature forms, rather than by regulating the stability of their precursors.

Fig. 4 — m⁶A modification regulates the expression of miR-378 and miR-378-5p. A–F GPMs were transfected with either control siRNA (siCtrl) or Mettl3 siRNA (siMettl3), as well as overexpression Mettl3 plasmid (oeMettl3) or empty Pex3 vector (Pex3). The mRNA A and B protein expression levels of Mettl3 were measured at 48 h post-transfection. C Statistical results of the western blot analysis of (B). D and E m⁶A levels in GPMs transfected with siCtrl, siMettl3, Pex3, and oeMettl3 were detected using dot blotting and EpiQuik m⁶A RNA Methylation Quantification Kit. Methylene blue staining served as a loading control. F Predicted secondary structure of precursor to miR-378 and miR-378-5p (pre-miR-378/miR-378-5p) using Mold software (http://www.unafold.org/mfold/applications/rna-folding-form.php). G The Ct values from qRT-PCR representing SELECT results for detecting m⁶A level at the potential m⁶A sites (A74) in pre- miR-378/378-5p in GPMs transfected with siMettl3. H and I Expression levels of pre- miR-378/378-5p, miR-378, and miR-378-5p in cells were detected by qRT-PCR. J Stability analysis of pre-miR-378/miR-378-5p mRNA in siCtrl and siMettl3 cells using qRT-PCR. The values are expressed as the mean ± SEM; *p < 0.05, **p < 0.01

Given Ythdf2's role as an mRNA binding protein in m⁶A RNA modification [39], we further investigate its potential interaction with pre-miR-378/miR-378-5p via m⁶A modification. RIP-qRT-PCR analysis showed a direct interaction between pre-miR-378/miR-378-5p and the Ythdf2 protein in GPMs (Fig. 5A). Knockdown of Ythdf2 was found to significantly increased the level of pre-miR-378/miR-378-5p, while overexpression of Ythdf2 led to a decrease in these levels (Fig. 5B). Additionally, Ythdf2 knockdown significantly reduced the expression levels of both miR-378 and miR-378-5p, whereas overexpression of Ythdf2 led to an increase in miR-378 expression (Fig. 5C). Notably, Ythdf2 knockdown did not affect the mRNA stability of pre-miR-378/miR-378-5p (Fig. 5D). Furthermore, silencing Ythdf2 countered the increase in miRNAs expression and the reduction of pre-miR-378/miR-378-5p caused by overexpressed Mettl3 (Fig. 5E). Collectively, these findings suggest that Ythdf2 may modulate the maturation process of pre-miR-378/miR-378-5p in an m⁶A-dependent manner, thereby regulating the expression levels of both mature miR-378 and miR-378-5p.

Fig. 5 — Ythdf2 regulates the expression of miR-378 and miR-378-5p in an m⁶A-dependent manner. A The interaction between Ythdf2 protein and pre-miR-378/miR-378-5p mRNA was analyzed by RIP assay. B and C GPMs were transfected with siCtrl or siYthdf2, as well as overexpression Ythdf2 plasmid (oeYthdf2) or Pex3. The mRNA levels of Ythdf2, pre-miR-378/miR-378-5p, miR-378, and miR-378-5p were quantified by qRT-PCR. D The stability of pre- miR-378/378-5p mRNA in siCtrl and siYthdf2 cells was assessed by qRT-PCR. E The expression levels of Mettl3, Ythdf2, pre-miR-378/miR-378-5p, miR-378 and miR-378-5p were quantified by qRT-PCR in GPMs transfected with either Pex3, oeMettl3, or both oeMettl3 and siYthdf2. The values are expressed as the mean ± SEM; *p < 0.05, **p < 0.01

Ythdf2 binds to DICER1 and TARBP2 and facilitates pre-miR-378/miR-378-5p processing

To further elucidate the molecular mechanism by which Ythdf2 regulates the maturation process of pre-miR-378/miR-378-5p, we first assessed its effect on the expression of known pre-miRNA maturation regulators, such as DICER1 and TARBP2, which are essential for cleaving most pre-miRNAs to generate transient double-stranded miRNA duplexes. qRT-PCR and western blot assays showed that knockdown of Ythdf2 did not affect the expression levels of either DICER1 or TARBP2 (Fig. 6A-C). Next, we conducted protein–protein docking analysis to identify potential interacting partners of Ythdf2 among DICER1 and TARBP2. The docking results revealed a strong binding potential, with docking scores of -229.01 for DICER1 and -251.36 for TARBP2, along with confidence scores of 0.829 and 0.883, respectively (Fig. 6D and E). Following this analysis, we examined the interaction patterns between the Ythdf2, DICER1, and TARBP2 proteins, focusing on their spatial structure binding sites and regions. A total of four salt bridge interactions and fifteen hydrogen bonds were identified between the Ythdf2 and DICER1 proteins (Figure S3A). In contrast, the interactions between Ythdf2 and TARBP2 contained one salt bridge interactions and seven of hydrogen bonds (Figure S3B). Further, endogenous Co-IP experiments confirmed the interaction of Ythdf2 with both DICER1 and TARBP2 proteins in GPMs (Fig. 6F). In GPMs, forced expression of pre-miR-378/miR-378-5p resulted in an over 70-fold increase in expression levels of mature miR-378 and miR-378-5p (Fig. 6G and H). However, this significant increase was markedly attenuated by the knockdown of either Ythdf2 or DICER1 (Fig. 6G and H). Furthermore, simultaneous interference with both Ythdf2 and DICER1 was more effective in diminishing the elevated expression of mature miR-378 and miR-378-5p induced by pre-miR-378/miR-378-5p overexpression than interfering Ythdf2 alone (Fig. 6G and H). These results further confirm that Ythdf2 interacts with DICER1 and TARBP2, thereby facilitating the processing of pre-miR-378/miR-378-5p into its mature forms.

Fig. 6 — Ythd2 binds to DICER1 and TARBP2 and facilitates pre-miR-378/miR-378-5p processing. The mRNA A and protein B levels of DICER1 and TARBP2 in siCtrl and siYthdf2 cells, as detected using qRT-PCR and western blot. C Statistical results of the western blot analysis of B. D Structure of the docking complex between Ythdf2 and DICER1 proteins. E Structure of the docking complex between Ythdf2 and TARBP2 proteins. F Co-IP of Ythdf2-FLAG with endogenous DICER1 and TARBP2 in GPMs transfected with Ythdf2-FLAG. G and H GPMs were transfected with the following combinations: siCtrl + pGCMV-miR vector (siCtrl + pre-miR-NC), siCtrl + pGCMV-pre-miR-378/miR-378-5p plasmid (siCtrl + pre-miR-378/miR-378-5p), siDICER1 + pGCMV-pre-miR-378/miR-378-5p plasmid (siDICER1 + pre-miR-378/miR-378-5p), siYthdf2 + pGCMV-pre-miR-378/miR-378-5p plasmid (siYthdf2 + pre-miR-378/miR-378-5p), and siDICER1 + siYthdf2 + pGCMV-pre-miR-378/miR-378-5p plasmid (siDICER1 + siYthdf2 + pre-miR-378/miR-378-5p). After 48 h, the expression levels of DICER1, Ythdf2, pre-miR-378/miR-378-5p, miR-378, and miR-378-5p in GPMs were detected using qRT-PCR. The values are expressed as the mean ± SEM; *p < 0.05, **p < 0.01. ^a–d Means with distinct superscripts within the same row indicate significant differences (p < 0.05)

miR-378 and miR-378-5p are functionally important targets of Ythdf2 in myogenesis

To demonstrate the role of miR-378 and miR-378-5P in Ythdf2-mediated myogenesis, we first examined their expression during myogenic differentiation. The expression levels of miR-378 and miR-378-5p were observed to be upregulated during myogenic differentiation (Fig. 7A). However, knockdown of either miR-378 or miR-378-5P using specific miRNA inhibitor resulted in a significant suppression of myotube formation during myogenic differentiation (Fig. 7B-D). Consistently, depletion of miR-378 or miR-378-5p resulted in significant decreases in both the protein abundance and the mRNA levels of key myogenic markers, including myosin heavy chain (MyHC), myogenic differentiation 1 (MyoD1), and myogenin (Fig. 7E-G). Additionally, we investigated the effect of miR-378 on the expression of polymerase alpha subunit B (POLA2) and MyoR (also known as musculus musculin, MSC) in GPMs, since these genes have been confirmed as downstream targets of miR-378 in the regulation of myoblast differentiation in both mice and cattle [38, 40]. qRT-PCR analysis showed that overexpression of miR-378 significantly reduced POLA2 expression, while knockdown of miR-378 obviously increased POLA2 expression (Figure S4A). This suggests that miR-378 may specifically target POLA2 to regulate myogenic differentiation of GPMs. In contrast, neither the knockdown nor overexpression of miR-378 had a significant impact on MSC expression (Figure S4B). These findings suggest that miR-378 and miR-378-5P is essential for myogenic differentiation of GPMs.

Fig. 7 — Knockdown of miR-378 or miR-378-5p impaired the myogenic differentiation of GMPs. A The expression levels of miR-378 and miR-378-5p during myogenic differentiation were determined by qRT-PCR. B–F GPMs were transfected with negative control (NC) inhibitor or miR-378/miR-378-5p inhibitor, and then were induced to myogenic differentiation for 3 days. The expression of miR-378 B and miR-378-5p C was measured at 36 h post-transfection.) Representative images (left) of myotube formation in differentiated cells transfect with either NC inhibitor or miR-378/ miR-378-5p inhibitor. Scale bars represent 100 μm. Quantitative analysis of the fusion index (right). The protein E and mRNA G expression levels of MyHC, MyoD1, and myogenin in differentiated cells, as detected using qRT-PCR and western blot. F Quantitation of the western blot results of (E). The values are expressed as the mean ± SEM; *p < 0.05, **p < 0.01

Next, we examined whether the overexpression of miR-378 or miR-378-5p could rescue the suppression of myogenic differentiation caused by Ythdf2 knockdown. As expected, overexpression of either miR-378 or miR-378-5p could partially alleviates the inhibition of myotube formation caused by Ythdf2 deficiency (Figs. 8A and 9A). Furthermore, the upregulation of these miRNAs restored the diminished expression levels of MyoD1, myogenin, and MyHC in Ythdf2-depleted cells (Figs. 8B–D and 9B–D). Additionally, we observed that forced expression of miR-378 did not influence phosphorylation levels of AKT in levels the Ythdf2-depleted cells (Fig. 8E and F). However, it effectively reduced the increase in phosphorylated AMPK levels induced by Ythdf2 knockdown [26], which was accompanied by a slightly increase in phosphorylated mTOR levels (Fig. 8E and F). Different from the effects observed with miR-378 overexpression, miR-378-5p overexpression significantly enhanced the phosphorylation levels of both AKT and mTOR, while not affecting phosphorylated AMPK levels in the Ythdf2-depleted cells (Fig. 9E and F). Collectively, these findings suggest that Ythdf2 regulates myogenic differentiation by mediating miR-378 and miR-378-5p expression.

Fig. 8 — Overexpression of miR-378 rescues Ythdf2 knockdown-induced inhibition of myogenic differentiation. A–D GPMs were transfected with indicated siRNAs (siCtrl, siYthdf2, and siYthdf2 + miR-378). A Fluorescence micrographs (left) of GPMs transfected with the indicated siRNAs after 3 days of differentiation. Scale bars represent 100 μm. Quantitative analysis of the fusion index (right). B qRT-PCR analysis of the mRNA level of Ythdf2, miR-378, MyHC, MyoD1, and myogenin in the differentiated GPMs with the indicated siRNA transfection. C Western blot analysis of the protein level of Ythdf2, MyHC, MyoD1, and myogenin in GPMs with transfection of indicated siRNAs at day 3 of differentiation. D Statistical results of the western blot analysis of C. E Western blot t analysis of the protein levels of p-mTOR, mTOR, p-AMPK, AMPK, p-AKT, and AKT in GPMs transfected with siCtrl, siYthdf2, and siYthdf2 + miR-378 mimics F Statistical results of the western blot analysis of (E). The values are expressed as the mean ± SEM; *p < 0.05, **p < 0.01

Fig. 9 — Overexpression of miR-378-5p rescues Ythdf2 knockdown-induced inhibition of myogenic differentiation. A Phase contrast microscopy images of GPMs transfected with the indicated siRNAs after 3 days of differentiation. Scale bars represent 100 μm. B qRT-PCR analysis of the mRNA levels of Ythdf2, miR-378-5p, MyHC, MyoD1, and myogenin in the differentiated GPMs with the indicated siRNA transfection. C Western blot analysis of the protein levels of Ythdf2, MyHC, MyoD1, and myogenin in GPMs transfected with the indicated siRNAs at day 3 of differentiation. D Statistical results of the western blot analysis of C. E Western blot t analysis of the protein levels of p-mTOR, mTOR, p-AMPK, AMPK, p-AKT, and AKT in GPMs transfected with siCtrl, siYthdf2, and siYthdf2 + miR-378-5p mimics. F Statistical results of the western blot analysis of E. The values are expressed as the mean ± SEM; *p < 0.05, **p < 0.01

Discussion

m⁶A modifications and miRNAs are critical post-transcriptional regulator of gene expression programs [41, 42], playing important roles in the development of various tissues in mammals. Recent evidence has indicated that m⁶A modification related proteins, including the m⁶A methyltransferases Mettl13 and Mettl14, demethylase FTO, and the “readers” protein Ythdf2, play key roles in skeletal muscle myogenesis and regeneration [26, 27, 43, 44]. Additionally, a growing number of muscle-specific miRNAs have been identified as important regulators of myoblast proliferation and differentiation [5, 6]. While recent research has clarified the roles of m⁶A modification and miRNAs in skeletal muscle development, their interactions in skeletal muscle development remains unclear. In the present study, we observed that Ythdf2 knockdown significantly inhibited myotube formation and altered the expression of certain myogenesis-related miRNAs. Furthermore, miR-378 and miR-378-5p were identified as potential m⁶A-modified miRNAs involved in myogenesis, regulated by Ythdf2-mediated pre-miR-378/miR-378-5p processing in an m⁶A dependent manner. To our knowledge, this is the first study demonstrating that Ythdf2 influences skeletal myogenesis by regulating the maturation of muscle-specific miRNAs.

Ythd2 been shown to be participate in the proliferation and myogenic differentiation of myoblast in our previous study [26]. A recent study reported that muscle-specific genetic deletion of Ythdf2 impairs skeletal muscle growth and eliminates overload-induced hypertrophy [45]. However, the finding that primary myoblast isolated from Ythdf2 muscle-specific knockout mice displayed no impediment in myoblast fusion appears to contradict the established role of Ythdf2 in myogenic differentiation. It is questionable to conclude definitively that Ythdf2 has no effect on myogenic differentiation. This discrepancy may stem from the conditional knockout model used, where Ythdf2 was deleted in skeletal muscle specifically after myogenin expression, as achieved through breeding Ythdf2^fl/fl mice with those expressing the Cre recombinase gene controlled by the skeletal muscle-specific myogenin promoter. Myogenin is a critical factor that drives myoblasts toward differentiation, leading them to exit the cell cycle and fuse into multinucleated myofibers [1]. Therefore, primary myoblasts isolated from this Ythdf2 muscle-specific knockout mice can only undergo Ythdf2 knockdown after the initiation of differentiation has begun, making them unsuitable for assessing the impact of Ythdf2 on myoblast differentiation. Taken together, these findings confirm that Ythdf2 plays a crucial role in muscle growth and development. Given recent reports suggesting that Ythdf2 can bind to m⁶A-modified pre-miRNAs and influence their maturation [25, 46], it is speculated that Ythdf2 may participate in the regulation of miRNA biogenesis during myogenic differentiation. To assess the impact of Ythdf2 on miRNA expression during skeletal myogenesis, we performed miRNA sequencing analysis following Ythdf2 knockdown in differentiating goat myoblasts. Our results showed that Ythdf2 knockdown led to significant differential expression of numerous miRNAs during myotube formation. Pathway enrichment analysis revealed that the predicted target genes of these DEMs are involved in key signaling pathways related to skeletal muscle development and function, including MAPK, FOXO, and Notch signaling. These findings suggested that Ythdf2 could modulate the expression of miRNAs involved in myogenesis. However, the mechanism underlying Ythdf2's regulation of miRNA biogenesis warrant further investigation.

MiRNA biogenesis is a complex, multi-step process that involves the sequential enzymatic cleavage of pri-miRNAs by Drosha and Dicer nucleases. Recent studies have provided substantial evidence that m⁶A modification serves as an important regulator of miRNA biogenesis [24, 47]. In various cancer types, the m⁶A methyltransferases Mettl3 and Mettl14 have been demonstrated to promote the maturation of specific cancer-related miRNAs from pri-miRNAs to pre-miRNAs by mediating m⁶A modifications [48–52]. Interestingly, in myogenic C2C12 cells, Mettl3 has been found to both enhance and repress muscle-specific miRNAs [22]. Consistently, in the present study, we also observed a similar phenomenon (Figure S5A and S5B), suggesting that m⁶A modifications regulate the expressions of muscle specific miRNAs through various multiple mechanisms. Notably, unlike previous studies that reported m⁶A modifications facilitating the processing of pri-miRNAs in the nucleus, we demonstrate that Ythdf2 can bind to the m⁶A modification site in the pre-miR-378/miR-378-5p transcript, facilitating its maturation in the cytoplasm. Ythdf2 is known to function by interacting with specific proteins. It initiates target mRNA degradation by recruiting the CCR4/NOT deadenylase complex to remove the poly(A) tail, RNase P to cleave the 5' end, or RNase MRP endoribonuclease for internal cleavage [26, 46, 53]. Moreover, Ythdf2 has been found to bind an m⁶A site in pre-miR-181b-1 in osteosarcoma, leading to its degradation and decreased miR-181b-1 expression [54]. A recent study reported that Ythdf2 promotes the maturation of pre-miR-126 in an m⁶A- and AGO2-dependent manner in acute myeloid leukemia cells [25]. In contrast, our findings reveal that Ythdf2 collaborates with microprocessor proteins DICER1 and TARBP2 to facilitate the maturation of pre-miR-378/miR-378-5p, thereby promoting the expression of mature miR-378 and miR-378-5p. Given Ythdf2's ability to bind to Ago2 and the potential interactions between Ago2 and DICER1 or TARBP2 [25, 26, 55], it is possible that Ago2, DICER1, and TARBP2 collectively contribute to the maturation of specific pre-miRNAs facilitated by Ythdf2. Collectively, these findings suggest that Ythdf2 can both positively and negatively regulate the maturation of m⁶A-modified pre-miRNA, depending on the recruited protein factors.

MiR-378, also known as miR-378a-3p, is a multifunctional microRNA that plays a crucial role in regulating various biological processes, including metabolism, angiogenesis, and muscle development [56–58]. It is highly conserved across species and has been reported to promote myogenic differentiation by inhibiting MyoR or POLA2 in mammal [38, 40]. In alignment with these findings, we found that miR-378 is upregulated during goat skeletal muscle development, whereas miR-378 knockdown significantly increased POLA2 expression and impaired myogenic differentiation of GPMs. Furthermore, miR-378-5p, another mature miRNA generated from the intron of the PPARGC1β gene, has also been shown to participate in the regulation of myogenic differentiation. In prior studies, we revealed that the deletion of Ythdf2 leads to increased phosphorylation of AMP-activated protein kinase (AMPK), which subsequently inhibits mTOR activity and hinders myogenic differentiation [26]. The BTG2 and ACVRL1 genes have been identified as potential targets of miR-378/miR-378-5p and are known to influence the activity of the mTOR pathway [59, 60]. It is plausible that miR-378/miR-378-5p modulates mTOR pathway by targeting genes like BTG2 and ACVRL1; However, further experiments are required to validate this hypothesis. Interestingly, forced expression of miR-378/miR-378-5p was able to attenuate the inhibition of mTOR activity caused by Ythdf2 knockdown, potentially accounting for the partial restoration of the phenotype in Ythdf2-depleted cells upon miR-378/miR-378-5p overexpression. These findings suggest that both miR-378 and miR-378-5p are crucial targets of Ythdf2 in the regulation of myogenic differentiation. It is worth noting that other pre-miRNAs carrying m⁶A modifications could also be targeted by Ythdf2 and be involved in myogenic differentiation, in addition to pre-miR-378/miR-378-5p. Therefore, further investigation is essential to identify additional m⁶A-modified miRNAs that are targets of Ythdf2, which will help clarify the function of Ythdf2-mediated processing of m⁶A-modified pre-miRNAs in skeletal muscle differentiation.

In conclusion, our results for the first time suggest that Ythdf2 plays an important role in pre-miRNA processing, contributing to myogenesis. Moreover, our findings demonstrate that Ythdf2 collaborates with DICER1 and TARBP2 to facilitate the processing of pre-miR-378/miR-378-5p, which in turn enhances the expression of miR-378 and miR-378-5p, thus supporting myogenic differentiation by activating the mTOR pathway (Fig. 10). These findings highlight the critical role of Ythdf2 in regulating pre-miRNAs maturation and provide valuable insights into the impact of m⁶A modification and miRNA interaction on skeletal muscle development.

Fig. 10 — Graphical abstract illustrating the role and underlying mechanism of the Ythdf2-mediated pre-miR-378/miR-378-5p maturation in myogenesis. Ythdf2 collaborates with DICER1 and TARBP2 to facilitate the processing of pre-miR-378/miR-378-5p in an m⁶A-dependent manner, thereby supporting myogenic differentiation through the activation of the mTOR pathway

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 4183 KB)^{(4.1MB, docx)}

Supplementary file2 (XLSX 5131 KB)^{(5MB, xlsx)}

Acknowledgements

We thank LC-Bio for sequencing, and the High-Performance Computing Platform of the Bioinformatics Center, Nanjing Agricultural University, for their data analysis supports.

Authour contributions

D KP conceived and designed the study. D KP, S YL, and L ZP performed the experiments. D KP and H SL analyzed the data. F YX, W WR and L ZP performed the tissue sampling. D KP and R CF wrote and revised the manuscript. W F and Z YL supervised the study and administered the project.

Funding

This study was supported by the National Natural Science Foundation of China (32202638), Natural Science Foundation of Jiangsu Province, China (BK20221018), National Key Research and Development Program of China (2021YFD1200902), China Postdoctoral Science Foundation (2022M721649), and Hainan Yazhou Bay Seed Lab (B21HJ1003).

Data availability

All data generated or analyzed during this study are included in this article and its supplementary information files.

Declarations

Conflict of interest

The authors declare no conflict of interest.

Ethical approval

All animal studies described in this manuscript were approved by the Ethics Committee of Nanjing Agricultural University, China (SYXK2022–0031).

Consent to participate

Not applicable.

Consent to publish

Not applicable.

Footnotes

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary file1 (DOCX 4183 KB)^{(4.1MB, docx)}

Supplementary file2 (XLSX 5131 KB)^{(5MB, xlsx)}

Data Availability Statement

All data generated or analyzed during this study are included in this article and its supplementary information files.

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[CR42] 42.Dykes IM, Emanueli C (2017) Transcriptional and post-transcriptional gene regulation by long non-coding RNA. Genom Proteom Bioinf 15(3):177–186 [DOI] [PMC free article] [PubMed] [Google Scholar]

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[CR46] 46.Heck AM, Russo J, Wilusz J, Nishimura EO, Wilusz CJ (2020) YTHDF2 destabilizes m(6)A-modified neural-specific RNAs to restrain differentiation in induced pluripotent stem cells. RNA 26(6):739–755 [DOI] [PMC free article] [PubMed] [Google Scholar]

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[CR48] 48.Feng H, Yuan X, Wu S, Yuan Y, Cui L, Lin D, Peng X, Liu X, Wang F (2023) Effects of writers, erasers and readers within miRNA-related m6A modification in cancers. Cell Prolif 56(1):e13340 [DOI] [PMC free article] [PubMed] [Google Scholar]

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[CR50] 50.Ma JZ, Yang F, Zhou CC, Liu F, Yuan JH, Wang F, Wang TT, Xu QG, Zhou WP, Sun SH (2017) METTL14 suppresses the metastatic potential of hepatocellular carcinoma by modulating N(6) -methyladenosine-dependent primary MicroRNA processing. Hepatology 65(2):529–543 [DOI] [PubMed] [Google Scholar]

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[CR52] 52.Han J, Wang JZ, Yang X, Yu H, Zhou R, Lu HC, Yuan WB, Lu JC, Zhou ZJ, Lu Q et al (2019) METTL3 promote tumor proliferation of bladder cancer by accelerating pri-miR221/222 maturation in m6A-dependent manner. Mol Cancer 18(1):110 [DOI] [PMC free article] [PubMed] [Google Scholar]

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[CR54] 54.Yuan Y, Yan G, He M, Lei H, Li L, Wang Y, He X, Li G, Wang Q, Gao Y et al (2021) ALKBH5 suppresses tumor progression via an m(6)A-dependent epigenetic silencing of pre-miR-181b-1/YAP signaling axis in osteosarcoma. Cell Death Dis 12(1):60 [DOI] [PMC free article] [PubMed] [Google Scholar]

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[CR56] 56.Podkalicka P, Mucha O, Kazirod K, Szade K, Stepniewski J, Ivanishchuk L, Hirao H, Pospiech E, Jozkowicz A, Kupiec-Weglinski JW et al (2022) miR-378 affects metabolic disturbances in the mdx model of Duchenne muscular dystrophy. Sci Rep 12(1):3945 [DOI] [PMC free article] [PubMed] [Google Scholar]

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PERMALINK

Ythdf2 facilitates precursor miR-378/miR-378-5p maturation to support myogenic differentiation

Kaiping Deng

Yalong Su

Zhipeng Liu

Silu Hu

Caifang Ren

Wurilege Wei

Yixuan Fan

Yanli Zhang

Feng Wang

Abstract

Supplementary Information

Introduction

Materials and methods

Animal samples

Cell culture and myogenic differentiation

Plasmid construction, small interfering RNA (siRNA), miRNA mimics and inhibitor, and cell transfection

Immunofluorescence

RNA isolation and library preparation for RNA sequencing

mRNA sequencing (mRNA-seq) and data analysis

miRNA sequencing (miRNA-seq) and data analysis

Co-analysis of miR-seq and mRNA-seq

Quantitative real-time PCR (qRT-PCR) for gene expression

Western blotting analysis

m6A dot blot assay

Quantification of m6A modifications

SELECT qRT-PCR

RNA immunoprecipitation (RIP) combined with quantitative real-time PCR (RIP-qRT-PCR)

Protein–protein docking analysis

Co-immunoprecipitation (Co-IP) assay

Statistical analysis

Results

Ythdf2 influences miRNAs expression during myogenic differentiation

Fig. 1.

Fig. 2.

Identification of potential miRNAs involved in Ythdf2-mediated myogenesis

Fig. 3.

Ythdf2 regulates the expression of miR-378 and miR-378-5p in an m6A-dependent manner

Fig. 4.

Fig. 5.

Ythdf2 binds to DICER1 and TARBP2 and facilitates pre-miR-378/miR-378-5p processing

Fig. 6.

miR-378 and miR-378-5p are functionally important targets of Ythdf2 in myogenesis

Fig. 7.

Fig. 8.

Fig. 9.

Discussion

Fig. 10.

Supplementary Information

Acknowledgements

Authour contributions

Funding

Data availability

Declarations

Conflict of interest

Ethical approval

Consent to participate

Consent to publish

Footnotes

References

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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Links to NCBI Databases

m⁶A dot blot assay

Quantification of m⁶A modifications

Ythdf2 regulates the expression of miR-378 and miR-378-5p in an m⁶A-dependent manner