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. 2026 Feb 18;105(5):106670. doi: 10.1016/j.psj.2026.106670

The mechanism by which methylase METTL3 affects intramuscular fat deposition

Baojun Yu a,b, Keqiang Li a,c, Xianglong Li a, Juan Zhang b,⁎
PMCID: PMC12969675  PMID: 41780492

Abstract

N6-methyladenosine (m6A) is a critical epigenetic modification that regulates lipid metabolism; however, its role in adipogenesis in chickens remains unclear. Here, we demonstrated that the m6A methylase METTL3 shows significant differences at the key stage of chicken development, and its expression in the breast muscle is significantly higher than in other tissues. Furthermore, METTL3 expression gradually decreases during the differentiation of both intramuscular preadipocytes (IMPA) and abdominal preadipocytes (APA). Gain- and loss-of-function assays demonstrated that METTL3 overexpression significantly inhibited the proliferation and differentiation of IMPA and APA cells, whereas METTL3 knockdown exerted the opposite effect. Combined with m6A sequencing (m6A-seq), we identified significant enrichment of m6A modification within the 3′ untranslated region (3′UTR) of PCYT1A mRNA, indicating it as a direct modification target of METTL3. Mechanistically, METTL3 knockdown reduced m6A methylation of PCYT1A, consequently enhancing PCYT1A mRNA stability and expression. This upregulation of PCYT1A promoted adipogenic differentiation in both IMPA and APA. Our study elucidates the functional mechanism by which METTL3-mediated m6A modification regulates lipid deposition through modulating PCYT1A expression, thereby identifying novel molecular targets for investigating adipogenesis in chickens.

Keywords: Chicken, Adipogenesis, m6A modification, METTL3, PCYT1A

Introduction

Over the past few decades, demand for poultry meat has increased significantly due to population growth and rising per capita meat consumption. The global consumption of meat birds continues to rise each year, driven by intensive selection for growth rates through genetic breeding efforts, as well as improvements in nutrition and management practices that have led to substantial increases in chicken production (Korver, 2023). However, the enhanced growth rate, breast muscle size, and yield of broilers have adversely affected the quality of breast meat, thereby impacting the nutritional, functional, mechanical, and sensory qualities of meat products (Huang and Ahn, 2018). Meat quality encompasses appearance, texture, nutritional value, safety, and eating quality and represents the most important economic trait in chicken production (Mir et al., 2017). Intramuscular fat (IMF) plays a decisive role in the development of meat product sensory characteristics, and appropriate IMF deposition significantly improves juiciness, tenderness, and flavor (Ventanas et al., 2007, 2008). Therefore, studying the regulatory mechanism of chicken fat deposition can provide new insights for breeding broiler breeds with excellent meat quality.

IMF deposition is a highly coordinated process in pluripotent cells that involves the maturation of mesenchymal stem cells, the proliferation of preadipocytes, and the accumulation of lipid droplets within adipocytes (Ponsuksili et al., 2024). Studies have shown that besides transcriptional regulation by specific factors, the IMF deposition process also involves epigenetic modification in the adipocyte differentiation of various biological processes (Song et al., 2020). N6-methyladenosine (m6A) is the most characteristic methylation modification in eukaryotic RNA, representing a novel post-transcriptional gene regulatory mechanism (Frye et al., 2018; Roundtree et al., 2017; Yang et al., 2018). In regulating gene expression, m6A modification is involved in almost all RNA metabolic processes (Zhao et al., 2017), thereby playing an important role in biological activities such as tissue growth and development, cell differentiation, and lipid metabolism (Frye et al., 2018; Lee et al., 2019; Song et al., 2020). METTL3 is the most important m6A methylase, which mediates the expression of key cell factors in an m6A-dependent manner and thereby affects adipogenesis. Wang et al. (2015) demonstrated for the first time that overexpression of METTL3 increased mRNA m6A levels in porcine adipocytes, which in turn inhibited adipocyte differentiation. Furthermore, METTL3 reduces cyclin D1 expression in an m6A-dependent manner and inhibits adipogenesis by blocking cell-cycle progression in 3T3-L1 preadipocytes (Liu et al., 2019). Although it has been confirmed that METTL3 plays an important regulatory role in the process of adipogenesis, the molecular mechanism by which its dependent m6A methylation regulates the differentiation of preadipocytes in chickens has not been reported.

Here, we designed the study to determine the role of METTL3 in chicken adipogenesis. The expression of METTL3 is significantly different during the development of chicken breast muscle, and its expression is significantly down-regulated with the differentiation of intramuscular preadipocytes (IMPA) and abdominal preadipocytes (APA). Therefore, we investigated the regulatory effect of METTL3 on the proliferation and differentiation of preadipocytes in chickens. Taking the differentially methylated genes screened by m6A-seq as candidate targets (Yu et al., 2023), the functional gene PCYT1A mediated by m6A modification was determined through targeted regulation verification, and the effect of PCYT1A on the differentiation of preadipocytes was further explored. Our research has clarified the mechanism of m6A modification in adipogenesis, providing a theoretical basis for improving chicken quality and molecular breeding.

Materials and methods

Ethics statement

This study was approved by the Animal Welfare and Ethics Review Committee of Ningxia University (NXU-2024-067) and conducted according to the Guidelines for Animal Use of the Committee on the Ministry of Agriculture of China. All methods were carried out in accordance with relevant guidelines and regulations. This study was carried out in accordance with the ARRIVE guidelines.

Animal and tissue collection

The experimental animals were provided by the Jingyuan Chicken National Breeding Farm in Pengyang County, Ningxia, and the chickens were fed and watered freely under the same feeding and management conditions. According to the growth and development laws and meat quality characteristics of the Jingyuan chicken, five hens with uniform body weight were selected for slaughter at 42, 126, and 180 days of age, respectively. They stopped eating and drank freely 12 hours before slaughter. Each chicken's left breast muscle and other organ tissues were collected, cut into pieces, and packed into freezing tubes, quick-frozen in liquid nitrogen, and then transferred to −80°C for storage. The determination of fat content in breast muscle is conducted in accordance with the national standard “National Food Safety Standard: Determination of Fat in Food” (GB 5009.6-2016).

Quantification of m6A modifications

The m6A levels in total RNA of muscle tissues at different stages were analyzed using the m6A RNA Methylation Quantification Kit (Epigentek, USA). Briefly, 200 ng of high-purity RNA was added to the binding wells, and antibody incubation and m6A RNA capture were performed according to the instructions. The absorbance at 450 nm of the test samples and control wells was then measured using a multifunctional microplate reader, and the m6A content of total RNA was calculated based on the standard curve method.

RNA extraction and real-time quantitative PCR (RT-qPCR)

RNAiso Plus reagent (Takara, Dalian, China) was used to extract the total RNA from the tissues or cells. RNA was reverse transcribed to cDNA following the instructions of the PrimeScript RT Reagent Kit (Perfect Real Time) (Takara, Dalian, China). The mRNA primers (Table 1) were designed using NCBI's Primer-BLAST, and quantitative PCR was performed on a real-time PCR detection system according to the instruction guide of UltraSYBR Mixture (CWBIO, Taizhou, China). The relative expression levels of the target genes were calculated by the 2-△△Ct method using chicken β-actin as an internal reference.

Table 1.

Sequence information.

Name Forward sequence (5′ → 3′) Reverse sequence (5′ → 3′) Product length/bp
METTL3 AAATCCCGTAAGCAGGCGTC CTCCACGATGGATTGCTCCT 150
METTL14 TTCCTATGGTGTGGTTCAG CAGTGCTCCTTGGTTCTT 170
FTO GACCTCTACTTGATGCTTGA TGAACAATCTGCCACTCTG 105
ALKBH5 CGCTCAGTCCTCTTACCA CATCCTCCTCCTCCTCATC 109
CDK1 TGCAAGGCTGTACCTCATT ACTCTTAACACGCGAACGA 103
PCNA GACTCCTCGCACGTCTCCCT TCCGCATTGTCTTCTGCTCTG 170
Cyclin D1 CAGAAGTGCGAAGAGGAAGT GATGGAGTTGTCGGTGTAAAT 186
Cyclin E GGTTGTTGGCATCAGTAAAG TATTACCTCATCTTCCTCGTTG 214
PPARγ ATACTCTCCTGGCTTCTCT GGTCACTGTCATCTAATTCC 171
C/EBPα TTCTACGAGGTCGATTCCCG AGCCTCTCTGTAGCCGTAG 96
C/EBPβ TATTACGAGGCGGACTGTT GCTGAAGTCAATGGCTCTC 114
FABP4 AGGAAGATGGCTGGTGTG TCTGCTGTGGTCTCATCAA 140
FASN GCATTAGCCAAGGTCATTC CAAGGAGCCATCGTGTAA 105
LPL TTGGTGACCTGCTTATGC ATTGCTGCCTCTTCTCCT 187
EHHADH AGTGGAGAAGTGGACAACA ACCAGAGAAGTCACAATGC 120
FADS2 GCCAAGTATGGAGTGCATTACG GTGACCTGTTCCCTCCCCAT 146
STEAP3 GCAGGCTATGGAGAAGAAG GATGGAAGTGAGGTGATGG 126
CCNE1 TGCCACAATATCCACAACA TTCCTCTATCTCACACCATTC 179
EGF GCGGAAGCGATAAGAGAT CACATATTGCGAAGGACAG 177
PCYT1A CTCTTCCCAAACACATACCT TTCTCACCACTTCATCTACG 139
β-actin CAGCCATCTTTCTTGGGTAT CTGTGATCTCCTTCTGCATCC 169
PCYT1A-3′ UTR TGTTTCGGATGGTGGCTTGT GCAAGGAGGAAGCAGGGATT 154
si-METTL3 GAUUGCUCCUUCCUCAACATT UGUUGAGGAAGGAGCAAUCTT
si-PCYT1A GCUGAUGGAAUAUUUGACUTT AGUCAAAUAUUCCAUCAGCTT
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Primary preadipocyte culture and induced differentiation

Primary preadipocytes were isolated from breast muscle and abdominal adipose tissue of two-week-old Jingyuan chickens using the method described by Zhang et al. (2019). Briefly, breast muscle and abdominal adipose tissues were collected under aseptic conditions, clipped, and then added to 5 times the volume of type I collagenase digest (1 mg/mL, Solarbio, Beijing, China) and digested at 37°C for 90 min. The digests were filtered through 200- and 400-mesh cell sieves and centrifuged at 1000 rpm for 10 min. Then the cell precipitates were resuspended with Dulbecco's modified Eagle's medium (DMEM)/F12 (BI, Jerusalem, Israel) complete medium containing 10% fetal bovine serum (FBS) (CellMax, Beijing, China) and 1% penicillin/streptomycin (Solarbio, Beijing, China), inoculated into culture flasks and cultured in an incubator at 37°C and 5% CO₂. After 2 h, the base medium was replaced with a fresh pre-warmed medium.

Intramuscular preadipocytes (IMPA) and abdominal preadipocytes (APA) were inoculated in 6-well plate cultures; the basal medium was discarded when the cells reached 80% confluence, and the complete medium supplemented with 160 μM oleate (Solarbio, Beijing, China) was added to induce cellular differentiation (Zhang et al., 2021). The cells were collected on days 0, 2, 4, 6, and 8 of the induced differentiation.

Plasmid and siRNA transfection

The sequence of the CDS region of chicken METTL3 (XM_040655036) was obtained from the GenBank database, and the overexpression plasmid (OE-METTL3) was constructed by NheI/HindIII cloning into the pcDNA3.1(+) vector. Meanwhile, the alanine in the functionally active region of METTL3 methylation was mutated to aspartic acid (DPPW→APPA) according to the literature (Lin et al., 2016; Wang et al., 2016; Wu et al., 2019) and cloned into the pcDNA3.1(+) vector to construct a METTL3 mutant plasmid (METTL3-MUT), and the unmutated recombinant plasmid was identical to OE-METTL3 (METTL3-WT). In addition, the mRNA sequence of chicken PCYT1A (XM_040678634) was obtained from GenBank, and its CDS region was cloned into the pcDNA3.1(+) vector to construct an overexpression plasmid of PCYT1A (OE-PCYT1A). The siRNAs of METTL3 and PCYT1A were designed and synthesized by Shanghai GenePharma. si-METTL3 and si-PCYT1A sequence information is shown in Table 1. Plasmids and siRNAs were transfected into cells using Advanced DNA RNA transfection reagent (ZETA LIFE, USA) according to the manufacturer’s instructions.

Western blot (WB)

Treated cells were taken out, washed 2-3 times with PBS, and proteins were extracted by adding RIPA lysate (Thermo Fisher Scientific) containing a mixture of 1% protease and phosphatase inhibitor, followed by detection of protein sample concentration using the BCA assay. To each protein sample of uniform concentration, 1/4 volume of 5 × loading buffer was added for heat denaturation, and the denatured proteins were added to SDS-PAGE gels for electrophoretic separation and transferred to PVDF membranes using the wet transfer method. Closure was performed at the end of membrane transfer, washed three times with TBST, and incubated overnight at 4°C with the addition of the target primary antibody. The following day, the corresponding secondary antibodies were added after three washes with TBST, and the mixture was incubated for 1 hour at room temperature on a shaker. The protein bands were then exposed to a Tanon system using an ECL luminescent solution (LABLEAD, Beijing, China) and analyzed in grayscale with ImageJ. Antibody information was shown as follows: METTL3 (Proteintech, 15073-1-AP, 1:1000), PCYT1A (Affinity, DF7927, 1:2000), and GAPDH (Abways, AB0037, 1:10000).

Cell counting kit 8 (CCK-8) assay

Cell proliferation was assessed using CCK-8 reagent (LABLEAD, Beijing, China). Cells were inoculated into 96-well plates and transfected with an overexpression plasmid and siRNA when the cells reached the appropriate density. At 12, 24, 36, and 48 h after transfection, 10 μL of CCK-8 reagent was added to each well. After incubation for 2 hours, the absorbance of each well at 450 nm was measured using a microplate reader (Shanghai Flash, SuPerMax 3100).

5-Ethynyl-2′-deoxyuridine (EdU) assay

Edu staining was performed on the cells according to the instructions of the Cell-Light Edu Apollo567 in vitro test kit (RiboBio, Guangzhou, China). In short, take out the 12-well plate cells transfected with overexpression plasmids and siRNA, add freshly prepared 50 μM EdU medium, incubate in the incubator for 2 hours, wash twice with PBS, then fix with 4% paraformaldehyde for 30 minutes. After that, neutralize the excess aldehyde groups with a 2 mg/mL glycine solution. The permeability of the cell membrane was enhanced by incubation with 0.5% Triton X-100. Apollo staining solution was added and incubated in the dark for 30 minutes. After permeation treatment with 0.5% Triton X-100, Hoechst 33342 was added for DNA staining. After cleaning with PBS, observe and take photos under a fluorescence microscope. Finally, the images were captured and analyzed using ImageJ software (National Institutes of Health).

Oil Red O and BODIPY staining

Cells were inoculated into 6-well plates and transfected with an overexpression plasmid and siRNA when the cells reached 80% confluence. Lipid droplet deposition was induced by adding differentiation medium 48 h after transfection. Lipid droplets were detected after 6 days of differentiation using the Oil Red O Stain Kit (Solarbio, Beijing, China) and BODIPY dye (Invitrogen, CA, USA). Briefly, cells were washed twice with PBS and incubated in the cell fixative for 30 min. Then, the lipid droplets were stained with Oil Red O or BODIPY. After cleaning with PBS, the nuclei were stained with DAPI solution (G-CLONE, Beijing, China), observed under a microscope, and photographed. All of the experiments were performed according to the manufacturer’s recommended protocol.

m6A real-time quantitative PCR

Cellular RNA (DNase-treated) was extracted using Total RNA Kit I (Omega), and 10 μg of RNA was used as input material. RNA enriched for m6A modifications was captured as directed by the instructions of the m6A RNA Methylation Fragment Enrichment Kit (Epigentek, USA). The methylation site of PCYT1A was identified based on its chromosomal location from previous m6A sequencing results (accession number PRJNA898123). This site was then compared with the predicted sites generated by SRAMP software (https://www.cuilab.cn/sramp) to ensure the reliability of the identified m6A modification site (Fig. S1). Subsequently, specific primers for PCYT1A were designed according to this site (Table 1). The m6A-enriched RNA and input samples were then reverse-transcribed into cDNA for qPCR. The relative m6A levels of PCYT1A were calculated with reference to the 2-△△Ct method.

mRNA stability analysis

Cells were inoculated into 12-well culture plates and were transfected with si-METTL3 when their density reached 80%. After 48 h of transfection, a cell culture medium with a final concentration of 5 μg/mL actinomycin D (ActD) was added to each well of cells, and the cells were collected at 0, 2, 4, and 6 h to extract RNA, which was reverse-transcribed to cDNA and then assayed by qPCR. The stability of mRNA was analyzed according to Ratnadiwakara et al. (Ratnadiwakara and Änkö, 2018).

Statistical analysis

Data were analyzed and plotted using the GraphPad Prism software (version 8.0.2). Final data results are expressed as mean ± standard error of the mean (SEM). An unpaired two-tailed Student's t-test was used to compare the two groups. The three groups were compared using a one-way analysis of variance (ANOVA) and Tukey's multiple comparison test. The correlation between the two indicators was analyzed using Pearson’s test. P < 0.05 is considered the standard for significance (*, **, and *** represent P < 0.05, P < 0.01, and P < 0.001, respectively).

Results

METTL3 negatively regulates IMF deposition

The differences in IMF deposition in breast muscle across three developmental stages were assessed using the Soxhlet extraction method. Results revealed a significant increase in IMF content with the growth age of Jingyuan chickens (Fig. 1A). Colorimetric assay results indicate that m6A levels exhibit an overall downward trend during breast muscle development. Compared with the 42-day-old group, m6A levels in 180-day-old breast muscle were significantly reduced (Fig. 1B). The expression changes of m6A methylase during breast muscle development in Jingyuan chickens were detected using qPCR. Compared with the 42-day age group, METTL3 expression in breast muscle decreased significantly at 126 days and increased significantly at 180 days. However, no apparent differences were observed in the expression of the m6A methyltransferase METTL14 and the demethylation enzymes FTO and ALKBH5 at different stages of breast muscle development (Fig. 1C). Further analysis of METTL3 tissue expression profiles across the three stages revealed that METTL3 expression was highest in breast muscle and was significantly higher than in other tissues (Fig. 1D). These results suggest that METTL3-mediated m6A methylation may regulate IMF deposition during chicken development.

Fig. 1.

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Analysis of m6A methylase expression levels in chicken tissue. (A) The IMF content in the breast muscle at 42 (42 D), 126 (126 D), and 180 (180 D) days of age (n = 5). (B) m6A levels in breast muscle across three developmental stages (n = 5). (C) The expression levels of methyltransferase and demethylase in the breast muscle across three developmental stages (n = 5). (D) Tissue expression profiles of METTL3 in three developmental stages (n = 3). Different capital letters indicate extremely significant differences between groups (P < 0.01).

Effect of METTL3 on the proliferation of chicken preadipocytes

In this study, we constructed an overexpression plasmid for METTL3 and transfected IMPA cells to confirm its normal expression (Fig. 2A, B). Meanwhile, overexpression of METTL3 in APA cells also achieved significant effects (Fig. S2A, B). Next, we assessed the impact of METTL3 overexpression on preadipocyte proliferation. The results showed that METTL3 overexpression inhibited the mRNA expression of proliferation-related genes, and the proliferation activity and number of positive cells in IMPA cells were significantly reduced (Fig. 2C-E). In APA cells, compared with the control group, transfection with OE-METTL3 significantly inhibited the expression of proliferation-related genes and cell proliferation capacity (Fig. S2C-E).

Fig. 2.

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Overexpression of METTL3 inhibits IMPA cell proliferation. (A) RT-qPCR and (B) western blot detection of METTL3 overexpression efficiency in IMPA cells (n = 3). (C) Overexpression of METTL3 inhibits mRNA expression of proliferation-related genes (n = 3). (D) CCK-8 and (E) EdU assays were used to detect the proliferation activity of IMPA cells after METTL3 overexpression (scale bar: 100 μm).

To better elucidate the functional role of METTL3 in preadipocytes, this study knocked down METTL3 expression in cells using siRNA. RT-qPCR results showed that the interference efficiency of si-METTL3 in IMPA and APA cells reached a significant level compared to the control group (Figs. 3A, S3A). After interfering with the expression of METTL3 in IMPA and APA cells, the mRNA expression of CDK1, PCNA, and Cyclin D1 was significantly increased (Figs. 3B, S3B). CCK-8 and EdU staining showed that preadipocytes that were METTL3-interfered with gained greater proliferative vigor (Figs. 3C, D, S3C, D). Together, these results indicate that METTL3 can inhibit the proliferation of chicken preadipocytes.

Fig. 3.

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Interference with METTL3 promotes IMPA cell proliferation. (A) Interference efficiency of METTL3 in IMPA cells (n = 3). (B) Interference with METTL3 promotes the expression of proliferation-related genes (n = 3). (C) CCK-8 and (D) EdU assays to detect the proliferation activity of IMPA cells after METTL3 interference (scale bar: 100 μm).

METTL3 regulates the adipogenesis of chicken preadipocytes in vitro

Further investigation of the effects of METTL3 on the differentiation of IMPA and APA cells was conducted by transfecting OE-METTL3. After transfecting IMPA cells, induced differentiation was performed. RT-qPCR results showed that PPARγ, C/EBPβ, FABP4, FASN, and LPL expression levels were significantly reduced after transfecting OE-METTL3 (Fig. 4A). Oil Red O staining results showed that the number of Oil Red spots in the OE-METTL3 group was significantly lower than that in the control group, and the fluorescent signal of cells after BODIPY staining was significantly reduced (Fig. 4B-D). Similarly, in APA cells overexpressing METTL3, compared with the control group, mRNA expression of PPARγ, C/EBPα, FABP4, and LPL was significantly downregulated, and lipid droplet accumulation was significantly inhibited (Fig. S4).

Fig. 4.

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METTL3 inhibits adipogenesis in IMPA cells. (A) mRNA expression of adipogenesis-related genes after overexpression and interference of METTL3 (n = 3). (B) Oil red O and (C) BODIPY staining results of IMPA cells after overexpression and interference of METTL3 (scale bar: 100 μm). (D) Quantitative results of Oil Red O and BODIPY staining.

At the same time, this study further verified that METTL3 interference impairs IMPA and APA cell differentiation. RT-qPCR results showed that METTL3 inhibition significantly upregulated mRNA expression of PPARγ, C/EBPα, C/EBPβ, FABP4, FASN, and LPL. After induction differentiation, Oil Red O and BODIPY staining were performed. Compared with the control group, the si-METTL3 group showed more pronounced Oil Red spots and fluorescent signals, with greater accumulation of lipid droplets (Figs. 4, S4). In summary, these results indicate that METTL3 can inhibit the adipogenic differentiation of chicken preadipocytes.

METTL3-mediated m6A modification gene screening

To identify key target genes regulated by METTL3-mediated m6A modification in adipogenesis, this study focused on analyzing candidate methylated genes FADS2, EHHADH, STEAP3, CCNE1, PCYT1A, and EGF, selected in previous studies. After overexpression of METTL3 in IMPA and APA cells, it was found that the mRNA expression of FADS2 and PCYT1A was significantly suppressed, with the effect on PCYT1A being more pronounced (Fig. 5A, B). RT-qPCR validated PCYT1A expression levels in breast muscles of 42-, 126-, and 180-day-old Jingyuan chickens, and the trends were consistent with the sequencing data (Fig. 5C). m6A-seq results showed that m6A modification was significantly enriched in the 3′UTR region of PCYT1A mRNA. Specific primers were designed based on the m6A peak sequence for m6A-qPCR validation, and the results showed that the m6A modification level in the PCYT1A 3′ UTR was consistent with the m6A-seq analysis (Fig. 5D).

Fig. 5.

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Screening of m6A modification genes regulated by METTL3. mRNA expression of m6A-modified genes after overexpression of METTL3 in (A) IMPA and (B) APA cells (n = 3). (C) mRNA expression of PCYT1A in the breast muscle at three developmental stages (n = 5). (D) m6A-qPCR detection of m6A modification levels of PCYT1A-3′ UTR in the breast muscle at three developmental stages (n = 5).

The functional relationship between METTL3 and PCYT1A was validated using an oleate-induced in vitro cellular model. The expression of METTL3 showed an overall decreasing trend during the IMPA and APA cell differentiation, which remained stable after a significant decrease on day 4 (Fig. 6A). PCYT1A expression significantly increased during IMPA cell differentiation, peaking on day 6. On day 2 of APA cell differentiation, the expression of PCYT1A significantly increased. Although expression decreased on day 4 of differentiation, the overall expression level remained higher than that in undifferentiated cells (Fig. 6B). Correlation analysis indicates that METTL3 negatively regulates PCYT1A expression during the differentiation of IMPA and APA cells (Fig. 6C). Therefore, we speculated that PCYT1A may be a candidate target gene of METTL3 for regulating adipogenesis through m6A methylation.

Fig. 6.

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Expression of METTL3 and PCYT1A during cell differentiation. (A) Changes in METTL3 expression in IMPA and APA cells at 0, 2, 4, 6, and 8 days of differentiation (n = 3). Different capital letters indicate extremely significant differences between groups (P < 0.01), and different lowercase letters indicate significant differences between groups (P < 0.05). (B) Changes in PCYT1A expression in IMPA and APA cells at 0, 2, 4, 6, and 8 days of differentiation (n = 3). (C) Correlation analysis between METTL3 and PCYT1A during IMPA and APA cell differentiation.

METTL3 regulates PCYT1A expression through m6A methylation

To confirm that METTL3 regulates PCYT1A expression through its methyltransferase activity, this study mutated the catalytic active site of METTL3, constructing an expression plasmid with lost methylation activity (METTL3-MUT). RT-qPCR and WB results showed that transfecting METTL3-WT and METTL3-MUT into IMPA and APA cells significantly enhanced METTL3 expression (Fig. 7A, C). Further analysis revealed that both mRNA and protein expression of PCYT1A were significantly downregulated in preadipocytes transfected with METTL3-WT, while transfection with METTL3-MUT had no obvious effect on PCYT1A expression (Fig. 7B, C). These results indicate that METTL3 regulates PCYT1A expression in preadipocytes in an m6A methylation-dependent manner.

Fig. 7.

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METTL3 affects the mRNA stability and expression of PCYT1A by regulating its m6A modification. (A) Expression efficiency of METTL3-WT and METTL3-MUT in IMPA and APA cells (n = 3). (B) RT-qPCR detection of the effect of METTL3-WT and METTL3-MUT on PCYT1A mRNA expression (n = 3). (C) WB detection of METTL3 overexpression and interference effect on PCYT1A protein expression in IMPA cells (n = 3). (D) RT-qPCR detection of the regulatory role of METTL3 interference on PCYT1A mRNA expression (n = 3). (E) m6A-qPCR detection of the effect of METTL3 interference on PCYT1A m6A modification levels (n = 3). (F) Half-life analysis of PCYT1A mRNA in IMPA and APA cells after METTL3 interference (n = 3).

At the same time, siRNA was used to validate the regulatory role of METTL3 on PCYT1A. RT-qPCR and WB results showed that interference with METTL3 in IMPA and APA cells significantly enhanced PCYT1A expression (Fig. 7D). m6A-qPCR results showed that interference with METTL3 significantly reduced the m6A level of PCYT1A-3′UTR (Fig. 7E). Interference with METTL3 and ActD treatment was performed in IMPA and APA cells. Compared with the control group, transfection of si-METTL3 prolonged the half-life of PCYT1A mRNA (Fig. 7F), suggesting that interference with METTL3 can enhance the stability of PCYT1A. Following METTL3 knockdown in IMPA cells, co-transfection with PCYT1A revealed that PCYT1A deficiency counteracts the effects of METTL3, while PCYT1A overexpression promotes its exponential expression (Fig. S5). In conclusion, in IMPA and APA cells, METTL3 affects PCYT1A mRNA stability by regulating m6A modification of PCYT1A, thereby negatively regulating PCYT1A expression.

PCYT1A promotes lipid accumulation in chicken preadipocytes

Next, we investigated the effect of PCYT1A on the differentiation of chicken preadipocytes. RT-qPCR results showed that overexpression of PCYT1A significantly upregulated the mRNA expression of PPARγ, C/EBPα, and C/EBPβ, while knockdown of PCYT1A significantly downregulated the expression of PPARγ, C/EBPα, and LPL (Fig. 8A). Lipid droplet content in IMPA cells was visualized using Oil Red O and BODIPY staining. The results indicated that overexpression of PCYT1A led to increased lipid droplet formation in IMPA cells after differentiation induction. In contrast, knockdown of PCYT1A resulted in significantly fewer lipid droplets than in the control group (Fig. 8B-D).

Fig. 8.

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PCYT1A promotes lipid accumulation in IMPA cells. (A) The regulatory role of PCYT1A overexpression and interference on adipogenesis-related genes (n = 3). (B) Oil red O and (C) BODIPY staining detect the effect of PCYT1A on fat droplet deposition in IMPA cells (n = 3). (D) Quantitative results of Oil Red O and BODIPY staining.

OE-PCYT1A and si-PCYT1A were transfected into APA cells further to validate the effect of PCYT1A on preadipocyte differentiation. RT-qPCR results showed that, compared with the control group, overexpression of PCYT1A significantly promoted the expression of PPARγ, C/EBPα, FASN, and LPL, while knockdown of PCYT1A inhibited the expression of adipogenesis-related genes to varying degrees (Fig. S6A). Oil Red O and BODIPY staining of induced APA cells showed that lipid droplet formation was significantly enhanced in the OE-PCYT1A group compared to the control group. In contrast, lipid droplet formation was reduced in the si-PCYT1A group (Fig. S6B, C). These results sufficiently confirm that PCYT1A positively regulates adipogenic differentiation in chicken preadipocytes.

Discussion

m6A modification participates in various biological activities, such as RNA processing and metabolism in eukaryotes. Its dynamic, reversible mode of action affects gene expression and cell fate by regulating multiple RNA-related signaling pathways. METTL3, the most important functional enzyme that catalyzes m6A methylation, plays an important role in tissue development, cell differentiation, and lipid metabolism (Song et al., 2020; Wu and Wang, 2021; Yu et al., 2022). This study examined the expression of m6A methyltransferases (METTL3, METTL14) and demethylases (FTO, ALKBH5) in breast muscle tissue at three developmental stages and found that only METTL3 showed significant differences, with its expression level in breast muscle significantly higher than in other tissues. Based on this, we explored the relationship between METTL3 and fat deposition and found that METTL3 expression significantly decreased during the differentiation of chicken IMPA and APA cells. These results suggest that METTL3-mediated m6A methylation modification may play an important role in adipogenesis in chicken meat.

Therefore, the present study confirmed that METTL3 could inhibit the proliferation of IMPA and APA cells using gain and loss-of-function assays. Consistent with this finding, the demethylase FTO can promote the proliferation of chicken preadipocytes (Li et al., 2022). Previous multiple studies have shown similar results to this study, namely that METTL3 can inhibit the proliferation of various cell types, such as bovine myoblasts (Yang et al., 2022), mouse C2C12 cells (Ru et al., 2025), mouse cardiomyocytes (Jiang et al., 2022), and human endometrial stromal cells (Zhang, 2022). Interestingly, the results of the present study also differ from some other reports, such as that METTL3 can promote cell proliferation in quail myoblasts (Liu et al., 2023), mouse myoblasts (Zhao et al., 2022), mouse cardiac fibroblasts (Zhou et al., 2022a), and human bladder cancer cells (Han et al., 2019). This difference suggests that METTL3 can either inhibit or promote cell proliferation, depending on the cell type and environment. This further demonstrates that METTL3 plays a refined and complex role in regulating cell development, as it regulates the fate of target mRNAs in specific signaling pathways either independently or in an m6A-dependent manner, while potentially being subject to multifaceted regulation by other transcriptional elements. The specific regulatory mechanisms involved remain to be further explored.

Studies have shown that METTL3 can promote m6A methylation of mRNA, and its mediated m6A modification inhibits adipogenesis, in contrast to FTO (Wang et al., 2015). Yao et al. (2019) found that METTL3 plays an important role in the differentiation and adipogenesis of porcine bone marrow stem cells (BMSC). Overexpression of METTL3 can increase the level of m6A modification and inhibit the differentiation of BMSC into adipocytes. Interfering with METTL3 can reduce m6A levels and promote adipogenic differentiation of BMSC. Liu et al. (2019) found that METTL3 is regulated by the transcription factor zinc finger protein 217, which suppresses METTL3 expression, thereby reducing cellular m6A modification levels and promoting adipogenic differentiation of preadipocytes. The same results were observed in Rex rabbit adipocytes, where METTL3 knockdown promoted preadipocyte differentiation (Luo et al., 2022). Corticosterone treatment significantly increased abdominal fat deposition and FASN protein expression in chickens while reducing the protein abundance of PPARα and METTL3. Knocking down METTL3 reduced the m6A level of PPARα mRNA and overall protein expression, indicating that m6A-mediated translation inhibition of PPARα contributes to corticosterone-induced visceral fat deposition in chickens (Zhou et al., 2022b). IMF deposition is a complex biological process, and the transition from preadipocytes to adipocytes is the key to fat deposition. The results of this study also highlighted the important role of METTL3 in regulating preadipocyte differentiation. Overexpression of METTL3 inhibited the expression of adipogenesis-related genes and lipid droplet formation ability in preadipocytes. In contrast, METTL3 knockdown promoted lipid droplet accumulation in cells. However, other reports have shown that METTL3-mediated m6A methylation destabilizes mRNA expression of metabolism-related genes, leading to metabolic disorders and lipid accumulation in the liver (Li et al., 2020). Similarly, in cardiomyocytes, METTL3 deficiency can reduce RNA m6A methylation and cardiac lipid deposition (Xu et al., 2022). Therefore, we speculate that METTL3-mediated regulation of m6A modification on lipid metabolism is species- and cell-specific.

Typically, METTL3-mediated m6A modification is important in guiding methylation at specific target sites. To identify target genes regulated by m6A modification during IMF deposition, this study focused on analyzing candidate differentially methylated genes previously identified (Yu et al., 2023). Preliminary validation of the m6A modification of PCYT1A mRNA potentially regulated by METTL3 was performed using RT-qPCR and m6A-qPCR. METTL3 is highly conserved across evolution and contains a SAM-binding domain and a methyltransferase domain that catalyzes m6A methylation (Wang et al., 2016). Therefore, we mutated the catalytic active site of METTL3 to verify whether its regulatory role on PCYT1A depends on m6A catalytic activity. Transfection of wild-type METTL3 plasmids into IMPA cells significantly suppressed PCYT1A expression levels, while m6A catalytic activity mutations had no significant effect on PCYT1A expression. Interference with METTL3 in IMPA and APA cells inhibited m6A modification levels in the PCYT1A-3′UTR and prolonged the half-life of PCYT1A mRNA, thereby enhancing PCYT1A stability and expression. These results indicate that METTL3 regulates PCYT1A stability in an m6A-dependent manner, thereby inhibiting PCYT1A expression in preadipocytes.

The surface monolayer of intracellular lipid droplets comprises phospholipids, of which phosphatidylcholine is the major functional component that stabilizes the neutral lipid core of triglycerides (Lee and Ridgway, 2018). Phosphate cytidylyltransferase 1, choline, alpha (PCYT1A) is a key rate-limiting enzyme regulating phosphatidylcholine synthesis (Andrejeva et al., 2019). During the differentiation of 3T3-L1 and human preadipocytes, mRNA and protein levels of PCYT1A increase, and PCYT1A silencing inhibits phosphatidylcholine synthesis, thereby reducing the number of lipid droplets in cells (Aitchison et al., 2015). In oleic acid-stimulated Drosophila S2 cells, PCYT1A homologs were exported from the nucleus to the lipid droplet surface. Among them, the increase in CDP-choline synthesis drove phosphatidylcholine production, thereby promoting the biogenesis and expansion of the lipid droplet monolayer (Guo et al., 2008; Krahmer et al., 2011). The expression levels of lipid droplet marker proteins PLIN2 and PLIN3 were significantly decreased in PCYT1A knockout mice. Combined with in vitro cell experiments, PCYT1A knockdown inhibited the formation of intracellular lipid droplets (Wang et al., 2024). Through in vitro cell function verification, this study found that PCYT1A overexpression significantly upregulated mRNA expression of adipogenesis-related genes in preadipocytes, and oleic acid induction led to increased lipid droplet formation. Deletion of PCYT1A yielded the opposite result. In summary, the present study confirmed that METTL3 plays an important role in adipogenic differentiation of chicken preadipocytes by regulating m6A modification of PCYT1A and altering its mRNA stability and expression.

This study focuses on the regulation of METTL3 on IMF deposition. As a core methyltransferase, METTL3 may coordinate adipogenesis by regulating multiple target genes. In the future, integrating multi-omics technologies, such as transcriptomics and epitranscriptomics, will enable systematic screening of the METTL3 target gene network and further explore whether the m6A reading protein is involved in the regulation of PCYT1A mRNA stability. Moreover, the specific role of PCYT1A in phospholipid metabolism and its regulatory circuit with key adipogenic transcription factors requires in-depth analysis at the metabolic level. This study provides new molecular insights into the role of METTL3-mediated m6A modification in chicken fat deposition. However, it is essential to further elucidate its global role in the regulatory network of lipid metabolism through multi-modeling, multi-omics, and multi-level follow-up studies, thereby providing a more robust theoretical foundation for the genetic improvement of chicken meat quality.

Conclusions

In conclusion, our results reveal the functional mechanism of m6A methylation in regulating lipid metabolism in chicken meat, and METTL3 can inhibit the proliferation and differentiation of chicken preadipocytes in vitro. In addition, we found that METTL3 regulates the stability and expression of PCYT1A mRNA via m6A methylation, thereby affecting adipogenesis in chicken meat. These findings highlight the important role of m6A modification-mediated gene expression regulation in preadipocyte differentiation and provide new insights for further studies on chicken adipogenesis.

CRediT authorship contribution statement

Baojun Yu: Writing – review & editing, Writing – original draft, Visualization, Software, Methodology, Formal analysis, Data curation. Keqiang Li: Software, Methodology, Formal analysis. Xianglong Li: Supervision, Formal analysis, Conceptualization. Juan Zhang: Supervision, Resources, Funding acquisition.

Disclosures

The authors declare no conflict of interest.

Acknowledgments

This study was supported by the Key R&D Program of the Ningxia Hui Autonomous Region (2022BBF02034), Hebei Provincial Chicken Modern Breeding Science and Technology Innovation Team (21326303D), and the doctoral research start-up project of Hebei Normal University of Science and Technology (2025YB014).

Footnotes

Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.psj.2026.106670.

Contributor Information

Baojun Yu, Email: yubaojunb@163.com.

Juan Zhang, Email: nxu9975@163.com.

Appendix. Supplementary materials

Supplementary Fig. S1. Visualized peak plots of m6A methylation in the 3′UTR region of PCYT1A mRNA.

mmc1.jpg (817.4KB, jpg)

Supplementary Fig. S2. Overexpression of METTL3 inhibits the proliferation of APA cells. (A) RT-qPCR and (B) western blot were used to detect the overexpression efficiency of METTL3 in APA cells (n = 3). (C) Overexpression of METTL3 inhibits the mRNA expression of proliferation-related genes (n = 3). (D) CCK-8 and (E) EdU assays were used to detect the proliferation activity of APA cells after overexpression of METTL3 (scale: 100 μm).

mmc2.jpg (1.3MB, jpg)

Supplementary Fig. S3. Interference with METTL3 promotes the proliferation of APA cells. (A) Interference efficiency of METTL3 in APA cells (n = 3). (B) METTL3 interference promotes the expression of proliferation-related genes (n = 3). (C) CCK-8 and (D) EdU assays detect the proliferation activity of APA cells after the interference of METTL3 (scale bar: 100 μm).

mmc3.jpg (1MB, jpg)

Supplementary Fig. S4. METTL3 inhibits adipogenesis in APA cells. (A) mRNA expression of adipogenesis-related genes after overexpression and interference of METTL3 (n = 3). (B) Oil red O and (C) BODIPY staining results of APA cells after overexpression and interference of METTL3 (scale bar: 100 μm). (D) Quantitative results of Oil Red O and BODIPY staining.

mmc4.jpg (3.9MB, jpg)

Supplementary Fig. S5. Co-transfection of METTL3 and PCYT1A was used to detect PCYT1A expression.

mmc5.jpg (274.9KB, jpg)

Supplementary Fig. S6. PCYT1A promotes fat droplet accumulation in APA cells. (A) The regulatory effect of PCYT1A overexpression and interference on adipogenesis-related genes (n = 3). (B) Oil red O and (C) BODIPY staining detection of the effect of PCYT1A on lipid droplet deposition in APA cells (n = 3). (D) Quantitative results of Oil Red O and BODIPY staining.

mmc6.jpg (4MB, jpg)

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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 Fig. S1. Visualized peak plots of m6A methylation in the 3′UTR region of PCYT1A mRNA.

mmc1.jpg (817.4KB, jpg)

Supplementary Fig. S2. Overexpression of METTL3 inhibits the proliferation of APA cells. (A) RT-qPCR and (B) western blot were used to detect the overexpression efficiency of METTL3 in APA cells (n = 3). (C) Overexpression of METTL3 inhibits the mRNA expression of proliferation-related genes (n = 3). (D) CCK-8 and (E) EdU assays were used to detect the proliferation activity of APA cells after overexpression of METTL3 (scale: 100 μm).

mmc2.jpg (1.3MB, jpg)

Supplementary Fig. S3. Interference with METTL3 promotes the proliferation of APA cells. (A) Interference efficiency of METTL3 in APA cells (n = 3). (B) METTL3 interference promotes the expression of proliferation-related genes (n = 3). (C) CCK-8 and (D) EdU assays detect the proliferation activity of APA cells after the interference of METTL3 (scale bar: 100 μm).

mmc3.jpg (1MB, jpg)

Supplementary Fig. S4. METTL3 inhibits adipogenesis in APA cells. (A) mRNA expression of adipogenesis-related genes after overexpression and interference of METTL3 (n = 3). (B) Oil red O and (C) BODIPY staining results of APA cells after overexpression and interference of METTL3 (scale bar: 100 μm). (D) Quantitative results of Oil Red O and BODIPY staining.

mmc4.jpg (3.9MB, jpg)

Supplementary Fig. S5. Co-transfection of METTL3 and PCYT1A was used to detect PCYT1A expression.

mmc5.jpg (274.9KB, jpg)

Supplementary Fig. S6. PCYT1A promotes fat droplet accumulation in APA cells. (A) The regulatory effect of PCYT1A overexpression and interference on adipogenesis-related genes (n = 3). (B) Oil red O and (C) BODIPY staining detection of the effect of PCYT1A on lipid droplet deposition in APA cells (n = 3). (D) Quantitative results of Oil Red O and BODIPY staining.

mmc6.jpg (4MB, jpg)

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