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. 2026 Aug 24;57(5):e70191. doi: 10.1002/age.70191

Transcriptome and Functional Analysis Uncover the Role of ADCY5 in Bovine Adipogenesis

Xuefeng Wei 1,✉, Xinyue Shan 1, Lize Yang 1, Xue Zhao 1, Yun Ma 2, Pengpeng Zhang 1, Yongjie Xu 1, Ruijie Hao 1,✉
PMCID: PMC13503113  PMID: 42637538

ABSTRACT

Adipose deposition is genetically regulated and acts as a core determinant of meat quality in livestock. Therefore, exploring the gene regulatory mechanisms underlying adipose deposition is essential to advance the research on adipose tissue development and molecular breeding in livestock. To clarify the molecular basis of the superior meat quality of Pinan (PN) cattle, high‐throughput RNA sequencing was performed to screen the key genes regulating adipose deposition in PN, with Nanyang (NY) cattle serving as the control (n = 3 per breed). A total of 265 differentially expressed genes (DEGs) were identified in the adipose tissue of PN cattle relative to NY cattle, comprising 135 upregulated and 130 downregulated genes. GO and KEGG enrichment analysis revealed that these DEGs were primarily enriched in lipid binding‐related functional categories, particularly lipid antigen binding and exogenous lipid antigen binding, as well as enzymatic functions such as protein xylosyltransferase activity. Meanwhile, RT‐qPCR confirmed significant differential expression of WNT16, IGFBP2, PEMT, ADCY5, and IDH3B in adipose tissue between PN and NY cattle, consistent with the RNA‐seq data. Moreover, functional validation experiments, including RT‐qPCR, CCK‐8, EdU, and Oil Red O staining, revealed that RNA interference (RNAi)‐mediated ADCY5 knockdown markedly promoted adipocyte proliferation, while significantly inhibiting adipocyte differentiation and lipid droplet formation. Collectively, the present study indicates that the identified DEGs are potentially involved in the regulation of bovine adipose tissue development. Notably, ADCY5 exhibits a crucial regulatory effect on cattle adipose deposition; however, the precise molecular mechanism remains to be further elucidated in future studies.

Keywords: ADCY5, adipocyte, adipose tissue, cattle, transcriptome

1. Introduction

In mammals, adipose tissue serves as a vital energy reservoir and functional metabolic organ that modulates glucose and lipid metabolism as well as systemic energy homeostasis. The biological processes of adipose tissue development, lipid deposition, and lipid metabolism are tightly associated with the growth, reproduction, and health status of domestic animals and further determine their livestock product quality. Depending on anatomical localization, cellular origin, and metabolic characteristics, adipose tissue is classified into distinct subtypes with unique lipid compositions and biological functions. As the predominant subtype, white adipose tissue (WAT) is predominantly distributed in visceral, subcutaneous, and intramuscular regions, exerting critical functions in mechanical protection, thermoregulation, and lipid metabolism (Haas et al. 2012). In contrast, brown adipose tissue (BAT) is primarily localized in the shoulder region of mammals, where abundant vascularization contributes to its typical brown phenotype. Under the regulation of the sympathetic nervous system, BAT specializes in lipolysis and heat production, thereby playing a pivotal role in glucose and lipid metabolism (Haas et al. 2012; Becher et al. 2021).

Adipose accumulation and metabolic disorders are closely correlated with multiple human diseases, particularly obesity and diabetes (Coelho et al. 2013). For livestock production, especially beef cattle, the modulation of adipose deposition and metabolism is a key determinant of core economic traits related to yield and meat quality. Therefore, systematically exploring the developmental patterns of bovine adipose tissue, identifying pivotal functional genes governing lipid deposition and metabolism, and elucidating their molecular regulatory mechanisms are essential to uncover the genetic basis of bovine adipose deposition, improve beef quality, enhance the market competitiveness of the cattle industry, and even provide theoretical references for human metabolic health research.

Adipose tissue is a complex heterogeneous tissue primarily composed of mature adipocytes, together with multiple stromal cell types, including preadipocytes, fibroblasts, endothelial cells, macrophages, and mesenchymal stem cells (MSCs) (Kershaw and Flier 2004; Cinti 2022). The proliferation and hypertrophy of adipocytes are the core cellular events driving adipose tissue development and lipid deposition in animals. Adipogenesis is a sophisticated and sequential gene regulatory network that precisely controls adipocyte proliferation, differentiation, lipid droplet formation, and metabolic activity. Deciphering the biological functions and molecular mechanisms of adipogenesis‐related genes is conducive to revealing the intrinsic genetic regulatory mechanisms of animal fat deposition.

Transcriptomic profiling based on mRNA expression analysis has become a powerful and prevalent approach to explore the molecular mechanisms underlying livestock phenotypic (Dillies et al. 2013; Reuter et al. 2015; Hrdlickova et al. 2017; Song et al. 2019). RNA sequencing (RNA‐seq), as a core transcriptomic technology, has been widely applied in biological research across animals, plants, and microorganisms (Driver et al. 2012; Paradis et al. 2015; Li et al. 2017), especially for characterizing gene expression signatures associated with organismal growth, tissue development, metabolic homeostasis, and disease progression (Jing et al. 2015; Jang et al. 2016; Keel et al. 2018; Pareek et al. 2019; Zhang et al. 2021). The Nanyang (NY) cattle, one of the five elite indigenous cattle breeds in China, are well‐known for their tall stature, tender meat, rich flavor, favorable marbling, and superior hide quality (Zhang et al. 2010; Du et al. 2016). However, their industrial application is restricted by inherent shortcomings, including a slow growth rate and low slaughter performance. To overcome these production deficiencies, Piedmontese cattle, characterized by rapid growth and muscular hypertrophy (Albera and Carnier 2004; Guo et al. 2010), were selected as terminal sires to crossbreed with NY cattle, generating the novel hybrid Pinan (PN) cattle. As a hybrid breed, PN cattle exhibit prominent heterosis, including exceptional meat quality, faster growth, and higher carcass yield, which greatly improves the economic benefits of beef cattle breeding (Wang et al. 2019; Liu et al. 2021). Nevertheless, the molecular mechanisms underlying the excellent heterosis and superior meat performance of PN cattle remain largely uncharacterized.

To comprehensively clarify the molecular mechanism governing the superior meat performance of PN cattle, the present study performed transcriptomic analysis of adipose tissues from PN and NY cattle via RNA‐seq. Candidate DEGs were further screened and functionally validated to explore the key molecular regulatory mechanisms of PN cattle adipose development and lipid deposition. The findings of this study aim to provide a solid theoretical foundation for the genetic improvement of PN cattle production performance and the scientific conservation and utilization of elite cattle germplasm resources.

2. Materials and Methods

2.1. Sample Preparation, Library Construction and RNA Sequenceing

Adipose tissue samples were collected from PN and NY cattle (n = 3 for each breed) at a local slaughterhouse in Nanyang City, China. The samples were immediately transported to the laboratory in liquid nitrogen and stored at −80°C until further experimental processing. All animal care and experimental protocols used in the present study were approved by the Animal Care and Use Committee of Xinyang Normal University (No: XFEC‐2024‐012).

Total RNA was isolated from bovine adipose tissue using TRIzol reagent (Takara), and genomic DNA was removed by DNase I treatment. RNA quality was measured utilizing an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, US). The procedures for cDNA library construction and Illumina sequencing were performed in strict accordance with the methods established in our previous studies (Wei et al. 2022).

2.2. Analysis of Sequencing Data

Raw sequencing reads were quality‐filtered and trimmed using Trimmomatic and subsequently aligned to the Bos Taurus reference genome (NCBI assembly Btau_5.0.1, GCF_000003205.7) using TopHat2/Bowtie2. Transcript abundance was quantified with Cufflinks, and gene expression levels were calculated as fragments per kilobase of transcript per million mapped reads (FPKM) to characterize the distribution of transcript lengths and chromosomal localization patterns. Differential expression genes (DEGs) analysis between PN and NY cattle adipose samples was performed using the edge R package, with trimmed mean of M‐values (TMM) normalization and a stringent false discovery rate (FDR)–adjusted p < 0.05.

Functional annotation of DEGs was performed through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyzes. The statistical significance of GO and KEGG terms was determined using right‐tailed hypergeometric tests, followed by Benjamini–Hochberg correction for multiple testing (FDR < 0.05).

2.3. Real‐Time Quantitative PCR

RT‐qPCR was performed to experimentally verify the RNA‐seq results and validate the differential expression patterns of candidate DEGs between PN and NY cattle. Amplifications were performed using SYBR Premix Ex Taq (Takara, Bio, Japan) under established RT‐qPCR cycling protocols (Wei et al. 2022). The relative gene expression levels were quantified using the 2−ΔΔCT method, with GAPDH selected as the endogenous reference gene. All specific primers spanning exon‐exon junctions were designed using primer Premier 5 software (detailed primer sequences are provided in Table S1).

2.4. Cell Culture and Transfection Assay

Primary adipocytes were isolated from subcutaneous adipose tissues of cattle using the tissue block isolation method. Briefly, fresh adipose tissues were collected in PBS containing 1.5% penicillin–streptomycin, minced into ~1 mm3 tissue blocks, and evenly inoculated into 90 mm culture dishes. the tissues were incubated at 37°C with 5% CO2. After 6 h of adherence culture, high‐glucose DMEM containing 20% fetal bovine serum (FBS) and 1% penicillin–streptomycin was added for routine culture. Approximately 10 days later, residual tissue blocks were removed, and the outgrown primary adipocytes were digested for subculture or cryopreservation. All procedures were performed under strict aseptic conditions. Cell transfection was performed using Lipofectamine 3000 transfection reagent according to the manufacturer's guidelines.

2.5. Cell Proliferation and Differentiation Assays

Cell proliferation capacity was evaluated using the Cell Counting Kit‐8 (CCK‐8) assay (Multisciences, Hangzhou, China) and 5‐ethynyl‐2′‐deoxyuridine (EdU) incorporation assay (Ribobio, Guangzhou, China):

CCK‐8 assay: Cells were seeded in 96‐well culture plates with six biological replicates per group. After routine culture, CCK‐8 reagent was added to each well and incubated for 4 h at 37°C. The absorbance value at 450 nm was measured by a microplate reader (Molecular Devices, Sunnyvale, CA, USA) to evaluate cell viability and proliferation.

EdU incorporation assay: The Cell‐Light EdU kit was used to determine cellular DNA synthesis rates following the manufacturer's instructions, with three independent biological replicates set for each group.

For adipogenic differentiation induction, primary adipocytes were cultured in 6‐well plates until reaching approximately 90% confluence. Cells were treated with differentiation induction medium (containing 1 μM dexamethasone, 0.5 mM IBMX, and 1 μM rosiglitazone, 10 g/mL insulin) for 48 h. Subsequently, the culture medium was replaced with maintenance medium (1 μM rosiglitazone + 10 μg/mL insulin) for continuous differentiation culture.

2.6. Statistical Analysis

All experimental data are presented as the mean ± standard error of the mean (SEM). Statistical differences in mRNA expression levels between groups were determined using independent‐samples Student's t‐test with SPSS vs. 19.0 software. Differences with p < 0.05 were considered statistically significant (*), and those with p < 0.01 were considered highly significant (**).

3. Results

3.1. Characterization of Bovine Adipose Tissue Transcriptome Data

RNA sequencing was performed on adipose tissue samples collected from NY and PN cattle (n = 3 per breed). A total of 78.9–90.2 million raw reads were generated for each library. After adapter removal and stringent quality filtering, 72.4–84.2 million high‐quality clean reads were mapped to the bovine reference genome (ARS‐UCD1.2), with overall mapping efficiencies ranging from 91.8% to 93.6% across all samples (Table 1). Uniquely mapped reads accounted for 86.3%–89.8% of all mapped clean reads.

TABLE 1.

Summary of reads mapping to the bovine reference genome.

Item NY001 NY002 NY003 Mean ± SD PN004 PN005 PN006 Mean + SD
All reads 86 311 786 84 369 024 82 165 272 84 282 027.33 ± 2E + 07 90 247 638 78 914 458 83 447 462 84 203 186 ± 5E + 07
Unmapped 6 785 133 6 807 876 5 802 775 6 465 261 ± 5E + 06 6 043 345 6 498 733 5 300 086 5 947 388 ± 6E + 06
Mapped 79 526 653 77 561 148 76 362 497 77 816 766 ± 1E + 07 84 204 293 72 415 725 78 147 376 78 255 798 ± 5E + 07
Mapped rate 0.921 0.919 0.929 0.923 ± 0.005 0.933 0.918 0.936 0.929 ± 0.010
Unique mapped 75 090 901 72 837 719 72 413 930 73 447 516.67 ± 1E + 07 80 229 568 68 493 691 74 899 775 74 541 011.33 ± 5E + 07
Unique mapped rate 0.87 0.863 0.881 0.871 ± 0.009 0.889 0.868 0.898 0.885 ± 0.015
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Comparative genomic localization analysis revealed consistent read distribution patterns between the two cattle breeds. Specifically, 29.2%–29.4% of clean reads were aligned to coding sequences (CDS), 40.6%–41.1% to exon regions, 42.1%–42.4% to intronic regions, and 16.6%–17.3% to intergenic regions (Figure 1A,B). Chromosomal alignment analysis further confirmed full genome‐wide coverage across all autosomes and sex chromosomes in both groups (Figure 1C,D).

FIGURE 1.

FIGURE 1

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Characterization of bovine adipose tissue transcriptome sequencing data. (A) Statistics of reads distribution in different regions of the genome in PN cattle. (B) Statistics of reads distribution in different regions of the genome in NY cattle. (C) Distribution of reads on chromosomes of PN cattle. (D) Distribution of reads on chromosomes of NY cattle.

In total, 15 724 unigenes were commonly expressed in adipose tissues of PN and NY cattle (Table 2). The kernel density distribution of normalized FPKM values exhibited highly overlapping curves between the two breeds (Figure 2A), reflecting strong consistency in transcriptome profiles and verifying the reproducibility of the sequencing data. Transcript length analysis revealed that the majority expressed transcripts ranged from 1000 to 3500 bp (Figure 2B). The FPKM values were evenly distributed across logarithmic scales (Figure 2B), indicating stable and sensitive transcriptional detection in the present transcriptome sequencing.

TABLE 2.

Numbers of differential genes in muscle tissue of PN and NY cattle.

Compare Algoritm Log2FC_Cutoff FDR_Cutoff AllGeneNum Differentially GeneNum UpGeneNum DownGeneNum
PN vs. NY EBSeq 1 0.05 15 724 265 135 130
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FIGURE 2.

FIGURE 2

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Differentially expressed genes in bovine adipose tissues. (A) Violin plot showing the distribution of FPKM values in adipose tissues of PN and NY cattle; (B) Statistics of gene length; (C) Heat map of 100 most differentially expressed genes between PN and NY cattle; (D) Volcano plots showing the relationship between fold‐change values and log10(FDR) for PN and NY cattle.

3.2. Identification of DEGs, Data Visualization and Functional Presentation

To systematically explore transcriptional differences in adipose tissue between PN and NY cattle, differential gene expression analysis was performed using the EBSeq algorithm with strict screening thresholds (︱log2FC︱ > 1 and FDR < 0.05). A total of 265 significantly DEGs were identified in PN cattle adipose relative to NY cattle, including 135 upregulated and 130 downregulated unigenes (Table 2). Two complementary visualization strategies were adopted to characterize the expression patterns of these DEGs. Hierarchical clustering analysis based on Pearson correlation coefficients was conducted to demonstrate the differential expression profiles across all samples (Figure 2C). Meanwhile, a volcano plot was generated to intuitively visualize the magnitude and statistical significance of differential expression (Figure 2D). All annotated DEGs are listed in detail in Table S3.

3.3. Analysis of DEGs by GO Enrichment and KEGG Pathway

To explore the potential molecular functions underlying adipogenic regulation in bovine adipose tissue, systematic functional annotation of DEGs was performed via Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyzes. In total, 343 significantly enriched GO terms (p < 0.05) were identified and classified into three primary functional categories, including 201 terms in biological process, 37 terms in cellular component, and 105 terms in molecular function (Table S4). Notably, the molecular function category was predominantly enriched in lipid‐related binding activities, particularly lipid antigen binding (GO: 0030882) and exogenous lipid antigen binding (GO: 0030884), as well as enzymatic functions represented by protein xylosyltransferase activity (GO: 0030158). The top enriched GO terms for the three ontological categories are displayed in Figure 3A, and the top 20 enriched molecular function terms are shown in Figure 3B.

FIGURE 3.

FIGURE 3

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GO and KEGG enrichment analysis of related differentially expressed genes (DEGs). (A) GO enrichment analysis of DEGs in biological process, cell components, and molecular function of PN cattle compared with NY cattle. (B) The Top 20 of GO Enrichment of DEGs. (C) Pathway analysis of DEGs in PN cattle compared with NY cattle. (D) The Top 20 of Pathway Enrichment of DEGs.

KEGG pathway enrichment analysis identified 153 enriched pathways, among which 20 pathways were significantly enriched (Figure 3C, Table S5). The key enriched pathways included metabolic pathways such as ovarian steroidogenesis (PATH: 04913) and glycerophospholipid metabolism (PATH: 00564), as well as the regulatory pathways of melanogenesis (PATH: 04916). The comprehensive pathway network indicated that these molecular interactions may orchestrate the transcriptional regulation of adipocyte differentiation and lipid accumulation. The top 20 enriched KEGG pathways are visualized in Figure 3D. Notably, the convergence of steroidogenic and phospholipid metabolic pathways suggests potential crosstalk between endocrine signaling and lipid biosynthesis during bovine adipogenesis.

3.4. Identification of the Expression of Selected Genes by RT‐qPCR

To verify the consistency of transcriptiomic profiles obtained from RNA‐seq data, RT‐qPCR was performed for mRNA expression validation. Eight DEGs with distinct expression differences in adipose tissue between NY and PN cattle were randomly selected for experimental validation. Based on FPKM values, WNT16, IGFBP2, PEMT, SLC5A1, and FBP2 were significantly upregulated in PN cattle (p < 0.05), while IDH3B, ADCY5, and ETNK2 were markedly downregulated in PN adipose tissue relative to NY cattle (Figure 4A). Further correlation analysis revealed a strong significant correlation (p < 0.01) between RT‐qPCR quantification results and RNA‐seq transcriptomic data (Figure 4B), confirming the high reliability and accuracy of the present transcriptome sequencing dataset.

FIGURE 4.

FIGURE 4

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Identification of the differentially expressed genes. (A) The RNA‐Seq results revealed the differentially expressed genes by FPKM; (B) Verification of the differentially expressed genes by RT‐qPCR. Values are mean ± SEM for three individuals. *p < 0.05, **p < 0.01, ***p < 0.001.

3.5. Interference With ADCY5 Promotes Proliferation and Inhibits Differentiation of Adipocytes

To explore the biological function of ADCY5 in bovine adipose development, siRNA was used to knock down endogenous ADCY5 expression in preadipocytes, and subsequent changes in cell proliferation and differentiation were evaluated. Three siRNA sequences targeting ADCY5 were designed and separately transfected into adipocytes. The transfection efficiency was verified via RT‐qPCR, and the results showed that siRNA1 exhibited the optimal interference effect (Figure S1). EdU incorporation and CCK‐8 assays were further performed to assess cell proliferative capacity. Functional tests showed that ADCY5 knockdown significantly promoted preadipocyte proliferation (Figure 5A–C). Consistent with these phenotypic changes, the mRNA expression levels of cell proliferation marker genes, including CyclinD1, CDK4, and PCNA, were markedly upregulated after ADCY5 silencing (Figure 5D–F). Collectively, these findings suggest that the downregulation of ADCY5 facilitates bovine preadipocyte proliferation.

FIGURE 5.

FIGURE 5

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Interference with ADCY5 promotes proliferation of adipocytes. (A) Cell proliferation was detected with EdU assay; scale bar: 50 μm; (B) EdU‐positive cell index statics are shown; (C) Cell proliferation index was detected by cell counting kit‐8(CCK8) assay. (D‐F) The expression of proliferation marker genes detected by RT‐qPCR. Values are mean ± SEM for three individuals. *p < 0.05, **p < 0.01, ***p < 0.001.

To further investigate the regulatory effect of ADCY5 on adipocyte differentiation, Oil red O staining experiment was performed to evaluate intracellular lipid droplet formation. The results showed that ADCY5 interference significantly reduced lipid droplet accumulation in differentiated adipocytes (Figure 6A). Meanwhile, RT‐qPCR detection revealed that the mRNA levels of key adipogenic marker genes (C/EBPα and PPARγ) were significantly decreased in the ADCY5‐knockdown group. These results suggest that suppressed ADCY5 expression inhibits bovine adipocyte differentiation and lipid formation.

FIGURE 6.

FIGURE 6

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Interference with ADCY5 inhibits differentiation of adipocytes. (A) Oil Red O staining was performed to observe the fat deposition, and stained adipocytes were eluted with isopropanol and analyzed via quantitative spectrophotometer at 490 nm OD; scale bar: 100 μm; (B) The expression of adipocyte differentiation marker genes C/EBPα and PPARγ detected by RT‐qPCR. Values are mean ± SEM for three individuals. *p < 0.05, **p < 0.01, ***p < 0.001.

4. Discussion

Adipose deposition plays a vital role in mammalian organ development and individual growth. However, the polygenic regulatory networks underlying bovine adipose deposition remain incompletely elucidated, and the core regulatory genes and their molecular mechanisms are largely unclarified. In the present study, RNA‐seq was performed to screen candidate genes associated with bovine adipose deposition. Transcriptomic comparison identified numerous DEGs in adipose tissue between PN and NY cattle, among which ADCY5 was screened as a key candidate gene. Subsequent functional validation demonstrated that ADCY5 knockdown significantly facilitated preadipocyte proliferation while inhibiting adipogenic differentiation, indicating the crucial regulatory function of ADCY5 in bovine adipocyte development.

RNA‐seq has become a predominant and powerful transcriptome‐wide approach for profiling gene expression patterns and identifying functional regulatory molecules, which facilitates the systematic exploration of key genes governing animal growth and tissue development. Previous transcriptomic studies have successfully screened adipogenic regulators using RNA‐seq. For instance, KLF16 was found to be differentially expressed during brown adipocyte differentiation in mice and was validated to inhibit adipogenesis by regulating PPARγ expression (Jang et al. 2016). Moreover, RNA‐seq‐based transcriptomic analyzes have been extensively conducted in multiple bovine tissues, including Cattle‐yak adipose (Song et al. 2019), skeletal muscle of Crossbred beef steer (Keel et al. 2018) and liver tissue of Polish Holstein Friesian cattle (Pareek et al. 2019). Consistent with previous findings, a total of 15 724 unigenes were annotated in bovine adipose tissue in this study, of which 265 DEGs were differentially expressed between PN and NY cattle. Chromosomal distribution analysis that these adipogenic‐related genes were widely localized to nearly all bovine chromosome, indicating the ubiquitous genomic distribution of regulatory factors involved in adipose development. Functional enrichment analysis demonstrated that the DEGs were significantly enriched in lipid‐binding terms, including lipid antigen binding and exogenous lipid antigen binding, as well as lipid metabolic pathways covering ovarian steroidogenesis and glycerophospholipid metabolism. These enriched functional categories and pathways imply that the divergent transcriptional regulation of lipid metabolism and endocrine signaling contributes to the differences in adipose deposition between the two cattle breeds.

Specifically, RT‐qPCR validation confirmed that IGFBP2, PEMT, SLC5A1, FBP2, IDH3B, ADCY5, and ETNK2 were significantly differentially expressed in PN versus NY cattle (p < 0.05), suggesting that these genes serve as key candidate regulators of bovine adipogenesis. Accumulating evidence has demonstrated that these DEGs participate in multiple fundamental cellular processes, including cell proliferation, apoptosis, and migration. Insulin‐like growth factor‐binding protein 2 (IGFBP2) has been recognized as a vital developmental regulator that modulates cellular proliferation, somatic development, and disease pathogenesis via the IGFs signaling axis (Li et al. 2020). Functionally, IGFBP2 inhibits the invasion of breast cancer cells while promoting proliferation and glycolysis in endometrial cancer through modulation of PKM2/HIF‐1α signaling Axis (Jin et al. 2025). SLC5A1 is a core gene involved in glucose metabolism, and its dysregulated expression leads to severe glucose metabolic disorders (Hoşnut et al. 2023). ETNK2 has been reported to regulate tumorigenesis by mediating immune cell infiltration (Chu et al. 2023). FBP2 encodes a key enzyme associated with glucose metabolism; this gene not only modulates the expression of lipid metabolism enzymes but also attenuates lipolysis in muscle tissue, thereby promoting intramuscular fat deposition (Bakshi et al. 2018; Pietras et al. 2022). PEMT downregulation impairs adipocyte differentiation and reduces lipid droplet formation, indicating an indispensable role of PEMT in adipogenesis (Gao et al. 2015; Presa et al. 2020). Moreover, PEMT contributes to insulin resistance, and its overexpression is closely associated with increased obesity susceptibility (Sun et al. 2023). Notably, although ADCY5 has been previously linked to neurological movement disorders and ovarian follicular development in goats by regulating steroid synthesis via CREB‐ and p38 MAPK‐mediated phosphorylation pathways (Shi et al. 2025), its biological function in bovine adipose development remains unreported. The molecular mechanisms by which ADCY5 regulates bovine adipose tissue formation also remain unclear. Therefore, further systematic and in‐depth investigations are required to elaborate the downstream signaling pathways and regulatory networks of ADCY5 during bovine adipogenesis.

Although the adipogenic functions of most of these screened DEGs have not been characterized in cattle, our transcriptomic and experimental results strongly suggest that these genes exert essential regulatory effects on fat development in PN cattle, which warrants further functional verification in subsequent studies. In the present study, we functionally identified ADCY5 as a critical determinant of bovine preadipocyte fate, which exerts dual regulatory effects on preadipocyte proliferation and differentiation. ADCY5 knockdown significantly accelerated preadipocyte proliferation, as evidenced by increased EdU‐positive cell ratios, elevated cell viability in CCK‐8 assays, and upregulation of the expression of core cell cycle genes (CyclinD1, CDK4, PCNA). In contrast, ADCY5 deficiency markedly suppressed adipogenic differentiation, accompanied by decreased intracellular lipid accumulation and downregulation of the expression of master adipogenic transcription factors C/EBPα and PPARγ.

This dual regulatory phenotype indicates that ADCY5 may act as a key molecular switch in governing the early stage of adipogenesis. Although the downstream regulatory mechanisms of ADCY5 remain to be fully clarified, its canonical function in cAMP production provides a reasonable mechanistic explanation. We speculate that the biological effects of ADCY5 on adipogenesis are primarily mediated through cAMP‐dependent signaling pathway (Kozon et al. 2024; Shi et al. 2025). The enhanced proliferative capacity induced by ADCY5 silencing may be attributed to reduced basal cAMP signaling, whereas the requirement of ADCY5 for adipogenic differentiation may depend on cAMP burst‐triggered activation of the adipogenic transcriptional program.

In conclusion, the present study demonstrates that ADCY5 functions as a vital molecular switch in adipose biology, balancing preadipocyte proliferation and differentiation to ensure orderly bovine adipose tissue development. Future studies are needed to further explore the temporal dynamics characteristics and tissue‐specific functions of ADCY5‐mediated cAMP signaling, as well as its potential roles in metabolic disease.

5. Conclusion

This study comprehensively characterized the transcriptome of bovine adipose tissue via RNA‐seq and identified a set of candidate genes potentially responsible for regulation of bovine adipogenesis. Subsequent functional validation confirmed that ADCY5 plays a crucial regulatory role in adipocyte development, suppressing preadipocyte proliferation while facilitating adipogenic differentiation. Accordingly, ADCY5 serves as a credible molecular biomarker for the precision breeding of PN cattle. By integrating transcriptome‐wide screening with functional verification, this study deepens the mechanistic understanding of bovine adipose deposition. Furthermore, these findings provide valuable genetic resources and candidate markers for marker‐assisted selection to improve meat quality traits in cattle.

Author Contributions

Ruijie Hao: conceptualization, resources, data curation. Lize Yang: resources, investigation, validation. Xuefeng Wei: conceptualization, funding acquisition, writing – original draft, project administration, writing – review and editing. Xinyue Shan: investigation, validation, data curation. Xue Zhao: resources. Yongjie Xu: conceptualization, methodology. Yun Ma: conceptualization, resources. Pengpeng Zhang: funding acquisition.

Funding

This work was supported by the National Natural Science Foundation of China, 31802043. Department of Science and Technology in Henan Province, 242102110046. Department of Education in Henan Province, 262300421528. Key Scientific Research Project Plan of Institutions of Higher Education in Henan Province, 24A230016.

Conflicts of Interest

The authors declare no conflicts of interest.

Supporting information

Figure S1: Interference efficiency detected by RT‐qPCR.

AGE-57-0-s006.tif (22.8KB, tif)

Table S1: Primers for RT‐qPCR.

AGE-57-0-s007.docx (15.9KB, docx)

Table S2: The analysis results of all expression genes in adipose tissue.

AGE-57-0-s004.xlsx (3.4MB, xlsx)

Table S3: The analysis results of all difference expression genes.

AGE-57-0-s005.xlsx (64.2KB, xlsx)

Table S4: GO analysis results of all difference expression genes.

AGE-57-0-s003.xlsx (151.9KB, xlsx)

Table S5: KEGG pathway analysis results of all difference expression genes.

AGE-57-0-s001.xlsx (66.8KB, xlsx)

Table S6: Summary of reads mapping to the bovine reference genome.

AGE-57-0-s002.docx (15.7KB, docx)

Acknowledgments

This work was supported by the National Natural Science Foundation of China (No. 31802043), the Department of Science and Technology in Henan Province (No. 242102110046), the Department of Education in Henan Province (No. 262300421528), Key Scientific Research Project Plan of Institutions of Higher Education in Henan Province (No. 24A230016), the Doctoral Scientific Research Foundation of XYNU, and the Nanhu Scholar Program for Young Scholars of XYNU.

Contributor Information

Xuefeng Wei, Email: weixuefeng.happy@163.com.

Ruijie Hao, Email: hrjxx@126.com.

Data Availability Statement

The data that supports the findings of this study are available in the [Link], [Link] of this article.

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Associated Data

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

Supplementary Materials

Figure S1: Interference efficiency detected by RT‐qPCR.

AGE-57-0-s006.tif (22.8KB, tif)

Table S1: Primers for RT‐qPCR.

AGE-57-0-s007.docx (15.9KB, docx)

Table S2: The analysis results of all expression genes in adipose tissue.

AGE-57-0-s004.xlsx (3.4MB, xlsx)

Table S3: The analysis results of all difference expression genes.

AGE-57-0-s005.xlsx (64.2KB, xlsx)

Table S4: GO analysis results of all difference expression genes.

AGE-57-0-s003.xlsx (151.9KB, xlsx)

Table S5: KEGG pathway analysis results of all difference expression genes.

AGE-57-0-s001.xlsx (66.8KB, xlsx)

Table S6: Summary of reads mapping to the bovine reference genome.

AGE-57-0-s002.docx (15.7KB, docx)

Data Availability Statement

The data that supports the findings of this study are available in the [Link], [Link] of this article.

Articles from Animal Genetics are provided here courtesy of Wiley

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