Background

Fat has unique distribution characteristics and different economic values in various tissues of animals. In broilers, high-intensity artificial breeding has effectively increased the meat yield but has also increased the abdominal fat content and reduced intramuscular fat deposition [1]. Excessive abdominal fat deposition has negative impacts on the feed efficiency and carcass yield [2, 3]. Decreased abdominal fat deposition is beneficial to reduce waste and improve consumer acceptance. In contrast, intramuscular fat is economically desirable in broiler production. Appropriately increased IMF content can improve the meat quality, including color, tenderness, flavor, and juiciness [4,5,6,7]. Lowering abdominal fat and increasing intramuscular fat can effectively increase the economic value of broilers.

Previous studies have shown that adipocytes with different origins exhibit differential differentiation capabilities [8]. Compared with subcutaneous preadipocytes, the cell size and lipid droplets in intramuscular adipocytes are smaller [9, 10], and the gene expression and enzyme activation related to lipid metabolism are lower in intramuscular adipocytes [11, 12]. Similarly, abdominal fat-derived preadipocytes exhibited a higher adipogenic differentiation ability than intramuscular fat-derived preadipocytes in chickens [13, 14]. However, it is still unknown whether the difference in the lipogenesis ability of preadipocytes from different tissues will disappear after cultivation in vitro.

In this study, we explored the lipogenesis characteristics of chicken preadipocytes of different origins after cultivation in vitro, including dedifferentiated intramuscular preadipocytes (DIMFPs) and dedifferentiated abdominal preadipocytes (DAFPs). These results will help to understand tissue-specific lipid deposition and optimize body fat distribution in broilers.

Results

The difference in lipid deposition in the two types of preadipocytes

Collect the DIMFP group and DAFP group cells were collected to detect the total lipid content by an Oil Red O staining assay. As shown in Fig. 1a, the total lipid content in DAFP cells was significantly (P < 0.05) higher than that in DIMFP cells. The main ingredients of lipids, triglycerides (TGs), phospholipids (PLIPs), and total cholesterol (TCHO) were also detected. Similarly, the TG content in DAFP cells was significantly (P < 0.05) higher than that in DIMFP cells. However, the contents of PLIP and TCHO showed no difference in the two types of preadipocytes (Fig. 1b).

Fig. 1
figure 1

Difference in lipid metabolism between DIMFPs and DAFPs of chickens. a and b The contents of total lipids and the main ingredients of lipids (TG, PLIP and TCHO). The total lipid and TG contents were increased in the DAFPs compared with the DIMFPs after two days at 100% confluence. Data are presented as the means ± SEM (n = 3; * P < 0.05)

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Identification of DEGs

Total RNA of each of the three cell repetitions of the DIMFP and DAFP groups was extracted for RNA sequencing. A total of 21,469 expressed genes were found in DIMFPs and DAFPs (Additional file 1: Table S1). Using gene expression profiling and comparing the DAFP group with the DIMFP group (DIMFP vs DAFP), a total of 3629 known DEGs (|log2 FC| ≥1, with P < 0.05) were screened (Fig. 2a), of which 2579 DEGs were downregulated and 907 DEGs were upregulated (Additional file 2: Table S2). Next, cluster analysis was performed on these 21,469 genes, and two results showed the same situation: three cell samples of the same groups were clustered together (Fig. 2b).

Fig. 2
figure 2

Volcano plot and cluster analysis of differentially expressed genes (DEGs). a Volcano plot. Red dots (UP) represent significantly upregulated genes (log2FC ≥ 1.0, FDR < 0.05); blue dots (DOWN) represent significantly downregulated genes (log2 FC ≤ − 1.0, FDR < 0.05); and black dots (NO) represent DEGs below the level of significance; (b) based on 3486 known DEGs in DIMFPs and DAFPs of chickens, cluster analysis was performed. The results show that the gene expression profiling data in the same group were closely related

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Analysis of the enriched GO terms and pathways in the two types of preadipocytes

Based on 3629 known DEGs, Gene Ontology (GO) analysis was performed, and 56 GO terms were enriched (P < 0.05), mainly including the following processes: cell adhesion, tight adhesion, cell differentiation, extracellular matrix, DNA binding, calcium ion binding, etc. (Additional file 3: Table S3). The top 10 terms of each of the biological process (BP), cellular component (CC) and molecular function (MF) terms are shown in Fig. 3.

Fig. 3
figure 3

List of enriched Gene Ontology (GO) terms with the top 10. The enriched Gene Ontology (GO) terms were enriched (P < 0.05) based on the 3486 DEGs, and the GO terms with the top 10 biological process (BP), cellular component (CC) and molecular function (MF) terms are listed

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Meanwhile, 47 pathways were found to be significantly enriched (corrected P-value < 0.05) (Additional file 4: Table S4), including some well-known pathways affecting lipid metabolism (PPAR, MAPK, TGF-beta, Wnt, and calcium signaling pathways) and other pathways related to cell communication (focal adhesion, cytokine-cytokine receptor interaction, ECM-receptor interaction, tight junction, regulation of the actin cytoskeleton, cell adhesion molecules, and adherens junction pathways). The top 15 enriched pathways are shown in Fig. 4.

Fig. 4
figure 4

List of enriched pathways with the top 15 based on the 3486 DEGs. The KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analysis showed that well-known pathways (MAPK, TGF-beta, Wnt, calcium, and PPAR signaling pathways) of lipid metabolism were enriched, and the enriched pathways with the top 15 were screened (adjusted P < 0.05)

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DEGs related to lipid metabolism in the two types of preadipocytes

GO enrichment analysis indicated 72 DEGs related to lipid metabolism, and some representative DEGs were screened (Additional file 5: Table S5). The DEGs related to lipid metabolism were mainly involved in adipocyte differentiation (such as CEBPA, PPARG, RBP7, and RXRG), fatty acid transport and fatty acid synthesis (such as ELOVL1, ELOVL6, FABP3, FABP4, FADS6, FADS1 L1, SCD, and SCD5), lipid stabilization (such as CIDEC, PLIN3, PLIN4, and MOGAT1), and lipolysis (such as DGKD, DGKH, DGKQ, and LPL). The 20 representative DEGs related to lipid metabolism were randomly selected to validate the gene expression profiling results by qRT-PCR, and the correlation of gene expression profiling and qRT-PCR was analyzed by Spearman rank correlation to confirm the accuracy of the data. The results showed that the fold change in gene expression between the two methods was significantly correlated (Fig. 5a) (r = 0.9666, P < 0.01).

Fig. 5
figure 5

Validation of DEGs related to lipid metabolism between DIMFPs and DAFPs of chickens. a Correlation analysis of gene expression profiling and real-time quantitative polymerase chain reaction (qRT-PCR) results by Spearman rank correlation in DIMFPs and DAFPs. A high correlation coefficient (r = 0.9666, P < 0.05) was detected, which indicates that the gene expression profiling data are reliable. n = 20; (b) and (c) qRT-PCR verification of DEGs detected by gene expression profiling. The expression levels of DEGs related to lipid metabolism determined by qRT-PCR in the DIMFPs and DAFPs. Each of these DEGs was upregulated or downregulated significantly (P < 0.05) in DIMFPs and DAFPs. Data are presented as the means ± SEM (n = 3; * P < 0.05, ** P < 0.01)

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Among these 20 verified genes, the expression levels of the CEBPA, DGKH, DGKQ, DGKD, FADS1L1, SCD, SCD5, and PPARG genes were significantly (P < 0.05 or P < 0.01) downregulated in DAFPs compared to DIMFPs (Fig. 5b). However, the expression levels of the CIDEC, ELOVL1, ELOVL6, FABP3, FABP4, FADS6, LPL, MOGAT1, PLIN3, PLIN4, RBP7, and RXRG genes were significantly (all P < 0.01) upregulated in DAFPs compared to DIMFPs (Fig. 5c).

Pathways involved in lipid metabolism

It was found that 19 genes related to lipid metabolism enriched in the PPAR signaling pathway (Additional file 6: Fig. S1). Among these 19 genes, the data from RNA-seq showed that APOA1, ADIPOQ, FABP3, FABP4, FABP7, HMGCS2, LPL and RXRG genes were down-regulated, but ACSL1, FABP5, PCK2, PDPK1, PPARG, SCD, SCD5, SLC27A6 genes were up-regulated (P < 0.05 or P < 0.01) in the DIMFPs. (Additional file 2: Table S2).

Also, there are a large number of DEGs that were enriched in MAPK- (80 genes), Calcium- (50 genes), and TGF beta (30 genes) signaling pathway, which involved in mediating the biology function of lipid metabolism (Additional file 7: Fig. S2, Additional file 8: Fig. S3, and Additional file 9: Fig. S4). Besides, 245 DEGs also were enriched the pathways related to cell communications (Focal adhesion, Cytokine-cytokine receptor interaction, ECM-receptor interaction, Tight junction, Regulation of actin cytoskeleton, cell adhesion molecules, Adherens junction). However, it was found that the enriched Wnt signaling pathway, as a well-known pathway affecting lipid metabolism, did not medicate the regulation of lipid metabolism. Based on the above information, we proposed the regulatory network for the difference of lipid deposition between chicken DAFPs and DIMFPs (Fig. 6).

Fig. 6
figure 6

Proposed regulatory network for the difference in lipid deposition in DIMFPs and DAFPs based on DEGs and enriched signaling pathways

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Discussion

Fat has unique distribution characteristics and different economic values in various tissues of animals. In broilers, intramuscular fat is economically desirable in production. Appropriately increased IMF content can improve meat quality, including tenderness, flavor, and juiciness [4,5,6]. However, excessive abdominal fat deposition has negative impacts on the feed efficiency and carcass yield [2, 3], and decreased abdominal fat deposition is beneficial to reduce waste production and improve consumer acceptance. Lowering abdominal fat and increasing intramuscular fat can effectively increase the economic value of broilers. Therefore, changing the constitution distribution is an important scientific problem for broilers.

Unlike the marbling distribution of IMF in domestic animals, the IMF of chickens cannot be obtained directly from anatomy. Moreover, chicken muscle tissue has a variety of cell compositions [15], and IMF preadipocytes cannot be separated by physical methods due to their similar density to muscle cells. Therefore, high-purity preadipocytes of IMF can only be obtained by the dedifferentiation of mature adipocytes in vitro as described previously [16]. In this study, abdominal fat preadipocytes and intramural preadipocytes were obtained from mature adipocytes of the same chicken to compare their lipogenesis ability under consistent experimental conditions in vitro, establishing a theoretical foundation for the body fat distribution of chickens and providing ideas and development directions for chicken production.

Adipocytes in different tissues are regulated by the adjacent microenvironment to perform the corresponding physiological function [40]. The edgeR R software package was used to analyze the differentially expressed genes (DEGs) between the DIMFP group and the DAFP group. The DEG screening conditions were | log2 FC | ≥1.0 and FDR < 0.05. Cluster analysis of DEGs was performed by the pheatmap software package of R software.

Gene ontology and Kyoto encyclopedia of genes and genomes analysis

The ClueGO plug-in and CluePedia plug-in in Cytoscape (https://cytoscape.org/) software were used to perform Gene Ontology (GO) enrichment analysis and functional classification of the DEGs. The significance level of GO term enrichment was set at P < 0.05. At the same time, the Kyoto Encyclopedia of Genes and Genomes (KEGG) [41] database was used for pathway enrichment analysis of DEGs. P < 0.05 was considered to be indicative of statistical significance. According to the results of GO enrichment analysis and KEGG pathway function enrichment, DEGs related to abdominal fat tissue metabolism were screened.

Real-time quantitative polymerase chain reaction

A Tiangen® FastQuant RT kit (Tiangen, Bei**g, China) was used for the reverse transcription of the RNA samples of the two groups of cells according to the steps provided by the manufacturer’s instructions, and Primer 5.0 software was used to design specific primers for each gene according to the GenBank sequence (Additional file 10: Table S6). The ABI 7500 real-time PCR detection system (Applied Biosystems, CA, USA) was used for relative quantitative analysis of gene expression in different samples. The total reaction system was 20 μL and contained 10 μL of SYBR Green mix (TaKaRa, Shanghai, China), 0.5 μL of forward primers, and 0.5 μL of reverse primers at a concentration of 10 nmol, 1 μL of cDNA, and 8 μL of ddH2O. The reaction program was denaturation at 95 °C for 30 s, followed by 40 cycles of amplification at 95 °C for 5 s and 60 °C for 32 s. The 2-△△Ct method [42] was used to calculate the fold change of gene expression with the expression of actin beta (β-actin), which was a reference gene.

Statistical analysis

Three comparison replicates (DIMFPs vs DAFPs) of the cell experiment were set according to the one-to-one correspondence of cell samples from the abdominal fat tissue and pectoralis major of the same chicken. All experiments were repeated three times, and the data obtained are expressed as the mean ± SEM. Statistically significant differences between the two culture conditions were tested by independent-samples t-tests using SAS 9.2 software (SAS Institute Inc., NC, USA). P < 0.05 (*) or P < 0.01 (**) was considered to be significant. All figures were constructed using GraphPad Prism version 5.02 (GraphPad Software Inc., CA, USA).