Skip to content


  • Research article
  • Open Access

Transcriptomic analysis of hepatic responses to testosterone deficiency in miniature pigs fed a high-cholesterol diet

  • 1,
  • 2,
  • 1,
  • 1,
  • 3,
  • 1,
  • 1,
  • 1,
  • 1,
  • 1 and
  • 1Email author
BMC Genomics201516:59

  • Received: 21 October 2014
  • Accepted: 26 January 2015
  • Published:



Recent studies have indicated that low serum testosterone levels are associated with increased risk of developing hepatic steatosis; however, the mechanisms mediating this phenomenon have not been fully elucidated. To gain insight into the role of testosterone in modulating hepatic steatosis, we investigated the effects of testosterone on the development of hepatic steatosis in pigs fed a high-fat and high-cholesterol (HFC) diet and profiled hepatic gene expression by RNA-Seq in HFC-fed intact male pigs (IM), castrated male pigs (CM), and castrated male pigs with testosterone replacement (CMT).


Serum testosterone levels were significantly decreased in CM pigs, and testosterone replacement attenuated castration-induced testosterone deficiency. CM pigs showed increased liver injury accompanied by increased hepatocellular steatosis, inflammation, and elevated serum alanine aminotransferase levels compared with IM pigs. Moreover, serum levels of total cholesterol, low-density lipoprotein cholesterol, and triglycerides were markedly increased in CM pigs. Testosterone replacement decreased serum and hepatic lipid levels and improved liver injury in CM pigs. Compared to IM and CMT pigs, CM pigs had lower serum levels of superoxide dismutase but higher levels of malondialdehyde. Gene expression analysis revealed that upregulated genes in the livers of CM pigs were mainly enriched for genes mediating immune and inflammatory responses, oxidative stress, and apoptosis. Surprisingly, the downregulated genes mainly included those that regulate metabolism-related processes, including fatty acid oxidation, steroid biosynthesis, cholesterol and bile acid metabolism, and glucose metabolism. KEGG analysis showed that metabolic pathways, fatty acid degradation, pyruvate metabolism, the tricarboxylic acid cycle, and the nuclear factor-kappaB signaling pathway were the major pathways altered in CM pigs.


This study demonstrated that testosterone deficiency aggravated hypercholesterolemia and hepatic steatosis in pigs fed an HFC diet and that these effects could be reversed by testosterone replacement therapy. Impaired metabolic processes, enhanced immune and inflammatory responses, oxidative stress, and apoptosis may contribute to the increased hepatic steatosis induced by testosterone deficiency and an HFC diet. These results deepened our understanding of the molecular mechanisms of testosterone deficiency-induced hepatic steatosis and provided a foundation for future investigations.


  • Testosterone
  • Nonalcoholic fatty liver disease
  • Hepatic steatosis
  • Miniature pigs
  • RNA-Seq


Serum testosterone levels decline gradually and progressively with aging in men. Low levels of testosterone are associated with metabolic disorders, including obesity, dyslipidemia, hypertension, and insulin resistance [1], all of which contribute to the development of nonalcoholic fatty liver disease (NAFLD) [2]. Recent studies have shown that men with low serum testosterone levels have a higher risk of developing hepatic steatosis [3-5]. Moreover, animal studies have demonstrated that the incidence of hepatic steatosis is increased in testosterone-deficient male mice [6,7]. These findings indicate the important role of testosterone in the pathophysiology of NAFLD. However, nutritional parameters, especially a high-cholesterol diet, have been also associated with the development of NAFLD [2,8]. Hypercholesterolemia induced by dietary cholesterol has recently been indicated as a major risk factor for hepatic steatosis [9,10]. In the absence of testosterone, mice develop hypercholesterolemia when fed a diet with no added cholesterol [11]. Hypercholesterolemia and elevated serum cholesterol levels are also observed in hypogonadal men [12,13]. Therefore, these previous findings suggest that testosterone deficiency and testosterone deficiency-induced hypercholesterolemia may aggravate the severity of NAFLD induced by a high-cholesterol diet. However, the mechanisms underlying the effects of testosterone deficiency on the promotion of diet-induced hepatic steatosis remain unclear.

Previous studies have used rodent models to investigate the influence of testosterone on the development of hepatic steatosis. For example, hepatic androgen receptor-knockout male mice receiving a high-fat diet develop insulin resistance and hepatic steatosis [14]. Moreover, dihydrotestosterone suppresses diet-induced hepatic steatosis in castrated male rats [15], and hepatic lipid deposition is elevated in testicular feminized mice (Tfm) compared with intact wild-type littermate controls [7]. Although rodents are commonly used to study hepatic steatosis and have provided valuable insights into the pathogenesis of this disease, the relevance of these models to human disease is limited [16]. As an alternative to rodent models, large animal models, such as pigs, may be more relevant to the study of NAFLD because these models more closely mimic human physiology and anatomy [16-18]. Importantly, castration-induced sex hormone deficiency in male pigs results in obesity, elevated serum triglycerides (TGs), and increased cholesterol levels [19,20], some of the typical causes of NAFLD, suggesting that pigs are suitable models for studying the effects of sex hormones on NAFLD development.

Despite the importance of testosterone in the regulation of hepatic steatosis, the genomic mechanisms through which testosterone deficiency aggravates diet-induced hepatic steatosis are still unclear. Transcriptome profiling is an effective and widely used tool to identify critical genes and pathways involved in pathological processes. Sequencing-based and hybridization-based approaches represent the two major approaches used in transcriptomics studies [21]. High-throughput RNA sequencing (RNA-Seq) has recently become an attractive method of choice in the study of transcriptomes, providing several advantages over microarrays.

In this study, we sought to gain insights into the roles of testosterone in modulating hepatic steatosis using a porcine model of testosterone deficiency and diet-induced hepatic steatosis. Additionally, we examined the contribution of liver genes to the development of hepatic steatosis induced by testosterone deficiency and a high-cholesterol diet using RNA-Seq. To the best of our knowledge, this is the first description of differences in whole-transcriptome patterns occurring in the liver following castration in pigs fed a high-cholesterol diet.


Body weights and serum testosterone levels

Pigs were separated into three groups: intact male pigs fed a high-fat and high-cholesterol (HFC) diet (IM); castrated male pigs fed an HFC diet (CM); and castrated male pigs fed an HFC diet and given testosterone replacement therapy (CMT). The body weights of pigs in each group were calculated and found to be linearly elevated over time. Initial body weights were similar in pigs from the IM, CM, and CMT groups (12.76 ± 0.45, 12.14 ± 0.35, and 12.35 ± 0.89 kg, respectively). Castrated pigs fed an HFC diet gained less weight than did pigs in the other groups. With testosterone replacement, the body weights of CMT pigs increased and were similar to the body weights of pigs in the IM group (Figure 1A).
Figure 1
Figure 1

Effects of castration and testosterone treatment on body weights and serum testosterone concentrations. (A) Body weights. (B) Serum testosterone concentrations. IM: intact male pigs fed an HFC diet; CM: castrated male pigs fed an HFC diet; CMT: castrated male pigs fed an HFC diet and given testosterone replacement therapy. Data are expressed as means ± SEMs, n = 6 per group. **P < 0.01.

Serum testosterone concentrations were not significantly different between groups before the study began (0 weeks). As expected, castration caused a significant decrease in serum testosterone levels. The concentration of serum testosterone at 12 weeks was significantly lower in CM pigs than in IM pigs (0.24 ± 0.05 vs. 3.52 ± 0.25 ng/mL, respectively). Testosterone treatment increased serum testosterone levels to 4.43 ± 0.31 ng/mL (Figure 1B).

Liver weight, body fat content, and serum biochemical parameters

Liver weight, body fat content, and serum biochemical parameters after 12 weeks of HFC feeding are presented in Table 1. The liver weights in CM pigs were higher than those observed in IM pigs, but lower than those in CMT pigs (P > 0.05). Liver weight indexes in CM pigs were higher than those in IM and CMT pigs, but these differences were not significant (P > 0.05). CM pigs had higher body fat percentages than IM (P < 0.01) and CMT pigs (P < 0.05). Serum alanine aminotransferase (ALT) levels were significantly increased in CM pigs compared with IM + HFC pigs (P < 0.05) and significantly reduced in CMT pigs by testosterone replacement (P > 0.05). Aspartate aminotransferase (AST) levels were highest in CM pigs, but the differences were not significant among groups (P > 0.05). Compared with IM and CMT pigs, CM pigs showed obviously lower serum levels of superoxide dismutase (SOD, P < 0.05) but higher levels of malondialdehyde (MDA, P < 0.01). Serum free fatty acid (FFA) levels tended to be higher in CM pigs than in IM and CMT pigs. Fasting serum glucose and insulin levels and homeostatic model assessment of insulin resistance (HOMA-IR) were not significantly different between CM and IM pigs (P > 0.05). However, testosterone replacement significant reduced serum insulin levels and HOMA-IR in CM pigs (P < 0.01).
Table 1

Liver weight, body fat content and serum biochemical parameters in miniature pigs fed a high-fat and high-cholesterol diet





Body weight (kg)

25.15 ± 0.86

23.69 ± 0.64

26.21 ± 1.20

Liver weight (g)

483.82 ± 47.04

524.72 ± 69.88

558.38 ± 27.95

Liver weight index (%)

19.18 ± 1.74

22.01 ± 2.47

21.30 ± 0.39

Body fat (%)

0.15 ± 0.00**

0.24 ± 0.02

0.19 ± 0.01#




37.17 ± 2.20*

46.88 ± 0.86

42.45 ± 3.68


42.37 ± 4.95

44.70 ± 6.86

41.45 ± 2.60

SOD (U/mL)

88.61 ± 7.09*

52.07 ± 9.58

100.69 ± 11.79##

GSH-PX (μmol/L)

810.07 ± 65.53

723.44 ± 61.82

900.43 ± 58.22


3.30 ± 0.32**

5.89 ± 0.68

2.81 ± 0.19##

FFA (mmol/L)

0.70 ± 0.13

0.98 ± 0.14

0.65 ± 0.10

Glucose (mmol/L)

5.09 ± 0.13

4.94 ± 0.14

5.15 ± 0.15

Insulin (mIU/L)

27.40 ± 0.66

28.60 ± 0.76

21.1 ± 0.47##


6.17 ± 0.10

6.29 ± 0.33

4.81 ± 0.35##

*P < 0.05 and **P < 0.01, IM vs. CM; # P < 0.05 and ## P < 0.01, CMT vs. CM.

Serum lipids

To analyze the effects of castration and testosterone treatment on lipid metabolism in HFC-fed pigs, serum lipids were measured at 0, 2, 4, 6, 8, 10, and 12 weeks postcastration. Serum total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and TGs were significantly increased in miniature pigs fed an HFC diet (Figure 2). CM pigs had higher TC levels than did IM and CMT pigs from the fourth week after HFC supplementation (P < 0.05; Figure 2A). There were no significant differences in serum TC levels between IM and CMT pigs (P > 0.05). Serum LDL-C followed a pattern similar to that of TC in all groups of pigs (Figure 2C). However, testosterone deficiency caused by castration had no significant influence on serum HDL-C levels in HFC-fed pigs (Figure 2B). Serum TG levels in CM pigs were higher than those in IM pigs at weeks 10 and 12 (P < 0.05) and those in CMT pigs beginning at week 4 (P < 0.05; Figure 2D).
Figure 2
Figure 2

Effects of castration and testosterone treatment on serum lipid levels. (A) Serum total cholesterol (TC) levels. (B) Serum low-density lipoprotein cholesterol (LDL-C) levels. (C) Serum high-density lipoprotein cholesterol (HDL-C) levels. (D) Serum triglyceride (TG) levels. IM: intact male pigs fed an HFC diet; CM: castrated male pigs fed an HFC diet; CMT: castrated male pigs fed an HFC diet and given testosterone replacement therapy. Data are expressed as means ± SEMs, n = 6 per group. *P < 0.05 and **P < 0.01, IM vs. CM; # P < 0.05 and ## P < 0.01, CMT vs. CM.

Liver histopathology and hepatic lipids

Liver histology results showed that testosterone deficiency induced by castration significantly increased hepatic fat accumulation in pigs fed an HFC diet (Figure 3). CM pigs developed massive micro- or macrovesicular steatosis, while the hepatocytes of IM pigs showed only mild microvesicular steatosis (Figure 3A). Moreover, castration significantly aggravated hepatic inflammation in pigs fed an HFC diet (Figure 3A). Testosterone treatment clearly improved hepatic steatosis and reduced hepatic necroinflammation in CM pigs (Figure 3A). Oil red O staining confirmed the occurrence of increased lipid deposition in the livers of CM pigs (Figure 3B).
Figure 3
Figure 3

Effects of testosterone on liver histology and hepatic lipids. (A) Liver sections stained with hematoxylin and eosin. Micro- and macrovesicular steatosis are indicated by arrow heads, and inflammation is indicated by arrows. (B) Oil red O staining of fat in hepatocytes. Increased lipid deposition is indicated by arrows. (C) Hepatic triglyceride (TG) content in IM, CM, and CMT pigs. (D) Hepatic cholesterol (TC) content in IM, CM, and CMT pigs. IM: intact male pigs fed an HFC diet; CM: castrated male pigs fed an HFC diet; CMT: castrated male pigs fed an HFC diet and given testosterone replacement therapy. Data are expressed as means ± SEMs, n = 6 per group. *P < 0.05; **P < 0.01.

Consistent with the observed increase in lipid deposition, we also detected marked increases in TG contents in the livers of CM pigs (Figure 3C). Moreover, testosterone treatment reduced hepatic TG contents in CM pigs (Figure 3C). Likewise, hepatic cholesterol contents in CM pigs were also significantly higher than those in IM and CMT pigs (P < 0.05; Figure 3D).

Gene expression analysis by RNA-Seq

To obtain a global view of the hepatic transcriptome responses to testosterone deficiency and testosterone treatment in pigs fed an HFC diet, we performed comparative RNA-Seq analyses of the liver transcriptomes. cDNA libraries were constructed using total RNA isolated from the livers of IM, CM, and CMT pigs. Using an Illumina HiSeq 2000 sequencer, we obtained approximately 40.58, 45.39, and 32.33 million high quality clean reads from IM, CM, and CMT pigs, respectively. For each sample, ~87% of reads could be mapped to the pig reference genome; of these mapped reads, ~79% aligned with unique genes unambiguously (Table 2).
Table 2

Summary of the sequencing reads alignment to the reference genome

Statistics term




All reads




Unmapped reads




Mapped reads




Mapping rate




Unique mapping




Unique mapping rate




Repeat mapping




In total, 18093, 18418, and 17740 expressed genes were detected in the livers of IM, CM, and CMT pigs, respectively. Of these genes, a total of 16981 genes were expressed in all three groups; 584, 315, and 191 genes were identified commonly between each pair of groups (CM versus IM, CMT versus CM, and CMT versus IM, respectively), while 337, 538, and 253 genes were discovered exclusively for IM, CM, and CMT, respectively (Additional file 1; Figure 4A). To identify differentially expressed genes (DEGs) in the livers of IM, CM, and CMT pigs, gene expression data from each group were compared using DEGSeq software [22]. Significance scores were corrected for multiple testing using the Benjamini-Hochberg correction [23]. We used the following criteria to identify DEGs: (1) gene expression level greater than or equal to 1 fragment per kilobases of exon per million fragments mapped (FPKM) in all samples; (2) change in expression level greater than or equal to 1.5 fold; and (3) a false discovery rate (FDR) of less than 0.05 [24]. Thus, a total of 1635 (826 upregulated and 809 downregulated), 1847 (915 upregulated and 934 downregulated), and 671 (313 upregulated and 358 downregulated) DEGs were detected in the livers of pigs for CM versus IM, CMT versus CM, and CMT versus IM groups, respectively (Figure 4B). In total, 2595 different genes were differentially expressed between any two groups (Figure 4C; DEG list provided in Additional file 2).
Figure 4
Figure 4

RNA-Seq analyses of differentially expressed genes (DEGs) in livers of IM, CM, and CMT pigs. (A) The numbers of upregulated and downregulated DEGs between groups. (B) Venn diagram showing the overlap of DEGs between groups. (C) Heat map for hierarchical cluster analysis of DEGs between samples. Red: upregulated genes; yellow: downregulated genes. IM: intact male pigs fed an HFC diet; CM: castrated male pigs fed an HFC diet; CMT: castrated male pigs fed an HFC diet and given testosterone replacement therapy.

Gene Ontology (GO) enrichment analysis of DEGs

To gain further insights into the biological functions of DEGs, we performed GO analyses by querying each DEG identified in the livers of IM, CM, and CMT pigs against the GO database. GO analysis of significantly upregulated DEGs between CM and IM pigs revealed genes that were mainly enriched in immune-related processes, such as the type I interferon signaling pathway, the cytokine-mediated signaling pathway, immune responses, innate immune responses, antigen processing and presentation, and apoptosis (Additional file 3). Downregulated DEGs were mainly involved in metabolism-related processes, such as lipid metabolism, fatty acid metabolism, fatty acid beta-oxidation, bile acid metabolic processes, steroid metabolic processes, ketone body biosynthetic processes, cholesterol metabolic processes, and the tricarboxylic acid and gluconeogenesis pathways (Additional file 3). Upregulated DEGs between CMT and CM pigs revealed genes that were mainly involved in metabolism-related processes, such as lipid metabolism, fatty acid metabolism, fatty acid beta-oxidation, steroid metabolism, bile acid metabolism, cholesterol metabolism, ketone body biosynthesis, and the tricarboxylic acid and gluconeogenesis cycles, while downregulated DEGs were mainly enriched in immune-related processes, such as the type I interferon signaling pathway, the cytokine-mediated signaling pathway, innate immune responses, immune responses, apoptosis, antigen processing and presentation, inflammatory responses, and responses to oxidative stress (Additional file 4).

The enriched GO analyses of all significant DEGs between any two groups were also investigated and were found to be mainly involved in small molecule metabolism, metabolic processes, lipid metabolism, fatty acid metabolism, steroid metabolism, cholesterol metabolism, fatty acid beta-oxidation, immune responses, inflammatory responses, apoptosis, and responses to oxidative stress (Figure 5A, Additional file 5).
Figure 5
Figure 5

Gene ontology (GO) and pathway analysis of differentially expressed genes (DEGs). (A) Top 20 significant GO terms (biological processes) associated with the identified DEGs. The vertical axis represents the GO category, and the horizontal axis represents the -Log2(P-value) of the significant GO terms. (B) Top 20 significant pathways involving DEGs. The vertical axis represents the pathway category, and the horizontal axis represents the -Log2(P-value) of the significant pathways. Greater -Log2(P-value) scores correlated with increased statistical significance.

Pathway analysis of DEGs

Pathway analysis using the KEGG database was performed to determine significant pathways involving the DEGs identified in this study. Our results showed that 64 pathways were significantly enriched for the identified DEGs (P < 0.05; Figure 5B). The enriched pathways are listed in Additional file 6. Moreover, pathway analysis showed that these genes were mainly involved in metabolic pathways, steroid hormone biosynthesis, the PPAR signaling pathway, peroxisomes, fatty acid degradation, pyruvate metabolism, steroid biosynthesis, the nuclear factor-kappaB (NF-κB) signaling pathway, primary bile acid biosynthesis, antigen processing and presentation, the tricarboxylic acid cycle, synthesis and degradation of ketone bodies, and glycerolipid metabolism (Figure 5B, Additional file 6).

Series-cluster analysis of DEGs

To refine the set of genes that were differentially expressed between any group, we categorized the 2595 DEGs into seven possible model profiles (Additional file 7) to enrich for gene expression tendencies using the Short Time-Series Expression Miner (STEM) program [25]. We identified two patterns of gene expression (profiles 2 and 5, Additional file 8) with significance (P < 0.05; Figure 6A). Profile 2 contained 738 genes that were characterized by decreased expression in CM pigs but increased expression in the CMT group. In contrast, profile 5 contained 869 genes that were characterized by increased expression in CM pigs but exhibited decreased expression in the CMT group. Significantly enriched GO terms from profiles 5 and 2 are illustrated in Figure 6B and Additional files 9 and 10. Cluster analysis showed that the significantly enriched GO terms from profile 5 were closely correlated with immune and inflammatory responses. The included genes were enriched in the type I interferon signaling pathway, cytokine-mediated signaling pathways, regulation of immune responses, innate immune responses, immune responses, and antigen processing and presentation (Figure 6B, Additional file 9). Profile 5 genes were also enriched in apoptotic processes and positive regulation of chemokine secretion (Additional file 9).
Figure 6
Figure 6

Significant gene expression tendencies and gene ontology (GO) analysis. (A) Differentially expressed genes between the groups described in Additional file 3 (Table S4) were separated into seven possible model profiles, including two significant gene expression tendencies (profiles 2 and 5). Profile 2 included 737 genes that were decreased in CM pigs, but increased in CMT pigs. Profile 5 included 838 genes that were increased in CM pigs, but decreased in CMT pigs. (B) Significantly enriched GO terms in profiles 2 and 5. The top 15 biological functions and the case genes in each cluster are listed. IM: intact male pigs fed an HFC diet; CM: castrated male pigs fed an HFC diet; CMT: castrated male pigs fed an HFC diet and given testosterone replacement therapy.

The genes involved in immune and inflammatory responses are displayed and clustered in Figure 7A. To verify the observed differential mRNA expression of immune and inflammatory response genes, we performed quantitative real-time RT-PCR (qRT-PCR) using RNA samples extracted from the livers of IM, CM, and CMT pigs. The hepatic expression of six immune and inflammatory response-related genes (IRF7, CXCL9, CXCL14, CCL2, CCR1, and TLR-2) was analyzed in the three groups. Consistent with RNA-Seq results, the expression of these six genes was upregulated in CM pigs and downregulated in CMT pigs after testosterone treatment (Figure 7B). In addition to qRT-PCR validation experiments, we also employed immunohistochemistry to examine the protein expression levels of CCL2, CXCL9, and IRF7 (Figure 7C), which are involved in the development of NAFLD. Based on immunostaining results, we observed similar differences in expression at the protein level. Staining levels tended to be increased in the livers of CM pigs compared to those observed in IM pigs (Figure 7C). However, this positive staining was reduced after testosterone treatment (Figure 7C).
Figure 7
Figure 7

Expression of genes involved in immune and inflammatory responses. (A) Heat map for genes involved in immune and inflammatory responses. (B) Expression levels of six genes detected by quantitative real-time RT-PCR (yellow box) were in agreement with the RNA-Seq results. Data are expressed as means ± SEMs, n = 6 per group. (C) Immunohistochemical assessment of chemokine (C-C motif) ligand 2 (CCL2), chemokine (C-X-C motif) ligand 9 (CXCL9), and interferon-regulatory factor 7 (IRF7), showing expression changes that were in accordance with the RNA-Seq and qRT-PCR results. IM: intact male pigs fed an HFC diet; CM: castrated male pigs fed an HFC diet; CMT: castrated male pigs fed an HFC diet and given testosterone replacement therapy. Scale bars = 100 μm.

Profile 2 genes were mainly enriched in various metabolic subprocesses, including fatty acid metabolism, fatty acid beta-oxidation, steroid biosynthesis, cholesterol and bile acid metabolism, and glucose metabolism (Figure 6B, Additional file 10). We found that the most genes enriched in fatty acid metabolic processes were involved in fatty acid oxidation (Figure 8A). It is well known that impaired fatty acid oxidation contributes to NAFLD; thus, we analyzed the genes participating in fatty acid oxidation further. Carnitine palmitoyltransferase 1A (CPT-1A) encodes the rate-limiting enzyme in fatty acid oxidation, which was downregulated 2.36-fold in the livers of CM pigs and upregulated 2.30-fold in the livers of CMT pigs. Peroxisome proliferator-activated receptor delta (PPARD) belongs to a class of ligand-dependent transcription factors involved in hepatic lipid metabolism and was downregulated 2.18-fold in the livers of CM pigs and upregulated 1.81-fold in the livers of CMT pigs. Moreover, the ACADL, ACOX1, ACO, and ECIl genes, encoding long-chain acyl-CoA dehydrogenase, palmitoyl acyl-CoA oxidase 1, acyl-CoA oxidase, and mitochondrial enoyl-CoA isomerase, respectively, were 2.66-, 2.05-, 1.99-, and 1.95-fold downregulated in the livers of CM pigs and 4.00-, 1.65-, 1.51-, and 2.52-fold upregulated in the livers of CMT pigs, respectively (Figure 8).
Figure 8
Figure 8

Expression of genes involved in fatty acid oxidation and cholesterol, bile acid, and glucose metabolism. (A) Heat map for genes involved in fatty acid oxidation. (B) Heat map for genes involved in cholesterol and bile acid metabolism. (C) Heat map for genes involved in glucose metabolism. (D, E) Expression levels of six genes detected by quantitative real-time RT-PCR (qRT-PCR) that were in agreement with the RNA-Seq results. Data are expressed as means ± SEMs, n = 6 per group. (F, G) Western blot analysis of peroxisome proliferator-activated receptor delta (PPARD) and carnitine palmitoyltransferase 1A (CPT-1A) showing expression changes that were in accordance with RNA-Seq and qRT-PCR results. IM: intact male pigs fed an HFC diet; CM: castrated male pigs fed an HFC diet; CMT: castrated male pigs fed an HFC diet and given testosterone replacement therapy. Data are expressed as means ± SEMs, n = 5 per group. *P < 0.05.

Enriched genes mediating cholesterol, bile acid, and glucose metabolism are also displayed in Figure 8. Genes involved in cholesterol biosynthesis (PMVK and TM7SF2), cholesterol esterification (LCAT and SORT2), cholesterol transport and absorption (LDLR and LIPC), and bile acid metabolic processes (NR1H4 and HSD3B7) were downregulated in the livers of CM pigs, but restored by testosterone treatment (Figure 8B). Several genes encoding enzymes involved in glucose metabolism were also downregulated in CM pigs. For example, PCK1, encoding the rate-limiting gluconeogenesis enzyme phosphoenolpyruvate carboxykinase (PEPCK), and PFKFB1, encoding the glycolysis enzyme 6-phosphofructo-2-kinase, were decreased in the livers of CM pigs, but increased in the livers of CMT pigs after testosterone treatment (Figure 8C).

We performed qRT-PCR to verify the mRNA expression profiles of the fatty acid oxidation-related genes CPT1A, PPARD, ACADL, ACO, ACOX1, and 3-hydroxyacyl-CoA dehydrogenase (HADH). Consistent with RNA-Seq analysis, the expression of these six genes was downregulated in CM pigs and upregulated in CMT pigs after testosterone treatment (Figure 8D, E). We then measured the protein expression levels of CPT1A and PPARD by western blot analysis. The protein levels of CPT1A and PPARD were decreased in the livers of CM pigs as compared to IM pigs and were increased in CMT pigs after testosterone treatment (Figure 8F, G).

Pathway-Act-Network analysis

To further understand the importance of pathway interactions and to screen key pathways for significant roles in NAFLD induced by testosterone deficiency and an HFC diet, we built a Pathway-Act-Network according to the direct or systemic interactions assigned between pathways in the KEGG database (Figure 9, Additional file 11). As shown in Figure 9, some DEGs involved in key pathways during NAFLD were identified, including metabolic pathways, fatty acid degradation, pyruvate metabolism, and the citrate cycle. Moreover, glycerolipid metabolism and the NF-κB signaling pathway in the interaction network were also predicted to play important roles.
Figure 9
Figure 9

Pathway-Act-Network analysis. The Pathway-Act-Network was built according to the interactions with pathways identified in the KEGG database. Cycle nodes represent pathways, and the arrow between two nodes represents an interaction target between pathways. The size of nodes represents the power of the interaction among the pathways (Additional file 11). Red nodes represent significant pathways and green nodes represent nonsignificant pathways.

To display a detailed pathway of fatty acid degradation and the relative differences in genes influenced by testosterone, a putative pathway of fatty acid degradation was constructed based on KEGG mapping. Enzymes and proteins involved in regulating fatty acid degradation (CPT-1A, ACO, and ACADL) were decreased in CM pigs, but recovered in CMT pigs (Additional file 12). We also constructed a putative pathway of peroxisome-related processes according to KEGG mapping (Additional file 13). Similarly, several genes involved in regulating peroxisome processes, such as PMP70 and PEX14, were decreased in CM pigs, but increased in CMT pigs.


In this work, we studied the effects of testosterone on the development of hepatic steatosis in pigs fed an HFC diet. Our data indicated that serum cholesterol (TC and LDL-C, but not HDL-C) and TG levels were significantly higher in CM pigs than in IM pigs. Moreover, testosterone deficiency exacerbated liver injury and increased hepatic TG contents (hepatic steatosis) in CM pigs. However, testosterone replacement attenuated these effects in CM pigs, suggesting that testosterone may play a protective role in diet-induced hepatic steatosis. In previous studies, researchers have used rodent models to evaluate the effects of testosterone on NAFLD; however, several of these were genetic animal models, i.e., androgen receptor (AR)-knockout mice [14] and Tfm mutant mice [7]. These models may have some utility for specific research aims, but most humans that develop NAFLD have few genetic defects. Other studies have also used orchidectomized mouse models; however, these animals do not have increased adiposity [26] or have reduced serum TG levels [6,26], which are inconsistent with findings in humans. We showed here that a porcine model of NAFLD induced by testosterone deficiency and HFC diet mimicked human fatty liver disease in terms of histological analyses and metabolic profiles. To the best of our knowledge, the present study is the first to demonstrate that testosterone deficiency aggravates diet-induced hepatic steatosis in a porcine model. Testosterone deficiency also caused significant changes in body fat percentages and serum biochemical parameters. Previous studies have shown that enzymes involved in fatty acid synthesis are increased in adipose tissues of castrated male pigs [19]. Thus, the higher body fat content observed in CM pigs may be due to the increased fatty acid synthesis in adipose tissue [27]. Estradiol has been reported to decrease fatty acid synthesis by increasing the phosphorylation of acetyl coenzyme-A carboxylase in rats fed a high-fat diet [15]. Moreover, previous studies have reported that serum ALT levels are significantly elevated in ovariectomized mice fed an HFC diet [8], and estradiol administration reduces hepatic MDA content but increases SOD activity in rats with hepatic fibrosis [28]. Thus, the significant changes in body fat and serum parameters induced by castration may be partly attributed to a reduction in estradiol [20]. However, we did not measure hepatic estradiol levels, and elucidation of the role of estrogens in the regulation of fat metabolism and serum parameters was not the primary goal of our study; these will be investigated in future studies.

In this study, we found that testosterone deficiency did not affect serum fasting glucose and insulin levels or HOMA-IR in CM pigs compared to IM pigs. However, testosterone replacement significantly reduced serum insulin levels and HOMA-IR in CM pigs. While previous studies have shown that androgen deficiency increases fasting glucose levels and reduces insulin sensitivity (IR) [29,30], the effects of testosterone on glucose metabolism and IR in clinical observations and experimental studies have not been consistent. For example, several studies have shown that low serum testosterone levels are associated with IR in men and that androgen therapy improves IR and fasting glucose levels in men [31,32]. However, other studies have found that reduction of testosterone levels in men did not significantly affect fasting glucose levels or IR [33,34]. Moreover, castration results in slightly increased fasting glucose levels, but has no effects on fasting insulin concentrations and IR in rats [35]. However, Nikoleanko et al. [26] showed that fasting glucose, fasting insulin, and HOMA-IR levels were not elevated in castrated male rats compared to intact animals and animals receiving testosterone replacement therapy. Using different mouse strains and diets, Inoue et al. [36] also indicated that castration does not induce serum glucose and insulin levels or related IR markers in any of the mouse models studied. To date, few reports have described the effects of testosterone on glucose metabolism and IR in pigs. Our previous study showed that there were no differences in serum levels of glucose and insulin between intact and castrated male pigs fed a normal diet [19]. In the present study, we still found that testosterone deficiency did not change fasting serum glucose and insulin levels in pigs fed an HFC diet. Our results were not consistent with those obtained by Christofferson et al. [20], who found that castration results in disturbed glucose metabolism. These discrepancies may be explained by breed differences and the different experimental model of testosterone deficiency.

Little is known regarding the molecular mechanisms underlying the testosterone deficiency-mediated promotion of fat deposition in the liver. Hepatic steatosis is regulated by multiple metabolic pathways. Previous studies have shown that disturbances in fatty acid oxidation account for excess lipid storage in the liver [37,38]. We found that many genes involved in fatty acid oxidation were downregulated in the livers of CM pigs, and these effects were prevented by testosterone replacement. PPARD regulates lipid oxidation processes [39,40], but its role in hepatic lipid metabolism remains unclear. We found that the levels of PPARD mRNA and protein were significantly reduced in the livers of CM pigs, and testosterone treatment restored the expression of PPARD in CMT pigs. These results are consistent with those obtained by Barroso et al. [41] and Bolic et al. [42], who showed that PPARD activation stimulates hepatic fatty acid oxidation and alleviates diet-induced hepatic steatosis. Moreover, this observation suggests that PPARD may be regulated by sex hormones and plays key roles in the regulation of hepatic steatosis; this provides a novel view of PPARD function in the modulation of hepatic lipid metabolism. In addition to its effects on lipid metabolism, PPARD has been reported to play roles in the regulation of glucose metabolism and IR [40,43]. Studies in genetic and diet-induced IR or diabetic mice have shown that PPARD exerts beneficial effects to ameliorate IR [40,43-45]. Because of our data regarding PPARD, and since the involvement of PPARD in IR is well established, we would expect that markers of IR in CM pigs should be elevated compared with those in IM and CMT pigs. However, there was no difference in fasting glucose, insulin, or HOMA-IR levels in CM pigs compared to IM pigs. Previous studies have indicated that PPARD regulates glucose flux and IR through the pentose phosphate pathway [40,43,46]. However, our transcriptomics data did not reveal any changes in the expression levels of glucose-6-phosphate dehydrogenase (G-6-PDH) and phosphogluconate dehydrogenase (PGD) (two key enzymes in the pentose phosphate pathway) in the livers of CM pigs compared to those of IM pigs. Moreover, PPARD has been reported to reduce glucose production indirectly via activation of AMPK rather than through a direct mechanism [40,47]. In our study, expression levels of AMPK and adiponectin signaling genes (ADIPOQ, ADIPOR1, and ADIPOR2) were not changed in CM pigs compared to IM pigs. Activation of PPARD has failed to enhance severe IR [47-49]. Moreover, in recent studies in rats and mice fed a high-fat diet, heterogeneous effects of PPARD on IR have been observed [49]. Thus, the reasons for the discrepancy between PPARD expression and IR markers in this study may be due to the different effects of PPARD on IR in different species [49]. However, testosterone replacement significantly improved fasting insulin and HOMA-IR levels and restored PPARD expression in CM pigs, despite the observation that gonadectomy apparently did not change fasting insulin, glucose, or HOMA-IR levels compared to those in intact pigs. CPT-1A is the rate-limiting enzyme of mitochondrial β-oxidation [50]. We found that hepatic CPT1A mRNA and protein levels were significantly reduced in the livers of CM pigs and subsequently restored in CMT pigs receiving testosterone supplementation. Other fatty acid oxidation-related genes, such as ACADL, ACOX1, ACO, HADH, and short chain enoyl-CoA hydratase (ECHS1) were also downregulated in the livers of CM pigs. Taken together, our results provided strong evidence that testosterone deficiency aggravated hepatic fat accumulation in CM pigs partly due to decreased hepatic fatty acid oxidation. Our results are consistent with a human study in which men with short-term hypogonadism showed decreased whole-body lipid oxidation [51]. Moreover, Lin et al. [14] observed reduced fatty acid oxidation in isolated primary hepatocytes from hepatic AR-knockout (H-AR-/y) mice, consistent with our results. Peroxisomes have many important functions in lipid metabolism, including fatty acid β-oxidation. A previous study reported that impaired peroxisome function contributes to NAFLD in mice [52]. In this study, we also found that the PMP70, PEX14, and PEM34 genes, which are involved in peroxisome-related processes, were downregulated in the livers of CM pigs. These results suggested that testosterone deficiency led to increased hepatic steatosis in CM pigs by affecting peroxisome function.

In addition to the decrease in liver fat oxidation, increased fat synthesis may also contribute to elevated liver fat accumulation [53]. TGs are the main lipids that accumulate during hepatic steatosis [54]. Glycerol 3-phosphate acyltransferase (GPAT) and diacylglycerol acyltransferase (DGAT) catalyze the initial and final steps in TG synthesis, respectively [55,56]. Increased levels of DGAT1 mRNA occur in the livers of humans with NAFLD [57], indicating the importance of DGAT1 in fatty liver development. Mice lacking DGAT1 have reduced tissue TG levels and are protected against hepatic steatosis [56]. Studies using GPAT-knockout mice [58] and mice overexpressing GPAT in the liver [55] have implicated this enzyme in hepatic steatosis. Stearoyl-CoA desaturase (SCD) catalyzes the de novo biosynthesis of monounsaturated fatty acids (mainly oleate and palmitoleate), which are critical substrates for the synthesis of TGs by GPAT [59]. To date, few studies have been conducted to explore the effects of testosterone on hepatic TG synthesis enzymes. Senmaru et al. [6] reported that orchidectomized mice fed HFD showed significantly increased DGAT2 expression. A recent study revealed that SCD1 expression was significantly elevated in Tfm mice than in wild-type controls [7]. These observations are consistent with our findings that the expression of the TG synthesis genes GPAT, DAGT, and SCD were significantly upregulated in the livers of CM pigs and that testosterone replacement reduced their expression in CM pigs. Our results suggested that testosterone deficiency might increase liver fat accumulation by inducing hepatic TG synthesis. Acetyl-CoA carboxylase alpha (ACACA) and fatty acid synthase (FASN) are also key lipogenic enzymes involved in hepatic lipid deposition. A recent study showed that hepatic ACACA and FASN expression levels were elevated in Tfm mice compared with wide-type littermates [7]. However, Nikolaenko et al. [26] found that there were no significant differences in liver FASN protein levels in C + HFD mice after castration. These results are inconsistent with our findings, which showed decreased ACACA and FASN expression in the livers of CM pigs. These differences might be species-specific or result from different experimental models of hepatic steatosis. In addition, hepatic fatty acid synthesis requires acetyl-CoA generated from multiple metabolic pathways, including glycolysis, the tricarboxylic acid cycle, and fatty acid β-oxidation [60]. Thus, the observed decrease in ACACA and FASN expression may be due to impaired glucose metabolism or fatty acid oxidation in the present study.

The spectrum of NAFLD ranges from simple fatty liver (hepatic steatosis) to nonalcoholic steatohepatitis (NASH; steatosis with inflammation and fibrosis). The “two-hit” theory of NAFLD progression proposes that inflammation, oxidative stress, and apoptosis play critical roles in the pathological progression of NAFLD [61]. Gene expression profiling indicated that several immune and inflammatory response genes were activated in the livers of CM pigs. Chemokines direct the trafficking of immune cells to sites of inflammation [62]. Chemokine (C-C motif) ligand 2 (CCL2; commonly known as monocyte chemoattractant protein-1 [MCP-1]) is one of the most important chemokines involved in inflammation, and elevated levels of CCL2 have been confirmed in the livers of patients with NAFLD [63,64]. Moreover, increased hepatic and serum MCP-1 expression levels have been described in diet-induced NAFLD [62,65]. Expression levels of C-C chemokine receptor 1 (CCR1) and chemokine (C-X-C motif) ligands 9, 10, 14 (CXCL9, CXCL10, and CXCL14) are increased in livers during HFD-induced hepatic steatosis [65-67]. We found that testosterone deficiency significantly increased mRNA and protein levels of the CCL2, CXCL9, CCR1, CXCL10, and CXCL14 chemokines in the livers of CM pigs, and testosterone replacement abolished these effects. Our data suggested that the induction of pro-inflammatory chemokines contributes to the mechanism of inflammatory recruitment in hepatic steatosis induced by testosterone deficiency and an HFC diet. Moreover, clinical and experimental observations have shown that tumor necrosis factor (TNF) may have a pathogenic role during NAFLD development, specifically by modulating chronic lobular inflammation with hepatocellular injury [63,67]. We found that hepatic TNF expression was reduced in CM pigs. This is inconsistent with previous observations [63,68]. Dela Pena et al. [69] demonstrated that knocking out the TNF gene does not prevent diet-induced NAFLD in mice. Similar studies by Deng et al. [70] showed that TNFR1-knockout mice still develop hepatic steatosis. Taken together, these studies suggest that TNF may not be a critical mediator of inflammation in this experimental form of hepatic steatosis. In the present study, numerous immunity and inflammation-related processes, including antigen processing and presentation, cytokine-mediated signaling pathways, and chronic inflammatory responses were induced in the livers of CM pigs. Interestingly, previous studies have shown marked induction of numerous immunity- and inflammation-related pathways in PPARD−/− mice [46]. Moreover, activation of PPARD may improve hepatic steatosis via directly suppressing the expression of cytokines or transcription factors associated with inflammation [71,72]. These observations suggest that testosterone deficiency may induce immune and inflammatory responses through modulation of hepatic PPARD expression. Moreover, testosterone has been suggested to act directly on immune cells by repressing transcription factors (such as FOS, JUN, and others) [73,74]. In our study, CM pigs had higher FOS expression than IM pigs. Moreover, testosterone replacement significantly reduced the increased FOS expression in CMT pigs. These results suggested that testosterone may inhibit liver FOS expression in CM pigs, thereby regulating the expression of genes involved in the immune response [74]. Additionally, previous studies have shown that testosterone can bind to intracellular receptors located in immune cells and activate hormone-responsive genes [74,75]. In our study, androgen receptor expression was reduced by about 1.8 fold in the livers of CM pigs compared to those in IM and CMT pigs, suggesting that testosterone may interact with immune cells through its receptor. Therefore, further studies are needed to elucidate the precise mechanisms mediating the observed responses.

Oxidative stress plays critical roles during the development of NAFLD [9]. SOD1 is an important antioxidant enzyme that can reduce reactive oxygen species and protect hepatocytes. SOD1 deficiency caused high levels of oxidative stress in the liver, resulting in hepatic lipid accumulation in mice [76]. In the present study, hepatic SOD1 gene expression was significantly decreased in the livers of CM pigs compared to IM pigs, suggestive of a reduced defense mechanism against oxidative stress. In contrast to SOD1, cytochrome P450 2E1 (CYP2E1) exerts pro-oxidant activity and may enhance oxidative stress. CYP2E1 expression in the liver is increased in humans and animal models of NAFLD [77]. Moreover, CYP2E1-null mice are protected against HFD-induced obesity and hepatic steatosis [78]. We showed that testosterone deficiency significantly induced hepatic expression of CYP2E1 and that testosterone replacement abolished these effects. Our data are in accordance with a previous study showing higher levels of CYP enzymes (including CYP2E1) in hepatic tissues of castrated ethanol-fed micropigs than in noncastrated counterparts [79]. Increased oxidative stress may induce hepatocyte apoptosis, resulting in more severe liver injury [80]. Although hepatic apoptosis was not detected histologically, it is important to note that several genes associated with apoptosis, including B-cell leukemia/lymphoma-2 (BCL2), caspase-2 (CASP2), and bcl-2 associated-x (BAX), were upregulated in the livers of CM + HFC pigs in response to testosterone deficiency in the present study. Similar to our study, Nikolaenko et al. [26] demonstrated that testosterone treatment improved diet-induced hepatic apoptosis in mice fed a high-fat diet.

The limitations of the current study include the small number of animals studied and the lack of confirmation of the results using human samples. Despite the fact that pigs have served as a suitable animal model for studying NAFLD, few animal models can entirely reflect the natural course and causative background of human NAFLD. Thus, it would be best to validate the identified DEGs in patients with hepatic steatosis. Furthermore, the dietary animal model used here did not manifest high serum TG levels, although pigs developed severe hypercholesterolemia and hepatic steatosis. The amount and type of dietary fat and diet duration may have influenced these effects. These issues should be addressed in future studies.


In summary, we demonstrated here that testosterone deficiency may aggravate hepatic steatosis and hypercholesterolemia in pigs fed an HFC diet, and these effects were improved by testosterone treatment. Importantly, hepatic transcriptomic analysis revealed that increased hepatic steatosis induced by testosterone deficiency and an HFC diet was mediated by altered expression of genes involved in multiple metabolic processes. We observed abnormal regulation of fatty acid metabolism and found that the expression of fatty acid oxidation-related genes was reduced in the livers of CM pigs. Moreover, genes associated with immune and inflammatory responses, oxidative stress, and apoptosis also contributed to the increased hepatic steatosis. These observations provide a molecular basis for understanding the mechanisms through which testosterone deficiency aggravates the progression of diet-induced hepatic steatosis.


Experimental animals

Eighteen sexually mature male Chinese Wuzhishan (WZS) miniature pigs (6–7 months old) were obtained from the Institute of Animal Sciences, Hainan Academy of Agricultural Sciences (Haikou, China). The animals were housed in single pens with a 12-h light/dark cycle. The room temperature was maintained at 22 ± 3°C, with a relative air humidity of 50% ± 20%. Before and after their arrival, the animals were fed a standard swine diet and had free access to water. The animals received a standard diet without cholesterol during a 7-week “pretreatment period” for acclimation to the environment and baseline determinations. At week 7, the pigs were either surgical castrated or given a sham operation as described previously [81]. Testosterone was administrated weekly to castrated pigs via intramuscular injection with testosterone propionate (10 mg/kg body weight; Sigma-Aldrich, St. Louis, MO, USA) dissolved in corn oil [82]. Testosterone replacement therapy was given on the same day of castration to avoid disruption of hormonal influences. The pigs were fed an HFC diet starting from week 8 and were divided into three groups (n = 6 animals/group) as follows: intact male pigs fed an HFC diet (IM), castrated male pigs fed an HFC diet (CM), and castrated pigs with testosterone replacement fed an HFC diet (CMT). The HFC diet was comprised of 73% normal swine diet, 15% lard, 10% egg yolk power, 1.5% cholesterol, and 0.5% sodium cholate. The HFC diet was similar to an atherogenic diet, which has been shown to induce hepatic steatosis and atherosclerosis [38,83]. Body weights were recorded every week for 12 weeks. All experimental procedures used in this study were approved by the Institutional Animal Care and Use Committee of the Zhejiang Chinese Medical University (Hangzhou, China).

At the end of the experimental period, the animals were killed by exsanguination under sodium pentobarbital anesthesia. The carcasses were eviscerated according to the procedures as previously described [19], and the carcass fat from the left side of each animal was weighed. Livers were removed and weighed, and liver weight indexes were calculated as the liver weight/body weight ratio (g/kg). Livers were then frozen immediately in liquid nitrogen and stored at −80°C for further analysis.

Serum measurements

Fasting blood samples were collected prior to castration and twice weekly throughout the study. Sera were separated from collected blood samples by centrifugation at 3000 × g at 4°C for 15 min and stored at −80°C for further analysis. Serum testosterone and Insulin concentrations were measured at week 7 (0 w; the start of the experimental period after the 7-week acclimation) and week 19 (12 w; the end of the experimental period), using a commercial RIA kit (Beijing North Institute of Biological Technology, Beijing, China). Serum TGs, TC, HDL-C, LDL-C, glucose, ALT, and AST were measured with an Automatic Biochemistry Analyzer (Hitachi 7020, Tokyo, Japan). HOMA-IR was calculated using the formula, base glucose × base insulin/22.5 [8,26]. Serum FFAs, SOD, glutathione peroxidase (GSH-PX), and MDA were measured using commercially available kits (Nanjing Jiancheng Biotech, Inc., Nanjing, China).

Biochemical analysis in liver samples

Hepatic lipids were measured using the methods described by Shi et al. [84] with slight modifications. Briefly, liver samples from each pig were homogenized at 4°C in phosphate-buffered saline (PBS, pH 7.2). Supernatants were then centrifuged at 3000 × g for 10 min at 4°C, and TG and TC levels were determined using commercially available kits (Rongsheng Biotech, Inc., Shanghai, China) according to the manufacturer’s instructions. Protein concentrations in the liver samples were measured with a BCA Assay Kit (Pierce, Rockford, IL, USA).

Liver histology

For histopathological analysis, pig liver tissues were fixed in 10% formalin, embedded in paraffin, and sectioned at 5-μm thicknesses using a microtome (Leica, Wetzlar, Germany). Subsequently, sections were stained with hematoxylin and eosin (H&E). In addition, frozen liver samples were embedded in Tissue-Tek OCT Compound (Sakura Finetek, Torrance, CA, USA), sectioned at 10-μm thicknesses using a cryostat (Leica), and stained with Oil Red O (Sigma-Aldrich) to study fat deposition. For each of the indicated histological procedures, representative photomicrographs were taken with a light microscope (Nikon Eclipse 80i, Nikon, Tokyo, Japan).

cDNA library preparation and Illumina sequencing

Liver tissues from pigs were subjected to total RNA extraction using TRIzol reagent (Invitrogen, Carlsbad, CA, USA) according to the manufacturer’s instructions. RNA samples were purified using an RNeasy Mini Kit (Qiagen, Hilden, Germany). RNA integrities were assessed with a 2100 Bioanalyzer (Agilent Technologies, Inc., Santa Clara, CA, USA) and agarose gel electrophoresis. All samples had a RNA integrity number (RIN) of more than 8.5. To reduce variation among individuals within each of the three groups, total RNA from pigs of the same group was pooled together in equal amounts to generate a mixed sample [85,86]. These three pooled RNA samples were subsequently used for cDNA library construction and Illumina deep sequencing. Sequencing libraries were prepared using a TruSeq RNA Sample Preparation Kit (Illumina, San Diego, CA, USA) according to the manufacturer’s instructions. Briefly, 10 μg of each total RNA sample was processed via poly-A selection with oligo(dT) magnetic beads and fragmentation. The resulting fragmented mRNAs were then processed by first-strand cDNA synthesis using reverse transcription with random primers, followed by second-strand cDNA synthesis using DNA polymerase I and RNase H (Invitrogen). Paired-end (PE) oligo adapters (Illumina) were then added to the cDNA fragments with T4 ligase. The resulting cDNA fragments were purified and enriched by polymerase chain reaction (PCR). The cDNA libraries were sequenced with an Illumina HiSeq2000 (Illumina), which generated paired-end raw reads of approximately 100-bp in size.

Raw sequencing data were evaluated by FAST-QC (, an online bioinformatics program used to characterize quality distributions of nucleotides, position-specific sequencing qualities, GC contents, the proportions of PCR duplication, and k-mer frequencies [87]. Raw reads after quality control testing were then mapped to the reference pig genome version 10.2 (Sscrofa 10.2), using TopHat software [88] with default parameters.

Analysis of DEGs

We applied the DEGSeq [22] algorithm to filter DEGs. The resulting significance scores were corrected for multiple testing using the Benjamini-Hochberg (BH) method [23]. An FDR of 0.05 or less and an absolute fold change of 1.5 or more were set as thresholds to evaluate the significance of gene expression differences [24]. The clustering software Cluster 3.0 was used to perform hierarchical clustering analysis. Clustering results were visualized using the Java TreeView program [89].

Functional enrichment analysis

To investigate gene functions and uncover signaling networks/pathways among the selected DEGs, GO analysis was applied to analyze the main function of DEGs according to the NCBI Gene Ontology database, which provides key functional classifications for genes [90]. According to the methods described by Wang et al. [91], Fisher’s exact test and the χ 2 test were used to classify the GO terms, and the FDR was calculated to correct the P-value. The smaller the FDR, the smaller the error would be when evaluating the P-value. The FDR was defined as \( DR=1-\frac{N_k}{T} \), where N k refers to the number of Fisher’s test P-values less than the χ 2 test P-values. Enrichment provided a measure of the significance of the function, such that as the enrichment was increased, the corresponding function was more specific, which aided in experimentally identifying GOs with more concrete functions [91]. GO categories with P-values of less than 0.01 after correction by FDR were selected for further analysis.

Pathway analysis was used to determine significant pathways associated with DEGs according to KEGG ( As with the GO analysis, Fisher’s exact test was used to classify significantly enriched pathways, and the resulting P-values were adjusted using the FDR algorithm. During the analysis of KEGG pathway terms, we required corrected P-values to be less than 0.05. In addition, the enriched pathways were selected to build Pathway-Act-Networks according to the relationships identified between the pathways in the KEGG database. Pathway assignments were also performed using the KEGG database and KegArray software [92].

The expression profiles of DEGs were determined by cluster analysis based on the STEM method ( [25,93]. Significant profiles were identified using Fisher’s exact test and multiple comparisons. GO analysis was also applied to the genes belonging to specific profiles.

qRT-PCR analyses

Total RNA from liver specimens was isolated using TRIzol reagent (Invitrogen) according to the manufacturer’s instructions. Approximately 1 μg total RNA was used for first-strand cDNA synthesis, which was carried out using an MMLV-RT Kit (Promega, Madison, WI, USA) according to the manufacturer’s protocol. qRT-PCR was performed using the StepOnePlus Real-Time PCR Detection System (Applied Biosystems, Inc., Foster City, CA, USA). The primers used for measuring the expression of mRNAs of interest are listed in Additional file 14. The amplifications were performed in 20-μL reaction mixtures containing 10.4 μL of 2× SYBR Premix Ex Taq (TaKaRa, Dalian, China), 0.4 μL of each primer (10 mM), 7.8 μL distilled water, and 1.0 μL cDNA. The following PCR conditions were used for all genes: 95°C for 5 min, followed by 40 cycles of 95°C for 15 s, 60°C for 30 s, and 72°C for 30 s. After amplification, melt curve analysis was performed to confirm the specificity of the reaction. All measurements were performed in triplicate. β-Actin was used as a reference gene to normalize gene expression. The 2-∆∆CT method was used to analyze the qRT-PCR data and assign relative expression differences [94].

Immunohistochemistry analysis

Immunohistochemistry was performed with paraffin-embedded sections using standard protocols. Briefly, liver sections were deparaffinized in xylene and rehydrated through a graded ethanol series. Endogenous peroxidase was blocked with 3% hydrogen peroxide (H2O2). The sections were boiled in 10 mM citrate buffer (pH 6.0) for 15 min for antigen retrieval. After blocking with 5% normal goat serum, sections were incubated at 4°C overnight with the following primary antibodies: anti-CCL2 (1:100; ab7814, Abcam, Cambridge, MA, USA), anti-CXCL9 (1:50; bs-2551R, Bioss, Beijing, China), and anti-IRF7 (1:250; bs-2994R, Bioss). Thereafter, the sections were rinsed in PBS and incubated with a biotinylated secondary antibody. The antigen was visualized with a diaminobenzidine (DAB) kit (Vector Laboratories, Burlingame, CA, USA) and counterstained with hematoxylin. A negative control without the primary antibody was included. Images were acquired using a Nikon Eclipse 80i fluorescence microscope and a DS-Fil CCD camera (Nikon).

Western blot analysis

Total protein was extracted from frozen liver samples (~80 mg) as described previously [2]. Samples were centrifuged for 15 min at 4°C and 12,000 × g, and supernatants were collected. Protein concentrations were measured with a BCA Protein Assay Kit (Pierce). After denaturation, liver protein samples were resolved by 10% sodium dodecyl sulfate-polyacrylamide gel electrophoresis and transferred to polyvinylidene membranes (Millipore Corp., Billerica, MA, USA). Membranes were stained with Ponceau S to visually check the quality of proteins that were transferred and were then blocked for 1 h in 1× TBS with 5% nonfat milk. Primary antibodies against CPT1A (1:400; SAB2100476, Sigma-Aldrich), PPARD (1:600; AV32878, Sigma-Aldrich), and GAPDH (1:600; SC-16654, Santa Cruz Biotechnology, Santa Cruz, CA, USA) were incubated with the membrane over night at 4°C. Membranes were then washed and incubated with Odyssey Infrared-labeled secondary antibodies (LI-COR Biosciences, Lincoln, NE, USA) for 1 h in the dark at 37°C. After the last washing step, the membranes were scanned and analyzed using an Odyssey Infrared Imaging System (LI-COR Biosciences).

Statistical analysis

Statistical analysis was performed using SPSS 13.0 software (SPSS, Chicago, IL, USA). The results are presented as means ± SEMs. Statistical differences between groups were examined using the unpaired Student’s t- test. Differences with P-values of less than 0.05 were considered statistically significant.

Data accessibility

The sequence data from this study have been submitted to the Gene Expression Omnibus (GEO) database ( under accession number GSE65696.



Alanine aminotransferase


Analysis of variance


Androgen receptor


Aspartate aminotransferase




Differentially expressed gene


False discovery rate


Free fatty acid


Gene ontology


Glutathione peroxidase


Hematoxylin and eosin


High-density lipoprotein cholesterol


High-fat and high-cholesterol


Low-density lipoprotein cholesterol


Nonalcoholic fatty liver disease


Nonalcoholic steatohepatitis


Phosphate-buffered saline




Quantitative real-time reverse transcription polymerase chain reaction


RNA integrity number


RNA sequencing


Standard error of the mean


Superoxide dismutase




Total cholesterol


Testicular feminized mice




Short Time-Series Expression Miner



This work was supported by grants from the National Natural Science Foundation of China (No. 31200921), Zhejiang Provincial Natural Science Foundation of China (Nos. LQ12C04003 and LY12C04002), Zhejiang Provincial Department of Science and Technology (No. 2014C37010), and the Fundamental Research Funds for the Central Universities (KYZ201414).

Authors’ Affiliations

Laboratory Animal Research Center, Zhejiang Chinese Medical University, Hangzhou, 310053, China
Department of Cancer Genetics, Roswell Park Cancer Institute, Elm and Carlton Streets, Buffalo, NY 14263, USA
College of Animal Science, Nanjing Agricultural University, Nanjing, 310058, China


  1. Rao PM, Kelly DM, Jones TH. Testosterone and insulin resistance in the metabolic syndrome and T2DM in men. Nat Rev Endocrinol. 2013;9(8):479–93.View ArticlePubMedGoogle Scholar
  2. Sumiyoshi M, Sakanaka M, Kimura Y. Chronic intake of a high-cholesterol diet resulted in hepatic steatosis, focal nodular hyperplasia and fibrosis in non-obese mice. Br J Nutr. 2010;103(3):378–85.View ArticlePubMedGoogle Scholar
  3. Volzke H, Aumann N, Krebs A, Nauck M, Steveling A, Lerch MM, et al. Hepatic steatosis is associated with low serum testosterone and high serum DHEAS levels in men. Int J Androl. 2010;33(1):45–53.View ArticlePubMedGoogle Scholar
  4. Kim S, Kwon H, Park JH, Cho B, Kim D, Oh SW, et al. A low level of serum total testosterone is independently associated with nonalcoholic fatty liver disease. BMC Gastroenterol. 2012;12:69.View ArticlePubMed CentralPubMedGoogle Scholar
  5. Hua X, Sun Y, Zhong Y, Feng W, Huang H, Wang W, et al. Low serum sex hormone-binding globulin is associated with nonalcoholic fatty liver disease in type 2 diabetic patients. Clin Endocrinol (Oxf). 2014;80(6):877–83.View ArticleGoogle Scholar
  6. Senmaru T, Fukui M, Okada H, Mineoka Y, Yamazaki M, Tsujikawa M, et al. Testosterone deficiency induces markedly decreased serum triglycerides, increased small dense LDL, and hepatic steatosis mediated by dysregulation of lipid assembly and secretion in mice fed a high-fat diet. Metabolism. 2013;62(6):851–60.View ArticlePubMedGoogle Scholar
  7. Kelly DM, Nettleship JE, Akhtar S, Muraleedharan V, Sellers DJ, Brooke JC, et al. Testosterone suppresses the expression of regulatory enzymes of fatty acid synthesis and protects against hepatic steatosis in cholesterol-fed androgen deficient mice. Life Sci. 2014;109(2):95–103.View ArticlePubMedGoogle Scholar
  8. Kamada Y, Kiso S, Yoshida Y, Chatani N, Kizu T, Hamano M, et al. Estrogen deficiency worsens steatohepatitis in mice fed high-fat and high-cholesterol diet. Am J Physiol Gastrointest Liver Physiol. 2011;301(6):G1031–43.View ArticlePubMedGoogle Scholar
  9. Subramanian S, Goodspeed L, Wang S, Kim J, Zeng L, Ioannou GN, et al. Dietary cholesterol exacerbates hepatic steatosis and inflammation in obese LDL receptor-deficient mice. J Lipid Res. 2011;52(9):1626–35.View ArticlePubMed CentralPubMedGoogle Scholar
  10. Kim EJ, Kim BH, Seo HS, Lee YJ, Kim HH, Son HH, et al. Cholesterol-induced non-alcoholic fatty liver disease and atherosclerosis aggravated by systemic inflammation. PLoS One. 2014;9(6):e97841.View ArticlePubMed CentralPubMedGoogle Scholar
  11. Hatch NW, Srodulski SJ, Chan HW, Zhang X, Tannock LR, King VL. Endogenous androgen deficiency enhances diet-induced hypercholesterolemia and atherosclerosis in low-density lipoprotein receptor-deficient mice. Gend Med. 2012;9(5):319–28.View ArticlePubMed CentralPubMedGoogle Scholar
  12. Kapoor D, Goodwin E, Channer KS, Jones TH. Testosterone replacement therapy improves insulin resistance, glycaemic control, visceral adiposity and hypercholesterolaemia in hypogonadal men with type 2 diabetes. Eur J Endocrinol. 2006;154(6):899–906.View ArticlePubMedGoogle Scholar
  13. Zhang N, Zhang H, Zhang X, Zhang B, Wang F, Wang C, et al. The relationship between endogenous testosterone and lipid profile in middle-aged and elderly Chinese men. Eur J Endocrinol. 2014;170(4):487–94.View ArticlePubMedGoogle Scholar
  14. Lin HY, Yu IC, Wang RS, Chen YT, Liu NC, Altuwaijri S, et al. Increased hepatic steatosis and insulin resistance in mice lacking hepatic androgen receptor. Hepatology. 2008;7(6):1924–35.View ArticleGoogle Scholar
  15. Zhang H, Liu Y, Wang L, Li Z, Zhang H, Wu J, et al. Differential effects of estrogen/androgen on the prevention of nonalcoholic fatty liver disease in the male rat. J Lipid Res. 2013;54(2):345–57.View ArticlePubMed CentralPubMedGoogle Scholar
  16. Lee L, Alloosh M, Saxena R, Van Alstine W, Watkins BA, Klaunig JE, et al. Nutritional model of steatohepatitis and metabolic syndrome in the Ossabaw miniature swine. Hepatology. 2009;50(1):56–67.View ArticlePubMed CentralPubMedGoogle Scholar
  17. Bell LN, Lee L, Saxena R, Bemis KG, Wang M, Theodorakis JL, et al. Serum proteomic analysis of diet-induced steatohepatitis and metabolic syndrome in the Ossabaw miniature swine. Am J Physiol Gastrointest Liver Physiol. 2010;298(5):G746–54.View ArticlePubMed CentralPubMedGoogle Scholar
  18. Vlaardingerbroek H, Ng K, Stoll B, Benight N, Chacko S, Kluijtmans LA, et al. New generation lipid emulsions prevent PNALD in chronic parenterally fed preterm pigs. J Lipid Res. 2014;55(3):466–77.View ArticlePubMedGoogle Scholar
  19. Yao YC, Cai ZW, Zhao CJ, Wu KL, Wu CX, Han WP, et al. Influence of castration-induced sex hormone deficiency on serum lipid levels and the genes expression in male pigs. Horm Metab Res. 2011;43(10):674–80.View ArticlePubMedGoogle Scholar
  20. Christoffersen BO, Gade LP, Golozoubova V, Svendsen O, Raun K. Influence of castration-induced testosterone and estradiol deficiency on obesity and glucose metabolism in male Gottingen minipigs. Steroids. 2010;75(10):676–84.View ArticlePubMedGoogle Scholar
  21. Zeng J, He X, Wu D, Zhu B, Cai S, Nadira UA, et al. Comparative transcriptome profiling of two Tibetan wild barley genotypes in responses to low potassium. PLoS One. 2014;9(6):e100567.View ArticlePubMed CentralPubMedGoogle Scholar
  22. Wang L, Feng Z, Wang X, Wang X, Zhang X. DEGseq: an R package for identifying differentially expressed genes from RNA-seq data. Bioinformatics. 2010;26(1):136–8.View ArticlePubMedGoogle Scholar
  23. Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Ser B Methodol. 1995;57(1):289–300.Google Scholar
  24. Song HK, Hong SE, Kim T, Kim do H. Deep RNA sequencing reveals novel cardiac transcriptomic signatures for physiological and pathological hypertrophy. PLoS One. 2012;7(4):e35552.View ArticlePubMed CentralPubMedGoogle Scholar
  25. Ernst J, Bar-Joseph Z. STEM: a tool for the analysis of short time series gene expression data. BMC Bioinformatics. 2006;7:191.View ArticlePubMed CentralPubMedGoogle Scholar
  26. Nikolaenko L, Jia Y, Wang C, Diaz-Arjonilla M, Yee JK, French SW, et al. Testosterone replacement ameliorates nonalcoholic fatty liver disease in castrated male rats. Endocrinology. 2014;155(2):417–28.View ArticlePubMedGoogle Scholar
  27. Mersmann HJ. Effect of sex on lipogenic activity in swine adipose tissue. J Anim Sci. 1984;58:600–4.PubMedGoogle Scholar
  28. Lu G, Shimizu I, Cui X, Itonaga M, Tamaki K, Fukuno H, et al. Antioxidant and antiapoptotic activities of idoxifene and estrodiol in hepatic fibrosis in rats. Life Sci. 2004;74(7):891–907.View ArticleGoogle Scholar
  29. Allan CA. Sex steroids and glucose metabolism. Asian J Andro. 2014;16:232–8.View ArticleGoogle Scholar
  30. Traish AM. Adverse health effects of testosterone deficiency (TD) in men. Steroids. 2014;88:106–16.View ArticlePubMedGoogle Scholar
  31. Yassin DJ, Doros G, Hammerer PG, Yassin AA. Long-term testosterone treatment in elderly men with hypogonadism and erectile dysfunction reduces obesity parameters and improves metabolic syndrome and health-related quality of life. J Sex Med. 2014;11(6):1567–76.View ArticlePubMedGoogle Scholar
  32. Yeap BB, Chubb SA, Hyde Z, Jamrozik K, Hankey GJ, Flicker L, et al. Lower serum testosterone is independently associated with insulin resistance in non-diabetic older men: the health in men study. Eur J Endocrinol. 2009;161:591–8.View ArticlePubMedGoogle Scholar
  33. Gopal RA, Bothra N, Acharya SV, Ganesh HK, Bandgar TR, Menon PS, et al. Treatment of hypogonadism with testosterone in patients with type 2 diabetes mellitus. Endocr Pract. 2010;16(4):570–6.View ArticlePubMedGoogle Scholar
  34. Gianatti EJ, Dupuis P, Hoermann R, Strauss BJ, Wentworth JM, Zajac JD, et al. Effect of testosterone treatment on glucose metabolism in men with type 2 diabetes: a randomized controlled trial. Diabetes Care. 2014;37(8):2098–107.View ArticlePubMedGoogle Scholar
  35. Christoffersen B, Raun K, Svendsen O, Fledelius C, Golozoubova V. Evaluation of the castrated male Sprague–Dawley rat as a model of the metabolic syndrome and type 2 diabetes. Int J Obes (Lond). 2006;30(8):1288–97.View ArticleGoogle Scholar
  36. Inoue T, Zakikhani M, David S, Algire C, Blouin MJ, Pollak M. Effects of castration on insulin levels and glucose tolerance in the mouse differ from those in man. Prostate. 2010;70(15):1628–35.View ArticlePubMedGoogle Scholar
  37. Rector RS, Thyfault JP, Uptergrove GM, Morris EM, Naples SP, Borengasser SJ, et al. Mitochondrial dysfunction precedes insulin resistance and hepatic steatosis and contributes to the natural history of non-alcoholic fatty liver disease in an obese rodent model. J Hepatol. 2010;52(5):727–36.View ArticlePubMed CentralPubMedGoogle Scholar
  38. Xie Z, Li H, Wang K, Lin J, Wang Q, Zhao G, et al. Analysis of transcriptome and metabolome profiles alterations in fatty liver induced by high-fat diet in rat. Metabolism. 2010;59(4):554–60.View ArticlePubMedGoogle Scholar
  39. Roberts LD, Hassall DG, Winegar DA, Haselden JN, Nicholls AW, Griffin JL. Increased hepatic oxidative metabolism distinguishes the action of Peroxisome proliferator-activated receptor delta from Peroxisome proliferator-activated receptor gamma in the ob/ob mouse. Genome Med. 2009;1(12):115.View ArticlePubMed CentralPubMedGoogle Scholar
  40. Liu S, Hatano B, Zhao M, Yen CC, Kang K, Reilly SM, et al. Role of peroxisome proliferator-activated receptor {delta}/{beta} in hepatic metabolic regulation. J Biol Chem. 2011;286(2):1237–47.View ArticlePubMed CentralPubMedGoogle Scholar
  41. Barroso E, Rodriguez-Calvo R, Serrano-Marco L, Astudillo AM, Balsinde J, Palomer X, et al. The PPARbeta/delta activator GW501516 prevents the down-regulation of AMPK caused by a high-fat diet in liver and amplifies the PGC-1alpha-Lipin 1-PPARalpha pathway leading to increased fatty acid oxidation. Endocrinology. 2011;152(5):1848–59.View ArticlePubMedGoogle Scholar
  42. Bojic LA, Telford DE, Fullerton MD, Ford RJ, Sutherland BG, Edwards JY, et al. PPARdelta activation attenuates hepatic steatosis in Ldlr−/− mice by enhanced fat oxidation, reduced lipogenesis, and improved insulin sensitivity. J Lipid Res. 2014;55(7):1254–66.View ArticlePubMedGoogle Scholar
  43. Lee CH, Olson P, Hevener A, MehI I, Chong LW, Olefsky JM, et al. PPARdelta regulates glucose metabolism and insulin sensitivity. Proc Natl Acad Sci USA. 2006;103(9):3444–9.View ArticlePubMed CentralPubMedGoogle Scholar
  44. Wu HT, Chen CT, Cheng KC, Li YX, Yeh CH, Cheng JT. Pharmacological activation of peroxisome proliferator-activated receptor δ improves insulin resistance and hepatic steatosis in high-fat diet-induced diabetic mice. Horm Metab Res. 2011;43(9):631–5.View ArticlePubMedGoogle Scholar
  45. Winzell MS, Wulff EM, Olsen GS, Sauerberg P, Gotfredsen CF, Ahrén B. Improved insulin sensitivity and islet function after PPARdelta activation in diabetic db/db mice. Eur J Pharmacol. 2010;626(2–3):297–305.View ArticlePubMedGoogle Scholar
  46. Sanderson LM, Boekschoten MV, Desvergne B, Müller M, Kersten S. Transcriptional profiling reveals divergent roles of PPARalpha and PPARbeta/delta in regulation of gene expression in mouse liver. Physiol Genomics. 2010;41(1):42–52.View ArticlePubMedGoogle Scholar
  47. Dimopoulos N, Watson M, Green C, Hundal HS. The PPARdelta agonist, GW501516, promotes fatty acid oxidation but has no direct effect on glucose utilization or insulin sensitivity in rat L6 skeletal muscle cells. FEBS Lett. 2007;581(24):4743–8.View ArticlePubMedGoogle Scholar
  48. Cresser J, Bonen A, Chabowski A, Stefanyk LE, Gulli R, Ritchie I, et al. Oral administration of a PPAR-delta agonist to rodents worsens, not improves, maximal insulin-stimulated glucose transcript in skeletal muscle of different fibers. Am J Physiol Regul Integr Comp Physiol. 2010;299(2):R470–9.View ArticlePubMedGoogle Scholar
  49. Ye JM, Tid-Ang J, Turner N, Zeng XY, Li HY, Cooney GJ, et al. PPARδ agonists have opposing effects on insulin resistance in high fat-fed rats and mice due to different metabolic responses in muscle. Br J Pharmacol. 2011;163(3):556–66.View ArticlePubMed CentralPubMedGoogle Scholar
  50. Monsenego J, Mansouri A, Akkaoui M, Lenoir V, Esnous C, Fauveau V, et al. Enhancing liver mitochondrial fatty acid oxidation capacity in obese mice improves insulin sensitivity independently of hepatic steatosis. J Hepatol. 2012;56(3):632–9.View ArticlePubMedGoogle Scholar
  51. Host C, Gormsen LC, Christensen B, Jessen N, Hougaard DM, Christiansen JS, et al. Independent effects of testosterone on lipid oxidation and VLDL-TG production: a randomized, double-blind, placebo-controlled, crossover study. Diabetes. 2013;62(5):1409–16.View ArticlePubMed CentralPubMedGoogle Scholar
  52. Weng H, Ji X, Naito Y, Endo K, Ma X, Takahashi R, et al. Pex11alpha deficiency impairs peroxisome elongation and division and contributes to nonalcoholic fatty liver in mice. Am J Physiol Endocrinol Metab. 2013;304(2):E187–96.View ArticlePubMedGoogle Scholar
  53. Ren LP, Chan SM, Zeng XY, Laybutt DR, Iseli TJ, Sun RQ, et al. Differing endoplasmic reticulum stress response to excess lipogenesis versus lipid oversupply in relation to hepatic steatosis and insulin resistance. PLoS One. 2012;7(2):e30816.View ArticlePubMed CentralPubMedGoogle Scholar
  54. Peterson JM, Seldin MM, Wei Z, Aja S, Wong GW. CTRP3 attenuates diet-induced hepatic steatosis by regulating triglyceride metabolism. Am J Physiol Gastrointest Liver Physiol. 2013;305(3):G214–24.View ArticlePubMed CentralPubMedGoogle Scholar
  55. Linden D, William-Olsson L, Ahnmark A, Ekroos K, Hallberg C, Sjogren HP, et al. Liver-directed overexpression of mitochondrial glycerol-3-phosphate acyltransferase results in hepatic steatosis, increased triacylglycerol secretion and reduced fatty acid oxidation. FASEB J. 2006;20(3):434–43.View ArticlePubMedGoogle Scholar
  56. Villanueva CJ, Monetti M, Shih M, Zhou P, Watkins SM, Bhanot S, et al. Specific role for acyl CoA:Diacylglycerol acyltransferase 1 (Dgat1) in hepatic steatosis due to exogenous fatty acids. Hepatology. 2009;50(2):434–42.View ArticlePubMed CentralPubMedGoogle Scholar
  57. Kohjima M, Enjoji M, Higuchi N, Kato M, Kotoh K, Yoshimoto T, et al. Re-evaluation of fatty acid metabolism-related gene expression in nonalcoholic fatty liver disease. Int J Mol Med. 2007;20(3):351–8.PubMedGoogle Scholar
  58. Neschen S, Morino K, Hammond LE, Zhang D, Liu ZX, Romanelli AJ, et al. Prevention of hepatic steatosis and hepatic insulin resistance in mitochondrial acyl-CoA:glycerol-sn-3-phosphate acyltransferase 1 knockout mice. Cell Metab. 2005;2(1):55–65.View ArticlePubMedGoogle Scholar
  59. Miyazaki M, Kim YC, Ntambi JM. A lipogenic diet in mice with a disruption of the stearoyl-CoA desaturase 1 gene reveals a stringent requirement of endogenous monounsaturated fatty acids for triglyceride synthesis. J Lipid Res. 2001;42(7):1018–24.PubMedGoogle Scholar
  60. Wakil SJ, Abu-Elheiga LA. Fatty acid metabolism: target for metabolic syndrome. J Lipid Res. 2009;50(Suppl):S138–43.PubMed CentralPubMedGoogle Scholar
  61. Xiao J, Xing F, Huo J, Fung ML, Liong EC, Ching YP, et al. Lycium barbarum polysaccharides therapeutically improve hepatic functions in non-alcoholic steatohepatitis rats and cellular steatosis model. Sci Rep. 2014;4:5587.PubMed CentralPubMedGoogle Scholar
  62. Obstfeld AE, Sugaru E, Thearle M, Francisco AM, Gayet C, Ginsberg HN, et al. C-C chemokine receptor 2 (CCR2) regulates the hepatic recruitment of myeloid cells that promote obesity-induced hepatic steatosis. Diabetes. 2010;59(4):916–25.View ArticlePubMed CentralPubMedGoogle Scholar
  63. Bertola A, Bonnafous S, Anty R, Patouraux S, Saint-Paul MC, Iannelli A, et al. Hepatic expression patterns of inflammatory and immune response genes associated with obesity and NASH in morbidly obese patients. PLoS One. 2010;5(10):e13577.View ArticlePubMed CentralPubMedGoogle Scholar
  64. Palmer C, Corpuz T, Guirguis M, O’Toole S, Yan K, Bu Y, et al. The effect of obesity on intrahepatic cytokine and chemokine expression in chronic hepatitis C infection. Gut. 2010;59(3):397–404.View ArticlePubMedGoogle Scholar
  65. Kirpich IA, Gobejishvili LN, Bon Homme M, Waigel S, Cave M, Arteel G, et al. Integrated hepatic transcriptome and proteome analysis of mice with high-fat diet-induced nonalcoholic fatty liver disease. J Nutr Biochem. 2011;22(1):38–45.View ArticlePubMedGoogle Scholar
  66. Estep JM, Baranova A, Hossain N, Elariny H, Ankrah K, Afendy A, et al. Expression of cytokine signaling genes in morbidly obese patients with non-alcoholic steatohepatitis and hepatic fibrosis. Obes Surg. 2009;19(5):617–24.View ArticlePubMedGoogle Scholar
  67. Li J, Gao J, Yan D, Yuan Y, Sah S, Satyal U, et al. Neutralization of chemokine CXCL14 (BRAK) expression reduces CCl4 induced liver injury and steatosis in mice. Eur J Pharmacol. 2011;671(1–3):120–7.View ArticlePubMedGoogle Scholar
  68. Zhang X, Shen J, Man K, Chu ES, Yau TO, Sung JC, et al. CXCL10 plays a key role as an inflammatory mediator and a non-invasive biomarker of non-alcoholic steatohepatitis. J Hepatol. 2014;61(6):1365–75.View ArticlePubMedGoogle Scholar
  69. Dela Pena A, Leclercq I, Field J, George J, Jones B, Farrell G. NF-kappaB activation, rather than TNF, mediates hepatic inflammation in a murine dietary model of steatohepatitis. Gastroenterology. 2005;129(5):1663–74.View ArticlePubMedGoogle Scholar
  70. Deng QG, She H, Cheng JH, French SW, Koop DR, Xiong S, et al. Steatohepatitis induced by intragastric overfeeding in mice. Hepatology. 2005;42(4):905–14.View ArticlePubMedGoogle Scholar
  71. Nagasawa T, Inada Y, Nakano S, Tamura T, Takahashi T, Maruyama K, et al. Effects of bezafibrate, PPAR pan-agonist, and GW501516, PPARdelta agonist, on development of steatohepatitis in mice fed a methionine- and choline-deficient diet. Eur J Pharmacol. 2006;536(1–2):182–91.View ArticlePubMedGoogle Scholar
  72. Lim HJ, Park JH, Lee S, Choi HE, Lee KS, Par HY. PPARdelta ligand L-165041 ameliorates western diet-induced hepatic lipid accumulation and inflammation in LDLR−/− mice. Eur J Pharmacol. 2009;622(1–3):45–51.View ArticlePubMedGoogle Scholar
  73. Pennell LM, Galligan GL, Fish EN. Sex affects immunity. J Autoimmun. 2012;38(2–3):282–91.View ArticleGoogle Scholar
  74. Furman D, Hejblum BP, Simon N, Jojic V, Dekker CL, Thiébaut R, et al. Systems analysis of sex differences reveals an immunosuppressive role for testosterone in the response to influenza vaccination. Proc Natl Acad U S A. 2014;111(2):868–74.View ArticleGoogle Scholar
  75. Olsen NJ, Kovacs WJ. Gonadal steroids and immunity. Endocr Rev. 1996;17(4):369–84.PubMedGoogle Scholar
  76. Uchiyama S, Shimizu T, Shirasawa T. CuZn-SOD deficiency causes ApoB degradation and induces hepatic lipid accumulation by impaired lipoprotein secretion in mice. J Bio Chem. 2006;281(42):31713–9.View ArticleGoogle Scholar
  77. Abdelmegeed MA, Banerjee A, Yoo SH, Jang S, Gonzalez FJ, Song BJ. Critical role of cytochrome P450 2E1 (CYP2E1) in the development of high fat-induced non-alcoholic steatohepatitis. J Hepatol. 2012;57(4):860–6.View ArticlePubMed CentralPubMedGoogle Scholar
  78. Zong H, Armoni M, Harel C, Karnieli E, Pessin JE. Cytochrome P-450 CYP2E1 knockout mice are protected against high-fat diet-induced obesity and insulin resistance. Am J Physiol Endocrinol Metab. 2012;302(5):E532–9.View ArticlePubMed CentralPubMedGoogle Scholar
  79. Niemela O, Parkkila S, Pasanen M, Viitala K, Villanueva JA, Halsted CH. Induction of cytochrome P450 enzymes and generation of protein-aldehyde adducts are associated with sex-dependent sensitivity to alcohol-induced liver disease in micropigs. Hepatology. 1999;30(4):1011–7.View ArticlePubMedGoogle Scholar
  80. Tao GZ, Lehwald N, Jang KY, Baek J, Xu B, Omary MB, et al. Wnt/beta-catenin signaling protects mouse liver against oxidative stress-induced apoptosis through the inhibition of forkhead transcription factor FoxO3. J Biol Chem. 2013;288(24):17214–24.View ArticlePubMed CentralPubMedGoogle Scholar
  81. van Eerdenburg FJ, Lugard-Kok CM, Dieleman SJ, Bevers MM, Swaab DF. Influence of gonadectomy and testosterone supplementation on the postnatal development of the vasopressin and oxytocin-containing nucleus of the pig hypothalamus. Neuroendocrinology. 1991;54(6):580–6.View ArticlePubMedGoogle Scholar
  82. Kojima M, Sekimoto M, Degawa M. Androgen-mediated down-regulation of CYP1A subfamily genes in the pig liver. J Endocrinol. 2010;207(2):203–11.View ArticlePubMedGoogle Scholar
  83. Khan MA, Earl FL, Farber TM, Miller E, Husain MM, Nelson E, et al. Elevation of serum cholesterol and increased fatty streaking in egg yolk:lard fed castrated miniature pigs. Exp Mol Pathol. 1977;26(1):63–74.View ArticlePubMedGoogle Scholar
  84. Shi Y, Guo R, Wang X, Yuan D, Zhang S, Wang J, et al. The regulation of alfalfa saponin extract on key genes involved in hepatic cholesterol metabolism in hyperlipidemic rats. PLoS One. 2014;9(2):e88282.View ArticlePubMed CentralPubMedGoogle Scholar
  85. Peng X, Wood CL, Blalock EM, Chen KC, Landfield PW, Stromberg AJ. Statistical implications of pooling RNA samples for microarray experiments. BMC Bioinformatics. 2003;4:26.View ArticlePubMed CentralPubMedGoogle Scholar
  86. Li G, Jia Q, Zhao J, Li X, Yu M, Samuel MS, et al. Dysregulation of genome-wide gene expression and DNA methylation in abnormal cloned piglets. BMC Genomics. 2014;15:811.View ArticlePubMed CentralPubMedGoogle Scholar
  87. Ramayo-Caldas Y, Mach N, Esteve-Codina A, Corominas J, Castelló A, Ballester M, et al. Liver transcriptome profile in pigs with extreme phenotypes of intramuscular fatty acid composition. BMC Genomics. 2012;13:547.View ArticlePubMed CentralPubMedGoogle Scholar
  88. Trapnell C, Pachter L, Salzberg SL. TopHat: discovering splice junctions with RNA-Seq. Bioinformatics. 2009;25(9):1105–11.View ArticlePubMed CentralPubMedGoogle Scholar
  89. Hill-Baskin AE, Markiewski MM, Buchner DA, Shao H, DeSantis D, Hsiao G, et al. Diet-induced hepatocellular carcinoma in genetically predisposed mice. Hum Mol Genet. 2009;18(16):2975–88.View ArticlePubMed CentralPubMedGoogle Scholar
  90. Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, et al. Gene ontology: tool for the unification of biology. The gene ontology consortium. Nat Genet. 2000;25(1):25–9.View ArticlePubMed CentralPubMedGoogle Scholar
  91. Wang W, Meng M, Zhang Y, Wei C, Xie Y, Jiang L, et al. Global transcriptome-wide analysis of CIK cells identify distinct roles of IL-2 and IL-15 in acquisition of cytotoxic capacity against tumor. BMC Med Genomics. 2014;7:49.View ArticlePubMed CentralPubMedGoogle Scholar
  92. Wheelock CE, Wheelock AM, Kawashima S, Diez D, Kanehisa M, van Erk M, et al. Systems biology approaches and pathway tools for investigating cardiovascular disease. Mol BioSyst. 2009;5(6):588–602.View ArticlePubMedGoogle Scholar
  93. Ehrenkaufer GM, Weedall GD, Williams D, Lorenzi HA, Caler E, Hall N, et al. The genome and transcriptome of the enteric parasite Entamoeba invadens, a model for encystation. Genome Biol. 2013;14(7):R77.View ArticlePubMed CentralPubMedGoogle Scholar
  94. Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2(−Delta Delta C(T)) Method. Methods. 2001;25(4):402–8.View ArticlePubMedGoogle Scholar


© Cai et al.; licensee BioMed Central. 2015

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated.