Animals and tissue preparation

The FL and LL chickens were bred and raised at INRA UE1295 Pôle d'Expérimentation Avicole de Tours, F–37380 Nouzilly, France, as described previously [24]. Briefly, 8 birds from each genotype (FL and LL) were randomly selected for tissue sampling at six ages (1, 3, 5, 7, 9, and 11 wk), weighed, bled into heparinized syringes, and killed by cervical dislocation. Abdominal fat was quickly dissected, weighed, a sample was immediately snap frozen in liquid nitrogen, and stored at −75°C for further processing. All animal procedures were performed under the strict supervision of a French government veterinarian and in accordance with protocols approved by the French Agricultural Agency, the Scientific Research Agency, and the Institutional Animal Care and Use Committee at INRA, Nouzilly, France. These procedures were also in compliance with the United States Department of Agriculture guidelines on the use of agricultural animals in research and approved by the University of Delaware Agricultural Animal Care and Use Committee.

RNA extraction, library preparation and RNA sequencing

Abdominal fat samples from eight individual 7-wk-old chickens (4 FL and 4 LL) were homogenized and cellular RNA extracted using guanidine thiocyanate and CsCl gradient purification [45] followed by DNase I treatment. Sample quality was analyzed with an RNA 6000 Nano Assay kit and the Model 2100 Bioanalyzer (Agilent Technologies; Palo Alto, CA). The rRNA ratio (28S/18S) was determined and all samples had an RNA integrity number (RIN) greater than 9.0. Sequencing libraries were made from 1 μg of total adipose RNA with the Illumina RNA Sample Prep Kit v2 following standard Illumina protocols. Individual RNA samples were indexed (bar-coded) to enable multiplexing of libraries within sequencing lanes. Libraries were pooled and sequenced using an Illumina HiSeq 2000 Sequencing System at the Delaware Biotechnology Institute, University of Delaware. Three separate schemes were used for paired-end (101 bp) sequencing of 8 libraries (4 FL and 4 LL) across two sequencing lanes per run. In Scheme A, two sequencing lanes were used for multiplexing of two FL and two LL samples per lane (n = 4/lane). Two libraries (1 FL and 1 LL) in sequencing lane 2 of Scheme A had low quality control (QC) scores and were eliminated from further analyses. Consequently, the two low QC libraries were re-sequenced in individual lanes in Scheme B (n = 1/lane). Finally, all eight (4 FL and 4 LL) libraries were multiplexed and sequenced in two replicate lanes in Scheme C (n = 8/lane). All samples in Schemes 1–3 were merged into one file of 12 samples from the FL and 12 samples from the LL cockerels for further analysis.

RNA sequence (RNA-seq) analysis

All reads generated from the three sequencing schemes (12 FL and 12 LL) described above were included in the RNA-Seq analysis using CLC Genomics Workbench 5.1 software (CLC bio, Cambridge, MA). The data analysis included sequence data filtering, read mapping, transcript and gene identification, analysis of differential gene expression, and functional annotation.

Availability of supporting data

The RNA-Seq reads in Sequence Read Archive (SRA) format were deposited into the National Center for Biotechnology Information Gene Expression Omnibus (NCBI GEO) database under the accession # GSE42980. Further data sets supporting the present results are included within the article and in supporting information files.

Quantitative RT-PCR analysis

For verification of expression, quantitative real-time PCR (qRT-PCR) analysis was performed on a subset of 47 DE genes identified by RNA-Seq analysis. First-strand cDNA synthesis was performed by incubation of a 13 μl reaction (containing 1 μg of total DNase-treated RNA, 1 μl of 100 μM oligo dT₂₀, 1 μl of 10 mM dNTP mix, and water to 13 μl total volume) for 5 min at 70°C and placed on ice for 2 min. A master mix containing 5 μl of 5x first-strand synthesis buffer, 1 μl of 0.1 M DTT, 1 μl of RNaseOUT, and 200 U of SuperScript III reverse transcriptase (Invitrogen, Carlsbad, CA) was added (final reaction volume of 20 μl). Primers were designed for qRT-PCR using Primer Express v2.0 software (Applied Biosystems, Foster City, CA). Detailed information for each primer pair, including gene name, gene symbol, forward and reverse primer sequences, GenBank accession number and amplicon size, are provided in S1 Table.

An ABI Prism Sequence Detection System 7900HT was used to perform the qRT-PCR assays, using 10 ng of total RNA, Power SYBR green PCR master mix (Applied Biosystems, Foster City, CA), and 400 nM of each primer pair (Sigma-Aldrich, St. Louis, MO) in duplicate wells. A disassociation step was used to validate specific amplification and verify absence of primer dimers. PCR products were analyzed using agarose gel electrophoresis to compare product size to the expected amplicon size. The cycle time (Ct) for each sample was normalized to the corresponding sample geometric mean of housekeeping genes [49]. We selected two housekeeping genes [pantothenate kinase 1 (PANK1) and ribosomal protein L14 (RPL14)] based on their invariability in qRT-PCR analysis and identified as the most stably-expressed genes using RefFinder software (http://www.leonxie.com/referencegene.php). The 2^-(ΔΔCt) formula was used to calculate relative abundance of transcripts [50]. The statistical analysis of normalized qRT-PCR data across three ages (3, 7 and 11 wk) was performed using a general linear model (GLM) procedure in Statistical Analysis System (SAS v9.3; Cary, NC). These data were analyzed using a two-factor analysis of variance to determine main effects (P≤0.05) of genotype (G), age (A), and the interaction of age with genotype (A × G). Where genes were only used for qRT-PCR analysis at one age (7 wk), a student’s T-test was used to identify significant (P≤0.05) differences between the FL and LL genotypes.

Mapped reads and detection of genes and transcripts

Sequence data from the 24 samples were mapped to the reference genome (Gallus gallus, build 2.1). Table 1 presents a summary of the RNA-Seq analysis including the number of mapped reads and detection of corresponding chicken genes and transcripts (see S2 Table for more details). The original sequencing run (Scheme A) was completed by multiplexing 2 FL and 2 LL samples (N = 4) in two separate sequencing lanes. Two samples (1 FL and 1 LL) in Lane 2 had low quality scores; therefore, the low-quality data was eliminated from further RNA-Seq analysis. Nonetheless, Scheme A provided an average of 32.5 M mapped reads for the FL (N = 3) and 36 M mapped reads for the LL (N = 3), which allowed detection of 73% genes and 65% of transcripts across the FL and LL genotypes. Subsequently, the two low quality score libraries were re-sequenced in separate lanes in another sequencing run (Scheme B), which gave the highest average detection levels of 78% for genes and 70% for transcripts across both genotypes. In Scheme C, the 8 libraries (4 FL and 4 LL samples) were multiplexed and sequenced in duplicate lanes within the same sequencing run. Scheme C represents the balanced block design with two technical replicates as described by Auer and Doerge [51] for proper statistical analysis of RNA-Seq experiments. Comparing sequencing depths (averaged across the FL and LL chickens), Scheme C allowed detection of 71% of genes and 63% of transcripts by multiplexing 8 libraries per lane which were sequenced in duplicate lanes. The average number of reads mapped across Scheme A, B and C was greater for the LL (41.6 M) than the FL (35.4 M), which is reflected in the slightly higher number of expressed genes found in abdominal fat of the LL cockerels. The overall average across genotype (FL and LL) and sequencing schemes (A, B and C) shows that 45% (38.5 M) of the total reads were mapped, which equates to identification of 74% of genes (13,265/17,934) and 66% of transcripts (14,724/22,298) based on the reference chicken genome. Genes from the reference chicken genome were mapped to UniProtKB accession numbers by the Protein Information Resource (PIR) ID mapping service [52]. The assigned fold-change values (i.e., FL/LL expression ratios) were based on the number of normalized reads from the RNA-Seq analysis.

Download:

• PPT
  PowerPoint slide
• PNG
  larger image
• TIFF
  original image

Table 1. Summary of RNA-Seq analysis of abdominal fat in divergent FL and LL chickens at 7 wk.

https://doi.org/10.1371/journal.pone.0139549.t001

A power analysis was performed on this RNA-Seq dataset using the web-based software program “Scotty” (http://euler.bc.edu/marthlab/scotty/scotty.php) [53]. This analysis demonstrates that our sample size of four birds/genotype (n = 4), sequenced across three depths [38.5 million mapped reads per sample averaged across depths (Table 1)], had power to detect 80% of genes expressed in each genotype (P≤0.01) at ≥ 1.5 fold difference and greater than 90% at a fold-change of ≥ 2 (S1 Fig). Further, the “Scotty” program performed hierarchical clustering using Spearman correlation as the distance metric. This correlation analysis grouped the two genotypes distinctly, where the individuals within each genotype (FL and LL) were closely linked.

Abdominal fat transcriptome of fed FL and LL chickens

First, the 900 highest-expressed (HE) genes, defined as genes with an average (across both genotypes) of >4289 reads/gene, were identified from RNA-Seq analysis of abdominal fat in FL and LL chickens at 7 wk (S3 Table). Of the HE genes, 164 were expressed higher in the FL (>1.2-fold difference), while 155 HE genes were up-regulated (< -1.2-fold difference) in visceral fat of the LL. Second, we identified 1687 DE genes with a FDR-corrected P-value (P≤0.05) and fold change ≥ 1.2 (or ≤ -1.2); and of these, 1182 DE genes were expressed higher in abdominal fat of LL chickens, whereas only 505 DE genes were expressed higher in FL chickens (S4 Table). A working list of 607 functional genes, associated with lipid metabolism (lipogenesis, lipolysis, lipid transport, etc.), was compiled from the RNA-Seq datasets using Ingenuity Pathway Analysis software (S5 Table). The Venn diagram (Fig 1) shows the intersection among HE genes, DE genes, and lipid metabolism genes, with 25 genes in common across all three gene sets. A total of 164 DE genes were shared between HE and DE gene lists. And, 108 DE genes are shared between the 1687 DE genes and the 607 lipid metabolism genes. Further, 87 genes are shared between the 900 HE genes and the 607 lipid metabolism genes.

Download:

• PPT
  PowerPoint slide
• PNG
  larger image
• TIFF
  original image

Fig 1. Venn diagram illustrating overlap among functional gene lists.

The Venn diagram shows the intersections of highly expressed (HE) genes in abdominal fat (S3 Table), differentially expressed (DE) genes (S4 Table), and Ingenuity annotated genes known to be involved in lipid metabolism (S5 Table). The numbers in overlapping arcs indicate the number of genes shared between and among these three categories.

https://doi.org/10.1371/journal.pone.0139549.g001

Ingenuity Pathway Analysis (IPA) of gene expression

Analysis of highest expressed genes in abdominal fat of FL and LL chickens.

The 900 highest-expressed (HE) genes in abdominal fat (S3 Table) were submitted to the Ingenuity Knowledge Base (http://www.ingenuity.com/) for functional annotation, mapping of genes to canonical pathways, and identifying gene interaction networks. There were 828 DE genes identified by IPA as “Analysis ready” (i.e., annotated in the Ingenuity Knowledge Base). A summary of the over-represented IPA functional categories found for 828 “Analysis ready” HE genes is presented in Table 2. The major IPA categories represented by the HE genes include the “Top Canonical Pathways, Diseases and Disorders, Molecular and Cellular Functions, Physiological System Development and Function, Top Gene Interaction Networks, and Top Tox [Toxicology] Lists”. Several subcategories under the IPA category “Diseases and Bio Functions” reveal the most prevalent biological processes found in abdominal fat. For example, several subcategories are related to the regulation of adiposity [“Metabolic Disease” (193 genes), “Endocrine System Disorders” (50 genes), “mTOR Signaling” (31 genes), “Insulin Receptor Signaling” (12 genes), and [“Type 2 Diabetes Signaling” (10 genes)]. Additional subcategories of interest are those involved in metabolism [“Lipid Metabolism” (164 genes), “Carbohydrate Metabolism” (65 genes), “Glycolysis I” (8 genes)] and hemostasis [“Thrombin Signaling” (23 genes)].

Download:

• PPT
  PowerPoint slide
• PNG
  larger image
• TIFF
  original image

Table 2. Ingenuity Pathway Analysis of highest-expressed (HE) genes in abdominal fat of FL and LL.

https://doi.org/10.1371/journal.pone.0139549.t002

Several categories under the IPA Top Tox Lists (Table 2) are also of particular interest. Of the 21 HE genes associated with “Hepatic Fibrosis”, 17 HE genes are expressed higher in abdominal fat of the LL chickens, including 5 collagen genes (COL3A-COL6A), fibronectin 1 (FN1), spondin 1 and 2 (SPON1, SPON2), fibrillin 1 (FBN1), transforming growth factor, beta receptor II (TGFBR2) and thrombospondin 1 (THBS1). The “PPAR/RXR Activation” category includes 28 genes that are highly expressed in the FL and involved in lipid synthesis [thyroid hormone responsive spot 14 alpha (THRSPA), stearoyl-CoA desaturase (SCD1), fatty acid synthase (FASN), sterol regulatory element binding factor 2 (SREBP2), lipoprotein lipase (LPL) and glycerol-3-phosphate dehydrogenase 1 (GDP1)]. Likewise, the “Mechanism of Gene Regulation by PPARs” category includes 18 HE genes.

Many HE genes found in abdominal fat of the FL and LL chickens are key transcriptional regulators of lipogenesis and adipogenesis (Fig 2). For example, several transcription factors [SREBF2, THRSP, nuclear receptor subfamily 1, group H, member 3 (NR1H3) or liver-activated receptor alpha (LXRA), and peroxisome proliferator-activated receptor gamma (PPARG)] interact with each other and ultimately effect the transcription of several downstream target genes (Fig 2A). Some HE targets of SREBF2 include fatty acid desaturase 2 (FADS2), acetyl-CoA carboxylase alpha (ACACA), SCD, FASN, ATP citrate lyase (ACLY), perilipin 2 (PLIN2), isocitrate dehydrogenase 1 (IDH1) and THRSP. The transcription factor THRSP, which itself targets ACACA, FASN and SCD, is also regulated by PPARG. Further, PPARG has numerous HE target genes that regulate lipid metabolism [acyl-Coenzyme A oxidase 1, palmitoyl (ACOX1), fatty acid binding protein 3–5 (FABP3, FABP4 and FABP5), catalase (CAT), perilipin 1 (PLIN1), lysosomal-associated protein transmembrane 4 A (LAPTM4A) and nuclear receptor subfamily 1, group H, member 3 (NR1H3 or LXRA)].

Download:

• PPT
  PowerPoint slide
• PNG
  larger image
• TIFF
  original image

Fig 2. Gene interaction networks of highest-expressed (HE) genes in abdominal fat of chickens associated with lipogenesis and adipogenesis.

Functional gene interaction networks were identified by Ingenuity Pathway Analysis (IPA). Genes are colored based on fold-change values determined by RNA-Seq analysis, where the red-color symbols signify higher expression in FL chickens and green-color gene symbols indicate higher expression in LL chickens. The false discovery rate (FDR) and fold-difference cutoff were not used in this functional analysis of the highest-expressed (HE) genes, which is simply based on a high number of reads mapped to known transcripts. Each gene was assigned a shape and function by IPA as shown in the “Network Shapes” legend inset. The direct gene interaction network in the top panel (A) was functionally annotated by IPA as “Lipid Metabolism, Molecular Transport, and Small Molecular Biochemistry”, which emphasizes transcriptional regulation of adipogenesis and lipogenesis. The direct gene interaction network in panel (B) was functionally annotated by IPA as related to “Cellular Development, Cellular Growth and Proliferation, and Cellular Movement”.

https://doi.org/10.1371/journal.pone.0139549.g002

The target genes that are regulated by these transcription factors (Fig 2A) belong to a group of genes functionally associated with “Lipid Metabolism”. Some genes associated with “Lipid Metabolism” are more specifically involved in: fatty acid synthesis, elongation, and desaturation [ACACA, ACOX1, acyl-CoA dehydrogenase, long chain (ACADL), acyl-CoA synthetase long-chain family member 1 (ACSL1) and diacylglycerol O-acyltransferase 2 (DGAT2), fatty acid elongase 1 (ELOVL1), FASN, FADS2, and SCD], fatty acid transport [fatty acid binding protein 4 (FABP3, FABP4 and FABP5)], and adipokine signaling [adiponectin (ADIPOQ) and LPL]. Some other HE genes that are involved in lipid metabolism include diacylglycerol kinase, zeta (DGKZ), insulin-like growth factor 2 receptor (IGF2R), insulin-like growth factor binding protein 2 and 7 (IGFBP2 and IGFBP7, respectively), malate dehydrogenase 2, NAD (MDH2), and somatostatin receptor 2 (SSTR2).

Signal transducers and activators of transcription 3 and 5B (STAT3 and STAT5B) are also highly expressed in adipose tissue of FL and LL chickens, respectively (Fig 2B). STAT3 is a binding partner of STAT5B, GHR, and mitogen-activated protein kinase kinase kinase kinase 4 (MAP4K4) and directly targets hexokinase 2 (HK2), tissue factor pathway inhibitor 2 (TFPI2) and protein disulfide isomerase family A, member 4 (PDIA4). Conversely, several genes that target STAT3 are also highly expressed [Janus kinase 1 (JAK1), kinase insert domain receptor (KDR), platelet-derived growth factor receptor, beta polypeptide (PDGFRB), and CREB binding protein (CREBBP), which also targets THRSP]. Another gene up-regulated in abdominal fat of FL chickens at 7 wk was the glycolytic enzyme glycerol-3-phosphate dehydrogenase 1 (GPD1), an important regulator of adiposity. Furthermore, NOTCH cellular signaling and growth regulation were significant processes found in abdominal fat of FL and LL chickens. Notch 1 (NOTCH1) has interactions with PDGFRB, transforming growth factor, beta receptor II and III (TGFBR2 and TGFBR3), actin, alpha 2 (ACTA2), contactin 2 (CNTN2) and SWI/SNF related, matrix associated, actin dependent regulator of chromatin, subfamily a, member 2 (SMARCA2).

Analysis of differential gene expression between FL and LL chickens.

The dataset of 1687 DE genes (S4 Table) was submitted to Ingenuity Pathway Analysis (IPA) (http://www.ingenuity.com/) for functional annotation and mapping to canonical metabolic and regulatory pathways. From these, a total of 1322 DE genes were identified as “Analysis ready” by IPA. A summary of the Ingenuity Pathway Analysis of these DE genes is presented in Table 3, which includes the major functional categories: “Top Canonical Pathways, Diseases and Disorders, Molecular and Cellular Functions, Physiological System Development and Function, Top Gene Interaction Networks, Top Tox [Toxicology] Lists, and Top 10 Up-regulated and Down-regulated Genes”. Annotated lists are provided for DE genes assigned by IPA to the “Top Canonical Pathways” (S6 Table) and “Top Tox Lists” (S7 Table) functional categories. A total of 1687 differentially-expressed (DE) genes from RNA-Seq analysis were submitted to IPA, which provided 1322 “Analysis Ready” DE genes for functional annotation and mapping to canonical pathways and gene interaction networks. P-values were determined by IPA software using Fisher’s Exact Test as described by Ingenuity. The percent overlap and ratio were calculated for the number of observed genes compared to the number of known genes in the Ingenuity Knowledge Base for that category. Adipose genes with positive expression ratios are expressed at higher levels in FL cockerels, whereas genes with negative expression ratios are more abundant in abdominal fat of the LL.

Download:

• PPT
  PowerPoint slide
• PNG
  larger image
• TIFF
  original image

Table 3. Ingenuity Pathway Analysis of DE Genes in Abdominal Fat of FL and LL Cockerels (7 wk).

https://doi.org/10.1371/journal.pone.0139549.t003

The top canonical pathway populated by 23 DE genes found in abdominal fat of the FL and LL chickens at 7 wk was the “Adipogenesis Pathway” (Table 3). Among the 8 DE genes up-regulated in the FL were frizzled class receptor 6 (FZD6), fibroblast growth factor receptor 3 (FGFR3), lipin 1 (LPIN1), CCAAT/enhancer binding protein (C/EBP) alpha (CEBPA), and perilipin 1 (PLIN1) (S7 Table), A total of 15 DE genes were expressed higher in the LL chickens; and among these, 12 genes encode transcription factors including Kruppel-like factor 5 (KLF5), nuclear receptor subfamily 2, group F, member 2 (NR2F2 or COUPTFII), early B-cell factor 1 (EBF1), SMAD family member 5 (SMAD5) and hypoxia inducible factor 1, alpha (HIF1A), The “Glucocorticoid Receptor (GR) Signaling” pathway contained 36 DE genes (10 genes up-regulated in the FL; 26 genes up-regulated in the LL). The highly-expressed DE genes in the FL included annexin A1 (ANXA1), plasminogen activator, urokinase (PLAU), CEBPA, Harvey rat sarcoma viral oncogene (HRAS), two RNA polymerases (TAF13 and POLR2H), and two heat-shock proteins (HSPA2 and HSPA8). A total of 14 transcription regulators related to GR signaling were more abundant in visceral fat of the LL, including progesterone receptor (PGR), androgen receptor (AR), nuclear receptor coactivator 2 and 3 (NCOA2; NCOA3), nuclear factor of activated T cells, cytoplasmic, calcineurin dependent 2 and 3 (NFATC2; NFATC3), and E1A-binding protein p300 (EP300). Of the 49 DE genes assigned to the “Axonal Guidance Signaling” pathway, 16 genes were up-regulated in the FL and 33 genes were more abundant in the LL, including 6 peptidases and 13 kinases. The “Hepatic Fibrosis” pathway also shows over-representation of 22 DE genes in visceral fat of the LL that encode 8 types of collagen, myosin, heavy chain (MYH10), 8 growth factor receptors [fibroblast growth factor receptor 2 (FGFR2), platelet-derived growth factor receptor, alpha and beta polypeptides (PDGFRA; PDGFRB), interleukin 1 receptor, type I (IL1R1), insulin-like growth factor 1 receptor (IGF1R), interferon gamma receptor 1 (IFNGR1), transforming growth factor, beta receptor II (TGFBR2), and angiotensin II receptor, type 1 (AGTR1)], and 4 growth factors (ligands) [(transforming growth factor, beta 2 (TGFB2), PDGFRB, tumor necrosis factor (ligand) superfamily, member 10 (TNFSF10) and c-fos induced growth factor (FIGF)]. In contrast, the FL chickens showed up-regulation of only five genes associated with fibrosis, namely three receptors (tumor necrosis factor receptor superfamily, member 1B (TNFRSF1B), endothelin receptor type B (EDNRB) and interleukin 1 receptor accessory protein-like 2 (IL1RAPL2), SMAD7 and platelet derived growth factor C (PDGFC)]. The “RXR Activation” pathway was similarly over-represented with highly-expressed DE genes from the LL (23 genes, including retinoic acid receptor beta (RARB), EP300, and Janus kinase 2 (JAK2), whereas only retinoid X receptor gamma (RXRG), aldehyde dehydrogenase family 1, subfamily A2 (ALDH1A2) and SMAD7 were expressed higher in the FL birds.

The “Top Tox” function identified by IPA for DE genes was “Cardiac Hypertrophy” (Table 3; S7 Table), which list 13 genes that are up-regulated in FL birds [i.e., PLAU, thioredoxin (TXN), FABP3, Parkinson protein 7 (PARK7), galactosidase, alpha (GLA), etc.] and 35 genes expressed higher in LL abdominal fat [i.e, KLF5, FN1, AGTR1/2, periostin (POSTN), angiopoietin 1 (ANGPT1), and]. The “Liver Proliferation” category includes 11 DE genes up-regulated in the FL and 17 DE genes expressed higher in the LL. Among the DE genes highly expressed in FL adipose tissue were leukotriene B4 receptor (LTB4R), protein S alpha (PROS1), chemokine (C-X-C motif) receptor 4 (CXCR4), follistatin (FST), and CEBPA. The DE genes over-expressed in the LL include midkine or neurite growth-promoting factor 2 (MDK), pleiotrophin (PTN), bone morphogenetic protein 7 (BMP7), cannabinoid receptor 1 (CNR1), AGTR1, and IGF1R as examples. The “Oxidative Stress” response shows 8 genes expressed higher in FL and 3 up-regulated in the LL. The “TGF-β signaling” function includes 3 genes up-regulated in the FL, whereas 11 DE genes were more abundant in the LL adipose tissue. Other interesting canonical pathways identified by IPA were “Renin-Angiotensin Signaling” (13 DE genes/109 known genes) “TR/RXR Activation” (11/85), “NF-κB Signaling” (22/173), and “Coagulation System” (8/35). Differential regulation of the IPA “Molecular and Cellular Function” subcategory “Lipid Metabolism” (173 DE genes) is of particular interest to this study.

A large group of DE genes involved in lipid metabolism were identified by IPA (Fig 3A). Eleven lipogenic genes [lipin 1 (LPIN1), FASN, SCD, RXRG, FABP3, FABP5, cytochrome P450, family 24, subfamily A, polypeptide 1 (CYP24A1), phospholipase A2, group VI (cytosolic, calcium-independent) (PLA2G6), peroxiredoxin 6 (PRDX6), solute carrier organic anion transporter family, member 1B3 (SLCO1B3) and acyl-CoA oxidase 2 (ACOX2)] were up-regulated in abdominal fat of FL chickens. Five transcription factors [EP300, prospero homeobox 1 (PROX1), NCOA2, forkhead box A2 (FOXA2), and nuclear receptor interacting protein 1 (NRIP1)], three ligand-activated nuclear receptors [liver receptor homolog–1 (NR5A2), chicken ovalbumin upstream promoter transcription factor II (COUPTFII or NR2F2), and RARB], three metabolic enzymes [arachidonate 5-lipoxygenase (ALOX5), cytochrome P450, family 2, subfamily C, polypeptide 8 (CYP2C8) and phospholipase A2, group VII (PLA2G7)], phosphoenolpyruvate carboxykinase 1, cytosolic (PCK1), which is the rate-limiting enzyme in gluconeogenesis, and liver fatty acid binding protein 1 (FABP1) were up-regulated in visceral fat of LL chickens. Another gene interaction network (Fig 3B) centered on the androgen receptor (AR) was expressed higher in the LL, which shows numerous direct targets of the AR, including bone morphogenetic protein 15 (BMP15, up-regulated in the FL) and TGFBR2 (up-regulated in the LL), which interact with TGF family members. Three additional members of the TGFBR family are of particular interest: gremlin 1, DAN family BMP antagonist (GREM1, up-regulated in the FL), endoglin (ENG), and activin A receptor, type I (AVR1), which were up-regulated in visceral fat of the LL. Other direct targets of AR that were up-regulated in abdominal fat of the FL chickens include carbonic anhydrase IV (CA4), retinoic acid receptor responder 1 (RARRES1), epoxide hydrolase 1 (EPHX1), 24-dehydrocholesterol reductase (DHCR24) and protein S-alpha (PROS1).

Download:

• PPT
  PowerPoint slide
• PNG
  larger image
• TIFF
  original image

Fig 3. Gene interaction networks in abdominal fat of FL and LL chickens at 7 wk.

Functional gene networks were identified by IPA, DE genes are colored based on fold-change values (FL/LL) from RNA-Seq analysis. Each gene was assigned a shape by IPA according to its function as shown in the “Network Shapes” box. The top panel (A) shows a direct gene network annotated by IPA as “Lipid Metabolism, Small Molecule Biochemistry and Molecular Transport” that involves the interaction of several transcription factors, ligand-activated nuclear receptors, lipogenic enzymes and fatty acid transporters. The bottom direct gene interaction network (B) is centered on the androgen receptor (AR) and several direct targets of the AR including transforming growth factor, beta receptor II (TGFBR2) and bone morphogenetic protein 15 (BMP15).

https://doi.org/10.1371/journal.pone.0139549.g003

Numerous G-protein coupled receptors (GPCR) were differentially expressed in abdominal fat of FL and LL chickens at 7 wk (Fig 4). Interestingly, three neuropeptides receptors [melanocortin (MC5R), somatostatin (SSTR2) and neuropeptide Y, (NPY2R)] were up-regulated in visceral fat of the FL chickens (Fig 4A). The urotensin 2 receptor (UTS2R) and endothelin receptor B (EDNRB) were also higher in FL chickens, while two ligands for the endothelin receptor (endothelin 1 and 2; EDN1 and EDN2) were expressed higher in the LL. Other genes up-regulated in LL chickens were the G-coupled protein receptors for glucagon-like peptide 1 (GLP1R), lysophosphatidic acid (LPAR3), glutamate (GRM8), cannabinoid (CNR1), thrombin (F2R), and angiotensin II [angiotensin II receptor, type 1 and 2 (AGTR1 and AGTR2)]. The mineralocorticoid nuclear receptor [MCR or nuclear receptor subfamily 3, group C, member 2 (NR3C2)], several of its targets [sodium channel, non-voltage-gated 1 alpha subunit (SCNN1A), FK506 binding protein 1B (FKBP1B), ATP-binding cassette, sub-family C (CFTR/MRP), member 9 (ABCC9), AGTR1 and EDN1)], parathyroid hormone-like hormone (PTHLH) and homeobox A3 (HOXA3) were also higher in abdominal fat of the LL chickens. Plasminogen activator, urokinase (PLAU) is responsible for the conversion of plasminogen to plasmin (an important step in the fibrinolytic pathway) was up-regulated in FL chickens. The most abundant gene found in this interaction network of FL abdominal fat was proprotein convertase subtilisin kexin type 9 (PCSK9), a potent inhibitor of the low-density lipoprotein receptor (LDLR) and regulator of plasma LDL cholesterol levels.

Download:

• PPT
  PowerPoint slide
• PNG
  larger image
• TIFF
  original image

Fig 4. Differential expression of G-protein coupled receptors in abdominal fat of FL and LL chickens.

(A) Gene interaction network of G-protein coupled receptors (GPCR), some of which interact with regulators of angiogenesis and blood pressure. Visceral adipose tissue shows an extensive over-representation of 29 GPCRs (B), where 21 DE genes are over-expressed in the LL and 8 DE genes are expressed higher in FL chickens. Many of these GPCRs could be considered as “ectopically expressed” in adipose tissue.

https://doi.org/10.1371/journal.pone.0139549.g004

RNA-Seq analysis revealed 29 GCPRs that were differentially expressed in abdominal fat of the FL and LL chickens at 7 wk of age (Fig 4B). Eight GCPR genes (EDNRB, FZD6, G protein-coupled receptor 132 (GPR132), latrophilin 3 (LPHN3), MC5R, neuropeptide Y receptor 2 (NPYR2), SSTR2 and UTS2R) were expressed at higher levels in the FL birds; whereas, 21 GCPRs were over-expressed in abdominal fat of the LL. Many of these differentially expressed GCPRs are usually expressed in tissues other than abdominal fat and have a variety of functions including cell adhesion and signaling, metabolism, angiogenesis, vasomotor tone, cell differentiation, embryonic development, etc.

Examination of DE genes over-expressed in abdominal fat of the LL chickens (Fig 5A) revealed an interaction network of several transcriptional regulators [(FOXA2, NCOA2, NCOA3, transducin (beta)-like 1 X-linked receptor 1 (TBL1XR1), spen family transcriptional repressor (SPEN) and human immunodeficiency virus type I enhancer binding protein 1 (HIVEP1)], transporters [transthyretin (TTR) and ATP-binding cassette, sub-family C, member 3 (ABCC3) ATP-binding cassette, sub-family A, member 1 (ABCA1)], enzymes [phosphoenolpyruvate carboxykinase 1 (PCK1), 3-hydroxy-3-methylglutaryl-CoA synthase 2 (HMGCS2) and amylase, alpha 2A (AMY2A)] and ligand-activated nuclear receptors [NR2F2, nuclear receptor subfamily 5, group A, member 2 (NR5A2) and RXRB]. Additional direct DE gene targets of the up-regulated transcription factors FOXA2 (Fig 5B) and AR (Fig 5C) in the LL were identified by the Ingenuity Upstream Regulatory Analysis, which predicts that these two upstream regulators are inhibited (blue-colored symbols and edges), since their direct target genes are also down-regulated in the FL (i.e., expressed higher in the LL). This network of up-regulated genes, which interact with six transcription factors and numerous up-regulated direct targets of FOXA2 and AR in abdominal fat of the LL (Fig 5) clearly implicates intense transcriptional regulation of the lean phenotype. In particular, FOXA2 appears to play a critical role in restricting visceral adipose accretion in the LL, since it directly up-regulates expression of fibrinogen beta (FGB, a key blood-clotting protein), glucagon (GCG, a lipolytic pancreatic hormone), PCK1 (the key enzymatic regulator of gluconeogenesis), HMGCS2 (which catalyzes the first reaction in ketogenesis), two major transport proteins (ALB and TTR), and alpha-2-macroglobulin (A2M, a protease inhibitor and clinical biomarker of type 2 diabetes).

Download:

• PPT
  PowerPoint slide
• PNG
  larger image
• TIFF
  original image

Fig 5. Gene interaction network of up-regulated genes and direct targets of up-regulated transcription factors in abdominal fat of the LL chickens.

(A) This direct gene interaction network of up-regulated DE genes in the LL chickens was identified by IPA as “Developmental Disorder, Hematological Disease, or Hereditary Disorder”. (B) The Ingenuity Upstream Regulator Analysis predicts inhibition of forkhead box A2 (FOXA2; blue-colored symbol with a z-score of -2.52), since 9 of its 17 direct targets have down-regulated expression ratios (FL/LL), which is consistent with inhibition of FOXA2 (i.e., down-regulated in FL or up-regulated in LL). (C) Likewise, the predicted inhibition of the androgen receptor (AR; blue-colored symbol with a z-score of -3.04) would lead to inhibition (blue arrows) of its direct targets, since 15 of 27 genes are inhibited in the FL (i.e., a reduced FL/LL ratio or up-regulated in the LL). According to RNA-Seq analysis, the expression of both FOXA2 (fold-change of -10.7) and AR (fold-change of -1.4) was higher in the LL.

https://doi.org/10.1371/journal.pone.0139549.g005

Another interesting gene interaction network involved in growth factor signaling was also highly represented by DE genes found in the LL adipose tissue (Fig 6A). Of the 17 genes up-regulated in the LL, there were 7 growth factor receptors (FGFR2, PDGFRA, fibronectin leucine rich transmembrane protein 2 (FLRT2), neurotrophic tyrosine kinase, receptor, type 2 (NTRK2), interleukin 13 receptor, alpha 1 (IL13RA1), and IGF1R), 2 growth factors [fibroblast growth factor 18 (FGF18) and FIGF], 4 kinases [neurotrophic tyrosine kinase, receptor, type 3 (NTRK3), phosphoinositide-3-kinase, regulatory subunit 2 (beta) (PIK3R2), neuropilin 2 (NRP2), and JAK2)], 1 peptidase [calpain 5 (CAPN5)], 1 transcription factor [homeobox B9 (HOXB9)], and 3 “other” genes [Cbl proto-oncogene B, E3 ubiquitin protein ligase (CBLB), SH2B adaptor protein 3 (SH2B3) and golgi glycoprotein 1 (GLG1)]. In contrast, only five DE genes in this network were up-regulated in the FL, including the insulin receptor substrate 2 (IRS2), FGFR3, PDGFC, fibroblast growth factor receptor-like 1 (FGFRL1), and the peptidase (CAPN2). The gene interaction network shown in Fig 2B was listed in Table 3, under the IPA “Top Gene Interaction Network” functionally annotated as “Cell Death and Survival, Gene Expression, Cell Cycle”. Fifteen DE genes in this network are up-regulated in the FL; and all appear to be direct targets of multiple transcription factors, which are expressed higher in the LL. Many of the DE genes up-regulated in the FL are enzymes [ACOX1, ACOX2, CDP-diacylglycerol synthase (phosphatidate cytidylyltransferase) 2 (CDS2), IMP (inosine 5'-monophosphate) dehydrogenase 2 (IMPDH2), chitobiase, di-N-acetyl- (CTBS), holocytochrome c synthase (HCCS), galactosidase, alpha (GLA), and phosphomannomutase 1 (PMM1)], although two highly-expressed DE genes in the FL encode transcription regulators [RXRG and DEAD (Asp-Glu-Ala-Asp) box polypeptide 20 (DDX20)]. In contrast, 8 of the 19 DE genes that are expressed higher in the LL are transcription factors [(PGR, MAX interactor 1, dimerization protein (MXI1), nuclear transcription factor Y, beta (NFYB), RE1-silencing transcription factor (REST), Max dimerization protein 4 (MXD4), metastasis associated 1 (MTA1), prickle homolog 1 (PRICKLE1) and SIN3 transcription regulator family member A (SIN3A)]. Three enzymes were among the other up-regulated genes in the LL are [transglutaminase 2 (TGM2), monoamine oxidase B (MAOB), and contactin 4 (CNTN4)], while two genes were kinases [(doublecortin-like kinase 3 (DCLK3) and hormonally up-regulated Neu-associated kinase (HUNK)].

Download:

• PPT
  PowerPoint slide
• PNG
  larger image
• TIFF
  original image

Fig 6. Gene interaction networks involved in growth factor signaling (A) and (B) transcription factor regulation.

(A) This gene network is highly populated by genes involved in growth factor signaling and functionally annotated by IPA as “Cellular Growth and Proliferation, Cell Cycle and Cancer”. (B) This gene interaction network is populated by several transcription factors up-regulated in the LL chickens and functionally annotated by IPA as “Cell Death and Survival, Gene Expression, Cell Cycle”.

https://doi.org/10.1371/journal.pone.0139549.g006

Ingenuity Upstream Regulator Analysis revealed 16 DE transcription regulators and their DE direct target genes from the RNA-Seq analysis of abdominal fat in the FL and LL cockerels at 7 wk (S8 Table). Only four DE transcription factors were up-regulated in the FL [ELL associated factor 2 (EAF2), SMAD7, PARK7 and CEBPA]. In contrast, 12 DE transcription regulators were expressed at higher levels in abdominal fat of the LL. The four highest expressed transcription factors in the LL were KLF5, PGR, homeobox A11 (HOXA11), and SWI/SNF related, matrix associated, actin dependent regulator of chromatin, subfamily b, member 1 (SMARCB1). The transcription factors in the LL with the greatest number of downstream DE target genes were EP300 (46 DE genes), AR (46 DE genes), NFYB (28 DE genes), and PGR (25 DE genes). This over-representation of DE upstream regulator genes in the LL emphasizes the importance of enhanced transcriptional regulation in expression of the divergent lean phenotype.

A comparison between the DE and HE gene sets has identified numerous candidate genes that control lipid metabolism and expansion of visceral fat (Table 4). Of these candidate genes, the most remarkable include FABP3, FABP5, FADS2, FASN, GPD1, HK2, HSD17B7, IGFBP2, MDH2, PGRMC1 and SCD. These genes could aid in the transport of lipid (FABP3 and FABP5) and the generation of substrate (HK2, GDP1, and MDH2) for lipid synthesis via the major lipogenic enzymes FASN and SCD, both of which are highly expressed in abdominal fat of FL chickens. These lipogenic genes are controlled by the interaction of multiple up-stream transcription regulators (THRSP, SREBF2, STAT5B, PPARG, NFKBIA, RARB and PARK7). Other DE and/or HE genes involved in angiogenesis and hemostasis include the natriuretic peptide receptor 3 (NPR3), PROS1, PDGFRB, EDNRB, PLAU, PROCR, and ANG.

Download:

• PPT
  PowerPoint slide
• PNG
  larger image
• TIFF
  original image

Table 4. Functional genes identified by RNA-Seq analysis of abdominal fat in FL and LL cockerels at 7 wk.

https://doi.org/10.1371/journal.pone.0139549.t004

Verification of RNA-seq analysis by quantitative RT-PCR

Based on biological function, several candidate genes were selected from the RNA-Seq analysis for qRT-PCR verification (Table 5). Of the genes shown, 41 were differentially expressed in the FL/LL by RNA-Seq analysis (FDR-adjusted P-value ≤ 0.05). All 41 genes were significantly different (P≤ 0.05) between FL and LL birds by qRT-PCR analysis. Neuropeptide Y (NPY) was a candidate gene not significantly different between the FL and LL chickens by either RNA-Seq or qRT-PCR analysis. The glucagon receptor (GCGR) was not differentially expressed by RNA-Seq; however, the abundance of GCGR in abdominal fat was 1.6 fold higher in the LL chickens by qRT-PCR analysis (P≤0.05). The short isoform of chicken growth hormone (scGH) was 1.5-fold higher (P≤0.05) in FL chickens by qRT-PCR analysis, while differential expression of scGH was not indicated by RNA-Seq analysis. Albumin (ALB; not shown) was highly up-regulated in abdominal fat of LL chickens by both RNA-Seq (38-fold) and qRT-PCR (73-fold) analyses. Furthermore, the fold change values for this gene set, across both RNA-Seq and qRT-PCR analyses, were highly correlated (r = 0.90) and significant (P≤0.001) as determined by Pearson correlation analysis. A complete list of the FL and LL expression means and their standard errors (SEM) for all genes in the qRT-PCR analysis is provided in S9 Table.

Download:

• PPT
  PowerPoint slide
• PNG
  larger image
• TIFF
  original image

Table 5. Verification of RNA-Seq gene expression in abdominal fat of FL and LL cockerels.

https://doi.org/10.1371/journal.pone.0139549.t005

The expression of six candidate genes [glucagon (GCG), glucagon receptor (GCGR), glucagon-like peptide 1 receptor (GLP1R), lysophosphatidic acid receptor 1 (LPAR1), attractin-like 1 (ATRNL1) and tubby (TUB)] was initially examined by qRT-PCR analysis at three different ages (3, 7 and 9 wk of age) to verify highest expression at 7 wk (Fig 7). A two-factor analysis of variance [genotype (FL and LL) x age (3, 7 and 11 wk)] shows significant (P≤0.05) main effects of genotype and age for all six genes. The abundance of all six genes reached a peak at 7 wk of age and was higher in abdominal fat of the LL than the FL chickens at 7 and 9 wk.

Download:

• PPT
  PowerPoint slide
• PNG
  larger image
• TIFF
  original image

Fig 7. Quantitative RT-PCR analysis of select candidate genes in abdominal fat of FL and LL chickens.

Six genes were selected for qRT-PCR analysis of expression profiles in abdominal fat of FL and LL chickens at three ages (3, 7 and 9 weeks of age) to confirm highest expression at 7 wk. Data points represent Least Square Means (LSMEANS; n = 4 birds/genotype) of gene expression in arbitrary units (AU) based on the delta-delta cycle time (^ΔΔCt) method. The general linear models (GLM) procedure in Statistical Analysis System (SAS) software (Cary, NC). A two-factor (genotype x age) analysis of variance (ANOVA) was used to determine significance (P≤0.05). The shaded box in each panel indicates significant main effects of genotype (G) or age (A); the number in parenthesis represents the common standard error (SE) of LSMEANS for that gene as determined by the GLM procedure in SAS. Gene symbols: attractin-like 1 (ATRNL1), glucagon (GCG), glucagon receptor (GCGR), glucagon-like peptide 1 receptor (GLP1R), lysophosphatidic acid receptor 1 (LPAR1), and tubby (TUB).

https://doi.org/10.1371/journal.pone.0139549.g007

Altered lipid metabolism in abdominal fat of FL and LL chickens

A recent review provides a comprehensive description of growth and energy metabolism in our divergently-selected FL and LL chickens, amassed from more than three decades of intensive investigation [28]. The “glucose-insulin imbalance” originally described by Simon et al [30,31] appears to be the major physiological difference noted between the FL and LL chickens, where the FL exhibit hypoglycemia and only slight hyperinsulinemia, which resembles the ‘pre-obese’ condition of juvenile mammals without true insulin resistance [26]. In fact, the FL chicken appears to be more sensitive to insulin [31] as indicated by their higher rate of glucose utilization and enhanced hepatic lipogenesis [26,35], higher secretion of very-low-density lipoproteins (VLDL) [27], and their greater storage capacity of lipids in abdominal fat [68]. Furthermore, the divergence in abdominal fatness in the FL and LL chickens does not depend on the type of dietary energy, which indicates genetic control [32,55]. Since the liver is considered as the primary site of lipogenesis in birds [10–12], most previous studies of the FL and LL were directed at understanding the genetic difference in hepatic lipogenesis, rather than the lipogenic capacity of abdominal fat.

A major finding of our time course microarray analysis of abdominal fat in FL and LL chickens [24] was the discovery of numerous DE genes involved in lipid synthesis. We have confirmed the up-regulation of many DE lipogenic genes in abdominal fat of FL chickens by both RNA-Seq and qRT-PCR analyses. Further, the abundant expression of lipogenic genes in abdominal fat in the FL was validated by the report that acute fasting [22] depressed expression of several lipogenic genes in the chicken. For example, the lipogenic enzyme ME1, which is critical for the synthesis of lipids via generation of NADPH required for the conversion of malonyl-CoA to palmitic acid (by FASN), was down-regulated in LL chickens and similar to its lower expression in adipose tissue of fasted chickens. Both the soluble (MDH1) and mitochondrial (MDH2) forms of malate dehydrogenase, which are expressed higher in adipose tissue and liver [57] of FL chickens, were among the top six percent of the highest expressed genes found by RNA-Seq analysis of abdominal fat in FL and LL chickens at 7 wk. Similar to the FL chickens [68], the expression of MDH1, MDH2 and ME1 show a strong positive correlation with increased adipocyte volume in genetically fat pigs [69]. Another gene differentially expressed in response to either genetic or nutritional perturbation is lipin 1 (LPIN1), which was identified as a reciprocal regulator of triglyceride synthesis and hydrolysis in adipocytes of LPIN1 knockout mice [70]. In chickens, adipose LPIN1 expression is elevated in response to short-term (5 hr) food deprivation [22], a 30% energy restriction [71] or in “leaner” and slow-growing Leghorn and Fayoumi breeds when compared to “fatter” broiler chickens [23]. However, LPIN1 was expressed higher in abdominal fat of our genetically fat (FL) chickens as indicated by both RNA-Seq and qRT-PCR analyses (see Fig 6B). The present study clearly shows that divergent genetic selection of broiler chickens for a 2.5–2.8 fold difference in abdominal fatness results in higher expression of LPIN1 in visceral fat of the FL, but not the LL chickens. Of our cross-validated candidate genes, LPIN1 is of particular interest for its potential to control several important metabolic processes including adipogenesis, lipogenesis and eicosanoid signaling. Involvement of LPIN1 in the regulation of adipogenesis occurs via control of phosphatidic acids levels, which influence PPARG expression [72] and LPIN1 is required for PPARG-driven adipogenesis both in vitro and in vivo [73,74]. Further, LPIN1 is also a co-regulator of nuclear receptor signaling by interaction with the PPARs (PPARA, PPARG and PPARGC1A) and CEBPA [75,76]. We found that atrial natriuretic peptide receptor 3 (NPR3) and AMP-activated protein kinase (AMPK) were both up-regulated in abdominal fat of the FL chickens (see Table 4). Atrial natriuretic peptide (ANP) provokes a strong lipolytic action in human adipocytes by activating AMPK and increasing mitochondrial biogenesis [77].

In the present study, we found that the expression of KLF5 was 2.5-fold greater in abdominal fat of the LL than in the FL at 7 wk (Table 3; S8 Table). The transcription factor KLF5 has been implicated in adipogenesis, since knockout of KLF5 retards expansion of white (visceral) adipose tissue [78]. Furthermore, this study shows that over-expression of KLF5 stimulates adipocyte differentiation via interactions with CEBPB and PPARG, which are key regulators of adipocyte differentiation. A recent study of KLF2 expression in abdominal fat during juvenile development (1–12 wk) of a different population of divergently-selected FL and LL broiler chickens shows that the abundance of KLF2 was greater in the LL at 1 wk, but higher in fat of the FL between 3–8 wk [79]. Functional in vitro analyses indicate that over-expression of KLF2 inhibits preadipocyte differentiation and expression of CEBPA and PPARG. These observations support their conclusion that KLF2 plays a role in divergent genetic selection of this distinct population of FL and LL chickens. Clearly, the role of multiple transcription factors in the divergence of abdominal fat accretion in FL and LL chickens needs further investigation.

Hormone signaling appears to play a major role in controlling lipid metabolism in abdominal fat of FL and LL chickens. For example, growth hormone (GH) signaling is highly active in abdominal fat of the LL birds (see Fig 2B). We found that the peripheral receptor for melanocyte-stimulating hormone and adrenocorticotropic hormone, MC5R, was expressed higher in abdominal fat of FL chickens. MC5R regulates fatty acid oxidation in skeletal muscle of mice [80] and in hepatocytes of sea bass, where a MC5R agonist stimulates lipolysis and the release of free fatty acids from cultured sea bass adipocytes [81]. Furthermore, MC5R has been associated with obese phenotypes in humans [82]; and the MC5R gene locus is highly conserved in the genomes of human, mouse and chicken [83]. Additionally, the membrane-bound progesterone receptor (PGRMC1) was highly expressed in abdominal fat of FL chickens (see Table 4). The PGRMC1 directly regulates cholesterol synthesis and metabolism of steroid hormones in mammals [84]. Progesterone signaling seems to be enhanced in abdominal fat of LL chickens as indicated by the 2-fold up-regulation of the progesterone receptor (PGR), which regulates the expression of 25 DE target genes in visceral fat. Progesterone administration in rats increases body and inguinal fat mass, a response only observed in females [85], whereas the significance of up-regulation of PGR in abdominal fat of LL cockerels in the present study remains unknown.

Androgen signaling also appears to be up-regulated in abdominal fat of LL chickens, where the AR was expressed 40 percent higher compared to their fatter counterparts. Androgen signaling in adipose tissue of murine models protects against obesity and regulates insulin action and glucose homeostasis, and AR knockout mice are more susceptible to high-fat diet–induced visceral obesity [86]. The up-regulation of AR and the 46 DE genes that are direct targets of AR found presently in abdominal fat of the LL suggests a similar mechanism for AR signaling in adipose tissue of chickens. Unfortunately, a recent study of gene expression in castrated (capon) chickens did not include a transcriptional analysis of abdominal fat in the capons, which become fatter, nor in the leaner intact or testosterone-implanted groups [87]. This report clearly shows the importance of androgen in limiting excessive fattening in the chicken, albeit more attention was focused on over-expression of PCK1 in the liver of capons rather than in abdominal fat as a direct target of androgen signaling.

Another intriguing finding in abdominal fat of FL and LL chickens was the abundance of genes involved in eicosanoid signaling. This includes production of eicosanoid precursors as well as downstream signaling events. In human breast cancer MCF7 cells, loss of FADS2 function blocks normal polyunsaturated fatty acid biosynthesis resulting in the FADS1 generation of polyunsaturated fatty acids which lack the 8–9 double bond of eicosanoid signaling precursors (i.e., arachidonic acid and eicosapentaenoic acid) [88]. Both FADS2 (higher in FL chickens) and FADS1 (higher in LL chickens) are differentially expressed in the present study. Another enzyme involved in eicosanoid signaling, DAGLA (higher in LL chickens), catalyzes the hydrolysis of diacylglycerol (DAG). The product of this reaction is arachidonic acid precursor 2-arachidonoyl-glycerol (2-AG), a major peripheral endocannabinoid signaling molecule [89]. In adipose tissue of rodents, 2-AG activates the CNR1 (a gene also up-regulated in LL chickens), an event that is up-regulated in fat treatment groups [89–91]. Furthermore, FAAH, the enzyme that degrades the active endocannabinoid 2-AG [92] was up-regulated in abdominal fat of FL chickens. Taken together, these findings provide evidence for enhanced endocannabinoid signaling in adipose tissue of the LL chickens.

Hemostatic gene expression in abdominal fat of chickens

The predominant expression of numerous hemostatic genes in abdominal fat of FL and LL chickens is clearly illustrated by an overlay on the coagulation cascade from the Kyoto Encyclopedia of Genes and Genomes (KEGG; http://www.genome.jp/kegg/) website (Fig 8). Seven hemostatic genes, up-regulated in the LL, were identified earlier in our time-course (1–11 wk) microarray analysis of abdominal fat in the FL and LL chickens [24]. The present RNA-Seq analysis of abdominal fat in the FL and LL chickens at 7 wk of age verifies and extends the remarkable involvement of the hemostatic system in divergent genetic selection of abdominal fatness in meat-type chickens. From our RNA-Seq analysis, an additional 11 genes [A2M, END1, END2, FGB, FGG, F2R, protein C receptor, endothelial (PROCR), SERPIND1, SERPINB5, THSD1, and THSD4] were up-regulated in the LL chickens, whereas another 4 genes (PROS1, PLAU, SERPINF2 and EDNRB) were expressed at higher levels in visceral fat of the FL at 7 wk. The extraordinary involvement of the coagulation system in limiting expansion of fat mass in the LL chickens is further demonstrated by the high abundance of additional six hemostasis-related genes (VFW, TFPI2, F13A1, SERPINH1, THBS1 and THBSR) across both genotypes. Furthermore, our time-course microarray analysis of liver samples from the same FL and LL chickens used for transcriptional analyses of their abdominal fat failed to show any effects of the FL or LL genotype on hepatic expression of these coagulation factors [Unpublished work; see NCBI GEO accession GSE8812]. Interestingly, the coagulation factor XIII, A1 polypeptide (F13A1) was previously identified as a novel obesity candidate gene in humans [93]. Collectively, our previous time-course microarray analysis [24] and the present RNA-Seq analysis of abdominal fat in the FL and LL chickens at 7 wk support the idea that coagulation and angiogenic factors are critical components in divergent genetic selection of visceral fat mass, which seem to function locally (paracrine or autocrine) and independently of the hemostatic system found in systemic circulation, since the liver is the main source of coagulation factors found in the bloodstream. The recent RNA-Seq analysis of breast muscle from broiler-type chickens afflicted with “Wooden Breast disease” has implicated the chicken’s coagulation system in progression of this novel muscular disorder [48]. Birds suffering from this myopathy exhibit down-regulation of eight hemostatic genes (A2M, FGA, FGB, FGG, KNG1, SERPINC1 and VWF) and up-regulation of four other coagulation genes (F5, F10, PROS1 and F2R).

Download:

• PPT
  PowerPoint slide
• PNG
  larger image
• TIFF
  original image

Fig 8. Prevalence of coagulation factors in abdominal fat transcriptome of FL and LL chickens.

This coagulation cascade was adapted from the Complement and Coagulation Cascades (map04610) found in the Kyoto Encyclopedia of Genes and Genomes (KEGG). Reprinted from the KEGG website (http://www.genome.jp/kegg-bin/show_pathway?map04610] under a CC BY license, with permission from KEGG, original copyright [map04610, Kanehisa Laboratories, April 03, 2009]. Genes are colored based on differential gene expression (FL/LL) levels from the present RNA-Seq analysis at 7 wk and our recent time-course (1–11 wk) microarray study [24] of abdominal fat in FL and LL chickens. The highest-expressed coagulation genes from the RNA-Seq analysis are also shown, along with several other genes related to hemostasis and angiogenesis.

https://doi.org/10.1371/journal.pone.0139549.g008

The serine protease thrombin (F2), which we identified as a DE gene in the time course microarray analysis of abdominal fat of the FL and LL chickens [24], is an extremely potent platelet agonist. In the present RNA-Seq study at 7 wk, F2 was not significantly different (1.3-fold higher in LL chickens; P≤ 0.07; data not shown) between the genotypes. Interestingly, we found that the receptor for F2 [F2R or proteinase-activated receptor–1 (PAR1)] was expressed higher in adipose tissue of LL chickens. PAR1 and PAR4 are expressed in human adipose tissue, where treatment with F2 induces expression and secretion of several adipokines (IL-1B, IL–6, MCP–1, and VEGF) [94]; however, this is mediated through the PAR4 rather than PAR1. In another study, Kajimoto et al. [95] found that the interaction of F2 and PAR1 in 3T3-L1 adipocytes stimulates FABP4 which regulates the expression of interleukin 6 (IL–6) and vascular endothelial growth factor (VEGF). Although there have been no studies describing F2-PAR1 interactions in adipose tissue of chickens, an earlier report indicates that interaction between thrombin and PAR1 is required for “endothelial mesenchymal transdifferentation” in the aorta of chick embryos [96]. Our present study shows that genes involved in thrombin signaling are differentially expressed in visceral fat of FL and LL chickens. The function of these coagulation factors in regulating expansion of visceral fat mass in the chicken certainly needs further definitive investigation.

The up-regulation of numerous genes involved in hemostasis (pro-coagulation and anti-coagulation) in visceral fat of LL chickens was originally reported in our time-course microarray analysis [24]. Although prothrombotic genes are associated with increased fatness in humans [97–100], our studies suggest a novel role of several hemostatic factors in limiting abdominal fat accretion in the LL chickens [24]. The present RNA-Seq analysis (at 7 wk) and our previous time-course (1–11 wk) microarray study [24] clearly show differential expression of numerous pro- and anti-coagulation genes in abdominal fat of FL and LL chickens (see Fig 8). Most remarkably, abdominal fat of LL chickens appears to be in a pro-coagulation state, since five genes driving thrombosis are up-regulated (F9, F2, FGA, FGB, and FGG). RNA-Seq analysis identified seven additional genes (F2R, FGB, FGG, PROCR, PROS1, PLAU, and SERPINF2) that were not found by our previous microarray analysis. Four related genes [serpin peptidase inhibitor, clade H, member 1, (SERPINH1), serpin peptidase inhibitor, clade B, member 5 (SERPINB5), thrombospondin, type I, domain containing 1 (THSD1) and thrombospondin, type I, domain containing 4 (THSD4)] were also identified by RNA-Seq analysis of abdominal fat. Likewise, five additional genes [endothelin 1 (EDN1), endothelin 2 (EDN2), endothelin receptor type B (EDNRB), thrombospondin 1 (THBS1) and thrombospondin receptor (CD36)] were found in the present study; these genes are usually involved in vasoregulation or activation of platelets and endothelial cells. We propose that these proteases and protease inhibitors found in visceral fat of the chicken could control the proteolytic activation or deactivation of adipokines and other endocrine factors. The down-regulation of PROS1, an inhibitor of blood coagulation, in the LL supports a pro-coagulation state in abdominal fat of these chickens. Further, the higher expression of PROC [24] and the PROC receptor (PROCR) in visceral fat of the LL chickens suggests increased activation of PROC and PAR1 (or F2R) by the multifunctional PROCR [101]. Fibrinogen (FGA, FGB and FGG) is mainly produced in the liver and secreted into systemic circulation. Interestingly, fibrinogen expression in FL chickens is nearly undetectable whereas all three fibrinogen subunits are expressed 10-fold higher in visceral fat of the LL. Similarly, the level of FGG in plasma was inversely related to adiposity in subcutaneous and visceral fat in humans [102] and in rats fed a high-fat diet for 8 wk [103]. Aside from its primary function in blood coagulation, fibrinogen has been identified as a binding surface for several proteins involved in vascular homeostasis [104]. The over-expression of fibrinogen and albumin (ALB) in abdominal fat of LL chicken could contribute to increased binding, uptake and/or transport of adipose-derived proteins. The differential expression of the large number of hemostatic factors observed in abdominal fat, but not in liver of our FL and LL chickens was not observed during nutritional or hormonal perturbation in the chicken [22], which suggests that these coagulation genes could have a novel role in divergent selection and the 2.5-fold difference in abdominal fatness observed in our unique experimental lines.

These hemostatic factors could contribute to local (paracrine/autocrine) and/or endocrine control of fat accretion and/or vasomotor tone, which would have important consequences on adipogenesis [105], angiogenesis and regulation of blood flow [106]. This apparent vascular regulation in visceral fat seems highly complex and under control of several mechanisms. One such mechanism is the renin-angiotensin system (RAS), which usually serves as a major systemic regulator of blood pressure; now, it is known that many components of RAS are also expressed in adipose tissue [107]. Support for this idea is provided by the present study and our observation that 11 of the 13 DE genes found in the renin-angiotensin signaling pathway, are expressed higher in abdominal fat of the LL chickens. As an active RAS ligand, angiotensin II is involved in lipid metabolism via regulation of insulin signaling in adipose tissue [105,108]. RAS plays an important role in the regulation of local and systemic blood pressure via vasoconstriction of peripheral arterioles. The G-coupled protein receptor for angiotensin II, AGTR1, was up-regulated in chickens after insulin immunoneutralization or acute fasting [22]. In the present study, we found that both AGTR1 and AGTR2 were down-regulated in adipose tissue of FL chickens (see Table 4). The down-regulation of angiotensin II receptors in adipose tissue of anabolic chicken models (FL, fed or normal insulin activity) suggests increased vasodilation in abdominal fat, a process that accompanies angiogenesis [109], allowing for increased blood flow and expansion of adipose mass. Furthermore, an overactive RAS could inhibit adipocyte differentiation [105] resulting in down regulation of adipogenesis in LL chickens.

Vascular tone is also mediated through the release of vasoconstrictors or vasodilators independent of the RAS, including catecholamines, endothelins and nitric oxide. Reduced expression of potent vasoconstrictors (EDN1 and EDN2) in adipose tissue of FL chickens strengthens the importance of increased vasodilation and therefore enhanced blood flow to support higher accretion of abdominal fat in FL chickens. While the endothelin receptor B (EDNRB) transcript was slightly higher in FL chickens (1.5-fold), the abundance of EDNRA was more than 10-fold higher, which suggests that EDNRA is the more active isoform in adipose tissue of FL chickens. In mammals, the major effects of vasodilation are mediated through either down regulation of vasoconstrictors or increased generation of nitric oxide (NO). The production of NO by nitric oxide synthase (NOS) is usually driven by hypoxia [110], where hypoxic conditions in adipose tissue usually lead to overproduction of and ultimately resistance to NO [111]. Since HIF1A was down-regulated in visceral fat of FL chickens and the abundance of NOS similar between genotypes, hypoxia and over-production of NO do not seem to be an issue. Rather, regulation of NO signaling in these chickens could be controlled by phosphodiesterases, which are expressed at much lower levels in FL chickens (PDE1C, PDE3A, PDE5A, PDE9A and PDE10A). Phosphodiesterases catalyze the degradation of cGMP [112], ultimately inhibiting the vasodilatory action of NO, and have been implicated in the treatment of cardiovascular diseases [113], respiratory diseases [114] and metabolic syndrome [115]. For example, PDE1C, a non-selective phosphodiesterase, is amongst the highest expressed phosphodiesterases in rat β-islet cells and knockdown of this gene significantly increases insulin secretion [116]. Higher expression of another nonselective phosphodiesterase, PDE3A, in adipose tissue in humans was correlated with weight loss after gastric bypass surgery [117]. Furthermore, inhibition of cGMP-specific phosphodiesterases (i.e., PDE5A and PDE9A) is effective in cardio-protection [113]. Taken together, altered RAS and cGMP signaling within adipose tissue of the FL chickens could ultimately result in vasodilation and increased blood flow to support their higher fat deposition.

The up-regulation of growth factors (PDGFC and FGFR3; see Fig 6A) and GREM1 in abdominal fat of FL chickens could support enhanced angiogenesis. The higher expression of FGFR3 in FL chickens is similar to that observed in adipose tissue of ApoE knockout mice, which exhibit increased adiposity when fed a high fat diet [118]. The expression of GREM1, a bone morphogenetic protein antagonist, correlates with increased angiogenesis in humans with pancreatic neuroendocrine tumors [119]; whereas, the knock-down of GREM1 in human HK–2 cells increases BMP7 signaling activity [120]. Correspondingly, BMP5 and BMP7 were down- regulated in abdominal fat of the FL chickens, whereas BMP15 expression was strongly up-regulated in these birds. The expression of BMP5 is down-regulated under highly vascularized conditions, like those simulated by tumor cell lines (i.e., adrenocortical carcinoma and adrenocortical tumor cell lines [121]). Another angiogenesis-related gene endoglin (ENG), a co-receptor for TGFβ, was expressed higher in abdominal fat of the LL chickens (see Fig 3B and Table 4). Knockout of this gene (Eng^-/-) is lethal to mid-gestation mouse embryos due to severely impaired angiogenesis and cardiac development [122,123]. Further, plasma insulin and hepatic triglyceride levels are reduced in heterozygous Eng^+/- mice fed a high-fat diet [124]. In addition, NPY-stimulated angiogenesis and adipogenesis in the mouse are mediated through the NPY2R receptor, a pathway augmented by glucocorticoids [125]. This study using mice provides strong evidence that up-regulation of NPY secretion and NPY2R expression within visceral fat contributes to obesity and metabolic syndrome in mammals. Our qRT-PCR analysis clearly shows overexpression of both NPY and NPY2R in visceral fat of FL chickens, which could contribute to their enhanced adipogenesis and angiogenesis. This idea is supported by a recent report of higher expression of NPY and its receptors (NPY1R and NPY5R) in abdominal fat of fatter high-growth chickens than that of the slow-growing leaner chickens [126]. Furthermore, NPY treatment of cultured chicken adipocytes boosts NPY2R-mediated proliferation, adipogenesis and lipid accumulation, which implicate a functional role for adipose-derived NPY and the NPY2R in expansion of visceral fat in the chicken [127]. The combined over-expression of angiogenic genes and under-expression of vasoactive factors identified in the present study could promote increased blood flow to support enhanced growth of visceral adipose tissue in FL chickens.

Collectively, our previous time-course microarray study [24] and the present RNA-Seq analysis of abdominal fat in FL and LL chickens have identified several novel features of the transcriptional response to divergent genetic selection for extremes in visceral fatness. The assumption that avian and mammalian species share similar mechanisms that regulate energy metabolism and adipogenesis must be tempered with a heightened awareness of novel avian characteristics. Namely, the loss of multiple adipokine genes (LEP [7], PAI–1, TNFA, resistin and omentin [8]) from the chicken genome has a major impact on our understanding of the avian regulatory systems that control energy intake, metabolism and adiposity. Most discussions of insulin resistance, type–2 diabetes, inflammation, and obesity in mammals are centered on involvement of these major adipokines. Many of the unique aspects of metabolism, including fasting hyperglycemia and insulin insensitivity, are likely reflected by absence of these and perhaps other “mammalian” regulators in the chicken—the premier avian model [1–4].

In summary, our RNA-Seq analysis of visceral adipose tissue in meat-type chickens divergently selected for a large difference in abdominal fatness reveals higher expression of numerous hemostatic and lipolytic genes in genetically lean chickens, whereas abundant expression of lipogenic, angiogenic and adipogenic genes were found in fat chickens. In both genotypes, abdominal fat shows “ectopic” expression of numerous endocrine factors and/or receptors that could contribute to their divergence in visceral fatness. We propose that over-expression of multiple hemostatic genes encoding serine proteases and serine protease inhibitors in visceral fat of lean chickens could be involved in processing of adipokines and other endocrine factors. The present RNA-Seq analysis of abdominal fat in genetically fat and lean chickens provides strong support for the idea that adipose tissue is an important endocrine organ in chickens. In addition, the abundance and differential expression of several key lipogenic and adipogenic genes in genetically fat chickens suggests that abdominal fat could make a more important contribution to lipid synthesis in birds than previously recognized. This idea is supported by an earlier paper [128], which indicated that fatty acids synthetized in liver of chickens are subject to oxidation by liver and muscle, whereas fatty acids synthetized by abdominal fat are retained there for storage. The importance of functional candidate genes identified in visceral fat from the present transcriptional profiling and bioinformatics analyses will require further definitive studies to verify their importance in lipogenesis and adipogenesis, and to gain mechanistic insight to genetic control of adiposity in the chicken.