All animal procedures were authorized by the Animal Care Committee of South China Agricultural University (Guangzhou, China). Animals involved in the present study were sacrificed as necessary to ameliorate their suffering.

In the present study, WC chickens were collected from Longquan Wenchang Chicken Industrial co., LTD (Wenchang, Hainan, China), and WRR chickens were collected from Guangdong Wen's Food Group, LTD (Xinxing, Guangdong, China). Birds were raised up to 120 d of age (D120) or 180 d of age (D180), six female birds of similar weight from each breed per age were sacrificed for muscle sample collection. The center of right breast muscle (B) was excised, divided into three parts for RNA-seq, qRT-PCR, and Oil Red O staining respectively, snap-frozen in liquid nitrogen immediately and stored long-term at −80°C. The whole left breast muscle was excised for IMF content measurement and stored at −30°C.

Frozen tissues were sectioned using a Leica Kryostat (Leica CM3050S, Leica instrument GmbH, Germany), fixed 30 min with 10% paraformaldehyde, and incubated 15 min at room temperature with Oil Red O, then visualized with light microscopy.

IMF contents were measured in a Soxhlet apparatus (Soxtherm, German), according to the description elsewhere (Zerehdaran et al., 2004; Cui et al., 2012). The data are represented as percentages of the wet weight of the muscle.

Total RNA was extracted from muscle samples or cells with RNAiso reagent (Takara, Otsu, Japan) and treated with DNase I (Takara). The integrity and concentration of RNA were assessed by 1.2% denatured gel electrophoresis and NanoDrop 2000c instrument (Thermo, Waltham, MA, USA). cDNA synthesis was carried out using a PrimeScript RT reagent Kit (Perfect Real Time) (Takara) according to the manufacturer's instruction.

For each breed at each age, two birds were selected randomly from the total of six birds for RNA-seq respectively. So eight muscle samples in total were subjected to RNA-seq analysis, four WC chicken samples including WC.D120.B-1, WC.D120.B-3, WC.D180.B-2, and WC.D180.B-3, and four WRR chicken samples including WRR.D120.B-4, WRR.D120.B-6, WRR.D180.B-2, and WRR.D180.B-5.

After the total RNA extraction and DNase I treatment, magnetic beads with Oligo (dT) were used for mRNA enrichment. The enriched mRNA was fragmented, and used as templates for synthesizing cDNA. Short cDNA fragments were purified, end-repaired, tailed with single nucleotide adenine, and then connected with adapters. With agarose gel electrophoresis, suitable fragments were amplified with PCR. Subsequently the sample library was assessed with an Agilent 2100 Bioanaylzer and ABI StepOnePlus Real-Time PCR System for quantity and quality. Finally, the library was sequenced using Illumina HiSeq™ 2000 (BGI, China).

Primary sequencing data that produced by Illumina HiSeq™ 2000, called raw reads, were subjected to quality control (QC) to determine whether a resequencing step was needed. After QC, raw reads were filtered, and clean reads were aligned to reference sequences with SOAPaligner/SOAP2 (Li et al., 2009). Then the alignment data were utilized to calculate distribution and coverage of reads on reference genes. Next, we proceeded with gene expression analysis, which included gene expression level and differential expression gene (DEG). Furthermore, we performed Gene Ontology (GO) enrichment analysis (Ashburner et al., 2000; Young et al., 2010), KEGG (Kyoto Encyclopedia of Genes and Genomes, http://www.genome.jp/kegg/) Pathway enrichment analysis (Altermann and Klaenhammer, 2005; Kanehisa et al., 2008) and Ingenuity® Pathway Analysis (IPA®, http://www.ingenuity.com/) of DEGs.

The primers for qRT-PCR were designed by Primer premier 5 software. The forward (F) and reverse (R) primer of each gene were derived from different exons, and the size of each PCR product was about 150 ~ 250 bp. qRT-PCR was carried out in a Bio-rad CFX96 Real-Time Detection system (Bio-rad, Hercules, CA, USA) employing KAPA SYBR FAST q-PCR Kit (KAPA Biosystems, Wobrun, MA, USA) according to the manufacturer's instruction. The 2^−(ΔΔCt) formula was used to quantify the relative gene expression with GAPDH as a reference gene (Vandesompele et al., 2002).

pcDNA-3.1(+)-SLC27A1 expression vector. The SLC27A1 coding sequence containing 1941 base pairs was amplified from chicken breast muscle cDNA, and the specific primers as follows: 5′-cttaagcttatgcagcccgtgggggtgt-3′ and 5′-gcagaattctcataaggcgactttcccggagca-3′. The PCR product was cloned into the pcDNA-3.1(+) vector (Promega, Madison, WI, USA) using restriction enzymes EcoRI and HindIII.

SiRNA oligonucleotides and negative control (NC) for gene interference were purchased from GenePharma (GenePharma, Suzhou, China).

The QM-7 myoblasts were incubated in a humidified atmosphere containing 5% CO₂ in M199 medium containing 10% fetal bovine serum (FBS), 10% tryptose phosphate broth, 0.1% penicillin, and 0.1% streptomycin (growth medium). Cells were incubated in this growth medium for 48 h, the density reached to 80 ~ 90%. Then the cells were induced to differentiate by lowering FBS concentration to 1% (differentiation medium) for another 48 h, reaching 80 ~ 90% preconfluent. Then the preconfluent myoblasts were used for subsequent transfection experiments.

The plasmids pcDNA3.1(+)-SLC27A1 and pcDNA3.1(+)-EGFP, or gga-1220 (siRNA) and NC, were transfected in QM-7 cells which incubated in 6-well plates using Lipofectamine® 3000 reagent (Invitrogen) following the manufacturer's guidelines. After that, cells were incubated and differentiated for 48 h, and reaching 80 ~ 90% confluent, then used for subsequent experiments.

Cells pretreated as described above were incubated further for 16 h at 37°C in serum free M199 medium containing 0.30 mM palmitate (Sigma, USA) bound to 1% bovine serum albumin (BSA, Sigma, USA) and 0.05 mM L-carnitine (Sigma, USA). After that, the cells were washed, collected and diluted with phosphate-buffered saline (PBS, pH 7.2–7.4). Cellular TG and free fatty acid (FFA) concentrations were measured using Chicken Triglyceride (TG) and FFA ELISA Kits (Jiyinmei Biological Technology Co., LTD, Wuhan, China), according to the manufacturer's guidelines.

Data are presented as means ± S.E.M based on at least three replicates for each treatment. A one-way ANOVA was used to determine statistical significance, where P < 0.05 was considered significant differences.

To visualize the difference of IMF deposition between breeds and within breeds, breast muscle samples were subjected to Oil Red O staining. Between the two breeds, the density and size of lipids in WC.D120.B (Figure 2A) and WC.D180.B (Figure 2B) were larger than those of in WRR.D120.B (Figure 2C) and WRR.D180.B (Figure 2D). Within breed, the density and size of lipids in D180 muscles were larger than that of in D120 muscles. To further quantify the difference of IMF deposition in chickens, we measured the IMF content of breast muscles using Soxhlet apparatus and the data were showed in Table 1. IMF content of WC muscles were significantly higher than that of WRR muscles (P < 0.01), 1.24 vs. 0.53 in D120 and 1.62 vs. 0.90 in D180, respectively. Within breed, the IMF content in D180 muscles were significantly higher than that in D120 muscles (P < 0.01).

To identify the underlying molecular mechanism responsible for chicken IMF deposition, the transcriptome of breast muscle of WC chicken and WRR chicken at different ages were analyzed with RNA-seq. Two birds per breed of each age were selected to produce cDNA libraries for RNA-seq separately. The clean reads of each sample were over 20 million, the expressed genes ranged from 16,202 to 17,838, and a little higher in WRR samples than in WC samples (Table 2).

Generally, false discovery rate (FDR) < 0.05 and two-fold difference together was regarded as differentially expressed. In the present study, there were 525, 161, 23, 87 DEGs detected in the comparisons of WRR.D120.B-VS-WC.D120.B, WRR.D180.B-VS-WC.D180.B, WC.D120.B-VS-WC.D180.B, and WRR.D120.B-VS-WRR.D180.B, respectively (Figure 3).

Of the shared DEGs among four comparisons, FBXO32 was the most common gene shared by all four comparisons, while PPP3CA was the common gene in WRR.D120.B-VS-WC.D120.B, WC.D120.B-VS-WC.D180.B, and WRR.D120.B-VS-WRR.D180.B. In addition, a total of 46 DEGs were shared by WRR.D120.B-VS-WC.D120.B and WRR.D180.B-VS-WC.D180.B, of which 12 were up-regulated in WC chicken, the rest were up-regulated in WRR chicken. These DEGs may be correlated with the different development properties of breast muscle between breeds. Otherwise, MUSTN1 and PPP3CA were the other two common genes shared by WC.D120.B-VS-WC.D180.B and WRR.D120.B-VS-WRR.D180.B, which might be involved in regulating the temporal characteristics of breast muscle development. The shared DEGs were presented in Supplementary Table 1.

To verify the gene expression pattern of DEGs detected by RNA-seq, a total of 20 genes were selected randomly to perform quantitative real-time PCR experiments and the primers were listed in Supplementary Table 2. The gene expression pattern of quantitative real-time PCR were generally accordant with that of RNA-seq, although different in fold changes (Figure 4), which indicated that our RNA-seq data were reliable.

GO-term analysis was used to investigate the function of DEGs. In the present study, the enriched GO-terms (Corrected P < 0.05) in the ontology classification “biological process” were represented in Figure 5. Between breeds, the enriched biological process mainly including multicellular organismal process, response to stimulus, biological regulation, regulation of biological process, regulation of cellular process, cellular developmental process, tissue development. The enriched biological process within WC chicken mainly focused on ion transport (Figure 5), no biological process was enriched within WRR chicken.

Based on GO function annotation, DEGs related to lipid metabolism would be attributable to chicken IMF deposition. Total of 33 (between breeds) and seven (between ages) DEGs were associated with IMF deposition (Supplementary Table 3). There were 24 DEGs down-regulated in WC chicken, including several well-known candidate genes for lipid metabolism, such as ABCA1 (Santamarina-Fojo et al., 2001), ACACB (Xu et al., 2014), CPT1A (Akkaoui et al., 2009), LPL (Claire et al., 2013; Zhang X. D. et al., 2015), and SLC27A1 (Sebastian et al., 2009; Guitart et al., 2014), of which SLC27A1 was also more down-regulated in WRR.D180.B than in WRR.D120.B. In other words, SLC27A1 were generally lower expressed in the higher IMF muscles.

In vivo, lots of genes execute their biological function concertedly, and pathway enrichment analysis can reveal the main biochemical metabolism process and signal transduction pathways in which DEGs are involved. In the present study, pathways significantly enriched with DEGs were assessed by a hypergeometric test using R packages (P < 0.05, FDR adjusted). As presented in Figure 6, there were 14 (in D120) and 13 (in D180) pathways identified in DEGs between breeds, with eight being shared by two ages which included MAPK signaling, TGF-beta, cytokine-cytokine receptor interaction, focal adhesion, regulation of actin cytoskeleton, arrhythmogenic right ventricular cardiomyopathy (ARVC), cardiac muscle contraction, hypertrophic cardiomyopathy (HCM). Within breeds, between different ages, DEGs in WC chicken were enriched in MAPK signaling and regulation of actin cytoskeleton, while DEGs in WRR chicken were enriched in VEGF signaling and fat digestion and absorption (Figure 6). Similar results were obtained by previous study on Beijing-you chickens and Arbor Acres chickens using Agilent cDNA microarray (Cui et al., 2012). These results indicate that not only the pathways related to lipid metabolism (MAPK signaling; Kokta et al., 2004; Du et al., 2010), but also those involved in cell-links [cytokine-cytokine receptor interaction (Ozaki and Leonard, 2002), focal adhesion (Petit and Thiery, 2000), regulation of actin cytoskeleton (Pollard, 2003)] and cell cycle (TGF-beta; Shi and Massague, 2003) could dedicate to the IMF deposition, for their crucial role in maintaining the morphology of tissue and cell growth and proliferation. In addition, key DEGs related to lipid metabolism include CPT1A, CETP, LPL, and SLC27A1, all being involved in PPAR signaling pathway (Figure 7B), although it did not reach up to statistical significance (P > 0.05).

IPA® was performed to investigate genes affecting lipid metabolism between breeds. A total of 16 networks were identified in WRR.D120.B-VS-WC.D120.B (Supplementary Table 4) to be associated with post-translational modification, organismal injury and abnormalities, cell-to-cell signaling and interaction, energy production, cancer and lipid metabolism. The DEGs ABCA1, CPT1A, LPL, and SLC27A1, which were down-regulated in WC.D120.B and involved in PPAR signaling pathway (Figure 7B), acted as important node gene and interacted in the network of lipid metabolism, molecular transport, small molecule biochemistry (Figure 7A). CETP was another important node gene in this network, but up-regulated in WC.D120.B.

In WRR.D180.B-VS-WC.D180.B, five networks were identified (Supplementary Table 4) and they were mainly related to connective tissue development and function, cancer, organismal injury and abnormalities, nerve system development and function, dermatological diseases and conditions.

Based on the above results and previous study, a network for SLC27A1 to regulate chicken IMF deposition was proposed (Figure 7C). In this proposed network, SLC27A1 might regulate LPL (Auwerx et al., 1996), or CPT1A (Mascaro et al., 1998; Song et al., 2010), or CETP (Li and Chiang, 2009), or ABCA1 (Chinetti et al., 2001), respectively or together via PPARs, and consequently regulate the lipid metabolism of WC chickens.

To further verify the role of SLC27A1 in lipid metabolism and its proposed molecular mechanism (Figure 7C), we overexpressed SLC27A1 in QM-7 cells. The primers for quantitative real-time PCR were presented in Supplementary Table 5.

Overexpression was achieved by transfection of QM-7 cells with pcDNA3.1(+)-SLC27A1 containing chicken full-length SLC27A1 cDNA. SLC27A1 mRNA levels increased over 34-fold in pcDNA3.1(+)-SLC27A1-transfected cells compared with control pcDNA3.1(+)-EGFP-transfected cells (Figure 8A). To assess the function of the overexpressed SLC27A1 in lipid metabolism, we measured the incorporation of palmitate into TG in QM-7 cells. Overexpressed SLC27A1 resulted in extremely significant decreases of cellular TG concentration (2.32 ± 0.23 mm/L vs. 3.52 ± 0.12 mm/L, P < 0.01, Figure 8B), and significant decreases of cellular FFA concentration (335.35 ± 12.13 μm/L vs. 355.94 ± 6.32, P < 0.05, Figure 8C), compared with control cells.

To investigate whether synergy or compensation effect exists among different fatty acid transporters, we evaluated SLC27A4, ACSL1, FABPpm/GOT2, FAT/CD36 mRNA levels in pcDNA3.1(+)-SLC27A1-transfected cells compared with control pcDNA3.1(+)-EGFP- transfected cells by quantitative real-time PCR (Figure 8D). SLC27A1 overexpression resulted in the up-regulated for SLC27A4 (P < 0.05), and no change was observed for ACSL1, GOT2, and CD36.

To investigate the molecular mechanism and biological pathway for SLC27A1 affecting IMF deposition, we assessed the mRNA levels of PPARs and DEGs involved in PPAR signaling pathway in pcDNA3.1(+)-SLC27A1-transfected cells compared with control pcDNA3.1(+)-EGFP-transfected cells by quantitative real-time PCR (Figure 8E). Overexpressed SLC27A1 resulted in the up-regulated for and CPT1A (P < 0.05), while no changes were observed for other genes.

SLC27A1 knockdown was accomplished by RNA interference to further assess the function of SLC27A1. SiRNA SLC27A1-1220 for SLC27A1 and NC for GAPDH were transfected into QM-7 cells respectively. SLC27A1 mRNA levels decreased nearly to 50% in SLC27A1-1220-transfected cells compared with control NC-transfected cells (Figure 9A). To assess the effect of the SLC27A1 knockdown in lipid metabolism, we measured the incorporation of palmitate into TG in QM-7 cells. SLC27A1 knockdown resulted in significant increases of cellular TG concentration (4.04 ± 0.10 and 3.55 ± 0.17 mm/L, P < 0.05, Figure 9B), and significant decreases of cellular FFA concentration (394.27 ± 18.36 μm/L and 465.01 ± 18.21, P < 0.05, Figure 9C), compared with control cells. The change pattern of FFA concentration in SLC27A1 knockdown was discrepant with that in SLC27A1 overexpression, suggesting that SLC27A1 may not be primary fatty acid transporter but function on lipid metabolism in QM-7 cell.

We also assessed SLC27A4, ACSL1, GOT2, and CD36 mRNA levels in SLC27A1-1220-transfected cells compared with control NC-transfected cells by quantitative real-time PCR (Figure 9D). SLC27A1 knockdown resulted in the down-regulated for SLC27A4 (P < 0.05), but no change was observed for ACSL1, GOT2 and CD36.

As well, we assessed the mRNA levels of PPARs and DEGs involved in the PPAR signaling pathway in SLC27A1-1220-transfected cells compared with control NC-transfected cells by quantitative real-time PCR (Figure 9E). SLC27A1 knockdown resulted in the down-regulated for CPT1A (P < 0.01), and no changes were observed for other genes.

IMF content is positively correlated with flavor, tenderness, and juiciness (Fernandez et al., 1999b; Chartrin et al., 2006; Gao and Zhao, 2009; Cannata et al., 2010; Hocquette et al., 2010; Madeira et al., 2013). In pigs, increases in IMF content are accompanied by the increase in sensory tenderness (P = 0.001) and sensory juiciness scores (P = 0.017; Cannata et al., 2010). In ducks, increasing lipid levels in breast muscle promoted tenderness and flavor, with correlation coefficients of 0.43 and 0.28, respectively (Chartrin et al., 2006). IMF affects meat quality positively mainly for two reasons. First, the oxidation of IMF can dissolve the muscle fiber bundle, thus improving the tenderness and juiciness of muscles. Second, IMF contains plenty of phospholipids, the degradation of phospholipids in heating produces various kinds of volatile aromatic compounds, thus improving the flavor of muscles. The present study showed that the IMF content of WC chickens were significantly higher than that of WRR chickens at two ages (Table 1), suggesting that the higher IMF content resulted in better meat quality of WC chickens.

In the present study, we compared and analyzed the breast transcriptional profiles of WC chickens and WRR chickens of distinct genetic background, and a lot of DEGs between breeds and within breeds affecting IMF deposition were identified. These DEGs such as ABCA1, CPT1A, LPL, and SLC27A1 were mostly down-regulated in WC chickens (Supplementary Table 3).

ABCA1 (ATP-binding cassette transporter A1) functions as a cholesteral efflux pump in the cellular lipid removal pathway (Santamarina-Fojo et al., 2001; Alder-Baerens et al., 2005). ABCA1 deficiency reduces lipid efflux, and results in lipid accumulation in the central nervous system (Hirsch-Reinshagen et al., 2004). CPT1A (Carnitine palmitoyl transferase I, liver) is a rate-limiting enzyme of mitochondrial fatty acid beta-oxidation (McGarry and Brown, 1997; Zammit, 2008; Akkaoui et al., 2009), and plays a prominent role in triglyceride metabolism. Overexpression of the CPT1A enhanced fatty acid oxidation in hepatocytes, β-Cells and muscle cells (Perdomo et al., 2004; Herrero et al., 2005; Stefanovic-Racic et al., 2008; Akkaoui et al., 2009), and decreased lipid accumulation (Stefanovic-Racic et al., 2008; Akkaoui et al., 2009). CETP (Cholesteryl ester transfer protein) is involved in the transfer of neutral lipids, including cholesteryl ester and triglyceride, among lipoprotein particles. Overexpressed CETP in SW872 cells and mice both reduced TG accumulation (Izem et al., 2015; Palmisano et al., 2016), while in chickens CETP was positively correlated with phospholipid accumulation (Cui et al., 2012). LPL (Lipoprotein lipase) has the dual functions of triglyceride hydrolase and lipoprotein uptake (Gotoda et al., 1989; Goldberg, 1996). LPL is an important candidate gene for chicken lipid metabolism, and the mRNA level and enzymatic activity of LPL was negatively correlated with IMF contents (Claire et al., 2013; Zhang X. D. et al., 2015). SLC27A1 is involved in translocation of long-chain fatty acids (LFCAs) across the plasma membrane and subsequently lipid metabolism in skeletal muscle (García-Martínez et al., 2005; Sebastian et al., 2009; Holloway et al., 2011; Guitart et al., 2014), heart (Chiu et al., 2005), 3T3-L1 cell (Lobo et al., 2007), and 293 cell (Hatch et al., 2002).

Overexpression of the SLC27A1 increased rate of fatty acid oxidation in heart (Chiu et al., 2005) and skeletal muscle (Nickerson et al., 2009; Sebastian et al., 2009; Holloway et al., 2011; Guitart et al., 2014), reduced TG accumulation in skeletal muscle (Guitart et al., 2014).

Moreover, ABCA1, CPT1A, LPL, and SLC27A1 were all involved in the PPAR signaling pathway (Figure 7B), a well-known pathway affecting lipid metabolism (Kokta et al., 2004; Du et al., 2010), and formed a IPA® network related to lipid metabolism, molecular transport, small molecule biochemistry (Figure 5A), implying that these genes may be key genes affecting chicken IMF deposition and their down-regulated expression means that a lower lipid catabolism exists in WC chicken.

Our RNA-seq data revealed that SLC27A1 was lower expressed in WC.D120.B and WRR.D180.B compared with in WRR.D120.B, while the IMF content of WC.D120.B and WRR.D180.B were higher than that of WRR.D120.B (Table 1). In other words, SLC27A1 is generally expressed lower in muscles with higher IMF contents. Our findings in cell experiments further confirmed these results. Overexpression of SCL27A1 in QM-7 cells caused the decrease in the cellular TG content (Figure 8B), while knockdown of SLC27A1 with RNAi resulted in the increase in the cellular TG content (Figure 9B). The reduced intramuscular TG was also observed in mouse skeletal muscle overexpressed SLC27A1 (Guitart et al., 2014). Overall, SLC27A1 is negatively correlated with the lipid accumulation.

Previous studies have shown that overexpressed SLC27A1 in the skeletal muscle promoted fatty acid oxidation (Holloway et al., 2011; Guitart et al., 2014). Overexpression of SLC27A1 increased the expression of CPT1A (Figure 8E), and knockdown of SLC27A1 decreased the expression of CPT1A (Figure 9E), suggesting that SLC27A1 may regulate the expression of CPT1A in some way. PPARs are known to be pivotal transcription factors of genes involved in lipid metabolism (Lemberger et al., 1996). Their binding to PPAR responsive element localized in the 5′-flanking region (Mascaro et al., 1998) and the second intron (Song et al., 2010) both increased CPT1A expression. As fatty acids and their derivatives are ligands for PPARs (Forman et al., 1995), it is possible that SLC27A1 overexpression increases fatty acids afflux and activation, which offers ligands for binding and activating PPARs, in turn activating the PPARs-dependent gene transcription, such as CPT1A, a rate-limiting enzyme of mitochondrial fatty acid oxidation (McGarry and Brown, 1997; Zammit, 2008; Akkaoui et al., 2009). In addition, cellular FFA change patterns were discrepant in SLC27A1 overexpression (Figure 8C) and knockdown (Figure 9C), indicating that SLC27A1 plays a supplementary role in fatty acid transport, similar in rat skeletal muscle (Nickerson et al., 2009). Therefore, SLC27A1 involves in fatty acids oxidation through collaboration with CPT1A (Sebastian et al., 2009), similar to FAT/CD36 (Campbell et al., 2004; Schenk and Horowitz, 2006), but not for its transport activity across mitochondrial membrane.

Several fatty acid transporters, fatty acid translocase (FAT/CD36; Campbell et al., 2004; Schenk and Horowitz, 2006; Smith et al., 2011), plasm membrane fatty acid binding protein (FABPpm/GOT2; Clarke et al., 2004), long chain Acyl-CoA synthetase (ACSLs; Ellis et al., 2011), and fatty acid transporters (FATPs; Stahl, 2004; Kazantzis and Stahl, 2012), have been identified contributing to fatty acids uptake and oxidation. Some transporters may cooperate concertedly in fatty acids uptake, such as FABPpm and CD36 in heart and muscle (Chabowski et al., 2007), CD36 and ACSL1 in MDCK cell (Schneider et al., 2014), and ACSL1 and FATP1 in adipocytes (Richards et al., 2006). Both FATP1 and FATP4 belong to the FATP family, and their amino acid identity is 60.3% (Herrmann et al., 2001). FATP1 may involve in fatty acid uptake by hormonal regulation, while FATP4 may mediate fatty acid uptake on the basal level (Stahl et al., 2002). These fatty acid transporters are coexpressed in skeletal muscle for unknown reasons, and their functional impact with each other remains unknown. In this study, overexpression or knockdown of the SLC27A1 could not change the expression of the ACSL1, GOT2, and CD36 (Figures 8D, 9D). These findings indicate that different fatty acid transporters have distinct transcription regulatory mechanism, while SLC27A4, for its high homology with SLC27A1, was regulated similar to SLC27A1.

In conclusion, the present study showed that a higher IMF content resulted in a better meat quality of WC chickens. Lower lipid metabolism exists in WC chickens, the higher IMF deposition in WC chickens may be due to its lower fatty acid oxidation, and lower expression of SLC27A1 down-regulated the fatty acid oxidation by collaboration with CPT1A. Moreover, these findings also indicate that reduced lipid catabolism, rather than increased lipid anabolism, contributes to chicken IMF deposition.

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.