Establishment of NAFLD mice model
Totally 20 male mice (8 weeks old, weighting 16-20 g) were obtained from Changzhou Cavens Experimental Animal Co., Ltd. All animals were kept in plastic cages at a constant temperature of 25 ℃, humidity of 40% and 12-h light/12-h dark cycle. The mice also had free food and water access during the experiment. In addition, we randomly divided the mice into two groups and provided with different diets for 32 weeks: control group fed with standard chow (n=10) and NAFLD group fed with high-fat diet (HFD) (n=10). The HFD was purchased from the Research Diets, Inc., New Brunswick, NJ (60% kcal fat; D12492). The levels of blood glucose were measured after fasting for 12 h. After that, all mice were anesthetized and sacrificed to collect blood for biochemical analysis, while the livers were harvested and weighted immediately. Serum and liver samples were stored in liquid nitrogen at -80 ℃ for subsequent experiments. A small pieces of hepatic tissues were fixed in 4% paraformaldehyde (PFA) > 48 h at 4 ℃ for histological analysis. This study was approved by the Animal Research Ethical Committee of the Fudan University Pudong Medical Center. All experimental procedures followed the Guidelines for the Care and Use of Laboratory Animals of the National Institute of Health in China.
Glucose tolerance test (GTT) and insulin tolerance test (ITT) were determined after fasting for 12 h. The 1.5 g kg-1 glucose was injected intraperitoneally to conduct GTT. In contrast, 0.5 IU kg-1 insulin was injected for ITT. After injection, the blood glucose level was determined using OneTouch Ultra Glucose Test Strips (LifeScan Inc., Milpitas, CA) at different timelines, including 0, 30, 60, 90, and 120 min.
Plasma triglyceride (TG) was measured using Triglyceride Kit (Wako Diagnostics, Richmond, VA), while the Cholesterol Assay Kit (BioVision, Irvine, CA) was used to determine the level of total cholesterol (TC). Plasma insulin was also measured with a MILLIPLEX(®) MAP Mouse Metabolic Magnetic Bead Panel kit following the manufacturer’s instructions. To determine the hepatic TG and TC levels in control and NAFLD group, hepatic tissues were rinsed with phosphatebuffered saline (PBS) and collected in isopropanol. The homogenate was generated after centrifugation at 12 000 × g for 15 min and then incubated at 4 °C. The supernatants were used for further analyses.
The hepatic tissues from each mouse were fixed in 4% paraformaldehyde, followed by dehydrated in grades of alcohol, and embedded in paraffin wax (Sakura, Tokyo, Japan). The sections with 5 μm thickness were stained with hematoxylin and eosin (H&E). The slices were also stained with Oil Red O (ORO) to analyze the accumulation of hepatic lipid. A light microscope was used to observe histological features of liver tissues under x200 (Olympus, Tokyo, Japan).
RNA insolation and quality control
Total RNA was extracted and purified using TRIzol reagent (Invitrogen, CA, USA) and RNeasy Mini kit (Qiagen). The RNA concentration was assessed using a spectrophotometer (NanoDrop ND-1000, Thermo Scientific), while the RNA integrity was measured using electrophoresis.
The analysis of CircRNA sequencing
RNA sequencing was applied using RNA samples from each group, while the RNase R was treated to remove linear RNAs from isolated RNA. The amplified circRNAs were reverse transcribed into cDNA using random primers following the manufacturer’s instructions. The cDNA was then synthesized and purified using the QiaQuick PCR extraction kit (Qiagen). The cDNA library was finally prepared according to illumine TruSeq library preparation instruction. CircRNA sequencing was conducted on an Illumina HiSeqTM 4000 (Illumina, CA, U.S.A).
Reverse transcription-quantitative polymerase chain-reaction (RT-qPCR) validations
RT-qPCR was carried out to validate the results of RNA sequencing. The isolated RNAs from liver tissues were reverse transcribed into cDNA using the RT-PCR kits (Takara) in accordance with the manufacture’s protocol, followed by amplifications using a SYBR Premix Ex Taq kit (Takara). The thermal conditions are as follows: 95˚C for 5 min, followed by 40 cycles of 10 sec at 95˚C, 60˚C for 30 sec and 72˚C for 30 sec. β‑actin was used as the internal reference. PCR bands were gel-purified and sequenced using Sanger method. The algorithm 2-ΔΔCq method was applied to normalize the relative gene expressions to β‑actin. The primer sequences used for RT-qPCR are listed in Table 1.
RNA sequencing and bioinformatics analysis
The raw data with low-quality reads were filtered out using Qubit3.0, while the remaining reads were mapped to the mouse genome (GRCm38) using Bowtie2 v2.2.8. The reference genome was established by software TopHat2 v2.1.1 (25,26). The remaining reads after alignment were subjected to CIRCexplore, MapSplice and CircRNA_finder software for circRNA identification. The chromosome distribution of the identified circRNAs were evaluated. The circRNAs were categorized as significantly differentially expressed using edgeR package (fold change ≥ 1.5 and p-value < 0.05). The differentially expressed circRNAs were selected using volcano plotting. Gene ontology (GO) was applied to annotate meaningful gene products, which contains three categories of biological function, namely biological process (BP), cellular components (CC) and molecular function (MF). In contrast, Kyoto Encyclopedia of Genes and Genomes (KEGG) was utilized to identify the target genes in biological pathways.
Once the differentially expressed circRNAs are identified, StarBase v2.0 software was used to predict the target miRNAs. Mireap (https://sourceforge.net/projects/mireap/), Miranda v3.3a, (http://miranda.org.uk/) and TargetScan v7.0, (http://www.targetscan.org) databases were applied to predict the novel circRNAs. After that, the circRNA-miRNA network was visualized using Cytoscape software. To improve the reliability of our prediction, the match score was set as > 140 and the minimum free energy < -20.
All data are expressed as mean ± standard deviation. An independent sample t-test was carried out to determine differences between groups using SPSS (version 23.0; IBM Corp., Armonk, NY, USA). Statistical significance was set at p < 0.05.