The research in the GEO database meets the following criteria: (1) Studies of liver regeneration after PH in mice. (2) Studies of mRNAs profile. (3) Next-generation sequencing or microarray assay. (4) Liver tissues at 48 and 72 h after PH. Based on these criteria, we included three data sets of liver regeneration (GSE4528, GSE6998, and GSE20427). The microarray data of GSE4528 was based on the GPL339 ([MOE430A] Affymetrix Mouse Expression 430A Array), including two normal mouse liver tissues, two liver tissues at 48 h after PH, and two liver tissues at 72 h after PH. The microarray data of GSE6998 was based on the GPL1261 ([Mouse430_2] Affymetrix Mouse Genome 430 2.0 Array), including two normal mouse liver tissues, two liver tissues at 48 h after PH, and two liver tissues at 72 h after PH. The microarray data of GSE6998 was based on the GPL1261 ([Mouse430_2] Affymetrix Mouse Genome 430 2.0 Array), including six normal mouse liver tissues, six liver tissues at 48 h after PH. Figure 1 shows the workflow of retrieval and bioinformatics analysis of available data sets from GEO.

The differential genes between normal liver tissues and liver tissues at 48 and 72 h after PH in each data set were analyzed using GEO2R online tool (Qian et al., 2019), P < 0.05 and | log fold change FC| ≥ 1 were set as the cut-off criteria. Then the consistent differential mRNAs among these three data sets were screened using Draw Venn Diagram (Dong et al., 2020)¹.

In order to further understand the functions of these differential genes in the process of liver regeneration, we used online software Database for Annotation, Visualization and Integrated Discovery (DAVID Bioinformatics Rescources 6.8) (Gan et al., 2018)² to perform a functional enrichment analysis of the differential genes, including GO analysis [biological pathways (BP), molecular functions (MF), and cell components (CC)] and KEGG pathways analysis. Then RStudio software (version 3.5.3) (Huang et al., 2020) was used to visualize the enrichment results. The screening conditions for GO term was top 5 terms with P < 0.05, and the screening conditions for KEGG pathwaywas P < 0.05.

In order to study the interaction between these differential genes, we used The Search Tool for the Retrieval of Interacting Genes (STRING) (Dong et al., 2020)³ database to generate PPI networks. The nodes and edges in the network represented genes and their interactions, respectively. At the same time, we used Cytoscape (version 3.7.0) (Dong et al., 2020) to construct a PPI network of the target genes. The shape of the node indicated the expression level and the color indicated the degree of connection.

Male mice aged 2–3 months were purchased from SLAC Laboratory (Shanghai, China) and kept under standard conditions (Lee et al., 2020). These mice were randomly divided into three groups: control group (n = 8), sham group (n = 8), and PH group (n = 8). PH surgery was mainly performed in accordance with the procedure described previously (Nevzorova et al., 2015) and the middle lobe and left lateral lobe of the mouse liver (about 2/3) were removed. The mice were euthanized at 48 h after PH, part of each liver was used to separate hepatocytes for cell cycle detection, part of each liver was fixed in 10% neutral buffered formalin for immunohistochemistry, and the rest of each liver was frozen in liquid nitrogen until use. The protocols for the care and use of animals were approved by the Animal Care and Use Committee of The Affiliated Hospital of Yunnan University.

BNL CL.2 normal mouse liver cell line was purchased from the Cell Bank of the Chinese Academy of Sciences (Shanghai, China). The cells were cultured in high-glucose Dulbecco’s modified Eagle’s medium (Hyclone, United States) supplemented with 10% fetal bovine serum (Hyclone, United States). Cells were transfected with si-NC (100 nM) or si-Ube2c (100 nM) for 48 h using Lipofectamine 3000 (Invitrogen, United States) according to the manufacturer’s instructions. Si-NC and si-Ube2c were synthesized in GenePharma (Shanghai, China), and the sequence was shown below: Mus-si-Ube2c-1 sense: 5′-CCC ACA GCA UUU AAG AAA UTT-3′, antisense: 5′-AUU UCU UAA AUG CUG UGG GTT-3′. Mus-si-Ube2c-2 sense: 5′-AAA AAA GAC AAC ACA AAA GAG-3′, antisense: 5′-CUU UUG UGU UGU CUU UUU UCU-3′. Mus-si-Ube2c-3 sense: 5′-UAA UAU ACA UUG UUA AGG GUU-3′, antisense: 5′-CCC UUA ACA AUG UAU AUU AAA-3′. Mus-si-NC sense: 5′-UUC UCC GAA CGU GUC ACG UTT-3′, antisense: 5′-ACG UGA CAC GUU CGG AGA ATT-3′.

Total RNA was extracted from cells using Trizol reagent (life, North American) and reverse-transcribed into complementary DNA using 5 × Prime Script RT Master Mix kit (Takara, Tokyo, Japan). SYBR real-time quantitative PCR (qPCR) Master Mix (Takara) was used to carry out qPCR according to the manufacturer’s instructions. Target gene expression was normalized to GAPDH levels in respective samples as an internal control and calculated using the 2^–ΔΔCt method. The primer sequences were shown in Table 1.

Liver tissues or cells were lysed in RIPA buffer with complete protease inhibitor (Sigma). Nucleoprotein was prepared as previously described (Ho et al., 2010). Then whole lysates (30 μg) were separated by polyacrylamide gel electrophoresis and proteins were transferred to polyvinylidene difluoride (PVDF) membranes. These membranes were incubated with primary antibodies against BUB3 (1:2,000, CY8528), CHK1 (1:1,000, CY5063), cyclin A (1:1,000, CY1026), MCM5 (1:2,000, CY7185), P21 (1:1,000, 27296-1-AP), Ube2c (1:1,000, 12134-2-AP), and GAPDH (1:2,000, ab9485) overnight at 4°C followed by incubate with secondary antibodies [goat anti-rabbit secondary antibody (HRP)] 2 h at room temperature. Immune complexes were detected using the Enhanced Chemiluminescence System (Thermo Fisher Scientific) and the intensity of each band was quantified using ImageJ software. Primary antibodies against Bub3, CHK1, cyclin A, and MCM5 were purchased from Abways (Shanghai, China). Primary antibodies against P21 and Ube2c were purchased from Proteintech (Wuhan, Hubei, China). Primary antibody against GAPDH was purchased from Abcam (Shanghai, China).

The 10% neutral buffered formalin fixed and paraffin-embedded liver tissues were used to prepare liver sections (4 μm). Sections were pre-treated using heat mediated antigen retrieval with sodium citrate buffer (pH 6) for 20 min. Then these sections were incubated with primary antibody overnight at 4°C and secondary antibody for 2 h at room temperature. The primary antibodies included BUB3 (1:100), CHK1 (1:50), cyclin A (1:50), MCM5 (1:100), P21 (1:100), Ube2c (1:200), and PCNA (1:5,000, 13110S, CST). Positive hepatocytes were observed and captured at 200× under microscopy.

BNL CL.2 normal mouse liver cells (2 × 10³ cells/well) were treated with si-Ube2c for 72 h in 96-well plates. According to the manufacturer’s protocol, Cell Counting Kit-8 (C0037, Beyotime, Shanghai, China) was used to detect cell viability at 0, 24, 48, and 72 h after treatment. A microplate reader (Multiskan^TM FC, Thermo Fisher Scientific) was used to measure the absorbance at 450 nm.

Cell Cycle and Apoptosis Analysis Kit (C1052) (Beyotime, Shanghai, China) was used to perform the flow cytometry and assess cell cycle progression according to the manufacturer’s protocol. In general, the cells were fixed in an ice bath pre-cooled 70% ethanol for 2 h. Then 0.5 mL of propidium iodide staining solution was added to each tube of cell samples, and keep in the dark at 37°C for 30 min. A flow cytometer (BD FACSCalibur) was used to detect the red fluorescence at the excitation wavelength of 488 nm. FlowJo V10 software was used for cell DNA content analysis.

Data were shown as mean ± standard deviation (SD). Statistical analysis was performed using one-way analysis of variance (ANOVA) by GraphPad Prism 8.0 statistical software (GraphPad Software, CA, United States) and significant differences were defined when P < 0.05.

For liver tissue at 48 h after PH, 1,160 differential genes in GSE4528, 1,182 differential genes in GSE6998, and 1,031 differential genes in GSE20427 were identified. Among the differential genes, 765, 559, and 469 genes were upregulated (Figure 2A) while 395, 623, and 562 genes were downregulated in GSE4528, GSE6998, and GSE20427, respectively (Figure 2B). The consistently upregulated and downregulated genes in all three independent cohorts were identified using Venn analysis and a Venn diagram was generated by Draw Venn Diagram. As a result, we got a total of 46 upregulated genes and 19 downregulated genes.

These 65 differential genes were submitted into DAVID for GO analysis and KEGG pathway analysis to gain insights into the biological functions of these consensus genes in residual liver. In BP term, the result demonstrated that these upregulated genes were mainly enriched in cell cycle, cell division, mitotic nuclear division; In CC term, these upregulated genes were mainly involved in nucleus, cytoplasm, nucleoplasm; In MF term, these upregulated genes were mainly associated with protein binding, ATP binding and nucleotide binding (Figure 2C). Downregulated genes were mainly enriched in lipid metabolic process, negative regulation of signal transduction and regulation of cell growth in BP term, and mainly associated with growth factor binding in MF term (Figure 2D). KEGG pathway analysis indicated that these 65 differential genes were mainly related to cell cycle, DNA replication and p53 signaling pathway (Figure 2E).

For liver tissue at 72 h after PH, 1,344 differential genes in GSE4528 and 1,633 differential genes in GSE6998 were identified. Among the differential genes, 832 and 1,151 genes were upregulated (Figure 3A) while 512 and 482 genes were downregulated in GSE4528 and GSE6998, respectively (Figure 3B). Venn analysis showed a total of 223 upregulated genes and 40 downregulated genes.

These 263 differential genes were also submitted into DAVID for GO analysis and KEGG pathway analysis. In BP term, the result demonstrated that these upregulated genes were mainly enriched in cell cycle, cell division, and mitotic nuclear division; In CC term, these upregulated genes were mainly involved in nucleus, cytoplasm, nucleoplasm; In MF term, these upregulated genes were mainly associated with protein binding, nucleotide binding and ATP binding (Figure 3C). Downregulated genes were mainly involved in endoplasmic reticulum in CC term (Figure 3D). KEGG pathway analysis indicated that these 263 differential genes were mainly related to cell cycle, DNA replication and nucleotide excision repair (Figure 3E).

We constructed a PPI network to further explore the interaction between the consensus genes by using STRING database and Cytoscape. As shown in Figure 4A, there were 61 nodes and 397 edges in the network between consensus genes in residual liver at 48 h after PH. The top 10 hub genes were: Ccna2, Aurkb, Aurka, Top2a, Kif11, Smc2, Pbk, Zwilch, Mcm5, and Rrm2. There were 243 nodes and 4,456 edges in the network between consensus genes in residual liver at 72 h after PH. The top 10 hub genes were: Zwilch, Spc25, Pbk, Trip13, Uhrf1, Kif11, Aurka, Aurkb, Rrm2, and Plk1 (Figure 4D). We analyzed the differential genes involved in cell cycle pathway, which was the most active pathway at 48 and 72 h after PH. The results showed that a total of 8 upregulated genes and 20 upregulated genes in cell cycle at 48 and 72 h after PH, respectively (Table 2). Venn analysis showed a total of 44 upregulated consensus genes and 8 downregulated consensus genes at 48 and 72 h after PH (Table 3), and Ccna2, Cdkn1a, Pbl1, Dbf4, Mcm7, Chek1, Mcm5, and Bub3 were both involved in cell cycle. Then PPI network showed 25 consensus genes were related to 6 genes of the cell cycle both at 48 and 72 h after PH. Among these 25 genes, only Igfbp3 was downregulated (Figures 4B,E). Furthermore, we found that only Ube2c were interacted with the six genes other than DBF4 (Figures 4C,F).

We constructed a mouse model for liver regeneration to verify the expression of target genes in residual liver at 48 h after PH. Western blotting results showed that protein levels of Ube2c, Cyclin A2, P21, CHK1, and MCM5 were both significantly increased in the residual liver at 48 h after PH (Figure 5A). Immunohistochemical staining results were similar to the results of western blotting (Figure 5B). At the same time, we used flow cytometry to detect the cell cycle of hepatocyte during liver regeneration. The results showed that the proportion of G0/G1 cells in PH group was obviously decreased compared to that in control group and sham group, while the proportion of S cells in PH group was obviously increased compared to that in control group and sham group (Figure 5C). In addition, the level of PCNA in PH group was also higher than that in control and sham group (Figure 5D). This indicates that PH stimulates the remaining liver cells to synthesize DNA, enter the cell cycle, and promote hepatocyte proliferation at 48 h.

We used qPCR to detect the interference of Ube2c and the effect of knocking down Ube2c on the expression of cycle-related genes. Compared with the control group and the si-NC group, si-Ube2c-1 has the best interference effect on Ube2c mRNA (Figure 6A). The decreased Ube2c mRNA caused a significant reduction in the transcription level of Mcm5, Chek1, and Ccna2, while the transcription level of Cdkn1a increased significantly (Figure 6B). The western blotting results also confirmed that the decrease of Ube2c protein was accompanied by the decrease of MCM5, CHK1, cyclin A2 proteins and the increase of P21 protein (Figure 6C). The results of flow cytometry showed that Ube2c knockdown increased the proportion of GO/G1 cells during liver regeneration (Figure 6D). Compared with the control group and the si-NC group, the cell viability of the si-Ube2c treatment group also decreased with time (Figure 6E). This indicates that Ube2c knockdown has an inhibitory effect on hepatocyte proliferation during liver regeneration.