Concentration and intervention time screening of LPS inducing cell proliferation
The proliferation ability of GMCs induced by different concentrations (0.5 μg/mL, 1.0 μg/mL, 3.0 μg/mL, 5.0 μg/mL and 10.0 μg/mL) of LPS were detected with CCK-8 assay at 24h and 48h. The relationship between cell proliferation, the concentration of LPS, and intervention time was presented in Figure 1. The results of the CCK-8 proliferation assay demonstrated that LPS could induce cell proliferation on GMCs, the maximum absorbance of OD 450nm was observed when the concentration of LPS was 3.0 μg/mL (Supplementary file 1), which means that 3.0 μg/mL was the optimal concentration of LPS to induce cell proliferation. Meanwhile, there was no significant difference between intervention time of 24h and 48h (p=0.62), when the concentration of LPS was 3.0 μg/mL. Therefore, 3.0 μg/mL LPS and intervention 24h were chosen for follow-up studies.
Characteristics of differentially expressed lncRNAs
In this study, six groups of cells were involved in subsequent experiments, including three groups of LPS-induced GMCs as the model group (LPS1-3) and three groups of normal GMCs as the control group (CON1-3).
After deduplication, quality trimming, and quality filtering, the sequencing datas at both ends of R1 and R2 were shown good quality (Q20 base and Q30 base were both greater than 95%). The clean reads of the six samples were all greater than 95%, which met the quality requirements of sequencing. The quality control result of sequencing data was presented in Tab. 1 (Supplementary file 2).
Violin plot showing the relative abundance of lncRNAs in each sample was presented in Fig. 2A. In the violin plot, the white dot represents the median, the violin shape represents the kernel density curves, and the black line represents the 95% confidence interval. Violin plot demonstrating that there were significant differences in lncRNAs’ expression between LPS induced GMCs as compared with control GMCs. The threshold for differentially expressed lncRNAs was set at absolute Fold Change (FC)≥1.5 and P<0.05 (Mirza et al. 2015, Weber et al. 2019), 1532 differentially expressed lncRNAs, including 594 upregulated lncRNAs and 938 downregulated lncRNAs, were selected from 46879 lncRNAs (Fig. 2B, Supplementary file 3) eventually. The heat map of the top 50 differentially expressed lncRNAs was shown in Fig. 2C. The top 10 upregulated and downregulated expressed lncRNAs were presented in Tab. 2, and the radar map (Fig.2D) demonstrated the top 10 upregulated and downregulated expressed lncRNAs in LPS induced GMCs as compared with control GMCs.
Construction of the lncRNA-mRNA regulatory network
To explore the functions of differentially expressed lncRNAs, 556 target mRNAs of 236 lncRNAs out of 1532 differentially expressed lncRNAs were screened out from LncTar after deleting the duplicate data (Supplementary file 4). The highly coordinated expression between lncRNAs and target mRNAs may be due to complementary base pairing between lncRNA and mRNA (Yang et al. 2014). In this lncRNA-mRNA regulatory network, we can see the interaction relationship between lncRNA and mRNA. For example, lncRNA NONMMUG029023.2 can regulate mRNA Stoml2 expression. Ptdss2 could be affected by lncRNA NONMMUG039651.2 and lncRNA NONMMUG095401.1 at the same time. The lncRNAs-mRNAs regulatory network was presented in Fig. 3.
To reveal the biological functions of differentially expressed lncRNAs in LPS-induced GMCs, we further performed GO biological process and KEGG pathway analysis on all mRNAs in the lncRNA–mRNA regulatory network. The results of GO and KEGG analysis were presented in Fig. 4.
Within the biological processes (BP) category of GO classification, cellular macromolecule metabolic process, negative regulation of biological process, and nitrogen compound metabolic process were the top 3 over-represented terms (Fig. 4A). Within the cellular components (CC) category of GO classification, intracellular, intracellular part, and membrane-bounded organelle were the top 3 over-represented terms (Fig. 4B). Within the molecular function (MF) category of GO classification, galactoside 2-alpha-L-fucosyltransferase activity, alpha-(1,2)-fucosyltransferase activity, and chromatin insulator sequence binding were the top 3 over-represented terms (Fig. 4C). The KEGG metabolic pathway analysis demonstrated that GnRH secretion, Melanoma, Ras signaling pathway, Glycosphingolipid biosynthesis-globo and isoglobo series, and beta-Alanine metabolism were the top 5 most significant enriched KEGG pathways (Fig. 4D).
RT-qPCR validation of 6 selected lncRNAs
To verify the accuracy of the sequencing results, we used RT-qPCR to detect the expression of 6 selected lncRNAs which are highly conservative with homo sapiens (Tab. 3) (Wang et al. 2019). All primers used for PCR amplification were presented in supplementary file 5. RT-qPCR was done as triplicates with the standard deviation for each PCR shown in Fig. 5. The results of RT-qPCR (Supplementary file 6) showed the same expression trend as the RNA-Seq results, and 6 selected lncRNAs were all upregulated in LPS-induced GMCs.
Construction of the lncRNA-associated ceRNA network
Except for lncRNA-mRNA regulatory network, lncRNAs can also participate in multiple gene networks that regulate diverse biological processes, like the ceRNA network (Li et al. 2021).
To construct a lncRNA-associated ceRNA network, We utilize 6 selected lncRNAs above that are conservative with homo sapiens and have been verified to build ceRNA networks. The ceRNA network consisted of the top 3 miRNAs combined with screened lncRNAs and mRNAs with high confidence (cumulative weighted context score cutoff level less than -0.8) bound to the miRNAs, including 6 lncRNAs, 18 miRNAs, and 419 mRNAs (Fig. 6, Supplementary file 7 & Supplementary file 8). It can be seen clearly in Fig. 6 that lncRNAs can be competing targets of shared miRNAs with other mRNAs and form a complex regulatory ceRNA network. For example, the lncRNA NONMMUG089165.1 could act as a sponge for mmu-miR-3960 to affect EVX1 expression. PARD3B could be affected by lncRNA NONMMUG039651.2/mmu-miR-7081-5P and lncRNA NONMMUG028702.2/mmu-miR-7044-5P axis at the same time.
To reveal the biological functions of lncRNAs in ceRNA network, we performed GO biological process and KEGG pathway analysis on all mRNAs involed in ceRNA network. The results of GO and KEGG analysis were presented in Fig. 7.
Within the biological processes (BP) category of GO classification, system development, animal organ development, and multicellular organism development were the top 3 over-represented terms (Fig. 7A). Within the cellular components (CC) category of GO classification, neuronal cell body membrane, cell body membrane, and alpha-beta T cell receptor complex were the top 3 over-represented terms (Fig. 7B). Within the molecular function (MF) category of GO classification, DNA-binding transcription activator activity, RNA polymerase II-specific, alpha-1,6-mannosylglycoprotein 6-beta-N-acetylglucosaminyltransferase activity, and DNA-binding transcription factor activity were the top 3 over-represented terms (Fig. 7C). The KEGG metabolic pathway analysis demonstrated that Collecting duct acid secretion, Circadian rhythm, Proteoglycans in cancer, Pathways in cancer, and Oxytocin signaling pathway were the top 5 most significant enriched KEGG pathways (Fig. 7D).
p>
Concentration and intervention time screening of LPS inducing cell proliferation
The proliferation ability of GMCs induced by different concentrations (0.5 μg/mL, 1.0 μg/mL, 3.0 μg/mL, 5.0 μg/mL and 10.0 μg/mL) of LPS were detected with CCK-8 assay at 24h and 48h. The relationship between cell proliferation, the concentration of LPS, and intervention time was presented in Figure 1. The results of the CCK-8 proliferation assay demonstrated that LPS could induce cell proliferation on GMCs, the maximum absorbance of OD 450nm was observed when the concentration of LPS was 3.0 μg/mL (Supplementary file 1), which means that 3.0 μg/mL was the optimal concentration of LPS to induce cell proliferation. Meanwhile, there was no significant difference between intervention time of 24h and 48h (p=0.62), when the concentration of LPS was 3.0 μg/mL. Therefore, 3.0 μg/mL LPS and intervention 24h were chosen for follow-up studies.
Characteristics of differentially expressed lncRNAs
In this study, six groups of cells were involved in subsequent experiments, including three groups of LPS-induced GMCs as the model group (LPS1-3) and three groups of normal GMCs as the control group (CON1-3).
After deduplication, quality trimming, and quality filtering, the sequencing datas at both ends of R1 and R2 were shown good quality (Q20 base and Q30 base were both greater than 95%). The clean reads of the six samples were all greater than 95%, which met the quality requirements of sequencing. The quality control result of sequencing data was presented in Tab. 1 (Supplementary file 2).
Violin plot showing the relative abundance of lncRNAs in each sample was presented in Fig. 2A. In the violin plot, the white dot represents the median, the violin shape represents the kernel density curves, and the black line represents the 95% confidence interval. Violin plot demonstrating that there were significant differences in lncRNAs’ expression between LPS induced GMCs as compared with control GMCs. The threshold for differentially expressed lncRNAs was set at absolute Fold Change (FC)≥1.5 and P<0.05 (Mirza et al. 2015, Weber et al. 2019), 1532 differentially expressed lncRNAs, including 594 upregulated lncRNAs and 938 downregulated lncRNAs, were selected from 46879 lncRNAs (Fig. 2B, Supplementary file 3) eventually. The heat map of the top 50 differentially expressed lncRNAs was shown in Fig. 2C. The top 10 upregulated and downregulated expressed lncRNAs were presented in Tab. 2, and the radar map (Fig.2D) demonstrated the top 10 upregulated and downregulated expressed lncRNAs in LPS induced GMCs as compared with control GMCs.
Construction of the lncRNA-mRNA regulatory network
To explore the functions of differentially expressed lncRNAs, 556 target mRNAs of 236 lncRNAs out of 1532 differentially expressed lncRNAs were screened out from LncTar after deleting the duplicate data (Supplementary file 4). The highly coordinated expression between lncRNAs and target mRNAs may be due to complementary base pairing between lncRNA and mRNA (Yang et al. 2014). In this lncRNA-mRNA regulatory network, we can see the interaction relationship between lncRNA and mRNA. For example, lncRNA NONMMUG029023.2 can regulate mRNA Stoml2 expression. Ptdss2 could be affected by lncRNA NONMMUG039651.2 and lncRNA NONMMUG095401.1 at the same time. The lncRNAs-mRNAs regulatory network was presented in Fig. 3.
To reveal the biological functions of differentially expressed lncRNAs in LPS-induced GMCs, we further performed GO biological process and KEGG pathway analysis on all mRNAs in the lncRNA–mRNA regulatory network. The results of GO and KEGG analysis were presented in Fig. 4.
Within the biological processes (BP) category of GO classification, cellular macromolecule metabolic process, negative regulation of biological process, and nitrogen compound metabolic process were the top 3 over-represented terms (Fig. 4A). Within the cellular components (CC) category of GO classification, intracellular, intracellular part, and membrane-bounded organelle were the top 3 over-represented terms (Fig. 4B). Within the molecular function (MF) category of GO classification, galactoside 2-alpha-L-fucosyltransferase activity, alpha-(1,2)-fucosyltransferase activity, and chromatin insulator sequence binding were the top 3 over-represented terms (Fig. 4C). The KEGG metabolic pathway analysis demonstrated that GnRH secretion, Melanoma, Ras signaling pathway, Glycosphingolipid biosynthesis-globo and isoglobo series, and beta-Alanine metabolism were the top 5 most significant enriched KEGG pathways (Fig. 4D).
RT-qPCR validation of 6 selected lncRNAs
To verify the accuracy of the sequencing results, we used RT-qPCR to detect the expression of 6 selected lncRNAs which are highly conservative with homo sapiens (Tab. 3) (Wang et al. 2019). All primers used for PCR amplification were presented in supplementary file 5. RT-qPCR was done as triplicates with the standard deviation for each PCR shown in Fig. 5. The results of RT-qPCR (Supplementary file 6) showed the same expression trend as the RNA-Seq results, and 6 selected lncRNAs were all upregulated in LPS-induced GMCs.
Construction of the lncRNA-associated ceRNA network
Except for lncRNA-mRNA regulatory network, lncRNAs can also participate in multiple gene networks that regulate diverse biological processes, like the ceRNA network (Li et al. 2021).
To construct a lncRNA-associated ceRNA network, We utilize 6 selected lncRNAs above that are conservative with homo sapiens and have been verified to build ceRNA networks. The ceRNA network consisted of the top 3 miRNAs combined with screened lncRNAs and mRNAs with high confidence (cumulative weighted context score cutoff level less than -0.8) bound to the miRNAs, including 6 lncRNAs, 18 miRNAs, and 419 mRNAs (Fig. 6, Supplementary file 7 & Supplementary file 8). It can be seen clearly in Fig. 6 that lncRNAs can be competing targets of shared miRNAs with other mRNAs and form a complex regulatory ceRNA network. For example, the lncRNA NONMMUG089165.1 could act as a sponge for mmu-miR-3960 to affect EVX1 expression. PARD3B could be affected by lncRNA NONMMUG039651.2/mmu-miR-7081-5P and lncRNA NONMMUG028702.2/mmu-miR-7044-5P axis at the same time.
To reveal the biological functions of lncRNAs in ceRNA network, we performed GO biological process and KEGG pathway analysis on all mRNAs involed in ceRNA network. The results of GO and KEGG analysis were presented in Fig. 7.
Within the biological processes (BP) category of GO classification, system development, animal organ development, and multicellular organism development were the top 3 over-represented terms (Fig. 7A). Within the cellular components (CC) category of GO classification, neuronal cell body membrane, cell body membrane, and alpha-beta T cell receptor complex were the top 3 over-represented terms (Fig. 7B). Within the molecular function (MF) category of GO classification, DNA-binding transcription activator activity, RNA polymerase II-specific, alpha-1,6-mannosylglycoprotein 6-beta-N-acetylglucosaminyltransferase activity, and DNA-binding transcription factor activity were the top 3 over-represented terms (Fig. 7C). The KEGG metabolic pathway analysis demonstrated that Collecting duct acid secretion, Circadian rhythm, Proteoglycans in cancer, Pathways in cancer, and Oxytocin signaling pathway were the top 5 most significant enriched KEGG pathways (Fig. 7D).