Differential lncRNA/mRNA Expression Profiling and Functional Network Analyses in Bmp2 Deletion of Mouse Dental Papilla Cells

Bmp2 is essential for dentin development and formation. Bmp2 conditional knock-out (KO) mice display a similar tooth phenotype of dentinogenesis imperfecta (DGI). To elucidate a foundation for subsequent functional studies of cross talk between mRNAs and lncRNAs in Bmp2-mediated dentinogenesis, we investigated the profiling of lncRNAs and mRNAs using immortalized mouse dental Bmp2 flox/flox (iBmp2fx/fx) and Bmp2 knock-out (iBmp2ko/ko) papilla cells. RNA sequencing was implemented to study the expression of the lncRNAs and mRNAs. Quantitative real-time PCR (RT-qPCR) was used to validate expressions of lncRNAs and mRNAs. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases were used to predict functions of differentially expressed genes (DEGs). Protein–protein interaction (PPI) and lncRNA–mRNA co-expression network were analyzed by using bioinformatics methods. As a result, a total of 22 differentially expressed lncRNAs (16 downregulated vs 6 upregulated) and 227 differentially expressed mRNAs (133 downregulated vs. 94 upregulated) were identified in the iBmp2ko/ko cells compared with those of the iBmp2fx/fx cells. RT-qPCR results showed significantly differential expressions of several lncRNAs and mRNAs which were consistent with the RNA-seq data. GO and KEGG analyses showed differentially expressed genes were closely related to cell differentiation, transcriptional regulation, and developmentally relevant signaling pathways. Moreover, network-based bioinformatics analysis depicted the co-expression network between lncRNAs and mRNAs regulated by Bmp2 in mouse dental papilla cells and symmetrically analyzed the effect of Bmp2 during dentinogenesis via coding and non-coding RNA signaling.

Integration of Molecular Inflammatory Interactome Analyses Reveals Dynamics of Circulating Cytokines and Extracellular Vesicle Long Non-Coding RNAs and mRNAs in Heroin Addicts During Acute and Protracted Withdrawal

Heroin addiction and withdrawal influence multiple physiological functions, including immune responses, but the mechanism remains largely elusive. The objective of this study was to investigate the molecular inflammatory interactome, particularly the cytokines and transcriptome regulatory network in heroin addicts undergoing withdrawal, compared to healthy controls (HCs). Twenty-seven cytokines were simultaneously assessed in 41 heroin addicts, including 20 at the acute withdrawal (AW) stage and 21 at the protracted withdrawal (PW) stage, and 38 age- and gender-matched HCs. Disturbed T-helper(Th)1/Th2, Th1/Th17, and Th2/Th17 balances, characterized by reduced interleukin (IL)-2, elevated IL-4, IL-10, and IL-17A, but normal TNF-α, were present in the AW subjects. These imbalances were mostly restored to the baseline at the PW stage. However, the cytokines TNF-α, IL-2, IL-7, IL-10, and IL-17A remained dysregulated. This study also profiled exosomal long non-coding RNA (lncRNA) and mRNA in the plasma of heroin addicts, constructed co-expression gene regulation networks, and identified lncRNA-mRNA-pathway pairs specifically associated with alterations in cytokine profiles and Th1/Th2/Th17 imbalances. Altogether, a large amount of cytokine and exosomal lncRNA/mRNA expression profiling data relating to heroin withdrawal was obtained, providing a useful experimental and theoretical basis for further understanding of the pathogenic mechanisms of withdrawal symptoms in heroin addicts.

Integration of molecular inflammatory interactome analyses reveals dynamics of circulating cytokines and extracellular vesicle long non-coding RNAs and mRNAs in heroin addicts during acute and protracted withdrawal

Heroin addiction and withdrawal influence multiple physiological functions, including immune responses, but the mechanism remains largely elusive. The objective of this study was to investigate the molecular inflammatory interactome, particularly the cytokines and transcriptome regulatory network in heroin addicts undergoing withdrawal, compared to healthy controls (HCs). Twenty-seven cytokines were simultaneously assessed in 41 heroin addicts, including 20 at the acute withdrawal (AW) stage and 21 at the protracted withdrawal (PW) stage, and 38 age- and gender-matched HCs. Disturbed T-helper(Th)1/Th2, Th1/Th17, and Th2/Th17 balances, characterized by reduced interleukin (IL)-2, elevated IL-4, IL-10, and IL-17A, but normal TNF-α, were present in the AW subjects. These imbalances were mostly restored to the baseline at the PW stage. However, the cytokines TNF-α, IL-2, IL-7, IL-10, and IL-17A remained dysregulated. This study also profiled exosomal long non-coding RNA (lncRNA) and mRNA in the plasma of heroin addicts, constructed co-expression gene regulation networks, and identified lncRNA-mRNA-pathway pairs specifically associated with alterations in cytokine profiles and Th1/Th2/Th17 imbalances. Altogether, a large amount of cytokine and exosomal lncRNA/mRNA expression profiling data relating to heroin withdrawal was obtained, providing a useful experimental and theoretical basis for further understanding of the pathogenic mechanisms of withdrawal symptoms in heroin addicts.

Integrating Transcriptome-Wide Association Study and mRNA Expression Profiling Identifies Novel Genes Associated With Osteonecrosis of the Femoral Head

ObjectiveThis study aims to identify novel candidate genes associated with osteonecrosis of the femoral head (ONFH).MethodsA transcriptome-wide association study (TWAS) was performed by integrating the genome-wide association study dataset of osteonecrosis (ON) in the UK Biobank with pre-computed mRNA expression reference weights of muscle skeleton (MS) and blood. The ON-associated genes identified by TWAS were further subjected to gene ontology (GO) analysis by the DAVID tool. Finally, a trans-omics comparative analysis of TWAS and genome-wide mRNA expression profiling was conducted to identify the common genes and the GO terms shared by both DNA-level TWAS and mRNA-level expression profile for ONFH.ResultsTWAS totally identified 564 genes that were with PTWAS value <0.05 for MS and blood, such as CBX1 (PTWAS = 0.0001 for MS), SRPK2 (PTWAS = 0.0002 for blood), and MYO5A (PTWAS = 0.0005 for blood). After comparing the genes detected by TWAS with the differentially expressed genes identified by mRNA expression profiling, we detected 59 overlapped genes, such as STEAP4 [PTWAS = 0.0270, FC (fold change)mRNA = 7.03], RABEP1 (PTWAS = 0.010, FCmRNA = 2.22), and MORC3 (PTWAS = 0.0053, FCmRNA = 2.92). The GO analysis of TWAS-identified genes discovered 53 GO terms for ON. Further comparing the GO results of TWAS and mRNA expression profiling identified four overlapped GO terms, including cysteine-type endopeptidase activity (PTWAS = 0.0006, PmRNA = 0.0227), extracellular space (PTWAS = 0.0342, PmRNA = 0.0012), protein binding (PTWAS = 0.0112, PmRNA = 0.0106), and ATP binding (PTWAS = 0.0464, PmRNA = 0.0033).ConclusionSeveral ONFH-associated genes and GO terms were identified by integrating TWAS and mRNA expression profiling. It provides novel clues to reveal the pathogenesis of ONFH.

Integrating transcriptome-wide association study and mRNA expression profile identified candidate genes related to hand osteoarthritis

Background Osteoarthritis (OA) is a common skeletal system disease that has been partially attributed to genetic factors. The hand is frequently affected, which seriously affects the patient’s quality of life. However, the pathogenetic mechanism of hand osteoarthritis (hand OA) is still elusive. Methods A genome-wide association study (GWAS) summary of hand OA was obtained from the UK Biobank dataset, which contains data from a total of 452,264 White British individuals, including 37,782 OA patients. The transcriptome-wide association study (TWAS) of hand OA was performed using FUnctional Summary-based ImputatiON (FUSION) with the skeletal muscle and blood as gene expression references. The significant genes identified by TWAS were further subjected to gene set enrichment analysis (GSEA) with the Database for Annotation, Visualization and Integrated Discovery (DAVID) tool. Furthermore, we compared the genes and gene sets identified by our TWAS with that of a knee OA mRNA expression profile to detect the genes and gene sets shared by TWAS and mRNA expression profiles in OA. The mRNA expression profiles of 18 normal knee cartilages and 20 OA knee cartilages were acquired from the Gene Expression Omnibus database (accession number: GSE114007). Results TWAS identified 177 genes with P < 0.05 for the skeletal muscle, including ANKRD44 (P = 0.0001), RIC3 (P = 0.0003), and AC005154.6 (P = 0.0004). TWAS identified 423 genes with P < 0.05 for the blood, including CRIM1 (P = 0.0002), ZNF880 (P = 0.0002), and NCKIPSD (P = 0.0003). After comparing the results of the TWAS to those of the mRNA expression profiling of OA, we identified 5 common genes, including DHRS3 (log2fold = − 1.85, P = 3.31 × 10− 9) and SKP2 (log2fold = 1.36, P = 1.62 × 10− 8). GSEA of TWAS identified 51 gene ontology (GO) terms for hand OA, for example, protein binding (P = 0.0003) and cytosol (P = 0.0020). We also detected 6 common GO terms shared by TWAS and mRNA expression profiling, including protein binding (PTWAS = 2.54 × 10− 4, PmRNA = 3.42 × 10− 8), extracellular exosome (PTWAS = 0.02, PmRNA = 1.18 × 10− 4), and cytoplasm (PTWAS = 0.0183, PmRNA = 0.0048). Conclusion In this study, we identified 5 candidate genes and 6 GO terms related to hand OA, which may help to uncover the pathogenesis of hand OA. It should be noted that the possible difference in the gene expression profiles between hand OA and knee OA may affect our study results, which should be interpreted with caution.

Comprehensive analysis of lncRNA and mRNA based on expression microarray profiling reveals different characteristics of osteoarthritis between Tibetan and Han patients

Background Osteoarthritis (OA) is thought to be the most prevalent chronic joint disease, especially in Tibet of China. Here, we aimed to explore the integrative lncRNA and mRNA landscape between the OA patients of Tibet and Han. Methods The lncRNA and mRNA expression microarray profiling was performed by SurePrint G3 Human Gene Expression 8x60K v2 Microarray in articular cartilage samples from OA patients of Han nationality and Tibetans, followed by GO, KEGG, and trans-regulation and cis-regulation analysis of lncRNA and mRNA. Results We found a total of 117 lncRNAs and 297 mRNAs differently expressed in the cartilage tissues of Tibetans (n = 5) comparing with those of Chinese Han (n = 3), in which 49 lncRNAs and 158 mRNAs were upregulated, and 68 lncRNAs and 139 mRNAs were downregulated. GO and KEGG analysis showed that several unreported biological processes and signaling pathways were particularly identified. LncRNA-mRNA co-expression analysis revealed a remarkable lncRNA-mRNA relationship, in which OTOA may play a critical role in the different mechanisms of the OA progression between Tibetans and Chinese Han. Conclusion This study identified different lncRNA/mRNA expression profiling between OA patients of Tibetans and Han, which were involved in many characteristic biological processes and signaling pathways.