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Next generation sequencing of long non-coding RNAs in diabetes mellitus rats after sleeve gastrectomy

ABSTRACT: Sleeve gastrectomy (SG) could improve diabetes mellitus dramatically. However, the mechanisms remain largely undetermined. With the advancement of in-depth bioinformatic analysis, non-coding RNAs especially long non-coding RNAs(lncRNAs), have been implicated in many biological processes. To explore whether lncRNAs mediate the amelioration of diabetes mellitus condition after SG, we subjected liver samples of diabetic rats after SG and shame operations for RNA sequencing. Further, interaction network between lncRNAs and mRNAs/microRNAs(miRNAs) were constructed to infer the function of lncRNAs in diabetic remission, followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. Through RNA sequencing, we identified more than 9000 lncRNAs with a dramatically differentially expressed profile of 147 lncRNAs. Some of these specific lncRNAs were only expressed in diabetic rats after SG, which may be promising biological markers of diabetic remission and SG prognosis. Through co-analysis between lncRNAs and mRNAs, 20 potential target genes of lncRNAs were screened out. Further bioinformatic analysis indicated the differentially expressed lncRNAs harbored various miRNAs binding sites and three representative lncRNA-miRNA networks of lnc50 and lnc136 were constructed. The KEGG analysis revealed that differential expressed lncRNAs were mainly related to mitogen-activated protein kinase (MAPK) pathway. These results demonstrated that SG dramatically altered expression profile of lncRNAs on diabetes mellitus, and altered lncRNAs expression may contribute to the improvement on diabetic remission through MAPK pathway by interaction with mRNA/miRNA. Our findings provide valuable resources for molecular mechanism of diabetic remission after SG and is benefit for development of lncRNAs-based diagnostic and therapeutic interventions of diabetes mellitus.

ORGANISM(S): Rattus norvegicus

PROVIDER: GSE162018 | GEO | 2023/11/23

REPOSITORIES: GEO

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Project description:Background Rotator cuff tears (RCT) is a common musculoskeletal disorder in the shoulder which cause pain and functional disability. Diabetes mellitus (DM) is characterized by impaired ability of producing or responding to insulin and has been reported to act as a risk factor of the progression of rotator cuff tendinopathy and tear. Long non-coding RNAs (lncRNAs) are involved in the development of various diseases, but little is known about their potential roles involved in RCT of diabetic patients. Methods RNA-Sequencing (RNA-Seq) was used in this study to profile differentially expressed lncRNAs and mRNAs in RCT samples between 3 diabetic and 3 nondiabetic patients. Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis were performed to annotate the function of the differentially expressed genes (DEGs). LncRNA-mRNA co-expression network and competing endogenous RNA (ceRNA) network were constructed to elucidate the potential molecular mechanisms of DM affecting RCT. Results In total, 505 lncRNAs and 388 mRNAs were detected to be differentially expressed in RCT samples between diabetic and nondiabetic patients. GO functional analysis indicated that related lncRNAs and mRNAs were involved in metabolic process, immune system process and others. KEGG pathway analysis indicated that related mRNAs were involved in ferroptosis, PI3K-Akt signaling pathway, Wnt signaling pathway, JAK-STAT signaling pathway and IL-17 signaling pathway and others. LncRNA-mRNA co-expression network was constructed, and ceRNA network showed the interaction of differentially expressed RNAs, comprising 5 lncRNAs, 2 mRNAs, and 142 miRNAs. TF regulation analysis revealed that STAT affected the progression of RCT by regulating the apoptosis pathway in diabetic patients. Conclusions We preliminarily dissected the differential expression profile of lncRNAs and mRNAs in torn rotator cuff tendon between diabetic and nondiabetic patients. And the bioinformatic analysis suggested some important RNAs and signaling pathways regarding inflammation and apoptosis were involved in diabetic RCT. Our findings offer a new perspective on the association between DM and progression of RCT.

Project description:Purpose: Whole-transcriptome sequencing technology and bioinformatics analysis were applied to systematically analyze the differentially expressed mRNAs, lncRNAs, circRNAs and miRNAs in adipose stem cells (ASCs) from diabetic, old and young patients. Methods: MRNAs, lncRNAs and cirRNAs profiles of adipose stem cells were generated by RNA sequencing, in triplicate, using Illumina HiSeq X Ten . MiRNAs profiles of adipose stem cells were generated by RNA sequencing, in triplicate, using BGISEQ-500. The sequence reads that passed quality filters were analyzed at the transcript isoform level by using sequence analysis programs, including HISAT, Stringtie, CIRI, find_circ and DESeq. qRT–PCR validation was performed using Takara, Vazyme and Clontech kits. Results: The data showed that 1377 mRNAs, 5353 circRNAs, 932 lncRNAs and 85 miRNAs were significantly differently expressed in adipose stem cells from old patients compared with young patients, with a fold change ≥2 or ≤ -2 and q value <0.001. The data showed that 1878 mRNAs, 22988 circRNAs, 2638 lncRNAs and 122 miRNAs were significantly differently expressed (DE) in adipose stem cells from old patients compared with diabetic patients, with a fold change ≥2 or ≤ -2 and q value <0.001. The results of qRT-PCR confirmed 25 mRNAs, 9 lncRNAs, 8 circRNAs and 13 miRNAs which were consistent with the RNA-seq data. GO and KEGG analyses demonstrated DE mRNAs were significantly enriched in aging and cell senescence terms separately. Conclusion: Our group simultaneously examined the changing expression of miRNAs, mRNAs, lncRNAs and circRNAs in ASCs associated with diabetes and aging. GO and KEGG pathway analyses were conducted to annotate the possible function of the differentially expressed mRNAs. PPI networks were established in order to find critical protein genes highly involved in our disease models. The ceRNA networks including lncRNA-miRNA-mRNA and cirRNA-miRNA-mRNA interactions were successfully constructed based on the bioinformatic analyses and PCR results. Thus, this study may contribute to our understanding of the underlying mechanisms of ASCs instability and provide novel targets to reverse the dysfunction of ASCs isolated from diabetic and old patients.

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Next generation sequencing of long non-coding RNAs in diabetes mellitus rats after sleeve gastrectomy

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