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Whole transcriptome analysis of leaves and petioles in Chinese cabbage [circRNA]

ABSTRACT: We use Chinese cabbage PHL as the material and sample during maturing repeating three times. 44796 differentially expressed mRNAs were identified by complete transcriptome sequencing of leaf and petiole, of which 10646 were significant differentially expressed. There were 10422 significant differentially expressed mRNAs annotated into molecular function, biological process and cell components. There were 723 GO terms, and the most enriched GO term was membrane component (GO: 0016021) . KEGG analysis showed that there were 31 significant pathways. Among them, the plant hormone signal transduction pathway (Ko04075) is the pathway with the most differentially enriched genes.A total of 2553 differentially expressed lncRNAs were obtained, of which 303 were significant differentially expressed lncRNAs. Target genes of significantly differentially expressed lncRNAs were predicted, and the predicted target genes were analyzed by GO and KEGG. There were 2425 GO terms and 127 pathways. The most enriched GO term was nucleus (GO: 0005634) , the most abundant pathway is starch and sucrose (Ko00500) .A total of 1070 differentially expressed miRNAs were obtained, of which 195 were significant differentially expressed. Go and KEGG analyses of the predicted target genes were performed. There were 551 GO terms and 24 pathways. The most abundant GO terms were membrane components (GO: 0016021) , the most abundant pathway is starch and sucrose (Ko00500) .A total of 886 differentially expressed circRNAs were obtained, including 7 significant differentially expressed circRNAs, which have 3 up-regulated circRNAs and 4 down-regulated circRNAs.

ORGANISM(S): Brassica rapa

PROVIDER: GSE182325 | GEO | 2022/08/26

REPOSITORIES: GEO

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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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Whole transcriptome analysis of leaves and petioles in Chinese cabbage [circRNA]

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