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Gene counts are sourced from ARCHS4, which provides uniform alignment of GEO samples.
You can learn more about ARCHS4 and its pipeline here.
Select conditions below to toggle them from the plot:
| GROUP | CONDITION | SAMPLES |
|---|---|---|
| adipose stem cells |
GSM5316439 GSM5316441 GSM5316443 GSM5316451 GSM5316452 GSM5316454
|
|
|
GSM5316444 GSM5316445 GSM5316446 GSM5316448 GSM5316449 GSM5316450 GSM5316456 GSM5316457 GSM5316458 GSM5316460 GSM5316461 GSM5316462
|
Submission Date: May 16, 2021
Summary: 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.
GEO Accession ID: GSE174502
PMID: No Pubmed ID
Submission Date: May 16, 2021
Summary: 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.
GEO Accession ID: GSE174502
PMID: No Pubmed ID
Visualize Samples
Visualizations are precomputed using the Python package scanpy on the top 5000 most variable genes.
Precomputed Differential Gene Expression
Differential expression signatures are automatically computed using the limma R package.
More options for differential expression are available to compute below.
Signatures:
Select conditions:
Control Condition
Perturbation Condition
Only conditions with at least 1 replicate are available to select
Differential expression signatures can be computed using DESeq2 or characteristic direction.
This pipeline enables you to analyze and visualize your bulk RNA sequencing datasets with an array of downstream analysis and visualization tools. The pipeline includes: PCA analysis, Clustergrammer interactive heatmap, library size analysis, differential gene expression analysis, enrichment analysis, and L1000 small molecule search.
