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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 |
|---|---|---|
| Pancreatic islets |
GSM4708547 GSM4708548 GSM4708549
|
|
|
GSM4708550 GSM4708551 GSM4708552
|
Submission Date: Aug 03, 2020
Summary: Purpose: The goal of this study is to investigate how METTL3 regulates islet β-cell function.
Methods: Total RNA was extracted using Tripure Isolation Reagent (Roche, Mannheim, Germany) from pancreatic islets of Mettl3flox/flox and β-Mettl3-KO mice at 8 weeks old. Each RNA sample was pooled from four Mettl3flox/flox and β-Mettl3-KO mice, respectively. Three independent biological replicates for each group were used for RNA-seq. RNA-seq was performed by deep sequencing using an Illumina Novaseq 6000 platform. Paired-end clean reads were aligned to the mouse reference genome(GRCm38.p6) with Hisat2 v2.0.5, and the aligned reads were used to quantify mRNA expression by using featureCounts v1.5.0-p3.
Conclusion: Our study represents the first detailed analysis of islet transcriptomes from Mettl3flox/flox and β-Mettl3-KO mice, generated by RNA-seq technology. The RNA-seq analysis showed that 2560 genes were downregulated and 3408 genes were upregulated in the pancreatic islets of β-Mettl3-KO mice. GO analysis showed that the downregulated genes were primarily related to insulin secretion, SNARE binding, and mitochondrial respiratory chain, whereas the upregulated genes were associated with the immune response, B cell activation, and antigen binding.
GEO Accession ID: GSE155612
PMID: 33417895
Submission Date: Aug 03, 2020
Summary: Purpose: The goal of this study is to investigate how METTL3 regulates islet β-cell function.
Methods: Total RNA was extracted using Tripure Isolation Reagent (Roche, Mannheim, Germany) from pancreatic islets of Mettl3flox/flox and β-Mettl3-KO mice at 8 weeks old. Each RNA sample was pooled from four Mettl3flox/flox and β-Mettl3-KO mice, respectively. Three independent biological replicates for each group were used for RNA-seq. RNA-seq was performed by deep sequencing using an Illumina Novaseq 6000 platform. Paired-end clean reads were aligned to the mouse reference genome(GRCm38.p6) with Hisat2 v2.0.5, and the aligned reads were used to quantify mRNA expression by using featureCounts v1.5.0-p3.
Conclusion: Our study represents the first detailed analysis of islet transcriptomes from Mettl3flox/flox and β-Mettl3-KO mice, generated by RNA-seq technology. The RNA-seq analysis showed that 2560 genes were downregulated and 3408 genes were upregulated in the pancreatic islets of β-Mettl3-KO mice. GO analysis showed that the downregulated genes were primarily related to insulin secretion, SNARE binding, and mitochondrial respiratory chain, whereas the upregulated genes were associated with the immune response, B cell activation, and antigen binding.
GEO Accession ID: GSE155612
PMID: 33417895
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.
