Cardiac adaptation to endurance exercise training requires suppression of GDF15 via PGC-1α
RNA-seq (gene expression) · mouse · 20 samples
- What it is
- RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
- Organism
- Mus musculus (mouse)
- Samples
- 20 samples: 5 × WT_Sed vs 5 × KO_Sed vs 5 × WT_Ex vs 5 × KO_ExGroups are read from the sample names, not from the paper. Check the list below.
- Data you can get
- A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Read the full summary ↓
Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.
Processed table
The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE302867_RAW.tar (it can run to tens of gigabytes).
Raw sequencing reads
The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.
What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.
Also filed as BioProject PRJNA1292724 and SRA study SRP601476. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 20 samples.
How we read this: 4 replicated groups read from 20 sample titles; they account for 20 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.
- GSM9112660 WT_Sed_1 WT_Sed
- GSM9112661 WT_Sed_2 WT_Sed
- GSM9112662 WT_Sed_3 WT_Sed
- GSM9112663 WT_Sed_4 WT_Sed
- GSM9112664 WT_Sed_5 WT_Sed
- GSM9112665 KO_Sed_1 KO_Sed
- GSM9112666 KO_Sed_2 KO_Sed
- GSM9112667 KO_Sed_3 KO_Sed
- GSM9112668 KO_Sed_4 KO_Sed
- GSM9112669 KO_Sed_5 KO_Sed
- GSM9112670 WT_Ex_1 WT_Ex
- GSM9112671 WT_Ex_2 WT_Ex
- GSM9112672 WT_Ex_3 WT_Ex
- GSM9112673 WT_Ex_4 WT_Ex
- GSM9112674 WT_Ex_5 WT_Ex
- GSM9112675 KO_Ex_1 KO_Ex
- GSM9112676 KO_Ex_2 KO_Ex
- GSM9112677 KO_Ex_3 KO_Ex
- GSM9112678 KO_Ex_4 KO_Ex
- GSM9112679 KO_Ex_5 KO_Ex
- GSE319401 Exercise Mitigates Cardiac Dysfunction Post-MI in Ovariectomized Mice via miR-21/Sox7-Mediated Suppression of Cardiac Fibroblast Activation 24 samples shares suppression, exercise
- GSE305395 PGC-1alpha pathway dysregulation disrupts myofiber specification in a mouse model of SBMA [AR113Q RNA-Seq] 27 samples shares pgc-1
- GSE329198 PGC-1alpha pathway dysregulation disrupts myofiber specification in a mouse model of SBMA 14 samples shares pgc-1
- GSE267183 GDF15 links beta-adrenergic induced lipolysis with anxiety 12 samples shares gdf15
- GSE305396 PGC-1alpha pathway dysregulation disrupts myofiber specification in a mouse model of SBMA [snRNA-Seq] 6 samples shares pgc-1
- GSE241770 ACSS2 mediates an epigenetic pathway to regulate maternal Beta-cell adaptation and progression of gestational diabetes (scRNA-Seq) 7899 samples shares adaptation
- GSE249591 Gene suppression by PRC2 enhances the gene inductions by Aire and the development of mimetic cell populations 572 samples shares suppression
- GSE5003 Oxidative metabolism and PGC-1 attenuate macrophage-mediated inflammation 9 samples shares pgc-1
Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.