Mitochondria complex III-generated superoxide is essential for IL-10 secretion in macrophages
RNA-seq (gene expression) · mouse · 40 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
- 40 samples: 9 conditions, mostly with about 5 replicates eachGroups 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.
- Paper
- Mitochondria complex III-generated superoxide is essential for IL-10 secretion in macrophagesScience advances · 2025
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 GSE282257_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 PRJNA1187793 and SRA study SRP546064. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 40 samples.
How we read this: 9 replicated groups read from 40 sample titles; they account for 40 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.
- GSM8640024 BMDM, WT_IL-4_1 BMDM, WT_IL-4
- GSM8640025 BMDM, KO_IL-4_1 BMDM, KO_IL-4
- GSM8640026 BMDM, WT_Unst_1 BMDM, WT_Unst
- GSM8640027 BMDM, KO_Unst_1 BMDM, KO_Unst
- GSM8640028 BMDM, KO+AOX_Unst_1 BMDM, KO+AOX_Unst
- GSM8640029 BMDM, WT_LPS_1 BMDM, WT_LPS
- GSM8640030 BMDM, KO_LPS_1 BMDM, KO_LPS
- GSM8640031 BMDM, KO+AOX_LPS_1 BMDM, KO+AOX_LPS
- GSM8640032 BMDM, WT_IL-4_2 BMDM, WT_IL-4
- GSM8640033 BMDM, KO_IL-4_2 BMDM, KO_IL-4
- GSM8640034 BMDM, WT_Unst_2 BMDM, WT_Unst
- GSM8640035 BMDM, KO_Unst_2 BMDM, KO_Unst
- GSM8640036 BMDM, KO+AOX_Unst_2 BMDM, KO+AOX_Unst
- GSM8640037 BMDM, WT_LPS_2 BMDM, WT_LPS
- GSM8640038 BMDM, KO_LPS_2 BMDM, KO_LPS
- GSM8640039 BMDM, KO+AOX_LPS_2 BMDM, KO+AOX_LPS
- GSM8640040 BMDM, WT_IL-4_3 BMDM, WT_IL-4
- GSM8640041 BMDM, KO_IL-4_3 BMDM, KO_IL-4
- GSM8640042 BMDM, KO+AOX_IL-4_1 BMDM, KO+AOX_IL-4
- GSM8640043 BMDM, WT_Unst_3 BMDM, WT_Unst
- GSM8640044 BMDM, KO_Unst_3 BMDM, KO_Unst
- GSM8640045 BMDM, WT_LPS_3 BMDM, WT_LPS
- GSM8640046 BMDM, KO_LPS_3 BMDM, KO_LPS
- GSM8640047 BMDM, KO+AOX_LPS_3 BMDM, KO+AOX_LPS
- GSM8640048 BMDM, WT_IL-4_4 BMDM, WT_IL-4
- GSM8640049 BMDM, KO_IL-4_4 BMDM, KO_IL-4
- GSM8640050 BMDM, KO+AOX_IL-4_2 BMDM, KO+AOX_IL-4
- GSM8640051 BMDM, WT_Unst_4 BMDM, WT_Unst
- GSM8640052 BMDM, KO_Unst_4 BMDM, KO_Unst
- GSM8640053 BMDM, KO+AOX_Unst_3 BMDM, KO+AOX_Unst
- GSM8640054 BMDM, WT_LPS_4 BMDM, WT_LPS
- GSM8640055 BMDM, KO_LPS_4 BMDM, KO_LPS
- GSM8640056 BMDM, KO+AOX_LPS_4 BMDM, KO+AOX_LPS
- GSM8640057 BMDM, WT_IL-4_5 BMDM, WT_IL-4
- GSM8640058 BMDM, KO_IL-4_5 BMDM, KO_IL-4
- GSM8640059 BMDM, KO+AOX_IL-4_3 BMDM, KO+AOX_IL-4
- GSM8640060 BMDM, WT_Unst_5 BMDM, WT_Unst
- GSM8640061 BMDM, KO_Unst_5 BMDM, KO_Unst
- GSM8640062 BMDM, WT_LPS_5 BMDM, WT_LPS
- GSM8640063 BMDM, KO_LPS_5 BMDM, KO_LPS
- GSE237783 Complex interaction of tumor-derived factors instructs the niche specific phenotypes of tumor-associated macrophages [RNA-Seq] 28 samples shares macrophages, complex
- GSE210798 Splenic CD169+Tim4+ Marginal Zone Metallophilic Macrophages Are Essential for Wound Healing and Resolution of Inflammation After Myocardial Infarction 24 samples shares macrophages, essential
- GSE279117 HIF1α deletion promotes mitochondrial repurposing in bone marrow-derived macrophages, but not in tissue-resident alveolar macrophages 24 samples shares mitochondria, macrophages
- GSE274650 G3BP1 translocates into mitochondria to impair MCU complex function and promotes NASH progression [G3bp1-HKO and G3bp1-Flox mice with BSA or PA treatment] 12 samples shares mitochondria, complex
- GSE325061 Ubiquitylation by the GID/CTLH complex regulates the metabolic and innate immune response of macrophages to infection by Mycobacterium tuberculosis 12 samples shares macrophages, complex
- GSE318448 Pharmacological elevation of lactate alleviates sepsis via histone lactylation-induced IL-10 production 10 samples shares il-10
- GSE342584 Tumor-targeted IL-10 combined with IL-2 amplifies anti-tumor immunity 3 samples shares il-10
- GSE319684 Timecourse of FACS sorted Ly6C+ monocytes, tissue resident alveolar macrophages (trAMs), monocyte derived alveolar macrophages (bmAMs) and epithelial cells from SARS-CoV-2 (maVie16) vs. IAV (PR8) infected mouse lungs 176 samples shares macrophages
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.