METTL3 dictates the development of thymocytes via restraining ferroptosis program during age related thymic involution
RNA-seq (gene expression) · mouse · 16 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
- 16 samples: 16 samples, each with a distinct title — no replicated groupsGroups 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
- METTL3 governs thymocyte development and thymic involution by regulating ferroptosisNature aging · 2024
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 GSE243187_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 PRJNA1017361 and SRA study SRP460517. Searching any of these in the dataset finder brings you back here.
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from 16 sample titles: 16 distinct titles with little repetition. 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.
- GSM7780393 young-1-DP
- GSM7780394 young-2-DP
- GSM7780395 young-3-DP
- GSM7780396 old-1-DP
- GSM7780397 old-2-DP
- GSM7780398 old-3-DP
- GSM7780399 old-4-DP
- GSM7780400 young-METTL3 KO-1-DP
- GSM7780401 young-METTL3 KO-2-DP
- GSM7780402 young-METTL3 KO-3-DP
- GSM7780403 WT-1-DP
- GSM7780404 WT-2-DP
- GSM7780405 WT-3-DP
- GSM7780406 METTL3 KO-1-DP
- GSM7780407 METTL3 KO-2-DP
- GSM7780408 METTL3 KO-3-DP
- GSE284224 Epitranscriptomic program promotes skeletal stem cell quiescence and pluripotency by regulating proteostasis via METTL3-FEM1B-GLI1 axis 44 samples shares mettl3, program
- GSE285781 MSCs can alleviate ferroptosis and improve DKD through the Smad2/3/METTL3/S1PR1 axis. 15 samples shares mettl3, ferroptosis
- GSE292815 Diet-induced phospholipid remodeling dictates ferroptosis sensitivity and tumorigenesis in the pancreas 39 samples shares ferroptosis, dictates
- GSE319419 Particle Reprogramming of the TLR–Ferroptosis Axis and Immunometabolic Pathways Inhibits Myeloid Suppression to Improve Checkpoint Blockade in Prostate Cancer [RNA-Seq Hi-Myc mice] 12 samples shares ferroptosis, program
- GSE319397 Particle Reprogramming of the TLR–Ferroptosis Axis and Immunometabolic Pathways Inhibits Myeloid Suppression to Improve Checkpoint Blockade in Prostate Cancer 9 samples shares ferroptosis, program
- GSE313769 SATB1 Lowers The TCR Signaling Threshold For Thymocytes Positive Selection via Super-enhancer Reprogramming 122 samples shares thymocytes, program
- GSE313112 Inhibition of METTL3 by STC-15 induces RNA misprocessing that results in dsRNA formation and activates innate immunity [RNA-Seq MC38] 69 samples shares mettl3
- GSE287484 Catalytic activity of nuclear METTL3 promotes functional m6A modifications that drive retinal development [mRNA-seq] 32 samples shares mettl3
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.