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Parenchymal damage and myeloid inflammation link the Rag GTPase – mTORC1 axis to mammalian aging [old]

GSE221283 Mus musculus (mouse) RNA-seq (gene expression) 10 samples Submitted 2024/04/02 Platform GPL21626
At a glance

RNA-seq (gene expression) · mouse · 10 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
10 samples
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.
Summary (written by the submitters)
The mechanistic target of rapamycin complex 1 (mTORC1) controls cellular anabolism in response to nutrient sufficiency and growth factor signaling, and genetic and pharmacological inhibition of mTORC1 extends longevity across eukaryotes. Up to date, mouse models to analyze the mechanisms of aging governed by mTORC1 has been limited by detrimental pleiotropic consequences of genetically-increased mTORC1 activity in mice.
Read the full summary ↓
RragcS74N/+, RragcS74C/+ and RragcT89N/+ knock-in mice endogenously express active mutant variants of RagC, a GTPase that signaling nutrient sufficiency to mTORC1. Rragcmutant/+ mice show an only moderate increase in nutrient signaling to mTORC1, and after one year of life exhibit multiple features of a premature aging phenotype that include prominent senescence in peripheral organs, parenchymal expression of inflammatory and chemo-attractant molecules, increased myeloid inflammation and extensive features of inflammaging. In vivo transplantation and ex vivo functional experiments with bone marrow-derived cells show that myeloid cells are abnormally activated by parenchymal signals evoked from Rragcmut/+ organs, to where myeloid cells extravasate to inflict additional inflammatory damage. Therapeutic suppression of myeloid inflammation in old Rragcmut/+ attenuates features of premature aging and extends longevity. We provide the first genetic link of elevated nutrient – mTORC1 activity and premature aging in mammals, and provide support for a two-component model in which increased nutrient signaling drives parenchymal damage and myeloid inflammation precipitates organ deterioration and accelerated aging.
This dataset
Open GSE221283 in finder → Find more mouse RNA-seq datasets →
Download · which file do I need?

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.

1 · Just have a look

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.

Series matrix ↓
2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE221283_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
3 · Start from the raw reads

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.

Raw reads on ENA ↗

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 PRJNA913833 and SRA study SRP413819. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
A cohort of 10 individual samples

The grouping that defines any comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Sample titles run YRN00149 … YRN00233 and carry no group information.

Samples in this study
Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

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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.