Age-dependent Transcriptional and Circuit Alterations in the brain Underlie Post-Anesthesia Neurobehavioral Dysfunction
RNA-seq (gene expression) · mouse · 66 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
- 66 samples: 12 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
- Age-dependent Transcriptional and Circuit Alterations in the brain Underlie Post-Anesthesia Neurobehavioral DysfunctionAging and disease · 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 GSE297195_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 PRJNA1262968 and SRA study SRP585271. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 66 samples.
How we read this: 12 replicated groups read from 66 sample titles; they account for 66 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.
- GSM8985361 Young_Sham_Hi_4 Young_Sham_Hi
- GSM8985362 Young_Sham_Hi_8 Young_Sham_Hi
- GSM8985363 Young_Sham_Hi_10 Young_Sham_Hi
- GSM8985364 Young_Sham_Hi_11 Young_Sham_Hi
- GSM8985365 Young_Sham_Hi_13 Young_Sham_Hi
- GSM8985366 Young_2h_Iso_Op_Hi_1 Young_2h_Iso_Op_Hi
- GSM8985367 Young_2h_Iso_Op_Hi_2 Young_2h_Iso_Op_Hi
- GSM8985368 Young_2h_Iso_Op_Hi_3 Young_2h_Iso_Op_Hi
- GSM8985369 Young_2h_Iso_Op_Hi_5 Young_2h_Iso_Op_Hi
- GSM8985370 Young_2h_Iso_Op_Hi_12 Young_2h_Iso_Op_Hi
- GSM8985371 Young_Sham_OB_4 Young_Sham_OB
- GSM8985372 Young_Sham_OB_8 Young_Sham_OB
- GSM8985373 Young_Sham_OB_10 Young_Sham_OB
- GSM8985374 Young_Sham_OB_11 Young_Sham_OB
- GSM8985375 Young_Sham_OB_13 Young_Sham_OB
- GSM8985376 Young_2h_Iso_Op_OB_1 Young_2h_Iso_Op_OB
- GSM8985377 Young_2h_Iso_Op_OB_2 Young_2h_Iso_Op_OB
- GSM8985378 Young_2h_Iso_Op_OB_3 Young_2h_Iso_Op_OB
- GSM8985379 Young_2h_Iso_Op_OB_5 Young_2h_Iso_Op_OB
- GSM8985380 Young_2h_Iso_Op_OB_12 Young_2h_Iso_Op_OB
- GSM8985381 Aged_Sham_Hi_1 Aged_Sham_Hi
- GSM8985382 Aged_Sham_Hi_2 Aged_Sham_Hi
- GSM8985383 Aged_Sham_Hi_3 Aged_Sham_Hi
- GSM8985384 Aged_Sham_Hi_4 Aged_Sham_Hi
- GSM8985385 Aged_Sham_Hi_5 Aged_Sham_Hi
- GSM8985386 Aged_Sham_Hi_6 Aged_Sham_Hi
- GSM8985387 Aged_2h_Iso_Op_Hi_1 Aged_2h_Iso_Op_Hi
- GSM8985388 Aged_2h_Iso_Op_Hi_2 Aged_2h_Iso_Op_Hi
- GSM8985389 Aged_2h_Iso_Op_Hi_3 Aged_2h_Iso_Op_Hi
- GSM8985390 Aged_2h_Iso_Op_Hi_4 Aged_2h_Iso_Op_Hi
- GSM8985391 Aged_2h_Iso_Op_Hi_5 Aged_2h_Iso_Op_Hi
- GSM8985392 Aged_2h_Iso_Op_Hi_6 Aged_2h_Iso_Op_Hi
- GSM8985393 Aged_2h_Iso_Op_Hi_7 Aged_2h_Iso_Op_Hi
- GSM8985394 Aged_Sham_OB_1 Aged_Sham_OB
- GSM8985395 Aged_Sham_OB_2 Aged_Sham_OB
- GSM8985396 Aged_Sham_OB_3 Aged_Sham_OB
- GSM8985397 Aged_Sham_OB_4 Aged_Sham_OB
- GSM8985398 Aged_Sham_OB_5 Aged_Sham_OB
- GSM8985399 Aged_Sham_OB_6 Aged_Sham_OB
- GSM8985400 Aged_2h_Iso_Op_OB_1 Aged_2h_Iso_Op_OB
+ 26 more — browse all 66 samples with per-sample file links →
- GSE275176 Transcriptomic alterations associated with the progression of metabolic dysfunction-associated steatotic liver disease in CC042 Collaborative Cross mice. 60 samples shares alterations, dysfunction
- GSE196482 Integrated analysis of early transcriptomic and proteomic alterations in mouse models of ALS/FTD identify early metabolic adaptions with similarities to mitochondrial dysfunction disorders 40 samples shares alterations, dysfunction
- GSE254915 TGF-β signaling mediates microglial resilience to age-dependent dorsal column myelin alterations 36 samples shares age-dependent, alterations
- GSE307255 HDL-mimetic peptide treatment reverses APOE4-induced transcriptomic and lipidomic alterations in the brain of humanized APOE mice 32 samples shares alterations, brain
- GSE308948 Intranasal delivery of SARS-CoV-2 triggers cellular and molecular alterations in the mouse trigeminal ganglion and brainstem: focus on the nociceptive pathways related to migraine 18 samples shares alterations, brain
- GSE271781 Molecular and spatial transcriptomic classification of midbrain dopamine neurons and their alterations in a LRRK2G2019S model of Parkinson’s disease 4 samples shares alterations, brain
- GSE291845 Transcriptional alterations in the brain following Dot1l conditional knockout using the Emx1-Cre mouse line at embryonic day 16.5 [EmxDotRNAE16] 2 samples shares alterations, brain
- GSE210620 Reduced Notch signaling in BBB vascular endothelial cells mediates high fat diet-induced alterations in brain glucose uptake and insulin signaling 25 samples shares alterations, brain
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.