GEO series

Inactivation of Atp7b copper transporter in the intestinal epithelial cells is associated with altered lipid processing and cell growth machinery that are independent from hepatic copper accumulation and liver histology severity

GSE279388 Mus musculus (mouse) RNA-seq (gene expression) 76 samples Submitted 2025/06/01 Platform GPL24247

At a glance

RNA-seq (gene expression) · mouse · 76 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: 76 samples: 7 conditions, mostly with about 6 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.

Summary (written by the submitters)

The clinical manifestations of Wilson disease (WD) are related to copper accumulation in the liver and brain, but little is known about the role of other organs expressing the ATP7B copper transporter on the metabolic changes characterizing WD. To examine the metabolic and morphological consequences of intestine Atp7b inactivation in absence of hepatic copper accumulation, we generated a new mouse strain, the Atp7bΔIEC mouse and characterized its phenotype over a time-course study.

Read the full summary ↓

Atp7bΔIEC mice were generated using B6.Cg-Tg(Vil1-cre)997Gum/J mice from the Jackson Laboratory and Atp7bLox/Lox mice. Cre-mediated removal of a 1.6-kb fragment in exon 2 results in enterocyte-specific Atp7b inactivation. Atp7bΔIEC mice were compared to wildtype mice with same genetic background (iWT). The Atp7b null global knockout (Atp7b -/-) on a C57Bl/6 background was previously generated and compared to respective WT. Mice were studied at 9, 16, 24, and 30 weeks of age. Liver and intestine histology, lipid metabolism parameters, and hepatic copper quantification were assessed. Transcriptome analysis in Atp7bΔIEC mice revealed changes in genes involved in AMPK signaling, fatty acid metabolism and cell cycle both in the intestinal epithelial cells and in the liver. No changes in hepatic and enterocyte copper levels were seen in Atp7bΔIEC livers, whereas, as expected, hepatic copper was 20-40 times higher in Atp7b -/- mice compared to WT mice. Intestine-specific Atp7b deficit affects systemic metabolic pathways independently from hepatic copper accumulation indicating evidence that WD phenotype is affected by organ-specific ATP7B variants.

This dataset

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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 GSE279388_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 PRJNA1172600 and SRA study SRP538397. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

7 conditions, mostly with about 6 replicates each

I ×24 KO ×24 iKO30 ×6 iWT30 ×6 KO30 ×6 H30 ×5 LH30 ×5

Supports a between-group comparison across 76 samples.

How we read this: 7 replicated groups read from 76 sample titles; they account for 76 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.

Samples in this study

GSM8568529 H30_1 H30
GSM8568530 H30_2 H30
GSM8568531 H30_3 H30
GSM8568532 H30_4 H30
GSM8568533 H30_5 H30
GSM8568534 I11 I
GSM8568535 I14 I
GSM8568536 I17 I
GSM8568537 I19 I
GSM8568538 I200 I
GSM8568539 I207 I
GSM8568540 I208 I
GSM8568541 I210 I
GSM8568542 I211 I
GSM8568543 I212 I
GSM8568544 I213 I
GSM8568545 I215 I
GSM8568546 I218 I
GSM8568547 I223 I
GSM8568548 I228 I
GSM8568549 I230 I
GSM8568550 I24 I
GSM8568551 I3 I
GSM8568552 I30 I
GSM8568553 I31 I
GSM8568554 I37 I
GSM8568555 I38 I
GSM8568556 I4 I
GSM8568557 I45 I
GSM8568558 iKO30_1 iKO30
GSM8568559 iKO30_10 iKO30
GSM8568560 iKO30_11 iKO30
GSM8568561 iKO30_4 iKO30
GSM8568562 iKO30_5 iKO30
GSM8568563 iKO30_7 iKO30
GSM8568564 iWT30_1 iWT30
GSM8568565 iWT30_10 iWT30
GSM8568566 iWT30_11 iWT30
GSM8568567 iWT30_4 iWT30
GSM8568568 iWT30_5 iWT30

+ 36 more — browse all 76 samples with per-sample file links →

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GSE319319 Xist RNA Dependent and Independent Mechanisms Regulate Dynamic X Chromosome Inactivation in B Lymphocytes 202 samples shares inactivation, independent
GSE282254 Xist RNA Dependent and Independent Mechanisms Regulate Dynamic X Chromosome Inactivation in B Lymphocytes [CUTandRUN_Xist] 77 samples shares inactivation, independent
GSE282253 Xist RNA Dependent and Independent Mechanisms Regulate Dynamic X Chromosome Inactivation in B Lymphocytes [CUTandRUN_F1] 64 samples shares inactivation, independent

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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.