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Intestinal epithelial cell diversity and function in respect to age, anatomical localization, and microbial exposure - the crypt/villus transcriptome

GSE283142 Mus musculus (mouse) RNA-seq (gene expression) 24 samples Submitted 2024/12/23 Platform GPL19057
At a glance

RNA-seq (gene expression) · mouse · 24 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
24 samples: 8 conditions, mostly in triplicateGroups 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 small intestinal epithelium is composed of several defined epithelial cell lineages, which in turn exhibit marked transcriptional and functional diversity along the crypt-villus and proximal-to-distal length of the intestinal tract.
Read the full summary ↓
While epithelial cell type and functional heterogeneity have been characterized in the adult intestinal epithelium, the temporal and spatial changes during the postnatal period, which accompany the transition from placental energy supply to enteral feeding and facilitate the establishment of the enteric microbiota and postanatal immune maturation, have not been systematically investigated. Here, we analyzed microdissected crypt and villus structures of 1-, 5-, 10-, and 25-day-old SPF mice by 3'mRNA-Seq and used differential gene expression and pathway analysis to identify age-specific expression patterns. We identify gene clusters temporally expressed in the neonatal intestine and correlate their expression with the functional changes during postnatal tissue maturation and the neonate to adult transition.
This dataset
Open GSE283142 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 GSE283142_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 PRJNA1192234 and SRA study SRP548360. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
8 conditions, mostly in triplicate
B6J, SPF, d1, intestinal crypt, Biol ×3 B6J, SPF, d1, intestinal villus, Biol ×3 B6J, SPF, d5, intestinal crypt, Biol ×3 B6J, SPF, d5, intestinal villus, Biol ×3 B6J, SPF, d10, intestinal crypt, Biol ×3 B6J, SPF, d10, intestinal villus, Biol ×3 B6J, SPF, d25, intestinal crypt, Biol ×3 B6J, SPF, d25, intestinal villus, Biol ×3

Supports a between-group comparison across 24 samples.

How we read this: 8 replicated groups read from 24 sample titles; they account for 24 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
Datasets on a similar topic

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