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Prenatal vitamin D deficiency alters immune cell proportions of offspring in young adult age [RNA-seq]

GSE242041 Mus musculus (mouse) RNA-seq (gene expression) 18 samples Submitted 2024/09/30 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 18 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
18 samples: 6 × PD1 liver VDD vs 6 × PD1 liver VDS vs 3 × MPP4 VDD vs 3 × MPP4 VDSGroups 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
Prenatal vitamin D deficiency exposure leads to long-term changes in immune cell proportionsScientific reports · 2024
Summary (written by the submitters)
Vitamin D deficiency is a common micronutrient deficiency worldwide, especially among reproductive-age women, and vitamin D deficiency during pregnancy increases the risks of offspring’s immune-related diseases later in life. The mechanisms of how our body remembers the exposure status of an adverse environment during development have not been fully elucidated yet.
Read the full summary ↓
Here we show that prenatal vitamin D deficiency exposure alters the immune cell proportion of the offspring at the prenatal and adult stage, which is attributed to transcriptional alterations of vitamin D receptor downstream genes. Further, we assessed the association between maternal vitamin D status and cord blood immune cell profiles from 75 healthy mother and their term baby pairs and found that maternal vitamin D deficiency significantly alters immune cell proportion in cord blood. Our findings demonstrate that prenatal vitamin D deficiency alters the immune cell compositions of offspring by changing the transcriptional properties of stem cells and altering long-term stem cell fate decisions.
Published in
Prenatal vitamin D deficiency exposure leads to long-term changes in immune cell proportions
Ueda K, Chin SS, Sato N et al. · Scientific reports 2024 · PMID 39191975 · doi:10.1038/s41598-024-70911-8
This dataset
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.

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 GSE242041_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1011260 and SRA study SRP457820. Searching any of these in the dataset finder brings you back here.

Study design
6 × PD1 liver VDD vs 6 × PD1 liver VDS vs 3 × MPP4 VDD vs 3 × MPP4 VDS

Supports a between-group comparison across 18 samples.

How we read this: 4 replicated groups read from 18 sample titles; they account for 18 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
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