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Bcl11a is essential for B-1a cell maintenance during aging (RNA-Seq)

GSE272987 Mus musculus (mouse) RNA-seq (gene expression) 16 samples Submitted 2025/06/19 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 16 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
16 samples: 7 conditions, mostly in duplicateGroups 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)
B-1a cells are important immune cells, serving as the first line of defense against pathogens. B-1a cell undergo a series of alterations during aging and decrease the protection to our body. However, the characteristics of B-1a cells during the aging process are not fully understood. In this study, we discrible transcriptional and epigenetic profiles of B-1a from 3-month-old and 24-month-old mice across both genders.
Read the full summary ↓
Interestingly，We found that the expression of the transcription factor Bcl11a was positively correlated with the number of B-1a cells in aged male and aged female mice.To further characterize senescent B-1a cells and the mechanisms of Bcl11a regulates B-1a. ATAC-seq and RNA-seq were performed on the B-1a isolated from young male mice (3-month-old),old male mice (24-month-old mice), young female mice (3-month-old),old female mice (24-month-old mice) of C57BL/6,and Bcl11a delated young male mice. CUT&tag was performed on the B-1a isolated from young male mice. Collectively, we provide a comprehensive resource to decode the aging process of B-1a, shedding light on how Bcl11a regulate B-1a cells maintenance.
This dataset
Open GSE272987 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 GSE272987_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 PRJNA1139754 and SRA study SRP522108. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
7 conditions, mostly in duplicate
WT, B1-a cell，3month, male, ×2 WT, B1-a cell，24month, male, ×2 WT, B1-a cell，3month, female, ×2 KO, B1-a cell，3month, male, ×2 KO, B1-a cell，24month, male, ×2 KO, B1-a cell, 24month, Female, ×2 KO, B1-a cell, 3month, Female, ×2 WT, B1-a cell, 24month, female, ×1 +1 more

Supports a between-group comparison across 14 samples.

How we read this: 7 replicated groups read from 16 sample titles; they account for 14 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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