GEO series

Transcriptomic analysis of human naive B cells stimulated by CD40L, CpG, anti-IgM IgG, IL-4 or combinations

GSE232769 Homo sapiens (human) RNA-seq (gene expression) 36 samples Submitted 2024/06/26 Platform GPL18573

At a glance

RNA-seq (gene expression) · human · 36 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: Homo sapiens (human)
Samples: 36 samples: 12 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.
Paper: Multi-omic Analysis of Human B-cell Activation Reveals a Key Lysosomal BCAT1 Role in mTOR Hyperactivation by B-cell receptor and TLR9Research square · 2024

Summary (written by the submitters)

B-lymphocytes play major adaptive immune roles, producing antibody and driving cell mediated responses. However, how B-cells acutely differentiate in response to receptor signaling codes, including T-cell dependent versus independent cues, remains incompletely understood. To gain insights, we used multi-omic profiling to characterize ex vivo primary human B-cell transcriptomic, proteomic and metabolomic remodeling by B-cell receptor (BCR), Toll-like receptor 9 (TLR9), CD40-ligand (CD40L), interleukin-4 (IL4) or combinations thereof, highlighting key stimulus-specific phenotypes.

Published in

Multi-omic Analysis of Human B-cell Activation Reveals a Key Lysosomal BCAT1 Role in mTOR Hyperactivation by B-cell receptor and TLR9

Gewurz B, Guo R, Lim M et al. · Research square 2024 · PMID 38854072 · doi:10.21203/rs.3.rs-4413958/v1

This dataset

Open GSE232769 in finder → Find more human 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 GSE232769_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 PRJNA973872 and SRA study SRP438347. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38854072) ↗

Study design

12 conditions, mostly in triplicate

B cells, unstimulated ×3 B cells, IgM ×3 B cells, CpG ×3 B cells, CD40L ×3 B cells, IL4 ×3 B cells, CD40L_IgM ×3 B cells, CD40L_IL4 ×3 B cells, IgM_CpG ×3 +4 more

Supports a between-group comparison across 36 samples.

How we read this: 12 replicated groups read from 36 sample titles; they account for 36 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

GSM7382524 B cells, unstimulated_1 B cells, unstimulated
GSM7382525 B cells, unstimulated_2 B cells, unstimulated
GSM7382526 B cells, unstimulated_3 B cells, unstimulated
GSM7382527 B cells, IgM_1 B cells, IgM
GSM7382528 B cells, IgM_2 B cells, IgM
GSM7382529 B cells, IgM_3 B cells, IgM
GSM7382530 B cells, CpG_1 B cells, CpG
GSM7382531 B cells, CpG_2 B cells, CpG
GSM7382532 B cells, CpG_3 B cells, CpG
GSM7382533 B cells, CD40L_1 B cells, CD40L
GSM7382534 B cells, CD40L_2 B cells, CD40L
GSM7382535 B cells, CD40L_3 B cells, CD40L
GSM7382536 B cells, IL4_1 B cells, IL4
GSM7382537 B cells, IL4_2 B cells, IL4
GSM7382538 B cells, IL4_3 B cells, IL4
GSM7382539 B cells, CD40L_IgM_1 B cells, CD40L_IgM
GSM7382540 B cells, CD40L_IgM_2 B cells, CD40L_IgM
GSM7382541 B cells, CD40L_IgM_3 B cells, CD40L_IgM
GSM7382542 B cells, CD40L_IL4_1 B cells, CD40L_IL4
GSM7382543 B cells, CD40L_IL4_2 B cells, CD40L_IL4
GSM7382544 B cells, CD40L_IL4_3 B cells, CD40L_IL4
GSM7382545 B cells, IgM_CpG_1 B cells, IgM_CpG
GSM7382546 B cells, IgM_CpG_2 B cells, IgM_CpG
GSM7382547 B cells, IgM_CpG_3 B cells, IgM_CpG
GSM7382548 B cells, CD40L_CpG_1 B cells, CD40L_CpG
GSM7382549 B cells, CD40L_CpG_2 B cells, CD40L_CpG
GSM7382550 B cells, CD40L_CpG_3 B cells, CD40L_CpG
GSM7382551 B cells, CD40L_IgM_IL4_1 B cells, CD40L_IgM_IL4
GSM7382552 B cells, CD40L_IgM_IL4_2 B cells, CD40L_IgM_IL4
GSM7382553 B cells, CD40L_IgM_IL4_3 B cells, CD40L_IgM_IL4
GSM7382554 B cells, BCAT1-KO, 1 B cells, BCAT1-KO,
GSM7382555 B cells, BCAT1-KO, 2 B cells, BCAT1-KO,
GSM7382556 B cells, BCAT1-KO, 3 B cells, BCAT1-KO,
GSM7382557 B cells, Control-KO, 1 B cells, Control-KO,
GSM7382558 B cells, Control-KO, 2 B cells, Control-KO,
GSM7382559 B cells, Control-KO, 3 B cells, Control-KO,

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