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Assessing the Impact of Cell Isolation Method on B cell Gene Expression using Next-Generation Sequencing

GSE279633 Homo sapiens (human) RNA-seq (gene expression) 11 samples Submitted 2025/04/07 Platform GPL21697
At a glance

RNA-seq (gene expression) · human · 11 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
11 samples: 11 samples, each with a distinct title — no replicated groupsGroups 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
Assessing the impact of cell isolation method on B cell gene expression using next-generation sequencingExperimental hematology · 2025
Summary (written by the submitters)
Transcriptional profiling of PBMCs is a widely explored research approach across multiple fields. Cell populations of interest are generally isolated prior to analysis, especially if low frequency cell populations are desired. B cells, in particular, make up approximately 5-10% of total PBMCs in healthy individuals, thus, isolation of B cell populations is crucial for researchers investigating B cell malignancies.
Read the full summary ↓
The most widely used cell isolation methods include negative or positive magnetic cell sorting (MCS) and fluorescence-activated cell sorting (FACS). In contrast to negative MCS, it is widely believed that positive MCS and FACS may affect gene expression due to the direct interaction of cell selection antibodies with surface markers. To the best of our knowledge, no specific studies have examined these effects within CD19+ B cell populations. To evaluate this, we have performed RNA-seq on B cells isolated from n=4 healthy donors using three distinct methods: positive and negative MCS using the EasySep StemCell Technologies kits and FACS, performed using the MACSQuant Tyto sorter (Miltenyi Biotec). We report significant gene expression changes following CD19-dependent B cell isolation via either positive MCS or FACS relative to negative MCS, including a general upregulation of genes associated with immune activity and receptor signaling and downregulation of RNA processing genes. These results suggest B cell isolation methods should be taken into consideration when designing experiments or incorporating publicly available sequencing datasets into ongoing research studies, as they may significantly impact the reliability and interpretability of the findings.
Published in
Assessing the impact of cell isolation method on B cell gene expression using next-generation sequencing
Henning AN, Pardoe J, Owusu-Ansah D et al. · Experimental hematology 2025 · PMID 40164324 · doi:10.1016/j.exphem.2025.104766
This dataset
Open GSE279633 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 GSE279633_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 PRJNA1173741 and SRA study SRP538958. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40164324) ↗
Study design
11 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 11 sample titles: 11 distinct titles with little repetition. 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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