GEO series

Multiplex base editing of BCL11A regulatory elements to treat sickle cell disease

GSE291384 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2025/07/28 Platform GPL34281

At a glance

RNA-seq (gene expression) · human · 12 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: 12 samples: 12 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: Multiplex base editing of BCL11A regulatory elements to treat sickle cell diseaseCell reports. Medicine · 2025

Summary (written by the submitters)

Sickle cell disease (SCD) is a genetic anemia caused by the production of an abnormal adult hemoglobin. The clinical severity is lessened by elevated fetal hemoglobin (HbF) production in adulthood. A promising therapy is the transplantation of autologous, hematopoietic stem/progenitor cells (HSPCs) treated with CRISPR/Cas9 to downregulate the HbF repressor BCL11A via generation of double strand breaks (DSBs) in the +58-kb erythroid-specific enhancer.

Read the full summary ↓

Here, to further enhance HbF production without increasing the mutagenic load, we targeted both +58-kb and +55-kb BCL11A erythroid-specific enhancers using base editors. We systematically dissected DNA motifs recognized by the key transcriptional activators within these regions and identified the critical nucleotides required for activator binding. Multiplex base editing of these residues was efficient and safe and generated no or little DSBs and genomic rearrangements. We observed substantial HbF reactivation, exceeding the levels achieved using the CRISPR/Cas9 nuclease-based strategy, thus efficiently rescuing the sickling phenotype. Multiplex base editing was efficient in long-term repopulating HSPCs and resulted in potent HbF reactivation in vivo. In summary, these results show that multiplex base editing of BCL11A erythroid-specific enhancers is a safe and potent strategy for treating sickle cell disease.

Published in

Multiplex base editing of BCL11A regulatory elements to treat sickle cell disease

Fontana L, Martinucci P, Amistadi S et al. · Cell reports. Medicine 2025 · PMID 41015034 · doi:10.1016/j.xcrm.2025.102376

This dataset

Open GSE291384 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 GSE291384_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 PRJNA1233274 and SRA study SRP568722. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41015034) ↗

Study design

12 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 12 sample titles: 12 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

GSM8834114 donor1_TE
GSM8834115 donor1_CBE
GSM8834116 donor1_DBE
GSM8834117 donor1_Cas9
GSM8834118 donor2_TE
GSM8834119 donor2_CBE
GSM8834120 donor2_DBE
GSM8834121 donor2_Cas9
GSM8834122 donor3_TE
GSM8834123 donor3_CBE
GSM8834124 donor3_DBE
GSM8834125 donor3_Cas9

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Search all human RNA-seq datasets in GEO →

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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.