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Multipotent progenitors with distinct origins, clonal lineage fates, transcriptomes, and surface markers yield two hematopoietic trees

GSE272588 Mus musculus (mouse) RNA-seq (gene expression) 605 samples Submitted 2025/11/05 Platform GPL34720Platform GPL30172
At a glance

RNA-seq (gene expression) · mouse · 605 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
605 samples: 135 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.
Paper
Multipotent progenitors with distinct origins, clonal lineage fates, transcriptomes, and surface markers yield two hematopoietic treesProceedings of the National Academy of Sciences of the United States of America · 2025
Summary (written by the submitters)
Multipotent progenitors (MPP) are the quantitative source of native hematopoiesis that have been thought to be replenished slowly by hematopoietic stem cells (HSC). However, recent fate mapping studies have revealed two developmentally distinct populations of MPP, HSC-derived MPP (hMPP), and HSC-independent, embryonic MPP (eMPP). These data raise fundamental questions on the distinctions and functions of these progenitors.
Read the full summary ↓
Here, we mapped the clonal dynamics of the two independent MPP systems, using in situ barcoding, and barcode linkage (hMPP), or disconnect (eMPP), with HSC. The cumulative output of eMPP to hematopoiesis was 35%, and their output was enriched for lymphoid fates. Conversely, hMPP output was enriched for myeloid-restricted fates. Distinguishing HSC from eMPP outputs revealed that only ~15% of adult HSC clones underwent multilineage differentiation (lymphoid, myeloid, and erythroid). To prospectively identify eMPP, we developed PolySMART for joint profiling of PolyloxExpress RNA barcodes, surface markers, and transcriptomes, and we found that the plasma cell marker CD138 enriches for eMPP. CD138+ MPP are primed for self-renewal and toward lymphoid fate, and become largely but not completely replaced by CD138− MPP over time, which may contribute to the loss of lymphoid output with age. Taken together, adult hematopoiesis consists of two distinct lineage trees. The source of the “eMPP tree” substantially contributes to hematopoiesis before it declines, while the HSC-hMPP tree supplies hematopoiesis life-long. Our molecular determinants distinguishing the two MPP systems may open avenues to further explore these unexpected layers of hematopoiesis.
Published in
Multipotent progenitors with distinct origins, clonal lineage fates, transcriptomes, and surface markers yield two hematopoietic trees
Shang F, Nizharadze T, Thiele R et al. · Proceedings of the National Academy of Sciences of the United States of America 2025 · PMID 41284889 · doi:10.1073/pnas.2505510122
This dataset
Open GSE272588 in finder → Find more mouse 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 GSE272588_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 PRJNA1137388 and SRA study SRP520846. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41284889) ↗
Study design
135 conditions, mostly in duplicate
TA5.B ×7 TA6.T ×7 TA6.B ×7 TA5.T ×6 TA5.G ×5 TE5.MyP ×4 TE5.LSK_PC ×4 TE5.LK_PC ×4 +194 more

Supports a between-group comparison across 333 samples.

How we read this: 135 replicated groups read from the first 400 of 605 sample titles; they account for 333 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

+ 565 more — browse all 605 samples with per-sample file links →

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