← BioTransfer GEO Dataset Finder
GEO series

MALAT1 is required for phenotypic consequences of TET2 mutations in myeloid neoplasms.

GSE243492 Mus musculus (mouse) Single-cell RNA-seq 12 samples Submitted 2024/08/13 Platform GPL24247
At a glance

Single-cell RNA-seq · mouse · 12 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Mus musculus (mouse)
Samples
12 samples: 6 × WT Bone marrow mononuclear, untreated, vs 3 × Tet2 knockout bone marrow mononuclear, untreated vs 3 × Tet2 knockout, Malat1 knockout bone marrow mononuclearGroups 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)
Loss of function mutations inTET2(LOF) occur in up to 58% and 30% of myeloid malignancies and clonal hematopoiesis (CH) respectively. Genetically engineered murine models of Tet2 LOF display splenomegaly, granulomonocytic expansion, and increased bone marrow hematopoietic stem and progenitors. However, the direct downstream effectors of TET2 LOF leading to this phenotype are unknown.
Read the full summary ↓
Using multiome single cell sequencing from a cohort of severe COVID patients with or without TET2 mutations we show that MALAT1, a therapeutically tractable long non-coding RNA, is overexpressed and is both necessary and sufficient to induce TET2 LOF phenotypes. We additionally demonstrate that TET2 LOF leads to decrease activity of the transcriptional repressor EGR1 leading to upregulation of MALAT1. This upregulation then leads to sustained NFkB activity by inhibiting the phosphatase activity of PP2A on P65 resulting in increased pro-inflammatory cytokines such as IL-6 required for TET2 LOF phenotypes in MALAT1 overexpressing mice
This dataset
Open GSE243492 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 GSE243492_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1017795 and SRA study SRP461361. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
6 × WT Bone marrow mononuclear, untreated, vs 3 × Tet2 knockout bone marrow mononuclear, untreated vs 3 × Tet2 knockout, Malat1 knockout bone marrow mononuclear

Supports a between-group comparison across 12 samples.

How we read this: 3 replicated groups read from 12 sample titles; they account for 12 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

Search all mouse RNA-seq datasets in GEO →

Share this dataset

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.