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METTL7B is an essential epigenetic regulator of lineage specification in glioblastoma [RNAseq]

GSE242328 Homo sapiens (human) Single-cell RNA-seq 16 samples Submitted 2024/07/01 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 16 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
Homo sapiens (human)
Samples
16 samples: 4 × G19.Sc vs 4 × G19.shMETTL7B vs 4 × N19.PK vs 4 × N19.M7BoeGroups 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
Lineage specification in glioblastoma is regulated by METTL7BCell reports · 2024
Summary (written by the submitters)
Glioblastomas are the most common malignant brain tumours in adults; they are highly aggressive, heterogeneous and plastic. We have identified METTL7B as an essential regulator of lineage specification in glioblastoma, with impact on both tumour size and invasiveness in in vivo models. Single cell transcriptomic analysis of these tumours and of cerebral organoids derived from expanded potential stem cells overexpressing METTL7B identified a regulatory role for the gene in the neural stem cells to astrocyte differentiation trajectory.
Read the full summary ↓
Mechanistically, METTL7B downregulates the expression of key neuronal differentiation players, including SALL2, via DNA methylation and post-translational modifications of histone marks.
Published in
Lineage specification in glioblastoma is regulated by METTL7B
Constantinou M, Nicholson J, Zhang X et al. · Cell reports 2024 · PMID 38848215 · doi:10.1016/j.celrep.2024.114309
This dataset
Open GSE242328 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 GSE242328_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 PRJNA1013105 and SRA study SRP458588. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38848215) ↗
Study design
4 × G19.Sc vs 4 × G19.shMETTL7B vs 4 × N19.PK vs 4 × N19.M7Boe

Supports a between-group comparison across 16 samples.

How we read this: 4 replicated groups read from 16 sample titles; they account for 16 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
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