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CRISPRi-based screens in iAssembloids to elucidate neuron-glia interactions

GSE272093 Homo sapiens (human) Single-cell RNA-seq 10 samples Submitted 2024/07/12 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 10 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
10 samples: 3 × 2D monoculture neuron CROP-seq vs 3 × 2D monoculture neuron CROP-seq sgRNA enrichment PCR vs 2 × iAssembloids neuron CROP-seq vs 2 × iAssembloids neuron CROP-seq sgRNA enrichment PCRGroups 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)
The sheer complexity of the brain has complicated our ability to understand its cellular mechanisms in health and disease. Genome-wide association studies have uncovered genetic variants associated with specific neurological phenotypes and diseases. In addition, single-cell transcriptomics have provided molecular descriptions of specific brain cell types and the changes they undergo during disease.
Read the full summary ↓
Although these approaches provide a giant leap forward towards understanding how genetic variation can lead to functional changes in the brain, they do not establish molecular mechanisms. To address this need, we developed a 3D co-culture system termed iAssembloids (induced multi-lineage assembloids) that enables the rapid generation of homogenous neuron-glia spheroids. We characterize these iAssembloids with immunohistochemistry and single-cell transcriptomics and combine them with large-scale CRISPRi-based screens. In our first application, we ask how glial and neuronal cells interact to control neuronal death and survival. Our CRISPRi-based screens identified that GSK3β inhibits the protective NRF2-mediated oxidative stress response in the presence of reactive oxygen species elicited by high neuronal activity, which was not previously found in 2D monoculture neuron screens. We also apply the platform to investigate the role of APOE- 4, a risk variant for Alzheimer’s Disease, in its effect on neuronal survival. We find that APOE- 4 expressing astrocytes may promote more neuronal activity as compared to APOE- 3 expressing astrocytes. This platform expands the toolbox for the unbiased identification of mechanisms of cell-cell interactions in brain health and disease.
This dataset
Open GSE272093 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 GSE272093_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 PRJNA1135105 and SRA study SRP519580. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
3 × 2D monoculture neuron CROP-seq vs 3 × 2D monoculture neuron CROP-seq sgRNA enrichment PCR vs 2 × iAssembloids neuron CROP-seq vs 2 × iAssembloids neuron CROP-seq sgRNA enrichment PCR

Supports a between-group comparison across 10 samples.

How we read this: 4 replicated groups read from 10 sample titles; they account for 10 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

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