GEO series

Integrative analysis of pooled CRISPR screens provide functional insights into AD GWAS risk genes

GSE301119 Homo sapiens (human) RNA-seq (gene expression) 28 samples Submitted 2025/07/08 Platform GPL34281

At a glance

RNA-seq (gene expression) · human · 28 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: 28 samples: 28 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.

Summary (written by the submitters)

Emerging research has implicated Alzheimer’s disease (AD) pathology with dysregulation of many key pathways in microglia, including lipid transport and metabolism, phagocytosis of plaques, and lysosomal function. However, the exact mechanisms underlying these pathways remain poorly understood. Leveraging high-throughput CRISPR screens to understand the interplay between these pathways may enable novel therapeutic strategies for AD and other neurological diseases.

Read the full summary ↓

Here, we constructed activation and interference CRISPRa/i libraries targeting 203 genes, 71 of which were identified through neurodegenerative GWAS, and 132 additional genes linked to microglial functions. We used this library to conduct pooled CRISPRa/i screens across a range of functional assays relating to lipid metabolism and lysosomal function using a monocytic cell line, THP-1. We identified a core set of lipid and lysosome mediators and validated a subset in primary macrophages. To gain insights into transcriptional states modulated by these genes we also applied the CRISPRa/i libraries to Perturb-seq, enabling us to capture transcriptomic changes. Through non-negative matrix factorization, we identified five gene programs altered by our perturbation library. We then used an integrative analysis of functional screen data with Perturb-seq data that enabled us to uncover novel functions and genetic relationships between perturbations. This multidimensional resource links genetic perturbations to phenotypes and transcriptional programs, establishing a scalable framework for systematic gene discovery in neurodegeneration and beyond.

This dataset

Open GSE301119 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 GSE301119_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 PRJNA1284088 and SRA study SRP596258. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

28 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 28 sample titles: 28 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

GSM9075670 hMP, donor1, CRISPRi, rep1, gene expression
GSM9075671 hMP, donor1, CRISPRi, rep2, gene expression
GSM9075672 hMP, donor1, CRISPRi, rep3, gene expression
GSM9075673 hMP, donor1, CRISPRi, rep4, gene expression
GSM9075674 hMP, donor1, CRISPRa, rep1, gene expression
GSM9075675 hMP, donor1, CRISPRa, rep2, gene expression
GSM9075676 hMP, donor1, CRISPRa, rep3, gene expression
GSM9075677 hMP, donor1, CRISPRa, rep4, gene expression
GSM9075678 hMP, donor2, CRISPRi, rep1, gene expression
GSM9075679 hMP, donor2, CRISPRi, rep2, gene expression
GSM9075680 hMP, donor2, CRISPRi, rep3, gene expression
GSM9075681 hMP, donor2, CRISPRa, rep1, gene expression
GSM9075682 hMP, donor2, CRISPRa, rep2, gene expression
GSM9075683 hMP, donor2, CRISPRa, rep3, gene expression
GSM9075684 hMP, donor1, CRISPRi, rep1, CRISPR guide capture
GSM9075685 hMP, donor1, CRISPRi, rep2, CRISPR guide capture
GSM9075686 hMP, donor1, CRISPRi, rep3, CRISPR guide capture
GSM9075687 hMP, donor1, CRISPRi, rep4, CRISPR guide capture
GSM9075688 hMP, donor1, CRISPRa, rep1, CRISPR guide capture
GSM9075689 hMP, donor1, CRISPRa, rep2, CRISPR guide capture
GSM9075690 hMP, donor1, CRISPRa, rep3, CRISPR guide capture
GSM9075691 hMP, donor1, CRISPRa, rep4, CRISPR guide capture
GSM9075692 hMP, donor2, CRISPRi, rep1, CRISPR guide capture
GSM9075693 hMP, donor2, CRISPRi, rep2, CRISPR guide capture
GSM9075694 hMP, donor2, CRISPRi, rep3, CRISPR guide capture
GSM9075695 hMP, donor2, CRISPRa, rep1, CRISPR guide capture
GSM9075696 hMP, donor2, CRISPRa, rep2, CRISPR guide capture
GSM9075697 hMP, donor2, CRISPRa, rep3, CRISPR guide capture

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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.