GEO series

Single-cell landscape and regulation of alternative polyadenylation in the brain

GSE291390 Homo sapiens (human) Single-cell RNA-seq 15 samples Submitted 2025/03/12 Platform GPL24676

At a glance

Single-cell RNA-seq · human · 15 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism: Homo sapiens (human)
Samples: 15 samples: 7 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.

Summary (written by the submitters)

As so far, the trans-regulation of alternative polydenylation (APA) are poorly understood. In this study, we de novo predicted multiple APA regulators based on large-scale single-cell data and detected some potential regulators, including PABPN1, SF3B4, U2AF2, HDAC1 and PCBP2. To further validate the function of these potential regulators, we generated two biological replicates of knock-down lines for each gene in HEK293T, and then carried out RNA-seq experiments after extracting nuclei to measure the transcriptome-wide APA usage difference.

This dataset

Open GSE291390 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 GSE291390_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 PRJNA1233287 and SRA study SRP568707. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

7 conditions, mostly in duplicate

HEK293T, shControl, ×3 HEK293T, shHDAC1, ×2 HEK293T, shPABPN1, ×2 HEK293T, shPCBP2, ×2 HEK293T, shSF3B4, ×2 HEK293T, shU2AF2, ×2 HEK293T, shZNF384, ×2

Supports a between-group comparison across 15 samples.

How we read this: 7 replicated groups read from 15 sample titles; they account for 15 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

GSM8834329 HEK293T, shHDAC1, rep1 HEK293T, shHDAC1,
GSM8834330 HEK293T, shHDAC1, rep2 HEK293T, shHDAC1,
GSM8834331 HEK293T, shPABPN1, rep1 HEK293T, shPABPN1,
GSM8834332 HEK293T, shPABPN1, rep2 HEK293T, shPABPN1,
GSM8834333 HEK293T, shPCBP2, rep1 HEK293T, shPCBP2,
GSM8834334 HEK293T, shPCBP2, rep2 HEK293T, shPCBP2,
GSM8834335 HEK293T, shSF3B4, rep1 HEK293T, shSF3B4,
GSM8834336 HEK293T, shSF3B4, rep2 HEK293T, shSF3B4,
GSM8834337 HEK293T, shU2AF2, rep1 HEK293T, shU2AF2,
GSM8834338 HEK293T, shU2AF2, rep2 HEK293T, shU2AF2,
GSM8834339 HEK293T, shZNF384,rep1 HEK293T, shZNF384,
GSM8834340 HEK293T, shZNF384,rep2 HEK293T, shZNF384,
GSM8834341 HEK293T, shControl, rep1 HEK293T, shControl,
GSM8834342 HEK293T, shControl, rep2 HEK293T, shControl,
GSM8834343 HEK293T, shControl, rep3 HEK293T, shControl,

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