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Mapping convergent regulators of melanoma drug resistance by PerturbFate

GSE291147 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 320 samples Submitted 2026/02/06 Platform GPL34281
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 320 samples

What it is
ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism
Homo sapiens (human)
Topic
MelanomaThis series is part of our curated briefing on it.
Samples
320 samples: 128 × PerturbFate pooled screen Tri-omics New RNA vs 128 × PerturbFate pooled screen Tri-omics Old RNA and ATAC vs 64 × PerturbFate pooled screen Dual-omicsGroups 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
Mapping convergent regulators of melanoma drug resistance by PerturbFateNature · 2026
Summary (written by the submitters)
High-throughput genomic studies have uncovered associations between diverse genetic alterations and disease phenotypes; however, elucidating how perturbations in functionally disparate genes give rise to convergent cellular states remains challenging.
Read the full summary ↓
Here, we present PerturbFate, a high-throughput, cost-effective, combinatorial-indexing single-cell platform that enables systematic interrogation of massively parallel CRISPR interference (CRISPRi) perturbations across the full spectrum of gene regulation, from chromatin remodeling and nascent transcription to steady-state transcriptomic phenotypes. Using PerturbFate, we profiled over 300,000 cultured melanoma cells to characterize multi-modal phenotypic and gene regulatory responses to perturbations in more than 140 Vemurafenib resistance-associated genes. We uncovered a shared dedifferentiated cell state marked by convergent cooperative transcription factor (TF) activities across diverse genetic perturbations. We further dissected phenotypic responses to perturbations in Mediator Complex components, linking module-specific biochemical properties to convergent transcriptional activations. Together, we reveal common regulatory nodes that drive similar phenotypic outcomes across distinct genetic perturbations. We also delineate how perturbations in functionally unrelated genes reshape cell state. PerturbFate thus establishes a versatile platform for identifying key molecular regulators by anchoring multi-modal regulatory dynamics to disease-relevant phenotypes.
Published in
Mapping convergent regulators of melanoma drug resistance by PerturbFate
Xu Z, Lu Z, Ugurbil A et al. · Nature 2026 · PMID 41986722 · doi:10.1038/s41586-026-10367-0
This dataset
Open GSE291147 in finder → Find more human RNA-seq datasets → Melanoma landscape →
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 GSE291147_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1231621 and SRA study SRP567948. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41986722) ↗
Study design
128 × PerturbFate pooled screen Tri-omics New RNA vs 128 × PerturbFate pooled screen Tri-omics Old RNA and ATAC vs 64 × PerturbFate pooled screen Dual-omics

Supports a between-group comparison across 320 samples.

How we read this: 3 replicated groups read from 320 sample titles; they account for 320 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

+ 280 more — browse all 320 samples with per-sample file links →

More Melanoma datasets

Search all human RNA-seq datasets in GEO →

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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.