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FOCAS: Transcriptome-wide screening of individual m6A sites functionally dissects epitranscriptomic control of gene expression in cancer [FOCAS_4cellline_RNAseq]

GSE301521 Homo sapiens (human) RNA-seq (gene expression) 72 samples Submitted 2025/10/21 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 72 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
72 samples: 36 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.
Paper
FOCAS: Transcriptome-wide screening of individual m(6)A sites functionally dissects epitranscriptomic control of gene expression in cancerCell · 2026
Summary (written by the submitters)
Although N6-methyladenosine (m6A) is a pervasive RNA modification essential for gene regulation, dissecting the functions of individual m6A sites remains technically challenging. To overcome this, we developed functional m6A sites detection by CRISPR-dCas13b-FTO screening (FOCAS), a CRISPR-dCas13b-based platform enabling high-throughput, site-specific functional screening of m6A.
Read the full summary ↓
Applying FOCAS to four human cancer cell lines identified 4,475 m6A-regulated genes influencing cell fitness via both mRNAs and non-coding RNAs (ncRNAs), many of which are newly linked to cancer and exhibit dynamic developmental expression. FOCAS uncovered context-dependent and reader-specific effects of m6A within the same gene, revealing its intricate regulatory logic. We further uncovered universal and cell-type-specific m6A patterns with unique sites enriched in ncRNAs and universal ones in transcription-related genes. In SMMC-7721 cells we identified m6A-regulated transcriptional networks that demonstrated extensive epitranscriptome-transcriptome crosstalk. Overall, this study established a powerful, unbiased approach for the functional dissection of m6A, advancing the understanding of its complexity and therapeutic relevance in cancers.
Published in
FOCAS: Transcriptome-wide screening of individual m(6)A sites functionally dissects epitranscriptomic control of gene expression in cancer
Zhang X, Zhang Y, Liu X et al. · Cell 2026 · PMID 41478283 · doi:10.1016/j.cell.2025.11.037
This dataset
Open GSE301521 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 GSE301521_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 PRJNA1285381 and SRA study SRP597908. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41478283) ↗
Study design
36 conditions, mostly in duplicate
SMMC-7721, sgCTRL ×2 SMMC-7721, sgC15orf39 ×2 SMMC-7721, sgEP300 ×2 SMMC-7721, sgFOSL2 ×2 SMMC-7721, sgKCTD1 ×2 SMMC-7721, sgPCNX3 ×2 SMMC-7721, sgSTARD9 ×2 SMMC-7721, sgZFP41 ×2 +28 more

Supports a between-group comparison across 72 samples.

How we read this: 36 replicated groups read from 72 sample titles; they account for 72 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

+ 32 more — browse all 72 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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