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m6Am sequesters PCF11 to promote full-length transcription [PCT]

GSE234131 Homo sapiens (human) RNA-seq (gene expression) 18 samples Submitted 2024/10/31 Platform GPL15520Platform GPL20795
At a glance

RNA-seq (gene expression) · human · 18 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
18 samples: 6 conditions, mostly in triplicateGroups 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
m(6)Am sequesters PCF11 to suppress premature termination and drive neuroblastoma differentiationMolecular cell · 2024
Summary (written by the submitters)
RNA modifications regulate how RNAs metabolize and function to impact development and diseases. N6,2’-O-dimethyladenosine (m6Am) is one such modification and despite being abundant, m6Am function remains unclear. Here, we identified cleavage and polyadenylation factor, PCF11 as a m6Am-specific binding protein. Direct quantification of mature versus nascent RNAs revealed that m6Am does not regulate mRNA stability but promotes transcription of nascent RNAs.
Read the full summary ↓
m6Am caused RNA Polymerase II (Pol II) to be more processive when transcribing m6Am-modified RNAs. Rather than PCF11 regulating m6Am-modified RNA, m6Am sequesters PCF11 away from proximal Pol II, suppressing premature dissociation of elongating Pol II and promoting Pol II full-length transcription of m6Am-modified RNAs. This establishes a mechanism through which an RNA modification regulates transcription.
Published in
m(6)Am sequesters PCF11 to suppress premature termination and drive neuroblastoma differentiation
An H, Hong Y, Goh YT et al. · Molecular cell 2024 · PMID 39481383 · doi:10.1016/j.molcel.2024.10.004
This dataset
Open GSE234131 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 GSE234131_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 PRJNA980176 and SRA study SRP441148. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39481383) ↗
Study design
6 conditions, mostly in triplicate
WT HEK293T siScram PCT ×3 WT HEK293T siPCF11 PCT ×3 Pcif1-KO HEK293T siScram PCT ×3 Pcif1-KO HEK293T siPCF11 PCT ×3 WT HEK293T no siDis3 control ×3 Pcif1-KO HEK293T no siDis3 control ×3

Supports a between-group comparison across 18 samples.

How we read this: 6 replicated groups read from 18 sample titles; they account for 18 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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