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TurboCas: A method for locus-specific labeling of genomic regions and isolating their associated protein interactome [RNAseq]

GSE259306 Homo sapiens (human) RNA-seq (gene expression) 111 samples Submitted 2024/12/21 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 111 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
111 samples: 53 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
TurboCas: A method for locus-specific labeling of genomic regions and isolating their associated protein interactomeMolecular cell · 2024
Summary (written by the submitters)
Regulation of gene expression during development and stress response requires the concerted action of transcription factors and chromatin-binding proteins. Because this process is cell-type specific and varies with cellular conditions, mapping of chromatin factors at individual regulatory loci is crucial for understanding cis-regulatory control.
Read the full summary ↓
Previous methods only characterize static protein binding. We present “TurboCas,” a method combining a proximity-labeling (PL) enzyme, miniTurbo, with CRISPR-dCas9 that allows for efficient and site-specific labeling of chromatin factors in mammalian cells. Validating TurboCas at the FOS promoter, we identify proteins recruited upon heat shock, cross-validated via RNA polymerase II and P-TEFb immunoprecipitation. These methodologies reveal canonical and uncharacterized factors that function to activate expression of heat-shock-responsive genes. Applying TurboCas to the MYC promoter, we identify two P-TEFb coactivators, the super elongation complex (SEC) and BRD4, as MYC co-regulators. TurboCas provides a genome-specific targeting PL, with the potential to deepen our molecular understanding of transcriptional regulatory pathways in development and stress response.
Published in
TurboCas: A method for locus-specific labeling of genomic regions and isolating their associated protein interactome
Cenik BK, Aoi Y, Iwanaszko M et al. · Molecular cell 2024 · PMID 39706164 · doi:10.1016/j.molcel.2024.11.007
This dataset
Open GSE259306 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 GSE259306_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 PRJNA1080614 and SRA study SRP491877. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39706164) ↗
Study design
53 conditions, mostly in duplicate
RNAseq_Abcf2_HS_neg ×2 RNAseq_Abcf2_HS_pos ×2 RNAseq_Acaca_HS_neg ×2 RNAseq_Acaca_HS_pos ×2 RNAseq_Acacb_HS_neg ×2 RNAseq_Acacb_HS_pos ×2 RNAseq_Amot_HS_neg ×2 RNAseq_Amot_HS_pos ×2 +50 more

Supports a between-group comparison across 106 samples.

How we read this: 53 replicated groups read from 111 sample titles; they account for 106 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

+ 71 more — browse all 111 samples with per-sample file links →

Datasets on a similar topic

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