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Identifying human pre-mRNA cleavage and polyadenylation factors by genome-wide CRISPR screens in a dual fluorescence readthrough reporter (2)

GSE243456 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 12 samples Submitted 2024/04/11 Platform GPL16791
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 12 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)
Samples
12 samples: 6 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
Identifying human pre-mRNA cleavage and polyadenylation factors by genome-wide CRISPR screens using a dual fluorescence readthrough reporterNucleic acids research · 2024
Summary (written by the submitters)
The majority of messenger RNA precursor (pre-mRNA) undergoes 3' end cleavage and polyadenylation (CPA), termed as to 3’ end processing. This processing is specified by a polyadenylation site (PAS) and adjacent RNA sequences and regulated by a large variety of core and auxiliary CPA factors. To date, most of the CPA factors have been discovered through biochemical and proteomic studies.
Read the full summary ↓
However, genome-wide genetic identification of CPA factors has been hampered by the lack of a reliable high-throughput method. Here, we developed a dual fluorescence readthrough reporter system with a PAS inserted between two fluorescent reporters, GFP and mCherry. This system enables the measurement of 3’ end processing in living cells via flow cytometry analysis. Using this system in combination with a human CRISPR library, we conducted a genome-wide screen for CPA factors. The screens identified most of the well-known CPA factors, including most components of the core CPA machineries (i.e. CPSF, CSTF, CFI, and CFII complexes), the CPA scaffold protein SYMPK, PPP1R10 in PNUTS-PP1 complex, as well as CBLL1 (a subunit of m6A RNA methyltransferase complex). Importantly, the screens also uncovered CCNK/CDK12 as a functional core CPA machinery. Furthermore, the screens identified RPRD1B, an RNA polymerase II (RNAP II) binding protein, as a CPA factor. Further characterization showed that RPRD1B binds RNA and regulates the release of RNAP II at the 3’ end of genes. Thus, this dual fluorescence reporter coupled with CRISPR screen provides a reliable tool for identifying bona fide CAP factors, offering a platform for investigating 3’ end processing in various contexts.
Published in
Identifying human pre-mRNA cleavage and polyadenylation factors by genome-wide CRISPR screens using a dual fluorescence readthrough reporter
Ni Z, Ahmed N, Nabeel-Shah S et al. · Nucleic acids research 2024 · PMID 38587191 · doi:10.1093/nar/gkae240
This dataset
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.

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 GSE243456_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1018532 and SRA study SRP461482. Searching any of these in the dataset finder brings you back here.

Study design
6 conditions, mostly in duplicate
ChIP-seq of Scramble knockout, ×2 ChIP-seq of RPRD1B knockout, ×2 Scramble input ChIP, ×2 ChIP-seq of GFP, ×2 ChIP-seq of GFP-RPRD1B, ×2 GFP input ChIP, ×2

Supports a case/control comparison: 2 samples read as cases, 2 as controls.

How we read this: 6 replicated groups read from 12 sample titles; they account for 12 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
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