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Genome-wide analysis reveals characteristics of off-target sites bound by the Cas9 endonuclease

GSE55887 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 12 samples Submitted 2014/05/18 Platform GPL15520
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
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.
Summary (written by the submitters)
RNA-guided genome editing with the CRISPR-Cas9 system has great potential for basic and clinical research, but the determinants of targeting specificity and the extent of off-target cleavage remain insufficiently understood. Using chromatin immunoprecipitation and high-throughput sequencing (ChIP-seq), we mapped genome-wide binding sites of catalytically inactive Cas9 (dCas9) in HEK293T cells, in combination with 12 different single guide RNAs (sgRNAs).
Read the full summary ↓
The number of off-target sites bound by dCas9 varied from ~10 to >1,000 depending on the sgRNA. Analysis of off-target binding sites showed the importance of the PAM-proximal region of the sgRNA guiding sequence and that dCas9 binding sites are enriched in open chromatin regions. When targeted with catalytically active Cas9, some off-target binding sites had indels above background levels in a region around the ChIP-seq peak, but generally at lower rates than the on-target sites. Our results elucidate major determinants of Cas9 targeting, and we show that ChIP-seq allows unbiased detection of Cas9 binding sites genome-wide
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 GSE55887_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 PRJNA241244 and SRA study SRP040086. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 12 more — browse all 12 samples with per-sample file links →

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