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Parkinson-associated risk variant in distal enhancer of α-synuclein modulates target gene expression

GSE71278 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 11 samples Submitted 2016/04/20 Platform GPL11154
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 11 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
11 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)
Genome-wide association studies (GWAS) have identified genomic loci associated with complex diseases but mechanistic insights are impeded by the lack of understanding of how specific risk variants functionally contribute to diseases. Here we describe an experimental strategy to robustly identify cis-acting effects of genetic variants in regulatory elements on gene expression by combining genome-wide epigenetic information with CRISPR/Cas genome editing in human pluripotent cells.
Read the full summary ↓
Using this genetically controlled system, we identify a common Parkinson’s disease (PD)-associated risk variant in a non-coding distal enhancer element that regulates the expression of SNCA, a key gene implicated in the pathogenesis of PD. We provide data suggesting that the transcriptional deregulation of SNCA is associated with sequence-dependent binding of the brain-specific transcription factors EMX2 and NKX6-1. Our work provides a general experimental strategy to functionally connect genetic variation with disease relevant phenotypes.
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 GSE71278_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 PRJNA290785 and SRA study SRP061464. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 11 more — browse all 11 samples with per-sample file links →

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