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Series GSE147672 Query DataSets for GSE147672
Status Public on Jul 26, 2020
Title Single-cell epigenomic identification of inherited risk loci in Alzheimer’s and Parkinson’s disease
Organism Homo sapiens
Experiment type Genome binding/occupancy profiling by high throughput sequencing
Other
Summary Genome-wide association studies (GWAS) have identified thousands of variants associated with disease phenotypes. However, the majority of these variants do not alter coding sequences, making it difficult to assign their function. To this end, we present a multi-omic epigenetic atlas of the adult human brain through profiling of the chromatin accessibility landscapes and three-dimensional chromatin interactions of seven brain regions across a cohort of 39 cognitively healthy individuals. Single-cell chromatin accessibility profiling of 70,631 cells from six of these brain regions identifies 24 distinct cell clusters and 359,022 cell type-specific regulatory elements, capturing the regulatory diversity of the adult brain. We develop a machine learning classifier to integrate this multi-omic framework and predict dozens of functional single nucleotide polymorphisms (SNPs), nominating gene and cellular targets for previously orphaned GWAS loci. These predictions both inform well-studied disease-relevant genes, such as BIN1 in microglia for Alzheimer’s disease (AD) and reveal novel gene-disease associations, such as STAB1 in microglia and MAL in oligodendrocytes for Parkinson’s disease (PD). Moreover, we dissect the complex inverted haplotype of the MAPT (encoding tau) PD risk locus, identifying ectopic enhancer-gene contacts in neurons that increase MAPT expression and may mediate this disease association. This work greatly expands our understanding of inherited variation in AD and PD and provides a roadmap for the epigenomic dissection of noncoding regulatory variation in disease.
 
Overall design Bulk ATAC-seq, single-cell ATAC-seq and HiChIP
 
Contributor(s) Corces RM
Citation(s) 33106633
Submission date Mar 27, 2020
Last update date Mar 29, 2022
Contact name Carlos Aguilar
E-mail(s) caguilar@umich.edu
Organization name University of Michigan - Ann Arbor
Department Dept. of Biomedical Engineering & Biointerfaces Institute
Lab NANO-OMIC-BIO-ENGINEERING-LAB
Street address 300 Pasteur Dr
City Ann Arbor
State/province MI
ZIP/Postal code 48109
Country USA
 
Platforms (2)
GPL20301 Illumina HiSeq 4000 (Homo sapiens)
GPL24676 Illumina NovaSeq 6000 (Homo sapiens)
Samples (162)
GSM4441680 BulkATAC Control Caudate 1
GSM4441681 BulkATAC Control Caudate 10
GSM4441682 BulkATAC Control Caudate 11
Relations
BioProject PRJNA616031
SRA SRP254409

Download family Format
SOFT formatted family file(s) SOFTHelp
MINiML formatted family file(s) MINiMLHelp
Series Matrix File(s) TXTHelp

Supplementary file Size Download File type/resource
GSE147672_200324_Brain_scATAC_SummarizedExperiment_forGEO.barcodes.tsv.gz 2.5 Mb (ftp)(http) TSV
GSE147672_200324_Brain_scATAC_SummarizedExperiment_forGEO.peaks.tsv.gz 12.1 Mb (ftp)(http) TSV
GSE147672_200324_Brain_scATAC_SummarizedExperiment_forGEO.rds.gz 1.5 Gb (ftp)(http) RDS
GSE147672_RAW.tar 348.2 Gb (http)(custom) TAR (of BED, BIGWIG, NARROWPEAK)
GSE147672_scATAC_bigwig.tar.gz 24.1 Gb (ftp)(http) TAR
GSE147672_scATAC_idr_peaks.tar.gz 68.5 Mb (ftp)(http) TAR
GSE147672_scATAC_overlap_peaks.tar.gz 125.1 Mb (ftp)(http) TAR
GSE147672_scATAC_pval_bigwig.tar.gz 17.9 Gb (ftp)(http) TAR
SRA Run SelectorHelp
Raw data are available in SRA
Processed data provided as supplementary file
Processed data are available on Series record

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