Leveraging single-cell ATAC-seq and RNA-seq to identify disease-critical fetal and adult brain cell types

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作者
Samuel S. Kim
Buu Truong
Karthik Jagadeesh
Kushal K. Dey
Amber Z. Shen
Soumya Raychaudhuri
Manolis Kellis
Alkes L. Price
机构
[1] Massachusetts Institute of Technology,Department of Electrical Engineering and Computer Science
[2] Harvard T.H. Chan School of Public Health,Department of Epidemiology
[3] Broad Institute of MIT and Harvard,Program in Medical and Population Genetics
[4] Memorial Sloan Kettering Cancer Center,Computational and Systems Biology Program, Sloan Kettering Institute
[5] Massachusetts Institute of Technology,Department of Mathematics
[6] Brigham and Women’s Hospital and Harvard Medical School,Division of Genetics, Department of Medicine
[7] Harvard T.H. Chan School of Public Health,Department of Biostatistics
来源
Nature Communications | / 15卷
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摘要
Prioritizing disease-critical cell types by integrating genome-wide association studies (GWAS) with functional data is a fundamental goal. Single-cell chromatin accessibility (scATAC-seq) and gene expression (scRNA-seq) have characterized cell types at high resolution, and studies integrating GWAS with scRNA-seq have shown promise, but studies integrating GWAS with scATAC-seq have been limited. Here, we identify disease-critical fetal and adult brain cell types by integrating GWAS summary statistics from 28 brain-related diseases/traits (average N = 298 K) with 3.2 million scATAC-seq and scRNA-seq profiles from 83 cell types. We identified disease-critical fetal (respectively adult) brain cell types for 22 (respectively 23) of 28 traits using scATAC-seq, and for 8 (respectively 17) of 28 traits using scRNA-seq. Significant scATAC-seq enrichments included fetal photoreceptor cells for major depressive disorder, fetal ganglion cells for BMI, fetal astrocytes for ADHD, and adult VGLUT2 excitatory neurons for schizophrenia. Our findings improve our understanding of brain-related diseases/traits and inform future analyses.
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