TY - JOUR
T1 - Impact of regulatory variation across human iPSCs and differentiated cells
AU - Banovich, Nicholas E.
AU - Li, Yang I.
AU - Raj, Anil
AU - Ward, Michelle C.
AU - Greenside, Peyton
AU - Calderon, Diego
AU - Tung, Po Yuan
AU - Burnett, Jonathan E.
AU - Myrthil, Marsha
AU - Thomas, Samantha M.
AU - Burrows, Courtney K.
AU - Romero, Irene Gallego
AU - Pavlovic, Bryan J.
AU - Kundaje, Anshul
AU - Pritchard, Jonathan K.
AU - Gilad, Yoav
N1 - Publisher Copyright:
© 2018 Banovich et al.
PY - 2018/1
Y1 - 2018/1
N2 - Induced pluripotent stem cells (iPSCs) are an essential tool for studying cellular differentiation and cell types that are otherwise difficult to access. We investigated the use of iPSCs and iPSC-derived cells to study the impact of genetic variation on gene regulation across different cell types and as models for studies of complex disease. To do so, we established a panel of iPSCs from 58 well-studied Yoruba lymphoblastoid cell lines (LCLs); 14 of these lines were further differentiated into cardiomyocytes. We characterized regulatory variation across individuals and cell types by measuring gene expression levels, chromatin accessibility, and DNA methylation. Our analysis focused on a comparison of inter-individual regulatory variation across cell types. While most cell-type–specific regulatory quantitative trait loci (QTLs) lie in chromatin that is open only in the affected cell types, we found that 20% of cell-type–specific regulatory QTLs are in shared open chromatin. This observation motivated us to develop a deep neural network to predict open chromatin regions from DNA sequence alone. Using this approach, we were able to use the sequences of segregating haplotypes to predict the effects of common SNPs on cell-type–specific chromatin accessibility.
AB - Induced pluripotent stem cells (iPSCs) are an essential tool for studying cellular differentiation and cell types that are otherwise difficult to access. We investigated the use of iPSCs and iPSC-derived cells to study the impact of genetic variation on gene regulation across different cell types and as models for studies of complex disease. To do so, we established a panel of iPSCs from 58 well-studied Yoruba lymphoblastoid cell lines (LCLs); 14 of these lines were further differentiated into cardiomyocytes. We characterized regulatory variation across individuals and cell types by measuring gene expression levels, chromatin accessibility, and DNA methylation. Our analysis focused on a comparison of inter-individual regulatory variation across cell types. While most cell-type–specific regulatory quantitative trait loci (QTLs) lie in chromatin that is open only in the affected cell types, we found that 20% of cell-type–specific regulatory QTLs are in shared open chromatin. This observation motivated us to develop a deep neural network to predict open chromatin regions from DNA sequence alone. Using this approach, we were able to use the sequences of segregating haplotypes to predict the effects of common SNPs on cell-type–specific chromatin accessibility.
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U2 - 10.1101/gr.224436.117
DO - 10.1101/gr.224436.117
M3 - Article
C2 - 29208628
AN - SCOPUS:85039994149
SN - 1088-9051
VL - 28
SP - 122
EP - 131
JO - Genome Research
JF - Genome Research
IS - 1
ER -