Genome ResearchGenomicsPeer-reviewed journal article
Impact of regulatory variation across human iPSCs and differentiated cells
Nicholas E. BanovichiD, Yang LiiD, Anil RajiD, Michelle C. WardiD, Peyton Greenside, Diego CalderoniD, Po‐Yuan Tung, Jonathan E. Burnett, Marsha Myrthil, Samantha Marie ThomasiD, Courtney K. BurrowsiD, Irene Gallego RomeroiD, Bryan J. PavloviciD, Anshul Bharat KundajeiD, Jonathan K. PritchardiD, Yoav GiladiD
Abstract
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 across different cell types and as models for studies of complex disease. 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, chromatin accessibility and DNA methylation. Regulatory variation between individuals is lower in iPSCs than in the differentiated cell types, consistent with the intuition that developmental processes are generally canalized. 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 QTLs are in shared open chromatin. Finally, we developed a deep neural network to predict open chromatin regions from DNA sequence alone and were able to use the sequences of segregating haplotypes to predict the effects of common SNPs on cell type-specific chromatin accessibility.
- organism: human
- assay: bulk RNA-seq
- assay: DNA methylation
- assay: ATAC-seq
- research focus: gene regulatory network inference
- research focus: differential expression
- approach: deep learning
- Citations
- 128
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