作者: Nicholas E. Banovich , Yang I. Li , Anil Raj , Michelle C. Ward , Peyton Greenside
关键词: Chromatin 、 Biology 、 Computational biology 、 Regulation of gene expression 、 Cellular differentiation 、 Genetic variation 、 Quantitative trait locus 、 Induced pluripotent stem cell 、 DNA methylation 、 Cell type
摘要: Induced pluripotent stem cells (iPSCs) are an essential tool for studying cellular differentiation and cell types that otherwise difficult to access. We investigated the use of iPSCs iPSC-derived study impact genetic variation on gene regulation across different as models studies complex disease. To do so, we established a panel from 58 well-studied Yoruba lymphoblastoid lines (LCLs); 14 these were further differentiated into cardiomyocytes. characterized regulatory individuals by measuring expression levels, chromatin accessibility, DNA methylation. Our analysis focused comparison inter-individual types. While most cell-type-specific quantitative trait loci (QTLs) lie in is open only affected types, found 20% QTLs shared chromatin. This observation motivated us develop deep neural network predict regions sequence alone. Using this approach, able sequences segregating haplotypes effects common SNPs accessibility.