Impact of regulatory variation across human iPSCs and differentiated cells [ATAC-seq iPSC]
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PROVIDER: PRJNA427323 | ENA |
REPOSITORIES: ENA
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Project description:Impact of regulatory variation across human iPSCs and differentiated cells [ATAC-seq iPSC-CM]
| PRJNA427322 | ENA
Project description: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.
2017-12-23 | GSE108458 | GEO
Project description: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.
2017-12-23 | GSE108459 | GEO
Project description: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.
2017-12-23 | GSE108460 | GEO
Project description:Induced pluripotent stem cells (iPSCs) are an essential tool for studying cellular differentiation and cell types that are otherwise difficult to access. Here we investigate the use of iPSCs and iPSC-derived cells to study the impact of genetic variation across different cell types and as models for the genetics 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 RNA, 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 effects lie in chromatin that is open only in the affected cell-types, we find that 20% of cell-type specific effects are in shared open chromatin. Finally, we developed deep neural network models to predict open chromatin regions in these cell types from DNA sequence alone and were able to use the sequences of segregating haplotypes to predict the effects of common SNPs on tissue-specific chromatin accessibility. Our results provide a framework for using iPSC technology to study regulatory variation in cell types that are otherwise inaccessible. Keywords: Expression profiling by high throughput sequencing
2017-12-05 | GSE107654 | GEO
Project description:Human iPSCs were differentiated towards an induced-SMC (iSMC) phenotype in a 10-day protocol. Proteomics was performed throughout the entire differentiation time course to provide a robust, well-defined starting and ending cell population. Proteomics data verified iPSC differentiation to iSMCs. Proteomics comparison with primary human SMCs showed a high correlation with iSMCs. After iSMC differentiation, we initiated calcification in the iSMCs by culturing the cells in osteogenic media for 17 days.
2022-10-14 | PXD032353 | Pride
Project description:Impact of regulatory variation across human iPSCs and differentiated cells [ATAC-seq LCL]
| PRJNA427321 | ENA
Project description:ATAC-seq samples from 2 species and 2 cell types were generated to study cis-regulatory element evolution. Briefly, previously generated urinary stem cell derived iPS-cells (Homo sapiens) of 2 human individuals and fibroblast derived cynomolgus macaque iPSCs (Macaca fascicularis) of 2 individuals (Geuder et al. 2021) were differentiated to neural progenitor cells via dual-SMAD inhibition as three-dimensional aggregation culture (Chambers et al. 2009; Ohnuki et al. 2014). The NPC lines were cultured in NPC proliferation medium and passaged 2 - 4 times until they were dissociated and subjected to ATAC-seq together with the respective iPSC clones. ATAC-seq libraries were generated using the Omni-ATAC protocol (Corces et al. 2017) with minor modifications.
2023-10-25 | E-MTAB-13373 | biostudies-arrayexpress
Project description: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.
2018-02-13 | GSE110544 | GEO
Project description:Impact of regulatory variation across human iPSCs and differentiated cells
| PRJNA354301 | ENA