Impact of regulatory variation across human iPSCs and differentiated cells [ATAC-seq LCL]
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA427321 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR6412830_1.fastq.gz | Fastqsanger.gz | |||
| SRR6412830_2.fastq.gz | Fastqsanger.gz | |||
| SRR6412840_1.fastq.gz | Fastqsanger.gz | |||
| SRR6412840_2.fastq.gz | Fastqsanger.gz | |||
| SRR6412831_1.fastq.gz | Fastqsanger.gz |
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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:Impact of regulatory variation across human iPSCs and differentiated cells
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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:Impact of regulatory variation across human iPSCs and differentiated cells [ATAC-seq iPSC]
| PRJNA427323 | 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.
2018-02-13 | GSE110544 | GEO
Project description:Purpose: There exists a rich bio-resource of numerous lymphoblastoid cell line (LCL) repositories generated from a wide array of patients, many of them with extensive genotypic and phenotypic data already generated. We have developed a highly efficient LCL to induced pluripotent stem cells (iPSC) reprogramming method and performed whole genome mRNA and miRNA analysis to understand mechanistic changes that take place at the transcriptome and cellular functional level during reprogramming of LCLs into iPSCs and further differentiation. Methods: Applying our optimized protocol which utilizes episomal plasmids encoding pluripotency transcription factors and mouse p53DD - p53 carboxy-terminal dominant-negative fragment and commercially available reprogramming media, we reprogrammed six LCLs into iPSCs and then differentiated them into neural stem cells (NSC). The LCLs, their reprogrammed iPSCs and differentiated NSC (n=18) were sequenced for mRNA and smallRNA on an illumina HiSeq 2500. Differential gene expression analysis was performed between LCL-iPSC and iPSC-NSC pairs in combination with functional annotations and Ingenuity® Pathway Analysis (IPA). Results: Our LCL reprogrammed iPSCs express the majority of genes and miRNAs known to contribute to stemness in human ESCs. The functional enrichment analysis of the up-regulated genes and activation of human pluripotency pathways in the reprogrammed iPSCs showed that the generated iPSCs have a transcriptional and functional profile very similar to that of human ESCs. The reprogrammed iPSCs also showed the potential to differentiate into cells of all three germ layers. Significantly, the transcriptomic effect of EBV encoded oncoproteins which were very pronounced in LCLs, were significantly inhibited in reprogrammed iPSCs. The transcriptomic and functional enrichment analysis of the NSC differentiated from the reprogrammed iPSCs showed that they share a functional profile of self-renewing NSCs. Conclusions: We have been able to develop a MEF feeder free protocol for efficient and reproducible reprogramming of LCLs into iPSC. In addition our comprehensive analysis of genome wide miRNA and mRNA of LCLs, their reprogrammed iPSC and differentiated NSCs provides important documentation of differentially expressed genes and miRNAs and their functional consequences during LCL to iPSC reprogramming and NSC differentiations that were previously unknown.
2017-02-11 | GSE74289 | GEO
Project description:Impact of regulatory variation across human iPSCs and differentiated cells [methylation]
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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.
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