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Genetic Variation, Not Cell Type of Origin, Underlies Regulatory Differences in iPSCs

ABSTRACT: Genetic Variation, Not Cell Type of Origin, Underlies Regulatory Differences in iPSCs

PROVIDER: PRJNA272898 | ENA |

REPOSITORIES: ENA

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Genetic Variation, Not Cell Type of Origin, Underlies Regulatory Differences in iPSCs [Methylation]

Project description:Analysis of contribution of cell type of origin and individual to gene expression differences in iPSCs. The hypothesis tested in the present study was that cell type of origin affects iPSC gene expression. Results show that individual has a much stronger effect than cell type of origin on differences between iPSCs derived from multiple individuals. DNA obtained from feeder-free iPSCs derived from multiple individuals and tissues and their corresponding cell type of origin

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Genetic Variation, Not Cell Type of Origin, Underlies Regulatory Differences in iPSCs [Expression]

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Genetic Variation, Not Cell Type of Origin, Underlies Regulatory Differences in iPSCs [Methylation]

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Genetic Variation, Not Cell Type of Origin, Underlies Regulatory Differences in iPSCs

Project description:This SuperSeries is composed of the SubSeries listed below. Refer to individual Series

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Genetic Variation, Not Cell Type of Origin, Underlies the Majority of Identifiable Regulatory Differences in iPSCs.

Project description:The advent of induced pluripotent stem cells (iPSCs) revolutionized human genetics by allowing us to generate pluripotent cells from easily accessible somatic tissues. This technology can have immense implications for regenerative medicine, but iPSCs also represent a paradigm shift in the study of complex human phenotypes, including gene regulation and disease. Yet, an unresolved caveat of the iPSC model system is the extent to which reprogrammed iPSCs retain residual phenotypes from their precursor somatic cells. To directly address this issue, we used an effective study design to compare regulatory phenotypes between iPSCs derived from two types of commonly used somatic precursor cells. We find a remarkably small number of differences in DNA methylation and gene expression levels between iPSCs derived from different somatic precursors. Instead, we demonstrate genetic variation is associated with the majority of identifiable variation in DNA methylation and gene expression levels. We show that the cell type of origin only minimally affects gene expression levels and DNA methylation in iPSCs, and that genetic variation is the main driver of regulatory differences between iPSCs of different donors. Our findings suggest that studies using iPSCs should focus on additional individuals rather than clones from the same individual.

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Genetic Variation, Not Cell Type of Origin, Underlies Regulatory Differences in iPSCs

Project description:This SuperSeries is composed of the SubSeries listed below.

2015-01-19 | GSE65079 | GEO

Homo sapiens

Project description:Genetic Variation, Not Cell Type of Origin, Underlies Regulatory Differences in iPSCs [Expression]

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Project description:Genetic Variation, Not Cell Type of Origin, Underlies Regulatory Differences in iPSCs [Methylation]

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Impact of regulatory variation across human iPSCs and differentiated cells [RNA-seq]

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

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