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Research Resources: Epigenomic and Transcriptomic Profile of Human Immune Cells

Research Resources: Epigenomic and Transcriptomic Profile of Human Immune Cells
研究资源:人类免疫细胞的表观基因组和转录组谱
批准号:
10462541
负责人:
Ferhat Ay
金额:
$109.03万
依托单位国家:
美国
项目类别:
财政年份:
2014
资助国家:
美国
项目状态:
已结题
起止时间:
2014-08-01 至 2024-07-31

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PROJECT SUMMARY While an enormous number of genetic variants have been associated with risk for human disease, how these variants affect gene expression in various cell types remains largely unknown. To address this gap as it relates to immune cells, as well as to identify which immune cell types are most susceptible to the effects of disease- risk variants, the DICE (Database of Immune Cell Expression, Expression quantitative trait loci (eQTLs) and Epigenomics) project was established in 2014, funded by the current R24 resource grant (R24AI108564). Our current datasets reveal the effects of disease risk-associated SNPs on common immune cell types (http://dice- database.org). However, this dataset is far from complete; the effects of disease-risk variants on several very important but rare and/or difficult to isolate cells, such as circulating innate immune cells and tissue-resident immune cells, have yet to be studied. Having accomplished the aims of the first DICE grant, we now propose to build on our findings through the following specific aims: In Aim 1, we will expand eQTL analysis to (A) Rare circulating immune cell types such as dendritic cells, innate lymphoid cells (ILCs), invariant NKT cells, gdT cells and CD4-CTL subsets, isolated from banked cryopreserved leukapheresis samples (>100) collected via the DICE project, (B) circulating immune cells activated ex vivo, and (C) Tissue-resident memory (TRM) T cell types such as CD8+ TRM, CD4+ TRM and tissue-resident NK cells isolated from lung tissue samples of 100 subjects to map tissue-specific immune eQTLs tissue-resident immune cell types. In Aim 2, we will define long-range enhancer-promoter 3D interactions in immune cell types to predict functionally important non-coding GWAS SNPs. In Aim 3, we will expand our existing website (http://dice-database.org) to make current and newly generated experimental data and analysis tools available to the community.
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Using Common Fund datasets for prioritization of disease-associated genetic variants
SARS-CoV-2-reactive tissue-resident memory T cells in healthy and cancer subjects
SARS-CoV-2-reactive tissue-resident memory T cells in healthy and cancer subjects
SARS-CoV-2-reactive tissue-resident memory T cells in healthy and cancer subjects
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