Single-cell chromatin accessibility identifies pancreatic islet cell type- and state-specific regulatory programs of diabetes risk.

Single-cell chromatin accessibility identifies pancreatic islet cell type- and state-specific regulatory programs of diabetes risk.
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单细胞染色质可及性识别胰岛细胞类型和特定州糖尿病风险的调节计划。

DOI:
10.1038/s41588-021-00823-0
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发表时间:
2021-04
期刊:
影响因子:
30.8
通讯作者:
Gaulton, Kyle J.
Gaulton, Kyle J.
中科院分区:
生物学1区
文献类型:
--
作者:
Chiou, Joshua;Zeng, Chun;Cheng, Zhang;Han, Jee Yun;Schlichting, Michael;Miller, Michael;Mendez, Robert;Huang, Serina;Wang, Jinzhao;Sui, Yinghui;Deogaygay, Allison;Okino, Mei-Lin;Qiu, Yunjiang;Sun, Ying;Kudtarkar, Parul;Fang, Rongxin;Preissl, Sebastian;Sander, Maike;Gorkin, David U.;Gaulton, Kyle J.

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单核ATAC-seq (snATAC-seq)为解剖复杂疾病的细胞类型特异性机制创造了新的机会。由于胰岛是2型糖尿病(T2D)的核心,我们使用组合条形码snATAC-seq分析了15.3万个胰岛细胞,并鉴定了12个细胞簇,包括多种α、β和δ细胞状态。我们编目了228,873个可访问的染色质位点,并确定了潜在的谱系和国家特异性调控的转录因子。我们观察到β细胞的空腹葡萄糖和T2D GWAS的状态特异性富集,以及其他内分泌细胞类型的富集。在定位于胰岛可接近染色质的T2D信号中,我们优先考虑具有预测调节功能和与靶基因共可接近的变异。KCNQ1位点上的T2D致病变异rs231361预测了与INS共同可及的β细胞增强子的影响,并且胚胎干细胞来源的β细胞的基因组编辑影响了INS水平。总之,我们的发现证明了单细胞表观基因组学在解释复杂疾病遗传学方面的力量。
Single nucleus ATAC-seq (snATAC-seq) creates new opportunities to dissect cell type-specific mechanisms of complex diseases. As pancreatic islets are central to type 2 diabetes (T2D), we profiled 15.3k islet cells using combinatorial barcoding snATAC-seq and identified 12 clusters, including multiple alpha, beta and delta cell states. We cataloged 228,873 accessible chromatin sites and identified transcription factors underlying lineage- and state-specific regulation. We observed state-specific enrichment of fasting glucose and T2D GWAS for beta cells as well as enrichment for other endocrine cell types. At T2D signals localized to islet accessible chromatin, we prioritized variants with predicted regulatory function and co-accessibility with target genes. A causal T2D variant rs231361 at the KCNQ1 locus had predicted effects on a beta cell enhancer co-accessible with INS, and genome editing in embryonic stem cell-derived beta cells affected INS levels. Together our findings demonstrate the power of single cell epigenomics for interpreting complex disease genetics.
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