单细胞多模式数据中的动态调控元素暗示了对自身免疫性疾病遗传性进行丰富的关键免疫细胞状态
Anika Gupta1,2,3,4,5, Kathryn Weinand1,2,3,4,5, Aparna Nathan1,2,3,4,5
1Center for Data Sciences, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
Nature genetics
|November 30, 2023
概括
研究人员确定了与自身免疫性疾病相关的免疫细胞中的动态调节元素. 这些元素显示细胞状态依赖的染色质可访问性,对遗传风险进行了丰富,精确确定了疾病发展关键的特定细胞类型.
科学领域:
- 免疫学 免疫学 免疫学
- 遗传学 遗传学是一种遗传学.
- 计算生物学 计算生物学
背景情况:
- 自免疫性疾病涉及免疫系统对宿主组织的攻击.
- 了解特定细胞状态中的遗传风险变异对于开发向疗法至关重要.
研究的目的:
- 识别具有可访问的染色质与细胞状态特定的基因表达相关的非编码基因组区域.
- 为了确定细胞状态依赖的染色质可访问性是否为自身免疫性疾病的遗传性而丰富.
主要方法:
- 多模式单核RNA测序和ATAC测序在28674个炎症突组织细胞上进行.
- 一个多变量波桑模型从基因表达数据中预测了色素可访问性峰值.
- 对细胞状态依赖的与细胞状态不变的可访问性峰值进行了遗传性丰富性分析.
主要成果:
- 与细胞状态不变的峰值相比,14种自身免疫性疾病的细胞状态依赖的染色质可访问性峰值在遗传性方面得到了显著的丰富.
- 这些动态峰值与特定的免疫细胞状态有关,包括T外围辅助细胞,调节性T,树突细胞和STAT1+CXCL10+髓质细胞.
- 这些发现凸显了动态调节要素在确定疾病关键遗传变异方面的重要性.
结论:
- 通过细胞状态依赖的染色质可访问性来识别的动态调节元素是理解自身免疫性疾病遗传学的关键.
- 这种方法可以精确地识别为遗传风险变体丰富的免疫细胞状态,为新的治疗策略铺平道路.
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