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An analytical framework for decoding cell type-specific genetic variation of gene regulation.

Yanyu XiaoJingjing WangJiaqi LiPeijing ZhangJingyu LiYincong ZhouQing ZhouMing ChenXin ShengZhihong LiuXiaoping HanGuoji Guo
Published in: Nature communications (2023)
A deeper understanding of genetic regulation and functional mechanisms underlying genetic associations with complex traits and diseases is impeded by cellular heterogeneity and linkage disequilibrium. To address these limits, we introduce Huatuo, a framework to decode genetic variation of gene regulation at cell type and single-nucleotide resolutions by integrating deep-learning-based variant predictions with population-based association analyses. We apply Huatuo to generate a comprehensive cell type-specific genetic variation landscape across human tissues and further evaluate their potential roles in complex diseases and traits. Finally, we show that Huatuo's inferences permit prioritizations of driver cell types associated with complex traits and diseases and allow for systematic insights into the mechanisms of phenotype-causal genetic variation.
Keyphrases
  • genome wide
  • single cell
  • deep learning
  • dna methylation
  • copy number
  • endothelial cells
  • gene expression
  • cell therapy
  • stem cells
  • mass spectrometry
  • human health
  • hiv testing