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一个全组织DNA甲基化图谱能够在细胞类型分辨率下对人类组织甲基化组进行计算机分解。

A pan-tissue DNA methylation atlas enables in silico decomposition of human tissue methylomes at cell-type resolution.

作者信息

Zhu Tianyu, Liu Jacklyn, Beck Stephan, Pan Sun, Capper David, Lechner Matt, Thirlwell Chrissie, Breeze Charles E, Teschendorff Andrew E

机构信息

CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.

University College London, London, UK.

出版信息

Nat Methods. 2022 Mar;19(3):296-306. doi: 10.1038/s41592-022-01412-7. Epub 2022 Mar 11.

Abstract

Bulk-tissue DNA methylomes represent an average over many different cell types, hampering our understanding of cell-type-specific contributions to disease development. As single-cell methylomics is not scalable to large cohorts of individuals, cost-effective computational solutions are needed, yet current methods are limited to tissues such as blood. Here we leverage the high-resolution nature of tissue-specific single-cell RNA-sequencing datasets to construct a DNA methylation atlas defined for 13 solid tissue types and 40 cell types. We comprehensively validate this atlas in independent bulk and single-nucleus DNA methylation datasets. We demonstrate that it correctly predicts the cell of origin of diverse cancer types and discovers new prognostic associations in olfactory neuroblastoma and stage 2 melanoma. In brain, the atlas predicts a neuronal origin for schizophrenia, with neuron-specific differential DNA methylation enriched for corresponding genome-wide association study risk loci. In summary, the DNA methylation atlas enables the decomposition of 13 different human tissue types at a high cellular resolution, paving the way for an improved interpretation of epigenetic data.

摘要

大块组织的DNA甲基化组代表了许多不同细胞类型的平均值,这妨碍了我们对细胞类型特异性对疾病发展贡献的理解。由于单细胞甲基组学无法扩展到大量个体队列,因此需要具有成本效益的计算解决方案,但目前的方法仅限于血液等组织。在这里,我们利用组织特异性单细胞RNA测序数据集的高分辨率特性,构建了一个针对13种实体组织类型和40种细胞类型定义的DNA甲基化图谱。我们在独立的大块和单核DNA甲基化数据集中全面验证了该图谱。我们证明它能正确预测多种癌症类型的起源细胞,并在嗅神经母细胞瘤和II期黑色素瘤中发现新的预后关联。在大脑中,该图谱预测精神分裂症起源于神经元,神经元特异性差异DNA甲基化在相应的全基因组关联研究风险位点中富集。总之,DNA甲基化图谱能够在高细胞分辨率下分解13种不同的人类组织类型,为改进表观遗传数据的解释铺平了道路。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2df1/8916958/a3cb26608244/41592_2022_1412_Fig1_HTML.jpg

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