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Virtual methylome dissection facilitated by single-cell analyses

机译：通过单细胞分析促进虚拟甲基姆解剖

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Numerous cell types can be identified within plant tissues and animal organs, and the epigenetic modifications underlying such enormous cellular heterogeneity are just beginning to be understood. It remains a challenge to infer cellular composition using DNA methylomes generated for mixed cell populations. Here, we propose a semi-reference-free procedure to perform virtual methylome dissection using the nonnegative matrix factorization (NMF) algorithm. In the pipeline that we implemented to predict cell-subtype percentages, putative cell-type-specific methylated (pCSM) loci were first determined according to their DNA methylation patterns in bulk methylomes and clustered into groups based on their correlations in methylation profiles. A representative set of pCSM loci was then chosen to decompose target methylomes into multiple latent DNA methylation components (LMCs). To test the performance of this pipeline, we made use of single-cell brain methylomes to create synthetic methylomes of known cell composition. Compared with highly variable CpG sites, pCSM loci achieved a higher prediction accuracy in the virtual methylome dissection of synthetic methylomes. In addition, pCSM loci were shown to be good predictors of the cell type of the sorted brain cells. The software package developed in this study is available in the GitHub repository (https://github.com/Gavin-Yinld). We anticipate that the pipeline implemented in this study will be an innovative and valuable tool for the decoding of cellular heterogeneity.
机译：可以在植物组织和动物器官内鉴定多种细胞类型，并且刚刚开始理解这种巨大的细胞异质性下面的表观遗传修饰。使用为混合细胞群产生的DNA甲基族来推断细胞组合物仍然是挑战。这里，我们提出了一种使用非负矩阵分解（NMF）算法进行虚拟甲基胺解剖的半参考程序。在我们实施以预测细胞亚型百分比的管道中，首先根据其DNA甲基化图案在块状甲状腺物中的DNA甲基化模式并基于其甲基化型材中的相关性聚集成基团。然后选择一种代表性的PCSM基因座以将靶向巯基分解成多个潜伏的DNA甲基化成分（LMC）。为了测试该管道的性能，我们使用单细胞脑静脉瘤以产生已知细胞组合物的合成甲基瘤。与高度可变的CPG位点相比，PCSM基因座在合成甲基孔的虚拟甲基姆解剖中实现了更高的预测精度。此外，PCSM基因座被证明是分类脑细胞的细胞类型的良好预测因子。本研究中开发的软件包可在GitHub存储库（HTTPS://github.com/gavin-yinld）中提供。我们预计本研究中实施的管道将是一种用于解码细胞异质性的创新和有价值的工具。

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