Chen Zeyuan Johnson, Das Sankha Subhra, Kar Asha, Lee Seung Hyuk T, Abuhanna Kevin D, Alvarez Marcus, Sukhatme Mihir G, Gelev Kyla Z, Heffel Matthew G, Zhang Yi, Avram Oren, Rahmani Elior, Sankararaman Sriram, Heinonen Sini, Peltoniemi Hilkka, Halperin Eran, Pietiläinen Kirsi H, Luo Chongyuan, Pajukanta Päivi
Department of Computer Science, University of California, Los Angeles, Los Angeles, CA 90095, USA.
Department of Computational Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA.
bioRxiv. 2024 Nov 3:2024.11.02.621694. doi: 10.1101/2024.11.02.621694.
Human subcutaneous adipose tissue (SAT) contains a diverse array of cell-types; however, the epigenomic landscape among the SAT cell-types has remained elusive. Our integrative analysis of single-cell resolution DNA methylation and chromatin conformation profiles (snm3C-seq), coupled with matching RNA expression (snRNA-seq), systematically cataloged the epigenomic, 3D topology, and transcriptomic dynamics across the SAT cell-types. We discovered that the SAT CG methylation (mCG) landscape is characterized by pronounced hyper-methylation in myeloid cells and hypo-methylation in adipocytes and adipose stem and progenitor cells (ASPCs), driving nearly half of the 705,063 detected differentially methylated regions (DMRs). In addition to the enriched cell-type-specific transcription factor binding motifs, we identified and as plausible candidates for regulating cell-type level mCG profiles. Furthermore, we observed that global mCG profiles closely correspond to SAT lineage, which is also reflected in cell-type-specific chromosome compartmentalization. Adipocytes, in particular, display significantly more short-range chromosomal interactions, facilitating the formation of complex local 3D genomic structures that regulate downstream transcriptomic activity, including those associated with adipogenesis. Finally, we discovered that variants in cell-type level DMRs and A compartments significantly predict and are enriched for variance explained in abdominal obesity. Together, our multimodal study characterizes human SAT epigenomic landscape at the cell-type resolution and links partitioned polygenic risk of abdominal obesity to SAT epigenome.
人类皮下脂肪组织（SAT）包含多种细胞类型；然而，SAT细胞类型之间的表观基因组格局仍不清楚。我们对单细胞分辨率的DNA甲基化和染色质构象图谱（snm3C-seq）进行综合分析，并结合匹配的RNA表达（snRNA-seq），系统地编目了SAT细胞类型中的表观基因组、三维拓扑结构和转录组动态。我们发现，SAT的CG甲基化（mCG）格局的特征是髓系细胞中显著的高甲基化以及脂肪细胞和脂肪干/祖细胞（ASPC）中的低甲基化，这驱动了检测到的705,063个差异甲基化区域（DMR）中近一半的差异。除了丰富的细胞类型特异性转录因子结合基序外，我们还确定了 和 作为调节细胞类型水平mCG图谱的合理候选者。此外，我们观察到整体mCG图谱与SAT谱系密切对应，这也反映在细胞类型特异性的染色体区室化中。特别是脂肪细胞显示出明显更多的短程染色体相互作用，促进了复杂局部三维基因组结构的形成，这些结构调节下游转录组活性，包括与脂肪生成相关的活性。最后，我们发现细胞类型水平DMR和A区室中的变异显著预测腹部肥胖中解释的变异并使其富集。总之，我们的多模态研究在细胞类型分辨率上表征了人类SAT表观基因组格局，并将腹部肥胖的分区多基因风险与SAT表观基因组联系起来。
