重编程
谱系(遗传)
生物
细胞生物学
祖细胞
内胚层
细胞命运测定
进化生物学
干细胞
计算生物学
细胞分化
细胞
遗传学
转录因子
基因
作者
Brent A. Biddy,Wenjun Kong,Kenji Kamimoto,Chuner Guo,Sarah Waye,Tao Sun,Samantha A. Morris
出处
期刊:Nature
[Springer Nature]
日期:2018-12-01
卷期号:564 (7735): 219-224
被引量:299
标识
DOI:10.1038/s41586-018-0744-4
摘要
Direct lineage reprogramming involves the conversion of cellular identity. Single-cell technologies are useful for deconstructing the considerable heterogeneity that emerges during lineage conversion. However, lineage relationships are typically lost during cell processing, complicating trajectory reconstruction. Here we present 'CellTagging', a combinatorial cell-indexing methodology that enables parallel capture of clonal history and cell identity, in which sequential rounds of cell labelling enable the construction of multi-level lineage trees. CellTagging and longitudinal tracking of fibroblast to induced endoderm progenitor reprogramming reveals two distinct trajectories: one leading to successfully reprogrammed cells, and one leading to a 'dead-end' state, paths determined in the earliest stages of lineage conversion. We find that expression of a putative methyltransferase, Mettl7a1, is associated with the successful reprogramming trajectory; adding Mettl7a1 to the reprogramming cocktail increases the yield of induced endoderm progenitors. Together, these results demonstrate the utility of our lineage-tracing method for revealing the dynamics of direct reprogramming.
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