表观遗传景观解释部分重编程细胞并识别关键重编程基因
Epigenetic landscapes explain partially reprogrammed cells and identify key reprogramming genes
摘要：
描述发育的一个常见比喻是崎岖的“表观遗传景观”，其中细胞命运被表示为由复杂的调控网络产生的吸引山谷。在这里，我们介绍了一个明确构建表观遗传景观，结合基因组数据与自旋玻璃物理技术的框架。每个细胞命运都是一个动态吸引子，然而细胞可以响应外部信号改变命运。我们的模型表明，部分重编程的细胞是高维景观的自然结果，并预测部分重编程的细胞应该是共表达来自多个细胞命运的基因的杂交种。我们通过重新分析现有的数据集来验证这一预测。我们的模型再现已知的重编程协议，并确定候选转录因子的重编程到新的细胞命运，这表明表观遗传景观是一个强大的范例，了解细胞的身份。
英文摘要：
A common metaphor for describing development is a rugged "epigenetic landscape" where cell fates are represented as attracting valleys resulting from a complex regulatory network. Here, we introduce a framework for explicitly constructing epigenetic landscapes that combines genomic data with techniques from spin-glass physics. Each cell fate is a dynamic attractor, yet cells can change fate in response to external signals. Our model suggests that partially reprogrammed cells are a natural consequence of high-dimensional landscapes, and predicts that partially reprogrammed cells should be hybrids that co-express genes from multiple cell fates. We verify this prediction by reanalyzing existing datasets. Our model reproduces known reprogramming protocols and identifies candidate transcription factors for reprogramming to novel cell fates, suggesting epigenetic landscapes are a powerful paradigm for understanding cellular identity.
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