生物信息学
斑马鱼
调节器
转录因子
生物
基因调控网络
表型
计算生物学
基因
脊索
遗传学
基因表达调控
系统生物学
细胞生物学
基因表达
胚胎发生
作者
Kenji Kamimoto,Blerta Stringa,Christy M. Hoffmann,Kunal Jindal,Lilianna Solnica‐Krezel,Samantha A. Morris
出处
期刊:Nature
[Springer Nature]
日期:2023-02-08
卷期号:614 (7949): 742-751
被引量:284
标识
DOI:10.1038/s41586-022-05688-9
摘要
Abstract Cell identity is governed by the complex regulation of gene expression, represented as gene-regulatory networks 1 . Here we use gene-regulatory networks inferred from single-cell multi-omics data to perform in silico transcription factor perturbations, simulating the consequent changes in cell identity using only unperturbed wild-type data. We apply this machine-learning-based approach, CellOracle, to well-established paradigms—mouse and human haematopoiesis, and zebrafish embryogenesis—and we correctly model reported changes in phenotype that occur as a result of transcription factor perturbation. Through systematic in silico transcription factor perturbation in the developing zebrafish, we simulate and experimentally validate a previously unreported phenotype that results from the loss of noto , an established notochord regulator. Furthermore, we identify an axial mesoderm regulator, lhx1a . Together, these results show that CellOracle can be used to analyse the regulation of cell identity by transcription factors, and can provide mechanistic insights into development and differentiation.
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