Dissecting cell identity via network inference and in silico gene perturbation.
Dissecting cell identity via network inference and in silico gene perturbation.
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DOI：
10.1038/s41586-022-05688-9
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发表时间：
2023-03
期刊：
影响因子：
64.8
通讯作者：
Morris, Samantha A.
中科院分区：
文献类型：
--
作者：
Kamimoto, Kenji;Stringa, Blerta;Hoffmann, Christy M.;Jindal, Kunal;Solnica-Krezel, Lilianna;Morris, Samantha A.
细胞身份是由基因表达的复杂调控所控制的，表现为基因调控网络。在这里，我们使用从单细胞多组学数据推断的基因调控网络来执行硅转录因子扰动，仅使用未受干扰的野生型数据模拟细胞身份的随之变化。我们将这种基于机器学习的方法CellOracle应用于成熟的范例-小鼠和人类造血，以及斑马鱼胚胎发生-并且我们正确地模拟了由于转录因子扰动而发生的表型变化。通过对发育中的斑马鱼进行系统的硅转录因子扰动，我们模拟并实验验证了一种以前未报道的表型，这种表型是由noto（一种已建立的脊索调节因子）的缺失造成的。此外，我们还鉴定了一个轴向中胚层调节因子lhx1a。总之，这些结果表明，CellOracle可以用于分析转录因子对细胞身份的调节，并可以为发育和分化提供机制见解。一种名为CellOracle的基于机器学习的策略将计算扰动与基因调控网络建模相结合，以分析转录因子如何调节细胞身份，并正确预测发育中的斑马鱼在转录因子扰动后的表型变化。
Cell identity is governed by the complex regulation of gene expression, represented as gene-regulatory networks. 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. A machine-learning-based strategy called CellOracle combines computational perturbation with modelling of gene-regulatory networks to analyse how cell identity is regulated by transcription factors, and correctly predicts phenotypic changes after transcription factor perturbation in the developing zebrafish.
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