TY - JOUR
T1 - Dissecting cell identity via network inference and in silico gene perturbation
AU - Kamimoto, Kenji
AU - Stringa, Blerta
AU - Hoffmann, Christy M.
AU - Jindal, Kunal
AU - Solnica-Krezel, Lilianna
AU - Morris, Samantha A.
N1 - Publisher Copyright:
© 2023, The Author(s), under exclusive licence to Springer Nature Limited.
PY - 2023/2/23
Y1 - 2023/2/23
N2 - Cell identity is governed by the complex regulation of gene expression, represented as gene-regulatory networks1. 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.
AB - Cell identity is governed by the complex regulation of gene expression, represented as gene-regulatory networks1. 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.
UR - http://www.scopus.com/inward/record.url?scp=85147705593&partnerID=8YFLogxK
U2 - 10.1038/s41586-022-05688-9
DO - 10.1038/s41586-022-05688-9
M3 - Article
C2 - 36755098
AN - SCOPUS:85147705593
SN - 0028-0836
VL - 614
SP - 742
EP - 751
JO - Nature
JF - Nature
IS - 7949
ER -