Optimal-Transport Analysis of Single-Cell Gene Expression Identifies Developmental Trajectories in Reprogramming

Understanding the molecular programs that guide differentiation during development is a major challenge. Here, we introduce Waddington-OT, an approach for studying developmental time courses to infer ancestor-descendant fates and model the regulatory programs that underlie them. We apply the method...

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Vydané v:Cell Ročník 176; číslo 4; s. 928
Hlavní autori: Schiebinger, Geoffrey, Shu, Jian, Tabaka, Marcin, Cleary, Brian, Subramanian, Vidya, Solomon, Aryeh, Gould, Joshua, Liu, Siyan, Lin, Stacie, Berube, Peter, Lee, Lia, Chen, Jenny, Brumbaugh, Justin, Rigollet, Philippe, Hochedlinger, Konrad, Jaenisch, Rudolf, Regev, Aviv, Lander, Eric S
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: United States 07.02.2019
Predmet:
Animals
Cell Differentiation - genetics
Cells, Cultured
Cellular Reprogramming - genetics
Embryonic Stem Cells - metabolism
Fibroblasts - metabolism
Gene Expression
Gene Expression Profiling - methods
Gene Expression Regulation, Developmental - genetics
Induced Pluripotent Stem Cells - metabolism
Mice
Sequence Analysis, RNA - methods
Single-Cell Analysis - methods
Transcription Factors - metabolism
reprogramming
iPSCs
development
optimal-transport
paracrine interactions
scRNA-seq
regulation
trajectories
ancestors
descendants
ISSN:1097-4172, 1097-4172
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Shrnutí:Understanding the molecular programs that guide differentiation during development is a major challenge. Here, we introduce Waddington-OT, an approach for studying developmental time courses to infer ancestor-descendant fates and model the regulatory programs that underlie them. We apply the method to reconstruct the landscape of reprogramming from 315,000 single-cell RNA sequencing (scRNA-seq) profiles, collected at half-day intervals across 18 days. The results reveal a wider range of developmental programs than previously characterized. Cells gradually adopt either a terminal stromal state or a mesenchymal-to-epithelial transition state. The latter gives rise to populations related to pluripotent, extra-embryonic, and neural cells, with each harboring multiple finer subpopulations. The analysis predicts transcription factors and paracrine signals that affect fates and experiments validate that the TF Obox6 and the cytokine GDF9 enhance reprogramming efficiency. Our approach sheds light on the process and outcome of reprogramming and provides a framework applicable to diverse temporal processes in biology.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:1097-4172
1097-4172
DOI:10.1016/j.cell.2019.01.006