Literature DB >> 30712874

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

Geoffrey Schiebinger1, Jian Shu2, Marcin Tabaka3, Brian Cleary4, Vidya Subramanian3, Aryeh Solomon3, Joshua Gould3, Siyan Liu5, Stacie Lin6, Peter Berube3, Lia Lee3, Jenny Chen7, Justin Brumbaugh8, Philippe Rigollet9, Konrad Hochedlinger10, Rudolf Jaenisch11, Aviv Regev12, Eric S Lander13.   

Abstract

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.
Copyright © 2019 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  ancestors; descendants; development; iPSCs; optimal-transport; paracrine interactions; regulation; reprogramming; scRNA-seq; trajectories

Mesh:

Substances:

Year:  2019        PMID: 30712874      PMCID: PMC6402800          DOI: 10.1016/j.cell.2019.01.006

Source DB:  PubMed          Journal:  Cell        ISSN: 0092-8674            Impact factor:   41.582


  98 in total

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