Deciphering Cell Fate Decision by Integrated Single-Cell Sequencing Analysis release_ecayod5czbaapoazv7mbbpaxf4

by Sagar, Dominic Grün

Published in Annual Review of Biomedical Data Science by Annual Reviews.

2020   Volume 3, p1-22

Abstract

Cellular differentiation is a common underlying feature of all multicellular organisms through which naïve cells progressively become fate restricted and develop into mature cells with specialized functions. A comprehensive understanding of the regulatory mechanisms of cell fate choices during development, regeneration, homeostasis, and disease is a central goal of modern biology. Ongoing rapid advances in single-cell biology are enabling the exploration of cell fate specification at unprecedented resolution. Here, we review single-cell RNA sequencing and sequencing of other modalities as methods to elucidate the molecular underpinnings of lineage specification. We specifically discuss how the computational tools available to reconstruct lineage trajectories, quantify cell fate bias, and perform dimensionality reduction for data visualization are providing new mechanistic insights into the process of cell fate decision. Studying cellular differentiation using single-cell genomic tools is paving the way for a detailed understanding of cellular behavior in health and disease. Expected final online publication date for the Annual Review of Biomedical Data Science, Volume 3 is July 20, 2020. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
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