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Recording development with single cell dynamic lineage tracing
Author(s) -
Aaron McKenna,
James A. Gag
Publication year - 2019
Publication title -
development
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.754
H-Index - 325
eISSN - 1477-9129
pISSN - 0950-1991
DOI - 10.1242/dev.169730
Subject(s) - biology , tracing , lineage (genetic) , cell lineage , evolutionary biology , computational biology , genetics , cellular differentiation , gene , computer science , operating system
Every animal grows from a single fertilized egg into an intricate network of cell types and organ systems. This process is captured in a lineage tree: a diagram of every cell's ancestry back to the founding zygote. Biologists have long sought to trace this cell lineage tree in individual organisms and have developed a variety of technologies to map the progeny of specific cells. However, there are billions to trillions of cells in complex organisms, and conventional approaches can only map a limited number of clonal populations per experiment. A new generation of tools that use molecular recording methods integrated with single cell profiling technologies may provide a solution. Here, we summarize recent breakthroughs in these technologies, outline experimental and computational challenges, and discuss biological questions that can be addressed using single cell dynamic lineage tracing.

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