Lineage tracing on transcriptional landscapes links state to fate during differentiation
Author(s) -
Caleb Weinreb,
Alejo Rodriguez-Fraticelli,
Fernando D. Camargo,
Allon M. Klein
Publication year - 2020
Publication title -
science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 12.556
H-Index - 1186
eISSN - 1095-9203
pISSN - 0036-8075
DOI - 10.1126/science.aaw3381
Subject(s) - biology , cell fate determination , cellular differentiation , embryonic stem cell , haematopoiesis , stem cell , progenitor cell , gene , lineage (genetic) , cell type , microbiology and biotechnology , cell , computational biology , genetics , evolutionary biology , transcription factor
Mapping cell fate during hematopoiesis Biologists have long attempted to understand how stem and progenitor cells in regenerating and embryonic tissues differentiate into mature cell types. Through the use of recent technical advances to sequence the genes expressed in thousands of individual cells, differentiation mechanisms are being revealed. Weinrebet al. extended these methods to track clones of cells (cell families) across time. Their approach reveals differences in cellular gene expression as cells progress through hematopoiesis, which is the process of blood production. Using machine learning, they tested how well gene expression measurements account for the choices that cells make. This work reveals that a considerable gap still exists in understanding differentiation mechanisms, and future methods are needed to fully understand—and ultimately control—cell differentiation.Science , this issue p.eaaw3381
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