Combining single-cell tracking and omics improves blood stem cell fate regulator identification
Author(s) -
Arne Wehling,
Dirk Loeffler,
Yang Zhang,
Tobías Kull,
Cinzia Donato,
Barbara M. Szczerba,
Germán Camargo Ortega,
Minkyoung Lee,
Andreas E. Moor,
Berthold Göttgens,
Nicola Aceto,
Timm Schroeder
Publication year - 2022
Publication title -
blood
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.515
H-Index - 465
eISSN - 1528-0020
pISSN - 0006-4971
DOI - 10.1182/blood.2022016880
Subject(s) - stem cell , biology , computational biology , computational fluid dynamics , cell division , pipeline (software) , identification (biology) , transcriptome , bioinformatics , genetics , computer science , cell , gene , physics , mechanics , programming language , gene expression , botany
Molecular programs initiating cell fate divergence (CFD) are difficult to identify. Current approaches usually compare cells long after CFD initiation, therefore missing molecular changes at its start. Ideally, single cells that differ in their CFD molecular program but are otherwise identical are compared early in CFD. This is possible in diverging sister cells, which were identical until their mother's division and thus differ mainly in CFD properties. In asymmetrically dividing cells, divergent daughter fates are prospectively committed during division, and diverging sisters can thus be identified at the start of CFD. Using asymmetrically dividing blood stem cells, we developed a pipeline (ie, trackSeq) for imaging, tracking, isolating, and transcriptome sequencing of single cells. Their identities, kinship, and histories are maintained throughout, massively improving molecular noise filtering and candidate identification. In addition to many identified blood stem CFD regulators, we offer here this pipeline for use in CFDs other than asymmetric division.
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