Combining single-cell tracking and omics improves blood stem cell fate regulator identification

Area of Science:

• Developmental Biology
• Stem Cell Biology
• Genomics

Background:

• Identifying molecular programs that initiate cell fate divergence (CFD) is difficult.
• Current methods often analyze cells too late in the process, missing early molecular changes.
• Comparing identical sister cells early in divergence is ideal for studying CFD.

Purpose of the Study:

• To develop a method for identifying molecular programs at the onset of cell fate divergence.
• To apply this method to asymmetrically dividing blood stem cells to find CFD regulators.
• To provide a versatile pipeline for studying CFD in various biological contexts.

Main Methods:

• Developed a pipeline (trackSeq) for imaging, tracking, isolating, and transcriptome sequencing of single cells.
• Utilized asymmetrically dividing blood stem cells to identify diverging sister cells at the start of CFD.
• Maintained cell identity, kinship, and history throughout the process for improved data analysis.

Main Results:

• Successfully identified numerous regulators of cell fate divergence in blood stem cells.
• The trackSeq pipeline enabled improved molecular noise filtering and candidate identification.
• Demonstrated the utility of trackSeq for studying CFD beyond asymmetric cell division.

Conclusions:

• The trackSeq pipeline provides a novel approach to study the molecular basis of cell fate divergence.
• This method allows for the early identification of CFD regulators by analyzing diverging sister cells.
• The developed pipeline is adaptable for investigating cell fate divergence in diverse biological systems.