Automated cell cycle and cell size measurements for single-cell gene expression studies

Area of Science:

• Genomics
• Cell Biology
• Molecular Biology

Background:

• Single-cell studies highlight cell-to-cell variability in gene expression.
• Heterogeneity in cell proliferation states is a significant source of this variation.
• Understanding these factors is crucial for transcriptomic analysis.

Purpose of the Study:

• To develop a universal, automatic, and toxic-free labeling method for single-cell high-throughput RT-qPCR.
• To investigate the influence of cell cycle and cell size on gene expression variability at the single-cell level.
• To enable unbiased gene expression analysis and improve single-cell tracking.

Main Methods:

• Cells were double-stained and isolated.
• Morphological parameters were analyzed.
• Transcriptomic analysis was performed on the same identified cells.
• The method is compatible with single-cell high-throughput RT-qPCR.

Main Results:

• The developed method allows for unbiased gene expression analysis.
• It can enhance single-cell tracking and imaging when combined with cell isolation.
• Cell-to-cell variability in chicken erythroid progenitors was found to be negligibly influenced by cell size or cell cycle.

Conclusions:

• The novel toxic-free labeling method provides a robust approach for single-cell transcriptomic analysis.
• Cell size and cell cycle have minimal impact on gene expression variability in chicken erythroid progenitors.
• This technique has broad applications in cell biology research and single-cell analysis.