TY - JOUR T1 - Automated cell cycle and cell size measurements for single-cell gene expression studies JF - bioRxiv DO - 10.1101/182766 SP - 182766 AU - Anissa Guillemin AU - Angelique Richard AU - Sandrine Gonin-Giraud AU - Olivier Gandrillon Y1 - 2017/01/01 UR - http://biorxiv.org/content/early/2017/08/31/182766.abstract N2 - Recent rise of single-cell studies revealed the importance of understanding the role of cell-to-cell variability, especially at the transcriptomic level. One of the numerous sources of cell-to-cell variation in gene expression is the heterogeneity in cell proliferation state. How cell cycle and cell size influences gene expression variability at single-cell level is not yet clearly understood. To deconvolute such influences, most of the single-cell studies used dedicated methods that could include some bias. Here, we provide a universal and automatic toxic-free label method, compatible with single-cell high-throughput RT-qPCR. This led to an unbiased gene expression analysis and could be also used for improving single-cell tracking and imaging when combined with cell isolation. As an application for this technique, we showed that cell-to-cell variability in chicken erythroid progenitors was negligibly influenced by cell size nor cell cycle. ER -