PT  - JOURNAL ARTICLE
AU  - Sydney M. Shaffer
AU  - Benjamin L. Emert
AU  - Raul Reyes-Hueros
AU  - Christopher Coté
AU  - Guillaume Harmange
AU  - Ann E. Sizemore
AU  - Rohit Gupte
AU  - Eduardo Torre
AU  - Abhyudai Singh
AU  - Danielle S. Bassett
AU  - Arjun Raj
TI  - Memory sequencing reveals heritable single cell gene expression programs associated with distinct cellular behaviors
AID  - 10.1101/379016
DP  - 2019 Jan 01
TA  - bioRxiv
PG  - 379016
4099  - http://biorxiv.org/content/early/2019/12/21/379016.short
4100  - http://biorxiv.org/content/early/2019/12/21/379016.full
AB  - Non-genetic factors can cause individual cells to fluctuate substantially in gene expression levels over time. Yet it remains unclear whether these fluctuations can persist for much longer than the time of one cell division. Current methods for measuring gene expression in single cells mostly rely on single time point measurements, making the duration of gene expression fluctuations or cellular memory difficult to measure. Here, we report a method combining Luria and Delbrück’s fluctuation analysis with population-based RNA sequencing (MemorySeq) for identifying genes transcriptome-wide whose fluctuations persist for several cell divisions. MemorySeq revealed multiple gene modules that are expressed together in rare cells within otherwise homogeneous clonal populations. Further, we found that these rare cell subpopulations are associated with biologically distinct behaviors, such as the ability to proliferate in the face of anti-cancer therapeutics, in different cancer cell lines. The identification of non-genetic, multigenerational fluctuations has the potential to reveal new forms of biological memory at the level of single cells and suggests that non-genetic heritability of cellular state may be a quantitative property.