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.
Main text:Cellular memory in biology, meaning the persistence of a cellular or organismal state over time, occurs over a wide range of timescales and can be produced by a variety of mechanisms. Genetic differences are one form of memory (Ben-David et al., 2018) , encoding variation between organisms on multi-generational timescales. Within an organism, mechanisms involving the regulation of gene expression encode the differences between cell types in different tissues, with cells retaining memory of their state over a large number of cell divisions (Bonasio et al., 2010) . In contrast, recent measurements suggest that the expression of many genes in single cells may have very little memory, displaying highly transient fluctuations in transcription. These rapid fluctuations have been referred to as gene expression "noise" and have generally been difficult to associate with physiological distinctions between single cells