Variation is function: Are single cell differences functionally important?

Abstract

There is a growing appreciation of the extent of transcriptome variation across individual cells of the same cell type. While expression variation may be a byproduct of, for example, dynamic or homeostatic processes, here we consider whether single‐cell molecular variation per se might be crucial for population‐level function. Under this hypothesis, molecular variation indicates a diversity of hidden functional capacities within an ensemble of “identical” cells, and this functional diversity facilitates collective behavior that would be inaccessible to a homogenous population. In reviewing this topic, we explore possible functions that might be carried by a heterogeneous ensemble of cells; however, this question has proven difficult to test, both because methods to manipulate molecular variation are limited and because it is complicated to define, and measure, population‐level function. We consider several possible methods to further pursue the hypothesis that “variation is function” through the use of comparative analysis and novel experimental techniques.

Variation in Activity State, Axonal Projection, and Position Define the Transcriptional Identity of Individual Neocortical Projection Neurons

“…Our results indicate not only that the gene expression profiles of cortical neurons reflect specific functional features of these cells but that cell-to-cell variation across individual neurons itself is a principal feature of subtype identity (Dueck et al, 2016). Subtype 2 L6CThNs were more transcriptionally heterogeneous than subtype 1 neurons under steady-state conditions in part because of baseline differences in gene expression associated with neural activity.…”

“…Cortical neurons are also highly dynamic, exhibiting, for example, activity-dependent changes in gene expression (Flavell and Greenberg, 2008; Lyons and West, 2011; West and Greenberg, 2011). Although recent studies have yielded insights into the diversity of cortical cell types (Darmanis et al, 2015; Hevner et al, 2003; Lake et al, 2016; Pollen et al, 2014; Sorensen et al, 2015; Sugino et al, 2006; Tasic et al, 2016; Zeisel et al, 2015), the sources of transcriptional variation both within and across cell types remain poorly understood (Dueck et al, 2016; Sanes and Masland, 2015; Wagner et al, 2016; Zeng and Sanes, 2017). …”

Cell cycle proliferation decisions: the impact of single cell analyses

“…Additional cell cycle variation could be a consequence of cell division itself. Although DNA is actively distributed equally to daughter cells, RNA, proteins, metabolites, and organelles may be randomly and unequally distributed at every cell division . For example, Czerniak et al .…”

Epigenetic and Transcriptional Variability Shape Phenotypic Plasticity

“…[3,4] Also, it is thought to be required for population robustness and higher-level function of multi-cellular organisms. [5] For example, variability in a population of cells allows essentially binary decisions, such as undergoing cell death, to turn into more flexible and fine-tuned responses at the level of the cell population as a whole. This creates an adaptive advantage and provides benefits in survival.…”