With the advent of single cell transcriptomics, many unanticipated cell biological phenomena have been discovered including, new classes of RNA, cytoplasmic RNA splicing, the dearth of cell specific gene expression and perhaps most surprisingly the discovery of vast cell-to-cell variation in transcription even in presumptively identical cells. These data have led to our hypothesis that there is a many-to-one relationship between transcriptome states and a cell’s phenotype. In this relationship the functional molecular ratios of the RNA are determined by the cell systems’ stoichiometric constraints, which underdetermine the transcriptome state. Because a broad set of multi-genic combinations support a particular phenotype, changes in the transcriptome state do not necessarily lead to changes in the phenotype. By analogy cellular phenotype should not be defined based upon the expression of individual RNAs but rather as dynamical changes in subsets of RNAs comprising selected RNA systems where the system-associated RNAs are balanced with each other to produce the associated cellular function. In this presentation data to support this idea will be presented using as a source of material live mouse and human cells, fixed tissue analysis and subcellular regional analysis. This idea provides a framework for understanding cellular heterogeneity in phenotypic response to various stimuli and provides a means for rethinking how to manipulate cellular responses so that desired outcomes are obtained including identification of molecules showing therapeutic efficacy.

Transcriptome variability and theories of phenotype – Multimodal subcellular genomics

256th National Meeting (2018)

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