Exploring transcription regulation through cell-to-cell variability

• Published in: Proceedings of the National Academy of Sciences - PNAS Vol. 108; no. 15; pp. 6329 - 6334
• Main Authors: Rinott, Ruty, Jaimovich, Ariel, Friedman, Nir
• Format: Journal Article
• Language: English
• Published: United States National Academy of Sciences 12.04.2011; National Acad Sciences
• Subjects: Biochemistry; Biological Sciences; Chromatin; Datasets; Deoxyribonucleic acid; DNA; Flow Cytometry; fluorescence; Gene Deletion; Gene expression; Gene Expression Regulation, Fungal; Genes; Genetic screening; Genetic Variation; Genotype & phenotype; Luminescent Proteins - biosynthesis; Luminescent Proteins - genetics; Morphology; Phenotype; Phenotypes; Promoter Regions, Genetic; Protein Biosynthesis - genetics; Protein synthesis; Proteins; Red Fluorescent Protein; Ribonucleases - genetics; Ribonucleases - metabolism; RNA; RNA, Transfer - metabolism; Saccharomyces cerevisiae; Saccharomyces cerevisiae - cytology; Saccharomyces cerevisiae - genetics; Saccharomyces cerevisiae - metabolism; Saccharomyces cerevisiae Proteins - genetics; Saccharomyces cerevisiae Proteins - metabolism; Statistical variance; transcription (genetics); Transcription, Genetic; Transcriptional regulatory elements; Transfer RNA; transport proteins; Yeast
• ISSN: 0027-8424; 1091-6490
• DOI: 10.1073/pnas.1013148108

The regulation of cellular protein levels is a complex process involving many regulatory mechanisms, each introducing stochastic events, leading to variability of protein levels between isogenic cells. Previous studies have shown that perturbing genes involved in transcription regulation affects the amount of cell-to-cell variability in protein levels, but to date there has been no systematic characterization of variability in expression as a phenotype. In this research, we use single-cell expression levels of two fluorescent reporters driven by two different promoters under a wide range of genetic perturbations in Saccharomyces cerevisiae, to identify proteins that affect variability in the expression of these reporters. We introduce computational methodology to determine the variability caused by each perturbation and distinguish between global variability, which affects both reporters in a coordinated manner (e.g., due to cell size variability), and local variability, which affects the individual reporters independently (e.g., due to stochastic events in transcription initiation). Classifying genes by their variability phenotype (the effect of their deletion on reporter variability) identifies functionally coherent groups, which broadly correlate with the different stages of transcriptional regulation. Specifically, we find that most processes whose perturbation affects global variability are related to protein synthesis, protein transport, and cell morphology, whereas most processes whose perturbations affect local variability are related to DNA maintenance, chromatin regulation, and RNA synthesis. Moreover, we demonstrate that the variability phenotypes of different protein complexes provide insights into their cellular functions. Our results establish the utility of variability phenotype for dissecting the regulatory mechanisms involved in gene expression.