Effect of promoter architecture on the cell-to-cell variability in gene expression

According to recent experimental evidence, the architecture of a promoter, defined as the number, strength and regulatory role of the operators that control the promoter, plays a major role in determining the level of cell-to-cell variability in gene expression. These quantitative experiments call for a corresponding modeling effort that addresses the question of how changes in promoter architecture affect noise in gene expression in a systematic rather than case-by-case fashion. In this article, we make such a systematic investigation, based on a simple microscopic model of gene regulation that incorporates stochastic effects. In particular, we show how operator strength and operator multiplicity affect this variability. We examine different modes of transcription factor binding to complex promoters (cooperative, independent, simultaneous) and how each of these affects the level of variability in transcription product from cell-to-cell. We propose that direct comparison between in vivo single-cell experiments and theoretical predictions for the moments of the probability distribution of mRNA number per cell can discriminate between different kinetic models of gene regulation.Comment: 35 pages, 6 figures, Submitte

Stochastic Modeling for the Expression of a Gene Regulated by Competing Transcription Factors

It is widely accepted that gene expression regulation is a stochastic event. The common approach for its computer simulation requires detailed information on the interactions of individual molecules, which is often not available for the analyses of biological experiments. As an alternative approach, we employed a more intuitive model to simulate the experimental result, the Markov-chain model, in which a gene is regulated by activators and repressors, which bind the same site in a mutually exclusive manner. Our stochastic simulation in the presence of both activators and repressors predicted a Hill-coefficient of the dose-response curve closer to the experimentally observed value than the calculated value based on the simple additive effects of activators alone and repressors alone. The simulation also reproduced the heterogeneity of gene expression levels among individual cells observed by Fluorescence Activated Cell Sorting analysis. Therefore, our approach may help to apply stochastic simulations to broader experimental data

Dynamic Chromatin Organization during Foregut Development Mediated by the Organ Selector Gene PHA-4/FoxA

Central regulators of cell fate, or selector genes, establish the identity of cells by direct regulation of large cohorts of genes. In Caenorhabditis elegans, foregut (or pharynx) identity relies on the FoxA transcription factor PHA-4, which activates different sets of target genes at various times and in diverse cellular environments. An outstanding question is how PHA-4 distinguishes between target genes for appropriate transcriptional control. We have used the Nuclear Spot Assay and GFP reporters to examine PHA-4 interactions with target promoters in living embryos and with single cell resolution. While PHA-4 was found throughout the digestive tract, binding and activation of pharyngeally expressed promoters was restricted to a subset of pharyngeal cells and excluded from the intestine. An RNAi screen of candidate nuclear factors identified emerin (emr-1) as a negative regulator of PHA-4 binding within the pharynx, but emr-1 did not modulate PHA-4 binding in the intestine. Upon promoter association, PHA-4 induced large-scale chromatin de-compaction, which, we hypothesize, may facilitate promoter access and productive transcription. Our results reveal two tiers of PHA-4 regulation. PHA-4 binding is prohibited in intestinal cells, preventing target gene expression in that organ. PHA-4 binding within the pharynx is limited by the nuclear lamina component EMR-1/emerin. The data suggest that association of PHA-4 with its targets is a regulated step that contributes to promoter selectivity during organ formation. We speculate that global re-organization of chromatin architecture upon PHA-4 binding promotes competence of pharyngeal gene transcription and, by extension, foregut development

Population differentiation in the banana leaf spot pathogen Mycosphaerella musicola, examined at a global scale

Single-copy restriction fragment length polymorphism (RFLP) markers were used to determine the genetic structure of the global population of Mycosphaerella musicola, the cause of Sigatoka (yellow Sigatoka) disease of banana. The isolates of M. musicola examined were grouped into four geographic populations representing Africa, Latin America and the Caribbean, Australia and Indonesia. Moderate levels of genetic diversity were observed for most of the populations (H = 0.22-0.44). The greatest genetic diversity was found in the Indonesian population (H = 0.44). Genotypic diversity was close to 50% in all populations. Population differentiation tests showed that the geographic populations of Africa, Latin America and the Caribbean, Australia and Indonesia were genetically different populations. Using F-ST tests, very high levels of genetic differentiation were detected between all the population pairs (F-ST > 0.40), with the exception of the Africa and Latin America-Caribbean population pair. These two populations differed by only 3% (F-ST = 0.03), and were significantly different (P < 0.05) from all other population pairs. The high level of genetic diversity detected in Indonesia in comparison to the other populations provides some support for the theory that M. musicola originated in South-east Asia and that M. musicola populations in other regions were founded by isolates from the South-east Asian region. The results also suggest the migration of M. musicola between Africa and the Latin America-Caribbean region