DNA supercoiling restricts the transcriptional bursting of neighboring eukaryotic genes.

DNA supercoiling has emerged as a major contributor to gene regulation in bacteria, but how DNA supercoiling impacts transcription dynamics in eukaryotes is unclear. Here, using single-molecule dual-color nascent transcription imaging in budding yeast, we show that transcriptional bursting of divergent and tandem GAL genes is coupled. Temporal coupling of neighboring genes requires rapid release of DNA supercoils by topoisomerases. When DNA supercoils accumulate, transcription of one gene inhibits transcription at its adjacent genes. Transcription inhibition of the GAL genes results from destabilized binding of the transcription factor Gal4. Moreover, wild-type yeast minimizes supercoiling-mediated inhibition by maintaining sufficient levels of topoisomerases. Overall, we discover fundamental differences in transcriptional control by DNA supercoiling between bacteria and yeast and show that rapid supercoiling release in eukaryotes ensures proper gene expression of neighboring genes.

Transcription factor clusters enable target search but do not contribute to target gene activation.

Many transcription factors (TFs) localize in nuclear clusters of locally increased concentrations, but how TF clustering is regulated and how it influences gene expression is not well understood. Here, we use quantitative microscopy in living cells to study the regulation and function of clustering of the budding yeast TF Gal4 in its endogenous context. Our results show that Gal4 forms clusters that overlap with the GAL loci. Cluster number, density and size are regulated in different growth conditions by the Gal4-inhibitor Gal80 and Gal4 concentration. Gal4 truncation mutants reveal that Gal4 clustering is facilitated by, but does not completely depend on DNA binding and intrinsically disordered regions. Moreover, we discover that clustering acts as a double-edged sword: self-interactions aid TF recruitment to target genes, but recruited Gal4 molecules that are not DNA-bound do not contribute to, and may even inhibit, transcription activation. We propose that cells need to balance the different effects of TF clustering on target search and transcription activation to facilitate proper gene expression.

Quantifying how post-transcriptional noise and gene copy number variation bias transcriptional parameter inference from mRNA distributions.

Transcriptional rates are often estimated by fitting the distribution of mature mRNA numbers measured using smFISH (single molecule fluorescence in situ hybridization) with the distribution predicted by the telegraph model of gene expression, which defines two promoter states of activity and inactivity. However, fluctuations in mature mRNA numbers are strongly affected by processes downstream of transcription. In addition, the telegraph model assumes one gene copy but in experiments, cells may have two gene copies as cells replicate their genome during the cell cycle. While it is often presumed that post-transcriptional noise and gene copy number variation affect transcriptional parameter estimation, the size of the error introduced remains unclear. To address this issue, here we measure both mature and nascent mRNA distributions of GAL10 in yeast cells using smFISH and classify each cell according to its cell cycle phase. We infer transcriptional parameters from mature and nascent mRNA distributions, with and without accounting for cell cycle phase and compare the results to live-cell transcription measurements of the same gene. We find that: (i) correcting for cell cycle dynamics decreases the promoter switching rates and the initiation rate, and increases the fraction of time spent in the active state, as well as the burst size; (ii) additional correction for post-transcriptional noise leads to further increases in the burst size and to a large reduction in the errors in parameter estimation. Furthermore, we outline how to correctly adjust for measurement noise in smFISH due to uncertainty in transcription site localisation when introns cannot be labelled. Simulations with parameters estimated from nascent smFISH data, which is corrected for cell cycle phases and measurement noise, leads to autocorrelation functions that agree with those obtained from live-cell imaging.

Following the tracks: How transcription factor binding dynamics control transcription.

Transcription, the process of copying genetic information from DNA to messenger RNA, is regulated by sequence-specific DNA-binding proteins known as transcription factors (TFs). Recent advances in single-molecule tracking (SMT) technologies have enabled visualization of individual TF molecules as they diffuse and interact with the DNA in the context of living cells. These SMT studies have uncovered multiple populations of DNA-binding events characterized by their distinctive DNA residence times. In this perspective, we review recent insights into how these residence times relate to specific and non-specific DNA binding, as well as the contribution of TF domains on the DNA-binding dynamics. We discuss different models that aim to link transient DNA binding by TFs to bursts of transcription and present an outlook for how future advances in microscopy development may broaden our understanding of the dynamics of the molecular steps that underlie transcription activation.

The Hda1 histone deacetylase limits divergent non-coding transcription and restricts transcription initiation frequency.

Nucleosome-depleted regions (NDRs) at gene promoters support initiation of RNA polymerase II transcription. Interestingly, transcription often initiates in both directions, resulting in an mRNA and a divergent non-coding (DNC) transcript of unclear purpose. Here, we characterized the genetic architecture and molecular mechanism of DNC transcription in budding yeast. Using high-throughput reverse genetic screens based on quantitative single-cell fluorescence measurements, we identified the Hda1 histone deacetylase complex (Hda1C) as a repressor of DNC transcription. Nascent transcription profiling showed a genome-wide role of Hda1C in repression of DNC transcription. Live-cell imaging of transcription revealed that mutations in the Hda3 subunit increased the frequency of DNC transcription. Hda1C contributed to decreased acetylation of histone H3 in DNC transcription regions, supporting DNC transcription repression by histone deacetylation. Our data support the interpretation that DNC transcription results as a consequence of the NDR-based architecture of eukaryotic promoters, but that it is governed by locus-specific repression to maintain genome fidelity.

Optimized protocol for single-molecule RNA FISH to visualize gene expression in S. cerevisiae.

Single-molecule RNA fluorescence in situ hybridization (smFISH) allows subcellular visualization, localization, and quantification of endogenous RNA molecules in fixed cells. The spatial and intensity information of each RNA can be used to distinguish mature from nascent transcripts inside each cell, revealing both past and instantaneous transcriptional activity. Here, we describe an optimized protocol for smFISH in Saccharomyces cerevisiae with optimized lyticase digestion time and hybrization steps for more homogenous results. For complete details on the use and execution of this protocol, please refer to Donovan et al. (2019).

Live-cell imaging reveals the interplay between transcription factors, nucleosomes, and bursting.

Transcription factors show rapid and reversible binding to chromatin in living cells, and transcription occurs in sporadic bursts, but how these phenomena are related is unknown. Using a combination of in vitro and in vivo single-molecule imaging approaches, we directly correlated binding of the Gal4 transcription factor with the transcriptional bursting kinetics of the Gal4 target genes GAL3 and GAL10 in living yeast cells. We find that Gal4 dwell time sets the transcriptional burst size. Gal4 dwell time depends on the affinity of the binding site and is reduced by orders of magnitude by nucleosomes. Using a novel imaging platform called orbital tracking, we simultaneously tracked transcription factor binding and transcription at one locus, revealing the timing and correlation between Gal4 binding and transcription. Collectively, our data support a model in which multiple RNA polymerases initiate transcription during one burst as long as the transcription factor is bound to DNA, and bursts terminate upon transcription factor dissociation.