Accessible chromatin is important for RNA polymerase II recruitment and transcription initiation at eukaryotic promoters. We investigated the mechanistic links between promoter DNA sequence, nucleosome positioning, and transcription. Our results indicate that positioning of the transcription start site-associated +1 nucleosome in yeast is critical for efficient TBP binding and is driven by two key factors, the essential chromatin remodeler RSC and a small set of ubiquitous general regulatory factors (GRFs). Our findings indicate that the strength and directionality of RSC action on promoter nucleosomes depends on the arrangement and proximity of two specific DNA motifs. This, together with the effect on nucleosome position observed in double depletion experiments, suggests that, despite their widespread co-localization, RSC and GRFs predominantly act through independent signals to generate accessible chromatin. Our results provide mechanistic insight into how the promoter DNA sequence instructs trans-acting factors to control nucleosome architecture and stimulate transcription initiation.

An important distinction is frequently made between constitutively expressed housekeeping genes versus regulated genes. Although generally characterized by different DNA elements, chromatin architecture and cofactors, it is not known to what degree promoter classes strictly follow regulatability rules and which molecular mechanisms dictate such differences. We show that SAGA‐dominated/TATA‐box promoters are more responsive to changes in the amount of activator, even compared to TFIID/TATA‐like promoters that depend on the same activator Hsf1. Regulatability is therefore an inherent property of promoter class. Further analyses show that SAGA/TATA‐box promoters are more dynamic because TATA‐binding protein recruitment through SAGA is susceptible to removal by Mot1. In addition, the nucleosome configuration upon activator depletion shifts on SAGA/TATA‐box promoters and seems less amenable to preinitiation complex formation. The results explain the fundamental difference between housekeeping and regulatable genes, revealing an additional facet of combinatorial control: an activator can elicit a different response dependent on core promoter class.

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.

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Summary Transcription factors are important regulators of cell fate and function. Knowledge about where transcription factors are bound in the genome is crucial for understanding their function. A common method to study protein-DNA interactions is chromatin immunoprecipitation (ChIP). Here, we present a revised ChIP protocol to determine protein-DNA interactions for the yeast Saccharomyces cerevisiae . We optimized several aspects of the procedure, including cross-linking and quenching, cell lysis, and immunoprecipitation steps. This protocol facilitates sensitive and reproducible quantitation of protein-DNA interactions. For complete details on the use and execution of this protocol, please refer to ( de Jonge et al., 2019 ).

Chromatin immunoprecipitation (ChIP) is a commonly used technique to investigate which parts of a genome are bound by a particular protein. The result of ChIP is often interpreted in a binary manner: bound or not bound. Due to this focus, ChIP protocols frequently lack the ability to quantitatively compare samples with each other, for example in a time series or under different growth conditions. Here, using the yeast S. cerevisiae transcription factors Cbf1, Abf1, Reb1, Mcm1 and Sum1, we optimized the five major steps of a commonly used ChIP protocol: cross-linking, quenching, cell lysis, fragmentation and immunoprecipitation. Quenching with glycine is inefficient and can lead to large degrees of variability, an issue that is resolved by using tris(hydroxymethyl)aminomethane (Tris). Another source of variability is degradation of the protein of interest during the procedure. Enzymatic cell lysis with zymolyase can lead to extensive protein degradation, which is greatly reduced by mechanical lysis through bead beating. Degradation also occurs during sonication of chromatin, affecting large proteins in particular. An optimal mix of protease inhibitors and cross-linking with a higher percentage of formaldehyde reduces the extent of this degradation. Finally we also show that the immunoprecipitation step itself can be greatly improved with magnetic beads and optimized incubation/washing steps. The study results in a highly optimized protocol, which is shorter, easier to perform and has a stronger, more reproducible signal with less background. This protocol is presented in detail. In addition, the results highlight the greatest sources of variability in many other protocols, showing which steps are important to focus on for reproducible and quantitatively comparable ChIP experiments.

Protein– DNA interactions are dynamic, and these dynamics are an important aspect of chromatin‐associated processes such as transcription or replication. Due to a lack of methods to study on‐ and off‐rates across entire genomes, protein– DNA interaction dynamics have not been studied extensively. Here, we determine in vivo off‐rates for the Saccharomyces cerevisiae chromatin organizing factor Abf1, at 191 sites simultaneously across the yeast genome. Average Abf1 residence times span a wide range, varying between 4.2 and 33 min. Sites with different off‐rates are associated with different functional characteristics. This includes their transcriptional dependency on Abf1, nucleosome positioning and the size of the nucleosome‐free region, as well as the ability to roadblock RNA polymerase II for termination. The results show how off‐rates contribute to transcription factor function and that DIVORSEQ (Determining In Vivo Off‐Rates by SEQ uencing) is a meaningful way of investigating protein– DNA binding dynamics genome‐wide.

Protein-DNA interactions are dynamic and these dynamics are an important aspect of chromatinassociated processes such as transcription or replication. Due to a lack of methods to study on-and off-rates across entire genomes, protein-DNA interaction dynamics have not been studied extensively. Here we determine in vivo off-rates for the Saccharomyces cerevisiae chromatin organising factor Abf1, at 191 sites simultaneously across the yeast genome. Average Abf1 residence times span a wide-range, varying between 4.5 and 37 minutes. Sites with different off-rates are associated with different functional characteristics. This includes their transcriptional dependency on Abf1, nucleosome positioning and the size of the nucleosome-free region, as well as the ability to roadblock RNA polymerase II for termination. The results show how off-rates contribute to transcription factor function and that DIVORSEQ (Determining In Vivo Off-Rates by SEQuencing) is a meaningful way of investigating protein-DNA binding dynamics genomewide.