Genome-wide determinants of sequence-specific DNA binding of general regulatory factors

MCM2-7 loading-dependent ORC release ensures genome-wide origin licensing

Origin recognition complex (ORC)-dependent loading of the replicative helicase MCM2-7 onto replication origins in G1-phase forms the basis of replication fork establishment in S-phase. However, how ORC and MCM2-7 facilitate genome-wide DNA licensing is not fully understood. Mapping the molecular footprints of budding yeast ORC and MCM2-7 genome-wide, we discovered that MCM2-7 loading is associated with ORC release from origins and redistribution to non-origin sites. Our bioinformatic analysis revealed that origins are compact units, where a single MCM2-7 double hexamer blocks repetitive loading through steric ORC binding site occlusion. Analyses of A-elements and an improved B2-element consensus motif uncovered that DNA shape, DNA flexibility, and the correct, face-to-face spacing of the two DNA elements are hallmarks of ORC-binding and efficient helicase loading sites. Thus, our work identified fundamental principles for MCM2-7 helicase loading that explain how origin licensing is realised across the genome.

General regulatory factors exert differential effects on nucleosome sliding activity of the ISW1a complex

BACKGROUND

Chromatin dynamics is deeply involved in processes that require access to DNA, such as transcriptional regulation. Among the factors involved in chromatin dynamics at gene regulatory regions are general regulatory factors (GRFs). These factors contribute to establishment and maintenance of nucleosome-depleted regions (NDRs). These regions are populated by nucleosomes through histone deposition and nucleosome sliding, the latter catalyzed by a number of ATP-dependent chromatin remodeling complexes, including ISW1a. It has been observed that GRFs can act as barriers against nucleosome sliding towards NDRs. However, the relative ability of the different GRFs to hinder sliding activity is currently unknown.

RESULTS

Considering this, we performed a comparative analysis for the main GRFs, with focus in their ability to modulate nucleosome sliding mediated by ISW1a. Among the GRFs tested in nucleosome remodeling assays, Rap1 was the only factor displaying the ability to hinder the activity of ISW1a. This effect requires location of the Rap1 cognate sequence on linker that becomes entry DNA in the nucleosome remodeling process. In addition, Rap1 was able to hinder nucleosome assembly in octamer transfer assays. Concurrently, Rap1 displayed the highest affinity for and longest dwell time from its target sequence, compared to the other GRFs tested. Consistently, through bioinformatics analyses of publicly available genome-wide data, we found that nucleosome occupancy and histone deposition in vivo are inversely correlated with the affinity of Rap1 for its target sequences in the genome.

CONCLUSIONS

Our findings point to DNA binding affinity, residence time and location at particular translational positions relative to the nucleosome core as the key features of GRFs underlying their roles played in nucleosome sliding and assembly.

Species-aware DNA language models capture regulatory elements and their evolution

BACKGROUND

The rise of large-scale multi-species genome sequencing projects promises to shed new light on how genomes encode gene regulatory instructions. To this end, new algorithms are needed that can leverage conservation to capture regulatory elements while accounting for their evolution.

RESULTS

Here, we introduce species-aware DNA language models, which we trained on more than 800 species spanning over 500 million years of evolution. Investigating their ability to predict masked nucleotides from context, we show that DNA language models distinguish transcription factor and RNA-binding protein motifs from background non-coding sequence. Owing to their flexibility, DNA language models capture conserved regulatory elements over much further evolutionary distances than sequence alignment would allow. Remarkably, DNA language models reconstruct motif instances bound in vivo better than unbound ones and account for the evolution of motif sequences and their positional constraints, showing that these models capture functional high-order sequence and evolutionary context. We further show that species-aware training yields improved sequence representations for endogenous and MPRA-based gene expression prediction, as well as motif discovery.

CONCLUSIONS

Collectively, these results demonstrate that species-aware DNA language models are a powerful, flexible, and scalable tool to integrate information from large compendia of highly diverged genomes.

The arginine methyltransferase Prmt1 coordinates the germline arginine methylome essential for spermatogonial homeostasis and male fertility

Arginine methylation, catalyzed by the protein arginine methyltransferases (PRMTs), is a common post-translational protein modification (PTM) that is engaged in a plethora of biological events. However, little is known about how the methylarginine-directed signaling functions in germline development. In this study, we discover that Prmt1 is predominantly distributed in the nuclei of spermatogonia but weakly in the spermatocytes throughout mouse spermatogenesis. By exploiting a combination of three Cre-mediated Prmt1 knockout mouse lines, we unravel that Prmt1 is essential for spermatogonial establishment and maintenance, and that Prmt1-catalyzed asymmetric methylarginine coordinates inherent transcriptional homeostasis within spermatogonial cells. In conjunction with high-throughput CUT&Tag profiling and modified mini-bulk Smart-seq2 analyses, we unveil that the Prmt1-deposited H4R3me2a mark is permissively enriched at promoter and exon/intron regions, and sculpts a distinctive transcriptomic landscape as well as the alternative splicing pattern, in the mouse spermatogonia. Collectively, our study provides the genetic and mechanistic evidence that connects the Prmt1-deposited methylarginine signaling to the establishment and maintenance of a high-fidelity transcriptomic identity in orchestrating spermatogonial development in the mammalian germline.

De novo distillation of thermodynamic affinity from deep learning regulatory sequence models of in vivo protein-DNA binding

Transcription factors (TF) are proteins that bind DNA in a sequence-specific manner to regulate gene transcription. Despite their unique intrinsic sequence preferences, in vivo genomic occupancy profiles of TFs differ across cellular contexts. Hence, deciphering the sequence determinants of TF binding, both intrinsic and context-specific, is essential to understand gene regulation and the impact of regulatory, non-coding genetic variation. Biophysical models trained on in vitro TF binding assays can estimate intrinsic affinity landscapes and predict occupancy based on TF concentration and affinity. However, these models cannot adequately explain context-specific, in vivo binding profiles. Conversely, deep learning models, trained on in vivo TF binding assays, effectively predict and explain genomic occupancy profiles as a function of complex regulatory sequence syntax, albeit without a clear biophysical interpretation. To reconcile these complementary models of in vitro and in vivo TF binding, we developed Affinity Distillation (AD), a method that extracts thermodynamic affinities de-novo from deep learning models of TF chromatin immunoprecipitation (ChIP) experiments by marginalizing away the influence of genomic sequence context. Applied to neural networks modeling diverse classes of yeast and mammalian TFs, AD predicts energetic impacts of sequence variation within and surrounding motifs on TF binding as measured by diverse in vitro assays with superior dynamic range and accuracy compared to motif-based methods. Furthermore, AD can accurately discern affinities of TF paralogs. Our results highlight thermodynamic affinity as a key determinant of in vivo binding, suggest that deep learning models of in vivo binding implicitly learn high-resolution affinity landscapes, and show that these affinities can be successfully distilled using AD. This new biophysical interpretation of deep learning models enables high-throughput in silico experiments to explore the influence of sequence context and variation on both intrinsic affinity and in vivo occupancy.

Basic helix-loop-helix pioneer factors interact with the histone octamer to invade nucleosomes and generate nucleosome-depleted regions

Nucleosomes drastically limit transcription factor (TF) occupancy, while pioneer transcription factors (PFs) somehow circumvent this nucleosome barrier. In this study, we compare nucleosome binding of two conserved S. cerevisiae basic helix-loop-helix (bHLH) TFs, Cbf1 and Pho4. A cryo-EM structure of Cbf1 in complex with the nucleosome reveals that the Cbf1 HLH region can electrostatically interact with exposed histone residues within a partially unwrapped nucleosome. Single-molecule fluorescence studies show that the Cbf1 HLH region facilitates efficient nucleosome invasion by slowing its dissociation rate relative to DNA through interactions with histones, whereas the Pho4 HLH region does not. In vivo studies show that this enhanced binding provided by the Cbf1 HLH region enables nucleosome invasion and ensuing repositioning. These structural, single-molecule, and in vivo studies reveal the mechanistic basis of dissociation rate compensation by PFs and how this translates to facilitating chromatin opening inside cells.

DNAffinity: a machine-learning approach to predict DNA binding affinities of transcription factors

We present a physics-based machine learning approach to predict in vitro transcription factor binding affinities from structural and mechanical DNA properties directly derived from atomistic molecular dynamics simulations. The method is able to predict affinities obtained with techniques as different as uPBM, gcPBM and HT-SELEX with an excellent performance, much better than existing algorithms. Due to its nature, the method can be extended to epigenetic variants, mismatches, mutations, or any non-coding nucleobases. When complemented with chromatin structure information, our in vitro trained method provides also good estimates of in vivo binding sites in yeast.

Predicting which genes will respond to transcription factor perturbations

The ability to predict which genes will respond to the perturbation of a transcription factor serves as a benchmark for our systems-level understanding of transcriptional regulatory networks. In previous work, machine learning models have been trained to predict static gene expression levels in a biological sample by using data from the same or similar samples, including data on their transcription factor binding locations, histone marks, or DNA sequence. We report on a different challenge-training machine learning models to predict which genes will respond to the perturbation of a transcription factor without using any data from the perturbed cells. We find that existing transcription factor location data (ChIP-seq) from human cells have very little detectable utility for predicting which genes will respond to perturbation of a transcription factor. Features of genes, including their preperturbation expression level and expression variation, are very useful for predicting responses to perturbation of any transcription factor. This shows that some genes are poised to respond to transcription factor perturbations and others are resistant, shedding light on why it has been so difficult to predict responses from binding locations. Certain histone marks, including H3K4me1 and H3K4me3, have some predictive power when located downstream of the transcription start site. However, the predictive power of histone marks is much less than that of gene expression level and expression variation. Sequence-based or epigenetic properties of genes strongly influence their tendency to respond to direct transcription factor perturbations, partially explaining the oft-noted difficulty of predicting responsiveness from transcription factor binding location data. These molecular features are largely reflected in and summarized by the gene's expression level and expression variation. Code is available at https://github.com/BrentLab/TFPertRespExplainer.

Evolution of transcription factor binding through sequence variations and turnover of binding sites

Variations in noncoding regulatory sequences play a central role in evolution. Interpreting such variations, however, remains difficult even in the context of defined attributes such as transcription factor (TF) binding sites. Here, we systematically link variations in cis-regulatory sequences to TF binding by profiling the allele-specific binding of 27 TFs expressed in a yeast hybrid, in which two related genomes are present within the same nucleus. TFs localize preferentially to sites containing their known consensus motifs but occupy only a small fraction of the motif-containing sites available within the genomes. Differential binding of TFs to the orthologous alleles was well explained by variations that alter motif sequence, whereas differences in chromatin accessibility between alleles were of little apparent effect. Motif variations that abolished binding when present in only one allele were still bound when present in both alleles, suggesting evolutionary compensation, with a potential role for sequence conservation at the motif's vicinity. At the level of the full promoter, we identify cases of binding-site turnover, in which binding sites are reciprocally gained and lost, yet most interspecific differences remained uncompensated. Our results show the flexibility of TFs to bind imprecise motifs and the fast evolution of TF binding sites between related species.

DNA Double Strand Break Repair and Its Control by Nucleosome Remodeling

DNA double strand breaks (DSBs) are repaired in eukaryotes by one of several cellular mechanisms. The decision-making process controlling DSB repair takes place at the step of DNA end resection, the nucleolytic processing of DNA ends, which generates single-stranded DNA overhangs. Dependent on the length of the overhang, a corresponding DSB repair mechanism is engaged. Interestingly, nucleosomes-the fundamental unit of chromatin-influence the activity of resection nucleases and nucleosome remodelers have emerged as key regulators of DSB repair. Nucleosome remodelers share a common enzymatic mechanism, but for global genome organization specific remodelers have been shown to exert distinct activities. Specifically, different remodelers have been found to slide and evict, position or edit nucleosomes. It is an open question whether the same remodelers exert the same function also in the context of DSBs. Here, we will review recent advances in our understanding of nucleosome remodelers at DSBs: to what extent nucleosome sliding, eviction, positioning and editing can be observed at DSBs and how these activities affect the DSB repair decision.

Cytomegalovirus late transcription factor target sequence diversity orchestrates viral early to late transcription

Beta- and gammaherpesviruses late transcription factors (LTFs) target viral promoters containing a TATT sequence to drive transcription after viral DNA replication has begun. Human cytomegalovirus (HCMV), a betaherpesvirus, uses the UL87 LTF to bind both TATT and host RNA polymerase II (Pol II), whereas the UL79 LTF has been suggested to drive productive elongation. Here we apply integrated functional genomics (dTag system, PRO-Seq, ChIP-Seq, and promoter function assays) to uncover the contribution of diversity in LTF target sequences in determining degree and scope to which LTFs drive viral transcription. We characterize the DNA sequence patterns in LTF-responsive and -unresponsive promoter populations, determine where and when Pol II initiates transcription, identify sites of LTF binding genome-wide, and quantify change in nascent transcripts from individual promoters in relation to core promoter sequences, LTF loss, stage of infection, and viral DNA replication. We find that HCMV UL79 and UL87 LTFs function concordantly to initiate transcription from over half of all active viral promoters in late infection, while not appreciably affecting host transcription. Both LTFs act on and bind to viral early-late and late kinetic-class promoters. Over one-third of these core promoters lack the TATT and instead have a TATAT, TGTT, or YRYT. The TATT and non-TATT motifs are part of a sequence block with a sequence code that correlates with promoter transcription level. LTF occupancy of a TATATA palindrome shared by back-to-back promoters is linked to bidirectional transcription. We conclude that diversity in LTF target sequences shapes the LTF-transformative program that drives the viral early-to-late transcription switch.

Herpesviruses have a group of genes earmarked for expression late in the infection. Beta- and gammaherpesviruses utilize a six-member set of viral late transcription factors to selectively activate these genes by binding to a DNA sequence signature in gene promoters. We made an unexpected discovery that a wider range of differences in sequence signatures configures the late gene expression program for human cytomegalovirus, a beta-herpesvirus of global public health importance. Diversity in signature patterns expands promoter targets and probably pre-sets amount of individual promoter output. A unique palindromic sequence signature is linked to the activation of back-to-back promoters at multiple locations in the viral genome. We deduce that diversity in late transcription factor targets functionally orchestrates the rollout of a productive late-stage infection. This may be a generalizable feature adopted by beta- and gammaherpesvirus subfamilies.

Transcriptional control of ribosome biogenesis in yeast: links to growth and stress signals

Ribosome biogenesis requires prodigious transcriptional output in rapidly growing yeast cells and is highly regulated in response to both growth and stress signals. This minireview focuses on recent developments in our understanding of this regulatory process, with an emphasis on the 138 ribosomal protein genes (RPGs) themselves and a group of >200 ribosome biogenesis (RiBi) genes whose products contribute to assembly but are not part of the ribosome. Expression of most RPGs depends upon Rap1, a pioneer transcription factor (TF) required for the binding of a pair of RPG-specific TFs called Fhl1 and Ifh1. RPG expression is correlated with Ifh1 promoter binding, whereas Rap1 and Fhl1 remain promoter-associated upon stress-induced down regulation. A TF called Sfp1 has also been implicated in RPG regulation, though recent work reveals that its primary function is in activation of RiBi and other growth-related genes. Sfp1 plays an important regulatory role at a small number of RPGs where Rap1–Fhl1–Ifh1 action is subsidiary or non-existent. In addition, nearly half of all RPGs are bound by Hmo1, which either stabilizes or re-configures Fhl1–Ifh1 binding. Recent studies identified the proline rotamase Fpr1, known primarily for its role in rapamycin-mediated inhibition of the TORC1 kinase, as an additional TF at RPG promoters. Fpr1 also affects Fhl1–Ifh1 binding, either independently or in cooperation with Hmo1. Finally, a major recent development was the discovery of a protein homeostasis mechanism driven by unassembled ribosomal proteins, referred to as the Ribosome Assembly Stress Response (RASTR), that controls RPG transcription through the reversible condensation of Ifh1.

Ruler elements in chromatin remodelers set nucleosome array spacing and phasing

Arrays of regularly spaced nucleosomes dominate chromatin and are often phased by alignment to reference sites like active promoters. How the distances between nucleosomes (spacing), and between phasing sites and nucleosomes are determined remains unclear, and specifically, how ATP-dependent chromatin remodelers impact these features. Here, we used genome-wide reconstitution to probe how Saccharomyces cerevisiae ATP-dependent remodelers generate phased arrays of regularly spaced nucleosomes. We find that remodelers bear a functional element named the 'ruler' that determines spacing and phasing in a remodeler-specific way. We use structure-based mutagenesis to identify and tune the ruler element residing in the Nhp10 and Arp8 modules of the INO80 remodeler complex. Generally, we propose that a remodeler ruler regulates nucleosome sliding direction bias in response to (epi)genetic information. This finally conceptualizes how remodeler-mediated nucleosome dynamics determine stable steady-state nucleosome positioning relative to other nucleosomes, DNA bound factors, DNA ends and DNA sequence elements.

Genome information processing by the INO80 chromatin remodeler positions nucleosomes

The fundamental molecular determinants by which ATP-dependent chromatin remodelers organize nucleosomes across eukaryotic genomes remain largely elusive. Here, chromatin reconstitutions on physiological, whole-genome templates reveal how remodelers read and translate genomic information into nucleosome positions. Using the yeast genome and the multi-subunit INO80 remodeler as a paradigm, we identify DNA shape/mechanics encoded signature motifs as sufficient for nucleosome positioning and distinct from known DNA sequence preferences of histones. INO80 processes such information through an allosteric interplay between its core- and Arp8-modules that probes mechanical properties of nucleosomal and linker DNA. At promoters, INO80 integrates this readout of DNA shape/mechanics with a readout of co-evolved sequence motifs via interaction with general regulatory factors bound to these motifs. Our findings establish a molecular mechanism for robust and yet adjustable +1 nucleosome positioning and, more generally, remodelers as information processing hubs that enable active organization and allosteric regulation of the first level of chromatin.

DNA sequence preferences or statistical positioning of histones has not explained genomic patterns of nucleosome organisation in vivo. Here, the authors establish DNA shape/mechanics as key elements that have evolved together with binding sites of DNA sequence-specific barriers so that such information directs nucleosome positioning by chromatin remodelers.

An all-to-all approach to the identification of sequence-specific readers for epigenetic DNA modifications on cytosine

Epigenetic modifications of DNA play important roles in many biological processes. Identifying readers of these epigenetic marks is a critical step towards understanding the underlying mechanisms. Here, we present an all-to-all approach, dubbed digital affinity profiling via proximity ligation (DAPPL), to simultaneously profile human TF-DNA interactions using mixtures of random DNA libraries carrying different epigenetic modifications (i.e., 5-methylcytosine, 5-hydroxymethylcytosine, 5-formylcytosine, and 5-carboxylcytosine) on CpG dinucleotides. Many proteins that recognize consensus sequences carrying these modifications in symmetric and/or hemi-modified forms are identified. We further demonstrate that the modifications in different sequence contexts could either enhance or suppress TF binding activity. Moreover, many modifications can affect TF binding specificity. Furthermore, symmetric modifications show a stronger effect in either enhancing or suppressing TF-DNA interactions than hemi-modifications. Finally, in vivo evidence suggests that USF1 and USF2 might regulate transcription via hydroxymethylcytosine-binding activity in weak enhancers in human embryonic stem cells.

Identifying readers of epigenetic marks is a critical step for understanding the role of epigenetic marks in biology. Here, the authors applied DAPPL, an all-to-all approach to profile the interactions between TFs and epigenetic modified DNA libraries.

Ash1 and Tup1 dependent repression of the Saccharomyces cerevisiae HO promoter requires activator-dependent nucleosome eviction

Transcriptional regulation of the Saccharomyces cerevisiae HO gene is highly complex, requiring a balance of multiple activating and repressing factors to ensure that only a few transcripts are produced in mother cells within a narrow window of the cell cycle. Here, we show that the Ash1 repressor associates with two DNA sequences that are usually concealed within nucleosomes in the HO promoter and recruits the Tup1 corepressor and the Rpd3 histone deacetylase, both of which are required for full repression in daughters. Genome-wide ChIP identified greater than 200 additional sites of co-localization of these factors, primarily within large, intergenic regions from which they could regulate adjacent genes. Most Ash1 binding sites are in nucleosome depleted regions (NDRs), while a small number overlap nucleosomes, similar to HO. We demonstrate that Ash1 binding to the HO promoter does not occur in the absence of the Swi5 transcription factor, which recruits coactivators that evict nucleosomes, including the nucleosomes obscuring the Ash1 binding sites. In the absence of Swi5, artificial nucleosome depletion allowed Ash1 to bind, demonstrating that nucleosomes are inhibitory to Ash1 binding. The location of binding sites within nucleosomes may therefore be a mechanism for limiting repressive activity to periods of nucleosome eviction that are otherwise associated with activation of the promoter. Our results illustrate that activation and repression can be intricately connected, and events set in motion by an activator may also ensure the appropriate level of repression and reset the promoter for the next activation cycle.

Nucleosomes inhibit both gene expression and DNA-binding by regulatory factors. Here we examine the role of nucleosomes in regulating the binding of repressive transcription factors to the complex promoter for the yeast HO gene. Ash1 is a sequence-specific DNA-binding protein, and we show that it recruits the Tup1 global repressive factor to the HO promoter. Using a method to determine where Ash1 and Tup1 are bound to DNA throughout the genome, we discovered that Tup1 is also present at most places where Ash1 binds. The majority of these sites are in “Nucleosome Depleted Regions,” or NDRs, where the absence of chromatin makes factor binding easier. We discovered that the HO promoter is an exception, in that the two places where Ash1 binds overlap nucleosomes. Activation of the HO promoter is a complex, multi-step process, and we demonstrated that chromatin factors transiently evict these nucleosomes from the HO promoter during the cell cycle, allowing Ash1 to bind and recruit Tup1. Thus, activators must evict nucleosomes from the promoter to allow the repressive machinery to bind.

Mechanisms coordinating ribosomal protein gene transcription in response to stress

While expression of ribosomal protein genes (RPGs) in the budding yeast has been extensively studied, a longstanding enigma persists regarding their co-regulation under fluctuating growth conditions. Most RPG promoters display one of two distinct arrangements of a core set of transcription factors (TFs) and are further differentiated by the presence or absence of the HMGB protein Hmo1. However, a third group of promoters appears not to be bound by any of these proteins, raising the question of how the whole suite of genes is co-regulated. We demonstrate here that all RPGs are regulated by two distinct, but complementary mechanisms driven by the TFs Ifh1 and Sfp1, both of which are required for maximal expression in optimal conditions and coordinated downregulation upon stress. At the majority of RPG promoters, Ifh1-dependent regulation predominates, whereas Sfp1 plays the major role at all other genes. We also uncovered an unexpected protein homeostasis-dependent binding property of Hmo1 at RPG promoters. Finally, we show that the Ifh1 paralog Crf1, previously described as a transcriptional repressor, can act as a constitutive RPG activator. Our study provides a more complete picture of RPG regulation and may serve as a paradigm for unravelling RPG regulation in multicellular eukaryotes.

Genome-wide off-rates reveal how DNA binding dynamics shape transcription factor function

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 SEQuencing) is a meaningful way of investigating protein-DNA binding dynamics genome-wide.

Specialized RSC: Substrate Specificities for a Conserved Chromatin Remodeler

The remodel the structure of chromatin (RSC) nucleosome remodeling complex is a conserved chromatin regulator with roles in chromatin organization, especially over nucleosome depleted regions therefore functioning in gene expression. Recent reports in Saccharomyces cerevisiae have identified specificities in RSC activity toward certain types of nucleosomes. RSC has now been shown to preferentially evict nucleosomes containing the histone variant H2A.Z in vitro. Furthermore, biochemical activities of distinct RSC complexes has been found to differ when their nucleosome substrate is partially unraveled. Mammalian BAF complexes, the homologs of yeast RSC and SWI/SNF complexes, are also linked to nucleosomes with H2A.Z, but this relationship may be complex and extent of conservation remains to be determined. The interplay of remodelers with specific nucleosome substrates and regulation of remodeler outcomes by nucleosome composition are tantalizing questions given the wave of structural data emerging for RSC and other SWI/SNF family remodelers.

An Optimized Chromatin Immunoprecipitation Protocol for Quantification of Protein-DNA Interactions

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 protocol to quantify protein-DNA interactions

•

Optimized for sensitivity and robustness

•

Optimized for quantitative comparisons between experiments, e.g., in time series

•

Highlights common ChIP pitfalls, variable steps, and how to increase reproducibility

Permutational analysis of Saccharomyces cerevisiae regulatory elements

Gene expression in Saccharomyces cerevisiae is regulated at multiple levels. Genomic and epigenomic mapping of transcription factors and chromatin factors has led to the delineation of various modular regulatory elements—enhancers (upstream activating sequences), core promoters, 5′ untranslated regions (5′ UTRs) and transcription terminators/3′ untranslated regions (3′ UTRs). However, only a few of these elements have been tested in combinations with other elements and the functional interactions between the different modular regulatory elements remain under explored. We describe a simple and rapid approach to build a combinatorial library of regulatory elements and have used this library to study 26 different enhancers, core promoters, 5′ UTRs and transcription terminators/3′ UTRs to estimate the contribution of individual regulatory parts in gene expression. Our combinatorial analysis shows that while enhancers initiate gene expression, core promoters modulate the levels of enhancer-mediated expression and can positively or negatively affect expression from even the strongest enhancers. Principal component analysis (PCA) indicates that enhancer and promoter function can be explained by a single principal component while UTR function involves multiple functional components. The PCA also highlights outliers and suggest differences in mechanisms of regulation by individual elements. Our data also identify numerous regulatory cassettes composed of different individual regulatory elements that exhibit equivalent gene expression levels. These data thus provide a catalog of elements that could in future be used in the design of synthetic regulatory circuits.

Universal promoter scanning by Pol II during transcription initiation in Saccharomyces cerevisiae

BACKGROUND

The majority of eukaryotic promoters utilize multiple transcription start sites (TSSs). How multiple TSSs are specified at individual promoters across eukaryotes is not understood for most species. In Saccharomyces cerevisiae, a pre-initiation complex (PIC) comprised of Pol II and conserved general transcription factors (GTFs) assembles and opens DNA upstream of TSSs. Evidence from model promoters indicates that the PIC scans from upstream to downstream to identify TSSs. Prior results suggest that TSS distributions at promoters where scanning occurs shift in a polar fashion upon alteration in Pol II catalytic activity or GTF function.

RESULTS

To determine the extent of promoter scanning across promoter classes in S. cerevisiae, we perturb Pol II catalytic activity and GTF function and analyze their effects on TSS usage genome-wide. We find that alterations to Pol II, TFIIB, or TFIIF function widely alter the initiation landscape consistent with promoter scanning operating at all yeast promoters, regardless of promoter class. Promoter architecture, however, can determine the extent of promoter sensitivity to altered Pol II activity in ways that are predicted by a scanning model.

CONCLUSIONS

Our observations coupled with previous data validate key predictions of the scanning model for Pol II initiation in yeast, which we term the shooting gallery. In this model, Pol II catalytic activity and the rate and processivity of Pol II scanning together with promoter sequence determine the distribution of TSSs and their usage.

Transcription Factor Binding in Embryonic Stem Cells Is Constrained by DNA Sequence Repeat Symmetry

Transcription factor (TF) recognition is dictated by the underlying DNA motif sequence specific for each TF. Here, we reveal that DNA sequence repeat symmetry plays a central role in defining TF-DNA-binding preferences. In particular, we find that different TFs bind similar symmetry patterns in the context of different developmental layers. Most TFs possess dominant preferences for similar DNA repeat symmetry types. However, in some cases, preferences of specific TFs are changed during differentiation, suggesting the importance of information encoded outside of known motif regions. Histone modifications also exhibit strong preferences for similar DNA repeat symmetry patterns unique to each type of modification. Next, using an in vivo reporter assay, we show that gene expression in embryonic stem cells can be positively modulated by the presence of genomic and computationally designed DNA oligonucleotides containing identified nonconsensus-repetitive sequence elements. This supports the hypothesis that certain nonconsensus-repetitive patterns possess a functional ability to regulate gene expression. We also performed a solution NMR experiment to probe the stability of double-stranded DNA via imino proton resonances for several double-stranded DNA sequences characterized by different repetitive patterns. We suggest that such local stability might play a key role in determining TF-DNA binding preferences. Overall, our findings show that despite the enormous sequence complexity of the TF-DNA binding landscape in differentiating embryonic stem cells, this landscape can be quantitatively characterized in simple terms using the notion of DNA sequence repeat symmetry.

Dual threshold optimization and network inference reveal convergent evidence from TF binding locations and TF perturbation responses

A high-confidence map of the direct, functional targets of each transcription factor (TF) requires convergent evidence from independent sources. Two significant sources of evidence are TF binding locations and the transcriptional responses to direct TF perturbations. Systematic data sets of both types exist for yeast and human, but they rarely converge on a common set of direct, functional targets for a TF. Even the few genes that are both bound and responsive may not be direct functional targets. Our analysis shows that when there are many nonfunctional binding sites and many indirect targets, nonfunctional sites are expected to occur in the cis-regulatory DNA of indirect targets by chance. To address this problem, we introduce dual threshold optimization (DTO), a new method for setting significance thresholds on binding and perturbation-response data, and show that it improves convergence. It also enables comparison of binding data to perturbation-response data that have been processed by network inference algorithms, which further improves convergence. The combination of dual threshold optimization and network inference greatly expands the high-confidence TF network map in both yeast and human. Next, we analyze a comprehensive new data set measuring the transcriptional response shortly after inducing overexpression of a yeast TF. We also present a new yeast binding location data set obtained by transposon calling cards and compare it to recent ChIP-exo data. These new data sets improve convergence and expand the high-confidence network synergistically.

Absolute nucleosome occupancy map for the Saccharomyces cerevisiae genome

Mapping of nucleosomes, the basic DNA packaging unit in eukaryotes, is fundamental for understanding genome regulation because nucleosomes modulate DNA access by their positioning along the genome. A cell-population nucleosome map requires two observables: nucleosome positions along the DNA ("Where?") and nucleosome occupancies across the population ("In how many cells?"). All available genome-wide nucleosome mapping techniques are yield methods because they score either nucleosomal (e.g., MNase-seq, chemical cleavage-seq) or nonnucleosomal (e.g., ATAC-seq) DNA but lose track of the total DNA population for each genomic region. Therefore, they only provide nucleosome positions and maybe compare relative occupancies between positions, but cannot measure absolute nucleosome occupancy, which is the fraction of all DNA molecules occupied at a given position and time by a nucleosome. Here, we established two orthogonal and thereby cross-validating approaches to measure absolute nucleosome occupancy across the Saccharomyces cerevisiae genome via restriction enzymes and DNA methyltransferases. The resulting high-resolution (9-bp) map shows uniform absolute occupancies. Most nucleosome positions are occupied in most cells: 97% of all nucleosomes called by chemical cleavage-seq have a mean absolute occupancy of 90 ± 6% (±SD). Depending on nucleosome position calling procedures, there are 57,000 to 60,000 nucleosomes per yeast cell. The few low absolute occupancy nucleosomes do not correlate with highly transcribed gene bodies, but correlate with increased presence of the nucleosome-evicting chromatin structure remodeling (RSC) complex, and are enriched upstream of highly transcribed or regulated genes. Our work provides a quantitative method and reference frame in absolute terms for future chromatin studies.

Homotypic cooperativity and collective binding are determinants of bHLH specificity and function

Eukaryotic cells express transcription factor (TF) paralogues that bind to nearly identical DNA sequences in vitro but bind at different genomic loci and perform different functions in vivo. Predicting how 2 paralogous TFs bind in vivo using DNA sequence alone is an important open problem. Here, we analyzed 2 yeast bHLH TFs, Cbf1p and Tye7p, which have highly similar binding preferences in vitro, yet bind at almost completely nonoverlapping target loci in vivo. We dissected the determinants of specificity for these 2 proteins by making a number of chimeric TFs in which we swapped different domains of Cbf1p and Tye7p and determined the effects on in vivo binding and cellular function. From these experiments, we learned that the Cbf1p dimer achieves its specificity by binding cooperatively with other Cbf1p dimers bound nearby. In contrast, we found that Tye7p achieves its specificity by binding cooperatively with 3 other DNA-binding proteins, Gcr1p, Gcr2p, and Rap1p. Remarkably, most promoters (63%) that are bound by Tye7p do not contain a consensus Tye7p binding site. Using this information, we were able to build simple models to accurately discriminate bound and unbound genomic loci for both Cbf1p and Tye7p. We then successfully reprogrammed the human bHLH NPAS2 to bind Cbf1p in vivo targets and a Tye7p target intergenic region to be bound by Cbf1p. These results demonstrate that the genome-wide binding targets of paralogous TFs can be discriminated using sequence information, and provide lessons about TF specificity that can be applied across the phylogenetic tree.

Satb1 integrates DNA binding site geometry and torsional stress to differentially target nucleosome-dense regions

The Satb1 genome organizer regulates multiple cellular and developmental processes. It is not yet clear how Satb1 selects different sets of targets throughout the genome. Here we have used live-cell single molecule imaging and deep sequencing to assess determinants of Satb1 binding-site selectivity. We have found that Satb1 preferentially targets nucleosome-dense regions and can directly bind consensus motifs within nucleosomes. Some genomic regions harbor multiple, regularly spaced Satb1 binding motifs (typical separation ~1 turn of the DNA helix) characterized by highly cooperative binding. The Satb1 homeodomain is dispensable for high affinity binding but is essential for specificity. Finally, we find that Satb1-DNA interactions are mechanosensitive. Increasing negative torsional stress in DNA enhances Satb1 binding and Satb1 stabilizes base unpairing regions against melting by molecular machines. The ability of Satb1 to control diverse biological programs may reflect its ability to combinatorially use multiple site selection criteria.

Shared nucleotide flanks confer transcriptional competency to bZip core motifs

Sequence-specific DNA binding recruits transcription factors (TFs) to the genome to regulate gene expression. Here, we perform high resolution mapping of CEBP proteins to determine how sequence dictates genomic occupancy. We demonstrate a fundamental difference between the sequence repertoire utilized by CEBPs in vivo versus the palindromic sequence preference reported by classical in vitro models, by identifying a palindromic motif at <1% of the genomic binding sites. On the native genome, CEBPs bind a diversity of related 10 bp sequences resulting from the fusion of degenerate and canonical half-sites. Altered DNA specificity of CEBPs in cells occurs through heterodimerization with other bZip TFs, and approximately 40% of CEBP-binding sites in primary human cells harbor motifs characteristic of CEBP heterodimers. In addition, we uncover an important role for sequence bias at core-motif-flanking bases for CEBPs and demonstrate that flanking bases regulate motif function across mammalian bZip TFs. Favorable flanking bases confer efficient TF occupancy and transcriptional activity, and DNA shape may explain how the flanks alter TF binding. Importantly, motif optimization within the 10-mer is strongly correlated with cell-type-independent recruitment of CEBPβ, providing key insight into how sequence sub-optimization affects genomic occupancy of widely expressed CEBPs across cell types.

Sfp1 regulates transcriptional networks driving cell growth and division through multiple promoter-binding modes

In this study, Albert et al. investigated the mechanisms by which the yeast Sfp1 protein coordinates both cell division and growth. They demonstrate that Sfp1 directly controls genes required for ribosome production and many other growth-promoting processes.

The yeast Sfp1 protein regulates both cell division and growth but how it coordinates these processes is poorly understood. We demonstrate that Sfp1 directly controls genes required for ribosome production and many other growth-promoting processes. Remarkably, the complete set of Sfp1 target genes is revealed only by a combination of ChIP (chromatin immunoprecipitation) and ChEC (chromatin endogenous cleavage) methods, which uncover two promoter binding modes, one requiring a cofactor and the other a DNA-recognition motif. Glucose-regulated Sfp1 binding at cell cycle “START” genes suggests that Sfp1 controls cell size by coordinating expression of genes implicated in mass accumulation and cell division.