Pdyn (prodynorphin), a gene encoding an opioid neuropeptide implicated in motivated behavior and neuropsychiatric disease states. CRISPR-based functional assays demonstrated that this enhancer is both necessary and sufficient for Pdyn transcription. This regulatory element is also conserved at the human PDYN locus, where its activation is sufficient to drive PDYN transcription in human cells. These results suggest that IEGs participate in chromatin remodeling at enhancers and identify a conserved enhancer that may act as a therapeutic target for brain disorders involving dysregulation of Pdyn.Neuronal and behavioral adaptations to novel stimuli are regulated by temporally dynamic waves of transcriptional activity, which shape neuronal function and guide enduring plasticity. Neuronal activation promotes expression of an immediate early gene (IEG) program comprised primarily of activity-dependent transcription factors, which are thought to regulate a second set of late response genes (LRGs). However, while the mechanisms governing IEG activation have been well studied, the molecular interplay between IEGs and LRGs remain poorly characterized. Here, we used transcriptomic and chromatin accessibility profiling to define activity-driven responses in rat striatal neurons. As expected, neuronal depolarization generated robust changes in gene expression, with early changes (1 hr) enriched for inducible transcription factors and later changes (4 hr) enriched for neuropeptides, synaptic proteins, and ion channels. Remarkably, while depolarization did not induce chromatin remodeling after 1 hr, we found broad increases in chromatin accessibility at thousands of sites in the genome at 4 hr after neuronal stimulation. These putative regulatory elements were found almost exclusively at non-coding regions of the genome, and harbored consensus motifs for numerous activity-dependent transcription factors such as AP-1. Furthermore, blocking protein synthesis prevented activity-dependent chromatin remodeling, suggesting that IEG proteins are required for this process. Targeted analysis of LRG loci identified a putative enhancer upstream of  Fos (aka c-Fos), Npas4, and Nr4a2. These genes follow a temporally dynamic profile, with elevated expression within 1 hr of a stimulus and rapid return to baseline levels. In contrast, the same stimuli promote expression of a more delayed gene expression program, termed late response genes (LRGs)  . This seFos and Jun family members, directly contributes to chromatin remodeling at LRG enhancers  gene locus that is conserved in the human genome. CRISPR-based activation and repression experiments provided functional validation that this region serves as a Pdyn enhancer in both rat neurons and dividing human cell lines. Collectively, these results highlight the mechanisms through which neuronal activity promotes gene expression changes to modify neuronal function, and have relevance for brain disease states characterized by alterations to this process.Here, we used next-generation sequencing approaches to characterize temporally distinct, activity-dependent transcriptomic and epigenomic reorganization in cultured rat embryonic striatal neurons, an in vitro model containing many cell types implicated in learning, motivation, reward, and substance use disorders . These eNpas4, Fos, Fosb, Fosl2, and Nr4a1  and a representative LRG (Pdyn) revealed that while Fos mRNA began to return to baseline in the wash off (1 hr stimulation) condition, Pdyn mRNA was equally elevated in response to 1 hr KCl (followed by 3 hr wash off) and 4 hr KCl stimuli  or no wash off for 3 hr . Reverse stimuli . Additio stimuli , includiplicates , suggestIn non-neuronal systems, LRG induction is dependent on activity-dependent chromatin remodeling at genomic enhancers . To idenEnhancers are marked by distinctive histone modifications, including histone acetylation (at H3K27) and increased ratios of histone monomethylation to trimethylation at H3K4 (H3K4me1:H3K4me3). In contrast, while promoters are also marked by H3K27ac, they tend to exhibit a lower H3K4me1:H3K4me3 ratio . To inveThe combination of RNA- and ATAC-seq results suggests a temporal decoupling between induction of IEG transcription factors and activity-dependent chromatin remodeling. IEG transcription factors were activated following 1 hr of depolarization , but actTo test this possibility, we searched for enriched motifs using a database of experimentally validated transcription factor-binding motifs with HOMER . AdditioThe HOMER database allowed us to investigate the enrichment of over 400 transcription factor motifs in over 5300 DARs. To understand if DARs could be separated based on the transcription factor motifs present within these regions, we used uniform manifold approximation and projection   and densThe significant enrichment of IEG transcription factor motifs within 4 hr DARs suggests that these inducible transcription factors may be required for subsequent activity-dependent chromatin remodeling. Furthermore, the temporal decoupling between IEG expression and activity-dependent chromatin remodeling suggests that IEGs must be translated before acting on genomic regions to induce an open chromatin state. To test the hypothesis that de novo protein translation is required for activity-dependent chromatin remodeling, we repeated ATAC-seq after 4 hr of depolarization in combination with protein synthesis inhibition. Cultured rat embryonic striatal neurons were pretreated with 40 μM anisomycin, a translation inhibitor, for 30 min followed by 10 mM KCl for 4 hr . As expeFos locus), which are accessible at baseline and do not undergo activity-dependent chromatin remodeling  located in non-coding regions of the genome, (2) inaccessible at baseline and accessible following depolarization, and (3) inaccessible when depolarization was paired with protein synthesis inhibition. These regions would be fundamentally different from enhancers regulating IEGs  resulted in significant upregulation of Pdyn mRNA  fused to the transcriptional activator VPR (CRISPRa) or the transcriptional repressor KRAB-MeCP2 (CRISPRi)  to target dCas9-KRAB-MeCP2 to the DAR in the presence of depolarization. As a negative control, we transduced cultured striatal neurons with a sgRNA for lacZ, a bacterial gene not found in the mammalian genome. As expected, activity-dependent Pdyn upregulation was observed in neurons transduced with lacZ sgRNAs and dCas9-KRAB-MeCP2 (Pdyn upregulation was blocked in neurons transduced with DAR-targeting sgRNAs and dCas9-KRAB-MeCP2 (Pdyn mRNA levels were attenuated by CRISPRi of the Pdyn DAR (Pdyn TSS is necessary for activity-dependent Pdyn transcription.The observation that CRISPRi)  to activCRISPRi) . To testAB-MeCP2 . HoweverAB-MeCP2 . AdditioPdyn DAR , suggestlacZ or the Pdyn DAR and dCas9-VPR (CRISPRa) to test if activation of this DAR is sufficient to promote Pdyn transcription. Pdyn mRNA levels were significantly increased in neurons transduced with DAR-targeting sgRNAs  were co-housed in pairs in plastic filtered cages with nesting enrichment in an Association for Assessment and Accreditation of Laboratory Animal Care-approved animal care facility maintained between 23 and 24°C on a 12-hr light/12-hr dark cycle with ad libitum food (Lab Diet Irradiated rat chow) and water. Bedding and enrichment were changed weekly by animal resources program staff. Animals were randomly assigned to experimental groups. All experiments were approved by the University of Alabama at Birmingham Institutional Animal Care and Use Committee (IACUC) under animal protocol number 20118 or 21306. For primary neuronal cultures, timed pregnant Sprague-Dawley dams were individually housed until embryonic day 18 when striatal cultures were generated as previously described .A receptor antagonist gabazine . All treatments were applied for 4 hr followed by RNA extraction and RT-qPCR.Cells were maintained in neurobasal media supplemented with B27 and LG for 11–12 days in vitro (DIV) with half media changes on DIV 1, 5–6, and 9–10. For depolarization experiments, neurons were treated with KCl dissolved in neurobasal media to a final concentration of 10 mM for 1 or 4 hr. To test the necessity of protein translation in mediating activity-dependent transcription and chromatin remodeling, anisomycin was dissolved in DMSO and treated to a final concentration of 40 μM for 30 min prior to depolarization. Additional stimuli outlined in CVCL_0063) were maintained in Dulbecco’s modified Eagle medium + 10% fetal bovine serum and plated at 80,000 cells/well in 24-well plates. 24 hr later cells were transfected with Fugene HD (Promega) and constructs containing dCas9-VPR and gRNA vectors targeting the conserved DAR region (500 ng plasmid DNA in molar ratios sgRNA:dCas9-VPR). Forty-eight hours later, cells were lysed and RNA was extracted.HEK-293T cells  )and β-tubulin primary antibody  overnight at 4°C. Following primary antibody incubation, secondary antibodies  for 1 hr at room temperature. Imaging was performed using a Licor Odyssey imager.DIV 11–12 cultured rat embryonic striatal neurons were treated with 40 μM anisomycin followed by 4 hr of depolarization with 10 mM KCl in 12-well plates. Following depolarization, media was removed, and wells were washed with 1× Tris-buffered saline (TBS). Cells were lysed using radio-immunoprecipitation assay (RIPA) lysis buffer . Following protein separation and transfer, Polyvinylidene difluoride (PVDF) membrane was incubated with FOS primary antibody  and submitted to the Genomics core lab at the Heflin Center for Genomic Sciences at the University of Alabama at Birmingham for library preparation as previously described . RNA-seqCTGTCTCTTATA-3′) were identified and removed. For rat striatal neuron experiments, FASTQ files were then aligned using Bowtie2 (ATAC-seq libraries were prepared as previously described . ATAC-se Bowtie2  (v2.4.4) Bowtie2  (v2.26.2 Bowtie2  (v1.13). Bowtie2  (v3.5.1) Bowtie2  (v1.11). Bowtie2  (v 2.1.1 Bowtie2  (v3.8.4) Bowtie2  , homogenized using a motorized homogenizer and RNase-free pestle, and incubated on ice for 5 min. Samples were then pipette mixed 15× and incubated on ice for an additional 10 min. Following lysis, four samples from same sex and treatment were grouped into a single sample, and 2 ml chilled wash buffer  was added. Samples were then passed through 70 and 40 μM Scienceware Flowmi Cell Strainers. Samples were then centrifuged at 250 rcf for 5 min at 4°C. Supernatant was removed and the pellet was resuspended in 1 ml of chilled wash buffer . 100 μl of sample was then stained with 7-aminoactinomycin D and used to set a representative gate for fluorescence-activated cell sorting (FACS). This gate was then used to purify nuclei further. Following FACS, samples were spun at 250 rcf for 10 min at 4°C to remove any remaining debris. Samples were then loaded into individual wells of the Chromium NextGem Single Cell Chip using four of the eight available wells.Flash-frozen NAc tissue was added to a tube containing 500 μl lysis buffer . The groups were then merged into one object based on a common set of features and the standard Signac dimensionality reduction and clustering workflow was performed using 2:30 dimensions and a resolution value of 0.2. Data were then integrated with the snRNA-seq data from the same samples. Common anchors between the two were used to predict and label the cell types present in the snATAC-seq data.10× Genomics snATAC-seq libraries were generated from male and female Sprague-Dawley rats exposed injected with 20 mg/kg cocaine  once daily for 7 days. snATAC-seq data were aligned to the mRatBN7.2/Rn7 reference assembly using cellranger-atac v2.1.0 and the procedure outlined by 10× Genomics . AnalysiDetection of cis-coaccessible sites in the snATAC-seq data was performed using Cicero v1.3.9  and Monohttps://github.com/Jeremy-Day-Lab/Phillips_etal_2023, (copy archived at All relevant data that support the findings of this study are available by request from the corresponding author (J.J.D.). Custom code can be found at  important study that uses chromatin accessibility as a measure to determine the impact of neuronal activity on the state of chromatin regulatory elements in striatal neurons. The authors provide convincing evidence of how Pdyn gene expression is highly dependent on a distal regulatory genomic region both at basal and upon neuronal activation in this particular system, a mechanism conserved as well in human neuronal cells. Although the basic idea of accessibility changes have been studied before, this paper ties previous findings all together in one place and uses the analysis to identify a functionally relevant and conserved enhancer for the prodynorphin gene with potential relevance for neuropsychiatric disorders beyond basic cellular neuroscience. The study will be of interest to neuroscientists studying the striatum, neuronal plasticity, or related neuropsychiatric disorders.This is an  Summary:In this manuscript the authors use ATAC-seq to find regions of the genome of rat embryonic striatal neurons in culture that show changes in regulatory element accessibility following stimulation by KCl-mediated membrane depolarization. The authors compare 1hr and 4hr transcriptomes to see both rapid and late response genes. When they look at ATAC-seq data they see no changes in accessibility at 1hr but strong changes at 4hr. The differentially accessible sites were enriched for the AP-1 site, suggesting regulation by Fos-Jun family members, and consistent with the requirement for IEG expression, anisomycin blocked the increase in accessibility. To test the functional importance of this regulation the authors focus on a putative enhancer 45kb upstream of the activity-induced gene encoding the neuromodulator dynorphin (Pdyn). To test the function of this region, the authors recruited CRISPRi to the site, which blocked KCL-dependent Pdyn induction, or CRISPRa, which selectively increased Pdyn expression in the absence of KCl. Finally the authors reanalyze other human and rat datasets to show cell-type specific function of this enhancer correlated to Pdyn expression.The idea that stimuli that induce expression of Fos in neurons can change accessibility of regulatory elements bound from Fos has been shown before, but almost all the data are from hippocampal neurons so it is nice to see the different cell type used here. The most interesting part of the study is the identification of the Pdyn enhancer because of the importance of this gene product in the function of striatal neurons. Overall the conclusions appear to be well supported by the data. This study aims to characterize transcriptional and epigenetic activity-dependent striatal neuronal adaptations using rat primary cultures, a model still poorly characterized up to date. In addition, the authors aim to interrogate regulatory mechanisms that could modulate the expression of a highly-striatal enriched gene responding to neuronal activation in striatal neuronal cells, the Pdyn gene.Among the major strengths of the article there is the generation of high quality neuronal RNA-seq and ATAC-seq data in rat striatal neuronal cells in basal level and upon neuronal activity, a experimental setup that has not been so characterized as other more common ones such as mouse hippocampal neuronal cells. In this model, the authors clearly demonstrate the need of protein translation to induce the transcriptional waves of late response genes. In addition, the functional characterization of an enhancer of the Pdyn gene might be of great interest for translational applications in which alterations of this gene might be occurring in neurological disorders.On the other hand, the manuscript presents some limitations to be considered. One of the major points in this regard is that, at least in part, some of the conclusions reached by the study related to the induction of particular transcriptional programs upon neuronal activation, the changes in chromatin state, and the need of protein translation for proper induction of LRGs have been already previously described in the literature, affecting the novelty of the study. However, it is needed to be mentioned, that these previous studies were not conducted using the same model , which can make some differences in the final outputs. The other major cautionary point in the study is the selection of the time point for distinguishing early versus late response genes, as the short difference in time and the overlap of part of the transcriptional signature between them suggest that the transcriptional waves are somehow partially overlapping , which could result in missing part of the late-response genes.Despite this, the conclusions raised in the study are well supported by the data generated in it.In summary, the study presents a useful set of transcriptomic and epigenomic data of activity-dependent striatal neuronal programs in rats, which will be of great use for the scientific community working in this not so well characterized model. In addition, the characterization of a Pdyn distal regulatory genomic region involved in its transcriptional regulation, both at basal levels and upon neuronal activation in this particular system, can present translational relevance for striatal disorders such as Huntington's disease or other neuropsychiatric disorders. This work contributes to the literature characterizing early and late waves of transcription and associated chromatin remodeling following neuronal depolarization, here in cultured embryonic striatum. While they find IEG transcription 1 h after depolarization, they find chromatin remodeling is slower (opening at the 4 h time point). While this is not the first paper to describe chromatin changes in response to neuronal activity, this paper ties previous findings all together in one place using novel sequencing analyses and visualizations. Previous work has found remodeling occurring at the 1 h time point, so the lack of differences at that early time point in the current study needs to be better understood and the "temporal decoupling" described by authors should be further explored. Differences may be due to chromatin at IEG regulatory regions already being open in embryonic tissue (here) vs generally more closed in adult tissue (previous), or due to previous studies using protocols to specifically silence neurons prior to activation. The authors next show that the chromatin remodeling that occurs at the late (4 h) stage is largely in putative regulatory regions of the genome (rather than gene bodies), and is dependent on translation, which validates and extends the prior literature. The authors then transition from genome-wide basic neuroscience to focus on a specific gene of interest, prodynorphin (Pdyn), and a putative enhancer they identify from their chromatin analysis. They target CRISPR-activating and -inhibiting complexes to the putative enhancer and demonstrate that accessibility of this locus is necessary and sufficient for Pdyn transcription. They then show that at least one PDYN enhancer is conserved from rodents to humans, and is only activity-regulated in human GABAergic but not glutamatergic neurons. Finally, the authors generate snATAC-seq and show Pdyn gene and enhancer activity is also cell-type-specific in rat striatum. The Pdyn work, in particular, is thorough and novel, and demonstrates a translational aspect of this work. The following is the authors’ response to the original reviews.We thank all the reviewers for their comments and constructive feedback regarding our manuscript. We have made many changes to strengthen the manuscript, including addition of two new experiments  that help to clarify the nature and scope of activation of late response genes in striatal neurons. Our specific responses to individual reviewer comments are provided below.Reviewer #1Public reviewWeaknesses: The timing and the location of the accessibility changes are meaningfully different from other similar studies, which should be discussed. The authors provide good data for the function of a single enhancer near Pdyn, but could contextualize this with respect to other regulatory elements nearby.In the revised manuscript, we have expanded our discussion of the differences between chromatin accessibility changes observed in this study and those found in prior reports in different systems. These differences are also addressed in extended detail below. Unfortunately, limitations on resources and time prevented a deeper exploration of additional candidate enhancers near the Pdyn locus. However, we believe our efforts to characterize an activity-dependent enhancer in the Pdyn locus provides a useful starting point, and future studies may seek to more completely define the contributions of nearby regulatory elements.Recommendations For The Authors1. At 1hr after stimulation in previous papers : 1718-1730.) there are large increases in accessibility directly over the IEGs, consistent with the concerted transcription of these genes following stimulation. It is surprising that the authors do not see this here, either at 1hr or at 4hr. This difference in results needs to be addressed.We thank the reviewer for bringing this discrepancy to our attention. Indeed, Su et al. 2017 and Fernandez-Albert et al. 2019 both describe increases in chromatin accessibility at IEG promoters. There are several experimental differences that could be contributing to differences between our study and previously published studies. Two major reasons include the developmental timepoint of the tissue/cells and the cell type/brain region that is being assayed. Su et al. assayed chromatin accessibility in ex vivo slices containing the dentate gyrus from adult mice, while Fernandez-Albert et al. assayed chromatin accessibility in forebrain principal neurons of adult mice following kainic acid injection. Bulk ATAC-Seq experiments described in the present manuscript were generated from cultured embryonic rat striatal neurons. Additionally, baseline chromatin accessibility seems to be significantly different between forebrain principal neurons studied in Fernandez-Albert et al. 2019 and the current study. For example, in Figure 3a of Fernandez-Albert et al. 2019, the Npas4 gene body is not accessible in a saline treated animal. In vehicle treated, cultured embryonic rat striatal neurons, the Fos gene body and associated enhancers are accessible at baseline , and do not increase with KCl depolarization.We have expanded our discussion of this discrepancy in the discussion section of the revised manuscript, and included additional citations addressing this difference.1. It is also somewhat surprising that the authors see almost no regions that show changes in accessibility at 1hr and then a very large number of differentially accessible regions at 4hr. This is quite different from the more rapid changes shown for example in Figure 7f in the human GABA neurons even though these are also studies in culture with rapid calcium channel opening. Can the authors speculate on the reason for the difference?Many previously published studies that use cultured neurons include a pre-treatment in which spontaneous neuronal activity is inhibited with the sodium channel blocker tetrodotoxin . The Sanchez-Priego et al. Cell Reports manuscript also blocked NMDA receptor activity with the competitive NMDAR antagonist D-AP5 for 12 hours prior to depolarization. Rapid changes in chromatin accessibility observed in other studies at <1 hour timepoints could be due to prior silencing of the cells and subsequent reduction in the accessibility and transcriptional activity of IEGs. Decreased baseline accessibility and transcriptional activity of IEGs can be observed in Figure 1a of Malik et al. 2014, which displays ChIP-Seq tracks for both RNA pol II and H3K27ac. At baseline, H3K27ac and RNA pol II enrichment is low throughout the Fos locus. Subsequent depolarization of silenced neurons drives accessibility and transcription of the Fos gene and associated enhancers. In contrast, we found accessible chromatin at Fos enhancer elements at baseline .The experiments described in the current study do not include any pre-treatment with tetrodotoxin or D-AP5, and thus the neurons are expected to be spontaneously active. This baseline electrophysiological activity may result in increased accessibility and transcription at IEG loci, which ultimately makes it difficult to identify activity-dependent increases in IEG accessibility at timepoints <1 hour. Furthermore, a previously published manuscript from our lab  conducted ATAC-seq on cultured embryonic rat cortical, hippocampal, and striatal neurons and found that transcribed enhancers for IEG loci (including Fos) had decreased chromatin accessibility following depolarization when compared to vehicle treatment. These differences in experimental design  may all contribute to differences in the temporal dynamics of chromatin remodeling between the current manuscript and previously published studies.1. Experimentally it can be challenging to repress a single enhancer and show a significant effect on gene regulation which makes the repression in Fig 6c somewhat unexpected. There are several regions near Pdyn that show activity-dependent changes in accessibility in the human cells  and presumably in the rat neurons too . Did the authors target any of these other regions?We chose the identified regulatory element upstream of the Pdyn TSS because it met several criteria that we determined are important for characterizing LRG enhancers. These criteria are outlined in the Results: “(1) located in non-coding regions of the genome, (2) inaccessible at baseline and accessible following depolarization, and (3) inaccessible when depolarization was paired with protein synthesis inhibition.” Indeed, ATAC-seq experiments presented in the current study demonstrate that thousands of genomic regions undergo reprogramming, and many of these regions meet these criteria . However, we lacked the time and resources to systematically investigate all other enhancers, and did not target any other regions within the Pdyn locus. While many enhancers may regulate a single gene, the identified enhancer seems to be particularly important for activity-dependent Pdyn gene expression. Importantly, CRISPRi-based repression of this enhancer  did not reduce basal Pdyn expression as compared to a non-targeting control, but completely blocked stimulus-dependent induction of Pdyn transcription. We believe this is a useful starting point, and future studies may seek to more completely define the contributions of nearby regulatory elements.1. The authors should clarify in the methods or figure legends the number of independent replicate libraries for each experiment and were the RNA and ATAC libraries made from the same or different experiments.We thank the reviewer for bringing this to our attention. We have clarified the number of replicates in the methods as outlined below. Additionally, RNA and ATAC libraries were generated from different experiments, and this information is also now included in the methods.Within the ATAC-Seq library preparation and analysis methods section: “ATAC-seq libraries were generated from experiments independent of the RNA-seq experiments. For the ATAC-seq experiment of neurons treated with vehicle or KCl for 1 h, there were 3 replicates within each treatment group . For the ATAC-seq experiment of neurons treated with vehicle or KCl for 4 h, there were 3 replicates within each treatment group . For the ATAC-seq experiment of neurons pre-treated with DMSO or Anisomycin, there were 4 replicates within each treatment group .”Within the RNA-seq library preparation and analysis methods section: “RNA-seq libraries were generated from experiments independent of the ATAC-seq experiments. For the RNA-seq experiment of neurons treated with vehicle or KCl for 1 h, there were 3 replicates within the KCl group and 4 replicates within the vehicle group. For the RNA-seq experiment of neurons treated with vehicle or KCl for 4 h, there were 4 replicates within each group .”Reviewer #2Public reviewFirst of all, at a conceptual level, most of the findings related to the induction of particular transcriptional programs upon neuronal activation the changes in chromatin state, and the need for protein translation for proper induction of LRGs have been broadly characterized previously in the literature . In addition, it is not so obvious why to focus on Pdyn gene regulatory regions among the thousands of genes upregulated and with modified chromatin landscape after neuronal activation. The authors highlight three particular traits of this gene as the reason to choose it, but those traits are probably shared by most of the genes that are part of the LRGs set.We thank the reviewer for these comments, and have included these important publications as citations in our manuscript. With over 5,000 differentially accessible chromatin regions following KCl stimulation, it was not possible to follow up on all regulatory regions or linked genes in a rigorous way. Therefore, we selected a target candidate enhancer near the Pdyn locus for mechanistic studies. In addition to the criteria highlighted in the manuscript, we chose this locus due to decades of literature establishing the importance of prodynorphin in the striatum, and the role of this gene in human neuropsychiatric diseases. We would argue that this increases the relevance of more detailed exploration of this gene, and makes our results applicable to a broader pre-existing literature.At the methodological level, some attention should be put into the timings chosen for generating the data. The authors claim that these time points (1h and 4hrs) identify the first (i.e IEGs) and second (i.e LRGs) waves of transcription. However, at 4hrs the highest over-expressed genes are still IEGs, as shown in the volcano plots of Figure 1B and 1C, showing a high overlap with up-regulated genes found at 1h . This might suggest that the 4hrs time point is somewhere in between the first and second wave of transcription, probably missing some of the still-to-be-induced LRGs of the latest one.Given that the depolarization applied in RNA-seq and ATAC-seq experiments is continuous, it was not unexpected to find IEGs present at both 1 h and 4 h timepoints. The revised manuscript contains a new experiment  demonstrating that a shorter depolarization period (1 h KCl followed by a 3 h wash off period) also induces Fos mRNA, but to a much lower extent than 4 h continuous stimulation. In contrast, both short (1 h) and long (4 h) depolarization periods induce Pdyn to equivalent levels when measured at 4 h after the onset of the stimulus. These experiments support our conclusion that LRGs require a temporal delay, and not simply extended stimulation. Nevertheless, the reviewer is correct that a 4 h timepoint may potentially miss some LRGs that are induced even later. We plan to explore the full timecourse of LRG induction in future studies.Finally, while only prosed as a suggestion, the assumption that from the data generated in this article, we can envision a mechanism by which AP-1 family of transcription factors interacts with the SWI/SNF chromatin remodeling complex is going too far, as no evidence is provided implicated SWI/SNF in the data presented in the manuscript.While speculative in the current context, we felt that it was important to highlight this prior literature to identify potential mechanisms that may link IEGs  to chromatin remodeling machinery. We have altered this section of the discussion to emphasize that this link is speculative in the context of neuronal chromatin remodeling.Recommendations For The Authors1. I couldn't find the number of replicates generated for each dataset, neither for RNA nor for ATAC-seq. It could be worth adding these data to the figure legends or in the material and methods.We thank the reviewer for bringing this to our attention. The number of replicates generated for each dataset are now included in the methods section .1. In Figure 1D, Gene Ontology terms appear significant only for each of the individual datasets. While this might be expected for the 1h time-point, the 4hrs time-point comprises a big extent of the genes up-regulated at 1h as well, and it is surprising no term related to chromatin or transcription regulation appears as significant. Is this due to the fact that the analysis has been conducted with two separated lists of genes and only the top terms are shown without crossing the data? This could be misleading for the reader and maybe a comparative GO term analysis might be better such as using CluterProfiler or similar tools, that might allow for real comparison of terms enriched in each dataset.We thank the reviewer for pointing this out. For Figure 1d, GO term analysis was conducted with two separated gene lists, each consisting of timepoint-specific upregulated DEGs. Thus, 772 genes were included for the analysis of 4 h GO terms and 39 genes were included for the analysis of 1 h GO terms. Previously, comparisons of cellular component GO terms included in the current study only included the top 10 GO terms. The revised manuscript contains an updated analysis that compares all enriched GO terms and identifies that three of the top 10 cellular component GO terms for the 1 h gene set are also identified as significantly enriched in the 4 h gene set. We have revised the graph in Fig. 1f to reflect this updated analysis. Overall, our conclusions  remains supported by this analysis.1. In Figure 3D, the graphs show the density of motifs within the DARs in units of"Motifs/Kb/peak" while the x-axis represents the peaks coordinates from -500bp to +500bp. It is not clear to me how this graph is generated and how within 1000bp the profiles can reach values of 18-20 Motifs/Kb/peak. Could this be clarified?The motif enrichment score was calculated by identifying the number of total motifs within defined 50bp genomic bins surrounding the center of the DAR regions. HOMER builds enrichment histograms that normalize motif presence to set size , and also to genomic space (base pairs). While HOMER’s default histogram represents motifs/bp/peak, we converted this to motifs/kb/peak for ease of interpretation. However, to avoid confusion we have returned the y axis labels to the default HOMER settings (motifs/bp/peak). The normalization and units for this graph have been clarified in the methods section.1. In Figure 4C the newly generated ATAC-seq data is just "targeted" analyzed, showing global tendencies are maintained between the initial generated data and this one. It could be interesting, however, to see the number of DARs obtained in these conditions, especially to see if some DARs are observed in the Anisomycin condition that might be translation-independent.The experiment described in Figure 4 was designed to both validate the 5,312 DARs and understand the role of protein translation in activity-dependent chromatin remodeling. One way to begin identifying translation-independent DARs is to compare the DMSO + Vehicle group to the Anisomycin + KCl group. With this comparison, any 4 h DAR that has increased accessibility in the Anisomycin + KCl group may be translation-independent as pretreatment with anisomycin did not prevent chromatin remodeling. After conducting this analysis, we identified a very small percentage (3.44%) of 5,312 4 h DARs that still exhibited significantly increased accessibility when pre-treated with Anisomycin. This small number is consistent with the robust effects of anisomycin on KCl-dependent remodeling shown in Fig. 4c-d. However, to confirm that these were in fact translation-independent activity-regulated DARs, we would need to perform direct comparison of chromatin accessibility between neurons pre-treated with Anisomycin and then treated with either vehicle or KCl. Since we did not include an anisomycin only group in experiments in Fig. 4, we cannot confidently claim whether this 3.4% of DARs are translationindependent. Nevertheless, we agree with the reviewer that this is an interesting avenue of future exploration.Reviewer #3Public review1. Throughout the paper, the authors emphasize a "temporal decoupling" of transcriptional and chromatin response to depolarization, based on a lack of significant chromatin changes at 1h, despite IEG transcription. However, previous publications show significant chromatin remodeling at 1h  or 2h . The discussion briefly mentions this contrast, but it remains difficult to conclude decisively whether there is temporal decoupling when such decoupling is not found consistently. If one is to make broad conclusions about basic neural chromatin response to depolarization, it would be ideal to know under which conditions there is temporal decoupling, or if this is a region-specific phenomenon.Indeed, prior studies referred to in our manuscript have identified chromatin remodeling at earlier timepoints than we identified here. As addressed above , it is possible that this discrepancy arises due to the difference in experimental model system, differences in the type of stimulation applied, pretreatment protocols used to silence neurons prior to activation, or even differences in developmental stage. Differences in each of these parameters make it difficult to make straightforward comparisons between datasets and results in this manuscript. It is possible that other cell types induce IEGs more quickly (or more robustly) in response to stimulation, which could lead to earlier chromatin remodeling. However, the common patterns of chromatin reorganization  lend support for the idea that the transcriptional waves identified here can also be found in other cell types and in other contexts.1. The UMAP analysis is a novel way to probe transcription factor enrichment, but it's unclear what this is actually showing. The authors sought to ask whether "DARs could be separated based on transcription factor motifs in these regions." However, the motifs present in any genomic stretch are fixed based on genomic sequence, so it seems like this analysis might be asking whether certain motifs are more likely to be physically clustered together in the genome, in activity-regulated regions . While still potentially interesting, this analysis does not seem to give much additional insight into activity-dependent chromatin remodeling beyond the motif enrichment analysis already performed. Nevertheless, to draw stronger conclusions, it would be necessary to compare clustering to a random set of genomic regions of the same length/size to interpret the clustering here. It would also be useful to know whether the ISL1 motif is also enriched in ubiquitously accessible genomic regions in the striatum (and not just DARs).We agree that additional analysis is needed to explore enrichment of various transcription factor motifs and activity at differently accessible regions of the genome. The motif enrichment analysis in Figure 3 demonstrated the types of motifs that were enriched in DARs , the overall degree of enrichment , and the distribution of those motifs across DAR sites . This analysis allowed us to understand whether motifs for cell-defining transcription factors like ISL1 are enriched uniquely in DARs, or are also found in other regions that are accessible at baseline . However, these approaches represent enrichment across all DARs as group, and do not show TF presence/absence at any specific DAR. The UMAP analysis presented in Figure 3e allowed identification of DAR clusters based on the presence or absence of specific transcription factor motifs, and allowed us to represent specific DARs in a reduced two-dimensional space. Because this analysis identifies the existence of distinct motifs within single DARs, it allowed us to speculate as to the possibility of transcription factor cooperation within DARs, or the meaning of DAR clusters that appear to be defined by specific motifs . Given the information that this adds to the initial analyses, we argue that its inclusion in the manuscript is useful and potentially informative for generating follow-up hypotheses.1. The authors identify late-response gene enhancers by 3 criteria. However, only Pdyn was highlighted thereafter. How many putative DARs met these three criteria in striatum? Only Pdyn?As illustrated in Figures 2 and 4, nearly all of the DARs in our dataset met these criteria, which included presence in non-coding genomic regions, increase in accessibility following stimulation, and prevention of chromatin accessibility changes by protein synthesis inhibition. We did not mean to indicate that the Pdyn locus was unique in this way. In addition to the criteria highlighted in the manuscript, we chose this locus due to decades of literature establishing the importance of prodynorphin in the striatum, and the role of this gene in human neuropsychiatric diseases. We would argue that this increases the relevance of more detailed exploration of the regulator mechanisms that control expression of this gene, and makes our results applicable to a broader pre-existing literature. The revised manuscript includes additional experiments that examine Pdyn expression changes in response to different stimuli, which help to justify the focus on this gene from the beginning of the manuscript.Recommendations For The Authors1. Figure 1 volcano plots show a scatter primarily in the up-regulated portion at both the 1-h and 4-h time points. However, the Venn diagrams show largely similar numbers of up- and downregulated genes at the 4-h time point. Is the clustering of down-regulated genes tighter/more overlapping? If so, semi-translucent volcano dots or some acknowledgment of the visual discrepancy would be useful.We thank the reviewer for bringing this to our attention. Down-regulated genes are clustering tighter on the volcano plot due to smaller fold changes. This visual discrepancy is acknowledged by the numeric indicators of up- and down-regulated genes in the upper left-hand corner of the volcano plot.1. Methods for RNA and ATAC seq analysis align to human genome Hg38, rather than rat?RNA- and ATAC-Seq analyses from rat neurons were aligned to the mRatBn7.2/Rn7 rat genome. RNA- and ATAC-Seq analyses from human neurons were aligned to the Hg38 human genome. We have updated the methods to make this clear.1. The introduction states that different classes of neurons induce distinct LRGs. Please add a citation. Citations are also needed for the last statement WRT consequences of chromatin remodeling near LRGs not being concretely linked to LRG transcription.We thank the reviewer for pointing this out. The revised manuscript now includes additional citations supporting each of these statements.1. Specify somewhere in Methods that DEGs were compared to vehicle for both 1-h and 4-h (and not 4 vs 1 h).We thank the reviewer for bringing this to our attention. We have updated the methods to include: “DEGs were calculated by comparing the KCl and Vehicle treatment groups at each respective timepoint.”1. In Figure 2E, why are the enrichments exactly opposite, especially given these are two different types of input ?Odds ratios were calculated by comparing baseline peaks  to KCl-induced DARs. This allowed us to identify the enrichment of DARs in specific genomic annotations in comparison to the genomic features that are accessible at baseline, rather than making comparisons to random probe sets or genomic space dedicated to these distinct annotations. This analysis identified that relative to baseline peaks, DARs are significantly depleted in coding regions of the genome and enriched in non-coding regions of the genome. However, given this analysis we agree that it does not make sense to graph both the vehicle (baseline) and DARs on this graph, given that enrichment of each set is determined relative to the other . We have updated Fig. 2e to only include points for 4 h DARs.1. Some references are off. One that I noted was "...chromatin remodeling in the mouse dentate gyrus following 1 h of electricoconvulsive stimulation" should be Su et al 2017 not Malik 2014. For the statement that IEGs are critical regulators of non-neuronal IEGs, the authors may want to add Hrvatin 2017 ref.We thank the reviewer for bringing this to our attention. We have revised the manuscript to include the correct citation for this claim, and also to incude the Hrvatin, et al reference.1. It would be helpful for the authors to write out the whole gene name for Pdyn somewhere.We have updated the text to include the gene name for Pdyn, both in the abstract and also in the introduction of the manuscript.1. Figure 5f: For ease, please include what is high vs low in the figure caption in addition to the main text.We thank the reviewer for bringing this to our attention. We have updated the figure caption and main text to include what is high vs low in Pseudotime estimates in Fig. 5f.1. How are the tracks ordered in Fig8c?Tracks within Fig. 8c demonstrate snATAC-seq signal at the Pdyn gene locus for transcriptionally distinct cell types within the NAc. The tracks are ordered by cluster size (nuclei number) in the snATAC-seq dataset.


During early embryonic development, the RNA-binding protein CPEB mediates cytoplasmic polyadenylation and translational activation through a combinatorial code defined by the cy-toplasmic polyadenylation element (CPE) present in maternal mRNAs. However, in non-neuronal somatic cells, CPEB accelerates deadenylation to repress translation of the target, including c-myc mRNA, through an ill-defined cis-regulatory mechanism. Using RNA mutagenesis and electrophoretic mobility shift assays, we demonstrated that a combination of tandemly arranged consensus (cCPE) and non-consensus (ncCPE) cytoplasmic polyadenylation elements (CPEs) constituted a combinatorial code for CPEB-mediated c-myc mRNA decay. CPEB binds to cCPEs with high affinity (Kd = ~250 nM), whereas it binds to ncCPEs with low affinity (Kd > ~900 nM). CPEB binding to a cCPE enhances CPEB binding to the proximal ncCPE. In contrast, while a cCPE did not activate mRNA degradation, an ncCPE was essential for the induction of degradation, and a combination of a cCPE and ncCPEs further promoted degradation. Based on these findings, we propose a model in which the high-affinity binding of CPEB to the cCPE accelerates the binding of the second CPEB to the ncCPEs, resulting in the recruitment of deadenylases, acceleration of deadenylation, and repression of c-myc mRNAs. Gene expression levels are often determined post-transcriptionally by the act of RNA-binding proteins (RBPs). Various RBPs regulate mRNA translation and stability in the cytoplasm, largely affecting cellular protein levels . RegulatCPEB is a well-characterized RNA-binding protein that regulates mRNA translation via cytoplasmic polyadenylation ,11. CPEBIn addition to CPEB’s role in cytoplasmic polyadenylation, we previously showed that CPEB destabilizes and represses the translation of c-myc mRNA by accelerating deadenylation in human cells . c-myc mIn the present study, we identified an RNA sequence encoding CPEB-mediated decay. We prepared various c-myc reporters with 3′UTR mutations and evaluated the effect of CPEB on the level of reporter mRNAs as well as CPEB-binding affinities. Our findings indicated that ncCPEs are indispensable for c-myc mRNA decay, but CPEB exhibits a low affinity for them. Detailed in vitro RNA-protein-binding assays revealed that a CPEB bound to a cCPE can enhance a second CPEB binding to an ncCPE. This study highlights the importance of the composition of CPEB binding elements in c-myc mRNA decay.The construction of pHA-CPEB, pCMV-5×myc-CPEB, pCMV-5×Flag-CPEB, pMAL-cRI-CPEB, and pFlag-CMV5/TO-BGG c-myc 3′UTR was described previously . HA-taggNorthern and Western blotting analyses were performed as described previously .HeLa cells were cultured in Dulbecco’s modified Eagle’s medium  supplemented with 5% fetal bovine serum. Transfection of plasmid DNA was performed using Lipofectamine 2000  as previously described .Lentiviruses were produced using the lentiviral vectors with the packaging vectors pSPAX2 and pMD2.G in LentiX-293T cells . Transfection was performed in 6 cm dishes using the PEI-Max reagent  according to the manufacturer’s instructions. Four hours after transfection, the medium was replaced with fresh DMEM containing 10% FBS, and the virus-containing medium was collected and filtered two days later.32P-UTP. A 15 fmol portion of a 32P-labeled, gel-purified RNA probe was denatured at 65 °C for 10 min and cooled to room temperature. The refolded RNA was incubated with MBP fusion proteins in an RNP binding buffer  at a final volume of 10 μL. The binding reaction mixture was then incubated at room temperature for 40 min. Heparin (50 ng) was added. The binding reaction (5 μL) was run in a 5% non-denaturing polyacrylamide gel in a 0.5 × TBE buffer. The gels were dried on a filter using a RAPIDDRY-MINI , and the bands were detected by autoradiography. Band intensities were estimated using MultiGauge software .For REMSA, wild-type or mutant c-myc 3′UTR RNAs were transcribed from PCR-amplified DNA templates using T7 RNA polymerase  in the presence of cis-regulatory elements.We have previously reported that CPEB promotes the deadenylation and decay of c-myc mRNA ; it is wTo determine the sequence elements of the c-myc 3′UTR required for CPEB-mediated decay, we first constructed two reporter genes appended with c-myc 3′UTR deletion mutants  was performed using radiolabeled c-myc 3′UTR pA2 RNA probes and a recombinant MBP-CPEB protein. To estimate the binding affinity of each possible CPEB-binding sequence, we prepared various combinations of c-myc 3′UTR mutant transcripts. As expected, CPEB showed a higher affinity for CPEs d.Intriguingly, when using a wild-type RNA probe, the binding of two CPEB molecules was observed a. The facis-regulatory elements remains limited. In this study, we found that a combination of tandemly arranged cCPE and ncCPE elements was involved in CPEB-mediated c-myc mRNA decay. In contrast to the combinatorial code demonstrated for CPEB-mediated cytoplasmic polyadenylation, the cCPE alone did not induce CPEB-mediated degradation of the c-myc reporter mRNA. CPEB bound to an ncCPE is responsible for the onset of c-myc mRNA decay. Consistent with this idea, when an ncCPE was inserted into the 3′UTR of p53 mRNA, the artificial cCPE-ncCPE chimeric code accelerated the degradation of p53 mRNA (The understanding of the RBP-binding sequences and the functions and composition of RBP-containing protein complexes has progressed remarkably; however, knowledge regarding the combinatorial effects of p53 mRNA . Additiop53 mRNA . FurtherIn summary, we identified a characteristic RNA sequence code for CPEB-mediated c-myc mRNA decay, which consists of consensus and non-consensus CPEs and provides novel insight into how RBP may regulate mRNA metabolisms depending on the contexture of the RNA sequence motifs.


Arabidopsis leaf epidermis, meristemoids undergo a series of stereotyped cell divisions, then switch fate to commit to stomatal differentiation. Newly created or reanalyzed scRNA-seq and ChIP-seq data confirm that stomatal development involves distinctive phases of transcriptional regulation and that differentially regulated genes are bound by the stomatal basic-helix-loop-helix (bHLH) TFs. Targets of the bHLHs often reside in repressive chromatin before activation. MNase-seq evidence further suggests that the repressive state can be overcome and remodeled upon activation by specific stomatal bHLHs. We propose that chromatin remodeling is mediated through the recruitment of a set of physical interactors that we identified through proximity labeling – the ATPase-dependent chromatin remodeling SWI/SNF complex and the histone acetyltransferase HAC1. The bHLHs and chromatin remodelers localize to overlapping genomic regions in a hierarchical order. Furthermore, plants with stage-specific knock-down of the SWI/SNF components or HAC1 fail to activate specific bHLH targets and display stomatal development defects. Together these data converge on a model for how stomatal TFs and epigenetic machinery cooperatively regulate transcription and chromatin remodeling during progressive fate specification.The development of multi-cellular organisms requires coordinated changes in gene expression that are often mediated by the interaction between transcription factors (TFs) and their corresponding cis-regulatory elements (CREs). During development and differentiation, the accessibility of CREs is dynamically modulated by the epigenome. How the epigenome, CREs and TFs together exert control over cell fate commitment remains to be fully understood. In the  Unraveling the regulatory mechanisms of developmentally important transcriptional programs during fate specification is therefore important for understanding development and is a key step towards reprogramming cells for different applications.Cells integrate a wide range of internal and external cues to execute complex patterns of gene expression. During development and processes such as wound healing and tissue regeneration, coordinated global changes in transcription lead to the formation of diverse types of cells with different fates. Disruption of such controlled gene expression can cause a variety of developmental and growth defects and can be lethal in extreme cases2. To initiate transcription, CREs are accessed by TFs, which then recruit cofactors to facilitate the assembly of the transcription machinery. Differential accessibility of CREs, therefore, lies at the core of executing cell type-specific gene expression programs. To regulate CRE accessibility, eukaryotes have complex and conserved mechanisms at the chromatin level. Open chromatin regions, which allow TFs to bind to the CREs, typically display low nucleosome density or nucleosome-free regions, while closed chromatin is tightly packed with a high nucleosome density3. Another level of regulation comes from histone variants and post-translational modifications of histone tails within the nucleosome. Active chromatin usually displays a combination of modifications such as H3K27ac and H3K4me3, and variants of core histone proteins such as H2A.Z and H3.37. Transcriptionally inactive genes, on the other hand, are localized within closed chromatin regions that are usually marked by repressive histone modifications such as H3K27me3 and H3K9me35.With all cells possessing identical genetic information, divergence in the transcriptome during fate transition is attributed to the complex interactions between cis-regulatory DNA elements (CREs) and transcription factors (TFs)9 and transcriptionally12. When and how such priming occurs are questions best answered by characterizing biologically relevant variations between single cells. In cell differentiation contexts, entropy has been introduced as a measure of variability, with the assumption that cell populations under strict regulatory constraints should exhibit well-defined and low entropy expression patterns, whereas those under weaker regulatory constraints should show diverse, higher entropy expression patterns15. Transcription factors (TFs) that are involved in priming cell fate can be identified using entropy as a method16.Before cell fate transition, progenitor cells are primed for distinct cell identities epigenetically17. Such TFs are thus crucial for the initiation of new cell fates, given the compact nature of DNA packaging. In plants, such activity has so far only been reported for LEAFY (LFY)18, a TF that is indispensable for flower development19. This was a landmark result, but for technical reasons, the chromatin remodeling function of LFY in fate specification was characterized in root explants, a callus-based regeneration system where sizable epigenetic reprogramming has occurred during the dedifferentiation process20. It remains to be shown whether plant TFs are able to reshape the native chromatin landscape in endogenous developmental pathways, and if so, how.While entropy measures can reveal state changes, we are still faced with the question how CREs in silent chromatin are first accessed and chromatin states reprogrammed. In addition to the epigenetic machinery, special “pioneer” TFs that are capable of binding nucleosomal (closed) CREs have been shown to override repressive chromatin states, initiate the remodeling of the epigenome and pave the way for the transcriptional machinery and other TFs to activate gene expression in animal systems 24. Expression of SPCH marks the entry into the stomatal lineage, creating a meristemoid that is capable of self-renewing through asymmetric cell divisions (ACDs)22. Activation of MUTE puts an end to ACDs and the transition from meristemoids to guard mother cell (GMC) fate22. The GMC undergoes a single symmetric cell division (SCD), and under the guidance of FAMA, creates a pair of cells that differentiate into the GC complex23. Mis-regulation of each stage-specific stomatal bHLH factor has a significant and characteristic impact on cell fate and development. Overexpression of SPCH induces precursor cell over-proliferation, whereas MUTE overexpression forces epidermal cells to adopt GMC-like fates, and subsequently divide into paired stomatal guard cells 22. Similarly, the gain-of-function scrm-D allele causes all epidermal cells to become guard cells24. Guard cell differentiation remains dependent on intact FAMA activity in these situations, and overexpression of FAMA can also promote transdifferentiation into cell with guard cell identity, albeit without cell division, so the stomata are not functional23. The competence of MUTE, FAMA and SCRM to direct cells toward guard cell fate makes them appealing candidates in breaking the barrier of repressive chromatin to activate gene expression during stomatal development.To address these open questions, we turned to stomatal development where, a simple and stereotyped lineage exhibits clear fate transitions guided by well-characterized transcription factors. Stomata are leaf pores surrounded by a pair of epidermal guard cells (GCs). Fate transitions during stomatal development require the activity of heterodimeric basic helix-loop-helix (bHLH) TF complexes consisting of one of three stage-specific bHLHs-SPEECHLESS (SPCH), MUTE or FAMA, and either SCREAM  or SCRM2, two redundant partners expressed throughout the lineage and required at each stageBy analyzing transcriptional entropy in stomatal lineage single cell RNA-seq data, we identify different phases of transcriptional regulation during stomatal development. Furthermore, we show that MUTE, FAMA and SCRM indeed can overcome repressive chromatin and each has the potential to induce nucleosome repositioning during these phases. Chromatin remodeling is potentially mediated by the SWITCH DEFECTIVE/SUCROSE NON-FERMENTABLE (SWI/SNF) complex and the histone acetyltransferase HAC1, both of which physically associate with the bHLHs in stomatal lineage cells. Stomatal lineage-specific knock down of components of the SWI/SNF complex or HAC1 results in reduced expression of the bHLHs’ targets and plants that are impaired in forming terminally differentiated stomata. Together, we provide compelling evidence of cell type-specific chromatin remodeling during plant development and lay the foundation for studying the mechanism of how dynamic interactions between CREs, TFs and epigenetic machinery mediate fate transitions in plants.25. Such biologically relevant heterogeneity can generally be attributed to cells in states of different plasticity15. The computation of transcriptional entropy, which quantifies the degree of uncertainty of a cell’s gene expression levels, has been used to measure cellular plasticity and can provide a robust proxy for the differentiation potential of a cell in Waddington’s epigenetic landscape13. In pluripotent animal cells with weak transcriptional regulation, more genes are expressed in a relatively homogeneous way, resulting in high entropy, while in more differentiated cells, transcriptional regulation is more constrained, displaying well-defined and low entropy expression patterns  data. This included published data for SPCH, MUTE and SCRM30 and a newly generated ChIP-seq dataset of FAMA . In reprogrammed GCs, targets of MUTE, FAMA and SCRM, but not of SPCH, were highly H3K27-trimethylated  datasets of tissues derived from meristemoids tissues . We thenthylated –d. This thylated . These dthylated . Levels 38. To put these data in context, we used LFY, a known nucleosome binder as a positive control and PIF4, a bHLH factor not known to bind nucleosomes, as a negative control. Nucleosome density was comparable among LFY, FAMA and SPCH targets, but MUTE and SCRM targets displayed a much higher nucleosomal signal  more enriched in SCRM binding -based proximity labeling to identify proteins associated with SCRM in its native context. Comparison of the complementing SCRM-TbID line with the cell-type specific controls and untreated SCRM-TbID samples revealed an enrichment of multiple subunits of the SWI/SNF chromatin remodeling complex, including the core ATPase BRAHMA (BRM), a core bromodomain-containing protein, BRD1, two regulatory subunits SWI3C and SWI3D, and several accessory proteins that have previously been found as part of the plant SWI/SNF complexes   . Interesid (Y2H) . Interacid (Y2H)  and bimoid (Y2H) , suggestid (Y2H)  and b). 51 revealed that both are expressed in the stomatal lineage and bind to a large proportion of the stomatal lineage bHLH ChIP-seq peaks  for the bHLHs, BRM and BRD1 within 50 bp from their peak centers  for the SWI/SNF genes  factors  and S6. e of GCs . These aenotypes .56. pAtML1 expression decreases in maturing tissue and a reporter ML1p::RCI2A-mCherry becomes undetectable in wild-type mature GCs , an HD-ZIP class IV TF, is preferentially expressed in the epidermal layer and is required for epidermal cell differentiationture GCs . In GCs  all GCs , suggestAi lines –d. ConcoAi lines . DepletipFAMA SWI/SNF or HAC1 amiRNAi lines , should cause premature disappearance of the FAMA-YFP signal. Indeed, these lines lost FAMA-YFP signal in very young GCs , to promote neurogenesis, and as a heterodimer with the ubiquitously expressed E12α, to reprogram fibroblast to mature into neuronal cells60. Similar to E12α, SCRM is expressed throughout the stomatal lineage. This opens the question whether the repressive chromatin association features we identified for SCRM are a result of heterodimerization with MUTE and FAMA, or vice versa, and whether the three of them can overcome repressive chromatin barriers by themselves. Although these bHLHs likely do not form homodimers under normal circumstances, one could try to force homodimerization of individual bHLHs and examine their affinity to nucleosomal DNA to answer this question.While the stomatal lineage bHLHs share common features with animal pioneer factors, they are unusual in the sense that the MUTE-SCRM and FAMA-SCRM heterodimers function together as a single unit for which the binding affinity at nucleosome-occupied regions is high. Interestingly, heterodimerization of the animal bHLH-type pioneering factor ASCL1 with E12α also greatly increases its affinity for nucleosome bindingof ASCL1 . Both th23. The phenotype of the ‘short-lived FAMA’ line , suggests termination of the GMC cell division program and GC fate commitment are two separate functions of FAMA  SPCHp::TbID-YFPnls, (described below), FAMAp::TbID-YFPnls50.All plants in this study were germinated and grown on half-strength Murashige and Skoog (1/2MS) agar (0.8%) plates under standard growth conditions  in a Percival growth chamber for 3, 5, 7, 10 or 21 days, according to the experimental purposes. The following plant materials were used in this study : Col-0 wild type (WT), FAMApro::amiRNA constructs, artificial microRNA sequences were designed for control miRNA, HAC1, BRM or SWI3C with WMD3 (http://wmd3.weigelworld.org) and amplified through the website’s standard protocol using the pRS300 plasmid as a template. pDONR-L4-FAMApro-R162, pENTR_L1-amiRNAi-L2 and R4pGWB501 or R4pGWB60165 were recombined. Constructs were transformed into ML1pro::mCherry-RCI2A or ML1pro::YFP-RCI2A63 lines. The short-lived FAMA line is an individual line that harbors the same construct as FAMApro::gFAMA-YFP/fama-161 but expresses gFAMA-YFP for a shorter period of time. The SCRMp::SCRM-TbID-Venus construct was generated by recombining pENTR 5’-L4-SCRMpro-R1 ,pENTR/D-L1-SCRM-L2 (containing SCRM amplified from Arabidopsis cDNA), pDONR R2-Turbo-mVenus-STOP-R350 and pB7m34GW,066 and transformed into ice1-2 +/− (SALK_00315) plants. Lines homozygous for the transgene and ice1-2 were selected in T2 and T3. pDONR. SPCHp::TbID-YFPnls was recombined from pENTR-L4-SPCHpro-R166, pENTR L1-Turbo-YFP-NLS-STOP-L250 and R4pGWB60165 and transformed into Col-0 wt. All constructs were transformed by floral dipping67 using the Agrobacterium strain GV3101.The constructs described here were created using Gateway LR recombination (Invitrogen 12538120). For 68. Briefly, 25 g of 4-day-old whole seedlings of FAMApro::FAMA-MYC/fama-136 and Col  were used. Samples were processed in standardsized aliquots during crosslinking, nuclei isolation and DNA fragmentation steps before combining for immunoprecipitation. Chromatin was fragmented by a Bioruptor (Diagenode) programed at high intensity for 3 x 7.5 min (cycles of 30 s on and 30 s off) at 4°C. Immunoprecipitation was performed with a monoclonal anti-MYC antibody , followed by incubation with magnetic beads . Immunoprecipitated DNA was purified by the ChIP DNA Clean & Concentrator (Zymo). Libraries were constructed using the Nugen Ovation Ultralow Library System following the manufacturer’s protocol. Col ChIP DNA was used as a control. Libraries were sequenced 50bp with single end on an Illumina HiSeq 2000. LFY, SPCH, MUTE, SCRM, PIF4, BRM, BRD1, H3K27me3 and H3K4me3 ChIP-seq datasets were retrieved from GEO dataset . Nuclei were then treated with 0.5 U/ul final concentration of Micrococcal Nuclease (NEB) in digestion buffer ) for 3 min at 37°C. Digestion was stopped with 10 mM EDTA and treated with Proteinase K (Roche). DNA was purified with phenol:chlorophorm:isoamyl alcohol (25:24:1) extraction and precipitated with 1/10 volume of 5 M sodium acetate and 2 volumes of ethanol. Purified DNA was run on 2% agarose gel and bands corresponding to ~150 bp were cut and purified with a Gel Purification kit (Promega). Libraries were constructed using the Nugen Ovation Ultralow Library System V2 following the manufacturer’s protocol. 75 bp of pair-end reads were sequenced on NextSeq 4000.3.5 dpg 69Arabidopsis genome using bowtie270. PCR duplicates were removed by Samtools71. Uniquely mapped reads were retained for peak calling using the MACS231 and for metaplots. Each ChIP contained at least 2 biological replicates. MACS231 was run using default settings and peaks with a FDR cutoff of 10−6 over Col control were selected. De-novo motif discovery was conducted using the findMotifsGenome function of HOMER72 with sequences that are 200bp surrounding the summits of peaks. Genes were annotated by ChIPseeker32 with a 3kb cutoff. Reads pile-up were calculated by bedtools73 and fold changes were calculated by DEseq274.ChIP-seq reads were mapped to the TAIR1075 pipeline with the same parameter as described in reference 13:13.scRNA-seq datasets were analyzed using standard Seurat77. BigWig files of the mapped reads were visualized by the Integrative Genomics Viewer (IGV)78.The stomatal bHLHs’ targets were determined by incorporating scRNA-seq datasets with the ChIPseq data sets. Specifically, genes that are expressed in at least 25% of cells that express specific stomatal bHLHs with a log2(fold change) of at least 0.223 were assigned as targets if they have at least one binding site of the corresponding bHLH. Heat maps and metaplot profiles of relative enrichment (log2 ChIP/Input) at defined genomic regions were generated by deeptools79 was used to identify nucleosome occupied regions using q < 10–50 as cutoff. ATAC-seq datasets in different types of tissue were retrieved from published data  mapping is performed with pair-end mode, 2) DANPOSdata see . Data pr50 with minor modifications. Briefly, 5 day old Col-0 WT, SCRMp::SCRM-TbID-Venus, SPCHp::TbID-YFPnls and FAMAp::TbID-YFPnls seedlings, grown on ½ MS plates with 0.5 % sucrose were submerged in liquid ½ MS medium with or without 50 μM biotin for three and 2.5 hours, respectively. Proteins were extracted from ~1.3g plant material with buffer 1 , cleared from debris by centrifugation and free biotin was depleted by buffer exchange to buffer 2  using PD-10 desalting columns . 14 mg protein were used for pulldowns with 200 μl streptavidin beads . Beads were washed twice with cold buffer 2, twice each with cold buffer 2 containing 500 mM and 1 M NaCl, once each with buffer 3  and 4 , once with cold 50 mM Tris pH 7.5 and stored at −80 °C. For on-beads digest, beads were washed again with 50 mM Tris pH 7.5 and once with 50 mM Tris pH 7.5, 1 M Urea. Trypsin digest and desalting and LC-MS were done as previously described. Protein identification and label-free quantification (LFQ) were done with MaxQuant (version 1.6.8.0)81 with standard settings, fast LFQ disabled and a LFQ min. ratio count of 1, searching against the TAIR10 database . Data filtering and statistical analysis were done in Perseus (version 1.6.2.3)82. LFQ values were log2 transformed and missing values were imputed from normal distribution using total matrix mode and standard settings. SCRM-TbID-enriched proteins were identified by consecutive pairwise comparisons with the controls . Proteins enriched versus WT (FDR = 0.05) were further tested for enrichment versus SPCHp and FAMAp driven nuclear TbID and untreated SCRM-TbID samples (FDR = 0.1). To compensate for higher expression of TbID by the FAMA promoter, protein LFQs values were normalized to TbID in each sample for this comparison. Proteins enriched versus all controls and identified by MS/MS were considered high confidence candidates.Proximity labeling with three replicates per line and condition was performed as previously describedSCRM, SCRM2, SPCH, MUTE, FAMA, BRM, BRD1, SWI3C, SWI3D, BRIP2, SWP73B, LUH, and HAC1 were amplified from Arabidopsis thaliana cDNA and cloned into pGAD-T7 or pGBK-T7 (Clontech). Combinations of bait end pray plasmids were then co-transformed into yeast strain AH109 and positive transformants were selected for by growth on synthetic dropout (SD) medium without leucine and tryptophane (-LT). Bait-prey interaction was tested by growth complementation assays on SD medium without leucine, tryptophane, histidine and adenine (-LTHA) as described in the Matchmaker™ GAL4 Two-Hybrid System 3 manual (Clontech). To overcome auto-activation from some of the constructs, 3-Amino-1,2,4-triazole (3-AT) was added to nutrient selection plates at different concentrations.The full length coding sequences of SCRM, MUTE, FAMA, and HAC1 were first cloned into pENTR/D-TOPO using TOPO cloning and then subcloned into pDEST-GW-VYCE and pDEST-VYCE(R)-GW for C- and N-terminal YFP-C fusions  or into pDEST-GW-VYNE and pDEST-VYNE(R)-GW for C- and N-terminal YFP-N fusions  using Gateway LR recombination83. Plasmids were transformed into Agrobacteria (strain GV3101). For BiFC, Agrobacteria from an overnight culture were diluted in LB medium containing antibiotics and grown for two hours, pelleted, resuspended in LB medium supplemented with 150 μM Acetosyringone and grown for another four hours at 30 °C, pelleted again and resuspended in a 5 % sucrose solution to an OD600 of 2. A YFP-C and a YFP-N fusion-containing suspension were mixed with a suspension of Agrobacteria containing a 35S::p19 plasmid (tomato bushy stunt virus (TBSV) protein; suppresses silencing) at a 1:1:0.5 ratio and infiltrated into young Nicotiana benthamiana leaves. Three leaves were infiltrated per protein pair to test, with all four possible combinations infiltrated on different quadrants of the same leaf for improved comparability. Two days after infiltration, leaf sections were imaged on a Leica Stellaris confocal microscope with HyD detectors using a 25x water objective, retaining the same settings for all images. Images were visualized using fire LUT (Look Up Table) in Fiji84 setting display range for brightness from 0-100 or 0-1000 for all images.Coding sequences of ML1pro::mCherry-RCI2A or ML1p::YFP-RCI2A63. ML1 promoter activity was visualized by ML1pro::mCherry-RCI2A. For GC phenotype quantification, cotyledons of 21 dpg plants were cleared in 7:1 ethanol:acetic acid solution and mounted in Hoyer’s solution. DIC images of the entire cotyledon were taken with a Leica DMi8 inverted scope using a 20x objective and the tiling function. All visible GCs on the abaxial side of the cotyledons were counted and classified. For each line, between two and five cotyledons were scored. Detailed images of GCs were taken with a 40x objective. All images were processed in ImageJ/Fiji84.Confocal images were taken with a Leica SP5 or Stellaris confocal microscope. Cell outlines were visualized by propidium iodide staining  or the plasma membrane markers FAMApro::amiHAC1 and FAMApro::amiBRM plants 14 dpg. RNA was extracted using the RNeasy Mini kit (Qiagen 74004) coupled with Dnase I treatment (Qiagen 79254) following the manufacturer’s instructions. For each replicate, 2 ug RNA was used to synthesize cDNA with the iScript™ cDNA Synthesis Kit (Bio-Rad 1708890). The SsoAdvanced™ Universal SYBR® Green Supermix (Bio-Rad 1725271) was used for qPCR, which was performed on a CFX96™ Real Time System (Bio-Rad).50 mg of true leaves for each replicate and three replicates were harvested from Col, https://www.rcsb.org/, PDB: 1kx5). The structures of bHLH dimers were modelled onto existing 3D structures of DNA-bound bHLH dimers using SWISS-model: HsMyoG was modelled on mouse MyoD (PDB: 1mdy) and the HsAsclI-HsTcf3(E12a) dimer was modelled on mouse NeuroD1-Tcf3 (PDB: 2ql2) as previously published60. For the SCRM dimers, multiple models were built and the model with the best score , human Mad-Max (PDB: 1nlw), was chosen for display. The structures were visualized in PyMOL (https://pymol.org/2/). Modelled dimers are shown with the DNA of their model template. Because helix length varied slightly between different models based on the template, helix length in the selected SWISS-model models were further compared to helix predictions from PSIPRED 4.0 (http://bioinf.cs.ucl.ac.uk/psipred)85 and AlphaFold87 .The 3D crystal structure of the nucleosome was retrieved from the protein data bank (1