E. coli PhoB-PhoR two-component system, which overcomes the cost of positive feedback and achieves both fast and optimal steadystate response for maximal fitness across different environments. Quantitation of the cellular activities enables accurate modeling of the response dynamics to describe how requirements for optimal protein concentrations place limits on response speed. An observed fast response that exceeds the limit led to the prediction and discovery of a coupled negative autoregulation, which allows fast gene expression without increasing steady-state levels. We demonstrate the fitness advantages for the coupled feedbacks in both dynamic and stable environments. Such regulatory schemes offer great flexibility for accurate control of gene expression levels and dynamics upon environmental changes.A fundamental trade-off between rapid response and optimal expression of genes below cytotoxic levels exists for many signaling circuits, particularly for positively autoregulated systems with an inherent response delay. Here, we describe a regulatory scheme in the  Positive autoregulation of transcription produces a delayed response. Gao and Stock describe the limit of response delay caused by requirements of optimal protein levels in the PhoBR twocomponent system. Coupled negative autoregulation is discovered to allow a strong promoter for fast response without incurring cost of increasing protein expression levels.  Cells have evolved complex gene regulatory networks to produce appropriate amounts of proteins at appropriate times to adapt to ever-changing environments. A few recurring network motifs, such as feed-forward loops and autoregulatory circuits, constitute the basic building blocks for more sophisticated regulatory networks . MoleculEscherichia coli, approximately half are autoregulated, and of these, ~30 TFs are positively autoregulated (Positive autoregulation occurs when a transcription factor (TF) activates its own expression. It has been established that positive autoregulation can increase the sensitivity to signals, produce a switch-like response, and promote bistability, history-dependent hysteretic responses, or memory . Positivegulated . The freE. coli belong to the family of two-component systems (TCSs) and positive autoregulation is more common than negative autoregulation in TCSs  concentrations and modulates its activities, including the autokinase, phosphotransferase, and phosphatase activities, to control the phosphorylation level of the RR transcription factor PhoB  cells causes a response delay, however, the delay is not as severe as predicted by the model. A coupled negative feedback through auto-repression of the phoB promoter was discovered to overcome the cost of positive autoregulation by enabling promoter features that reduce the response delay. Unlike autoregulatory variants that have only positive feedback and cannot resolve the trade-off between response speed and amplitude, the coupled feedbacks enable WT cells to achieve fast response speed as well as optimal expression levels for greater fitness.In this study, by measuring E. coli phoBR system, we examined the activation dynamics of the phoA-yfp reporter upon Pi starvation. The phoA promoter activity is calculated as the optical density (OD) normalized first derivative of YFP fluorescence and it has been shown to faithfully track with PhoB phosphorylation output  and the transcription feedback that determines the expression of phoBR   . The affr assays  and thusr assays . Strengtpromoter . The respromoter  to gener Figures  and S3.PphoB) expressed PhoB rapidly and the kinetics were much faster than the model predicted  showed only a marginal increase in PhoB expression speed . Autoregulated promoter strength determines both the kinetics and steady-state expression level of PhoB. High promoter strength can increase the expression speed of PhoB and reduce the rising time  of Pi starvation, but it eventually results in a higher steady-state PhoB level than that of WT . Indeed, phoB promoter activity decreased sharply after the initial increase upon Pi starvation   that displayed little binding to PhoB~P  of PhoB~P for the activation site. Low affinity for the repression site (KRP) causes the negative feedback to be effective later when PhoB~P becomes sufficiently abundant to occupy the 10 region.Given the presence of a repression site in addition to the previously established activation site, a coupled feedback model was built to understand expression kinetics of the R operon . Once thphoB-rp2, is ~2-fold that of WT  leads to very low expression of PhoB. This coupled feedback system offers multiple adjustable elements that provide great flexibility in controlling expression kinetics and output levels. As discussed earlier, an optimal PhoB expression level requires a corresponding promoter strength, which places a limit on PhoB expression rising time in a model with only positive feedback. The coupled negative feedback allows high promoter strength to exceed the rising-time limit. Combinations of different values of promoter strengths and PhoB affinities can enable a full range of diverse expression kinetics, all with similar steady-state PhoB levels  in continuous cultures   , and cpx E. coli . Strong Promoter strength affects response speed as well as steadystate expression levels of TCSs. Optimal steady-state levels of TCS proteins are correlated with the concentration-dependent RRP output profiles, which are determined by intrinsic TCS enzyme activities , 2013b. Response acceleration by negative feedbacks has been described in many systems . It has Vibrio cholerae .Further information and requests for resources and reagents should be directed to and will be fulfilled by the corresponding author Ann M. Stock  as the nitrogen source. For continuous cultures, amino acids were not added and the concentration of NH4Cl was reduced to 250 μM to limit the culture growth  of ~0.04 and the steady OD of the continuous culture were ~0.08.Bacteria were grown at 37°C in LB broth or MOPS minimal media  with 0.4escribed . Plasmide growth . Phosphae growth . The dilphoB-rp-hi; RG280-f and RG281-r for phoB-rp2; RG282-f and RG283-r for phoB-rp1. Recombinant PCR fragments were digested with PstI/XbaI and cloned into pJZG202 to give pRG367, 368 and 369. Individual promoter fragments corresponding to PphoBwt and PphoB-rp2 were then excised and ligated with a promoter-less phoBR fragment followed by insertion into SphI/SmaI-digested pAH144 to give pRG390 and pRG391.To generate promoter mutants with altered PhoB repression sites, the following primers were used for site-directed mutagenesis with pJZG202 as PCR template: RG278-f and RG279-r for phoB-rp2 variants with reduced promoter strength, primer RG294-f and the degenerate primer RG293-r were used to generate recombinant PCR fragments with random mutations at two positions in the 10 region of phoB promoter. The resulting DNA fragments were ligated into the PstI and XbaI sites of pJZG202 and screened for reporter activities that were comparable to that of the WT phoB promoter. One such clone with a sequence of CATGAT at the 10 region was selected and designated as pRG387. PCR fragments containing either the phnC promoter or the promoter region of pRG387 were fused with phoBR by recombinant PCR and inserted into the BsrGI and SphI sites of pRG390 to give pRG396 and pRG393. The four integration plasmids, pRG390, 391, 393 and 396, were integrated into the chromosome of RU1621 at the HK022 phage attachment site (phoBwt), RU1879 (phoB-rp2), RU1880 (phoB-rp2-dn) and RU1881 (phnC).To screen for ent site  to creatPtet-cfp was excised from a pRG252-derived plasmid and inserted into pRG22 to give pRG411, the CFP-expressing marker plasmid. Primers RG322-f and RG323-r were used to introduce site-specific mutations into the cfp gene of pRG411. The resulting plasmid pRG426 has a non-fluorescent CFP protein (CFP T65A W66S G67A) expressed from the Ptet promoter, enabling the differentiation of fluorescent cells that carry pRG411.To evaluate cell fitness in bacterial competition assays, a DNA fragment containing 2PO4) MOPS media. Once the OD reached 0.3–0.5, bacteria were harvested and washed with MOPS medium  twice and directly resuspended in MOPS medium  for Pi starvation. The starting OD was typically between 0.1–0.2. To enable simultaneous PhoB induction and Pi starvation shown in Cells from overnight MOPS batch cultures were used to inoculate fresh Pi-replete (1 mM KHin vivo phosphorylation levels were measured using previously established procedures (PhoB expression and ocedures . SpecifiphoBwt) after 120 min of Pi starvation, was used as a reference sample in each blot for comparison to all other samples. The steadystate PhoB concentration of the WT strain has been determined previously  as the primary antibody and a Cy5-conjugated goat anti-rabbit IgG (1:5000) as the secondary antibody. Fluorescent blots were visualized using a FluorChem Q imager (Alpha Innotech) and quantified by ImageJ . For Phoeviously , thus alnd order Lagrange interpolating polynomial using the following equation,f (ti) represents the fluorescence at the ith time point. The first derivatives were normalized to the OD to represent the promoter activity [(dFluo./dt)/OD].Inoculated cultures in 96-well plates were continuously assayed for YFP fluorescence  and OD 600 nm using a Varioskan plate reader (Thermo Scientific) with constant shaking. Fluorescence and OD readings were smoothed with a moving average of three time points for further analyses. First derivatives of fluorescence (dFluo./dt) were calculated numerically as described  by diffeTo analyze the dependence of reporter activities (Fluo./OD) on PhoB expression levels Figures , a slighPhoB-binding sites  were used for EMSA with phosphorylated PhoB proteins as described previously (0-GCTCACCA TTTGTATATCTCCTTC was used in combination with other promoter-specific primers to generate fluorescent DNA fragments containing either the phoB or phnC promoters. PCR products were purified with QIAquick columns (QIAGEN) and used for subsequent EMSA assays. For binding analyses of the phoB promoter repression site, fluorescein-labeled oligos were used instead of the full length of the promoter. DNA concentrations were determined by absorbance reading at 260nm using Nanodrop. DNA sequences used for EMSA are shown below with PhoB-binding sites underlined and lower case letters indicating common DNA sequences from the reporter vector:DNA fragments labeled with 5eviously . RG-FAM-AATTAACCAAATCGTCACAATAATCCG CCACGATGGAGCCACTTTTTTAGGGAGGCTGCATCATGCAAACGATTtgatctagaaataattttgtttaactttaagaaggagatatacaaatggtgagcCTGCAGGAAGAAGGAAAACGCTGGTTTGACAATCTTGCCGCTAACGGAAAAATCGAAATGGCCTGGCAGGAAACTTTCTGGGCGC ATGGCTTTGGCAAAGTCACCGATAAATTTGGCGTACCGTGGATGATTAATGTCGTCAAACAACAACCAACGCAATAACCCGCCGGG AGGCCCGCCCTCCCGCACTGTCATCGAATTCCCGTTAACTCTTCATCTGTTAGTCACTTTTTTTTCATAAATCTGTCATAAATCTGACGCATAATGACGTCGCATTAAT GATCGCAACCTATTTATTACAACAGGGCtgatctagaaataattttgtttaactttaagaaggagatatacaaatggtgagcGCCACGGAAATCAATAACCTGAAGATATGTGCGACGAGC’-FAM- AATGCGA CGTCA TTATG CGTCA GATTTAT5’-FAM- AATGCGA GCACA TTATG GAACA GATTTAT52, 1 mM dithiothreitol and 5% glycerol. Purified PhoB protein (~35 μM) was phosphorylated with 50 mM phosphoramidate for at least 1.5 h and different concentrations of PhoBP were subsequently incubated with approximately 0.1 mM fluorescent DNA for 30 min in the presence of 15 μM non-fluorescent competitor dsDNA oligos. PhoB-bound DNA complexes were analyzed by 12% TBE gels  and visualized by fluorescence imaging using a FluorChem Q imager. The fraction of bound DNA was calculated based on quantification of DNA band intensities using ImageJ. Binding curves were generally fitted with the Hill equation (OriginPro 8) to derive the dissociation constant KD. For DNA fragments that have a relatively strong affinity with KD close to the experimental DNA concentration, specifically, the phoB promoter, protein bound to DNA causes a non-trivial reduction in the concentration of free PhoB~P thus the total concentration of PhoB~P cannot be used directly for curve fitting. We assumed a two-site per DNA-binding model and used the Simbiology tool of MATLAB to estimate the KD. The estimated KD is 0.25 μM, about one seventh the KD of phnC, which is consistent with the difference in off-rates measured previously  the phosphorylation cycle that determines the output PhoBP concentration by various kinase and phosphatase activities of PhoR, and (ii) the transcription feedback that controls the expression of PhoB and PhoR proteins.in vitro analyses  of Pi starvation was used to estimate kdil while both P0 and kdil were kept constant throughout the modeled time course. For data in P0 and kdil were allowed to decrease simultaneously, following the fitted Hill function and reflecting a general reduction of growth and transcription. As for the value of P, it was found that Pi-depletion increased the PhoB concentration ~21 fold  carrying pRG426 expressing a non-fluorescent CFP variant. Continuous cultures were inoculated with mixed populations of bacteria and the same Pi-depleted condition as described in growth conditions was maintained. Bacterial cultures were sampled 24 h after inoculation and diluted 2500 fold before spreading on chloramphenicol-containing LB plates. At least two aliquots were plated for each sample. Bacterial colonies, ~500–1000 per plate, were visualized a day later by fluorescence imaging using a FluorChem Q imager. The numbers of total and fluorescent colonies were counted with ImageJ using an image-thresholding algorithm. Similar as the algorithm developed for single-cell imaging  to start another round of starvation. Plates were stored at 4°C overnight every 2 or 3 rounds of starvation before inoculation for the next round. CFP fluorescence  and OD were measured every 10 min during the competition. Pure populations of bacteria carrying pRG411 or pRG426 were grown simultaneously as controls. Basal fluorescence of bacteria carrying pRG426 was treated as background fluorescence and subtracted from the measured fluorescence. The population of fluorescent bacteria was calculated by dividing the OD-normalized fluorescence of the bacterial mixture with that of pure fluorescent cells that carry pRG411.In all analyses, mean values are presented and SDs are shown as error bars. The numbers of independent samples or replicates are reported in individual figure legends. Fluorescence reporter data were analyzed by Microsoft Excel and MATLAB r2009. Data fitting were performed using OriginPro8 (OriginLab).Band intensities of western blots or EMSA gels were quantified with ImageJ 1.50i (NIH) using the gel analyzer tool to generate line graphs for all bands of interest. Relative band intensities were computed as relative peak areas for individual bands and subsequently compared to the calibration samples or the control samples with known quantities of protein for quantification. Details of control or calibration samples are documented in 12


The gene editing tool CRISPR-Cas has become the foundation for developing numerous molecular systems used in research and, increasingly, in medical practice. In particular, Cas proteins devoid of nucleolytic activity  can be used to deliver functional cargo to programmed sites in the genome. In this review, we describe current CRISPR systems used for developing different dCas-based molecular approaches and summarize their most significant applications. We conclude with comments on the state-of-art in the CRISPR field and future directions. In recent years, precise genomic and epigenomic editing has transformed into a fast-growing area of research, with lucrative applications in medicine and biotechnology. Targeted modifications of genomes in various organisms, from bacteria to plants to mammals, can be applied to treating human diseases and to developing bacterial strains and genetically engineered organisms with desired properties. Discovery of site-specific CRISPR-Cas nucleases and adapting these bacterial tools for gene editing applications have revolutionized genetic engineering and molecular biology. Robust activity, easy design, and capacity to target virtually any DNA or RNA site has put CRISPR-Cas at the forefront of gene editing techniques, with yet-undiscovered potential applications of optimized CRISPR-Cas components and novel CRISPR-Cas systems. In simplest terms, CRISPR-Cas systems are based on nucleolytic activity of Cas9 protein guided by a chimeric RNA molecule  to the desired site in the genome. An important property of CRISPR-Cas is the high specificity defined by gRNA sequences that recognize the nucleic acid target and the protospacer adjacent motif (PAM) sequence, adjacent to the target, and required for CRISPR-Cas activity.Type II CRISPR-Cas systems are most commonly used, while CRISPR-Cas systems of other types  have also been leveraged for genomic and epigenomic editing. The Cas9 protein of the type II CRISPR-Cas system harbors two nucleolytic domains (RuvC and HNH) that cleave target DNA strands and generate double-stranded breaks (DSB) . IntroduIn this review, we will discuss modifications of dCas proteins and the corresponding molecular techniques, principles of gRNA design, and applications of dCas-based technologies, as well as future developments.Activity of genes is mainly determined by chromatin architecture in regulatory regions (promoters and enhancers). Chromatin exists in two major forms: Transcriptionally inactive heterochromatin and active euchromatin. Epigenetically modifying DNA or histones alters chromatin state. Controlling the processes of epigenomic remodeling determines gene transcription. dCas proteins can be designed to directly modify DNA epigenetics by methylation or demethylation, as well as to change epigenetic marks on histones by acetylation/deacetylation, methylation/demethylation, or recruitment of transcription factors. Different types of dCas-X proteins and their potential applications are reviewed below. Manipulating epigenetics is needed to studying gene function and regulatory genetic elements, as well as for developing potential therapeutics that, for example, suppress viral genome activity, modulate immune responses, suppress oncogenes, or program stem cells.Methylation of DNA in regulatory regions of genes suppresses gene transcription . DNA metdCas9-X technology has, for the first time, provided an opportunity to perform precise epigenetic DNA modifications. One of the first CRISPR-based tools to directly methylate DNA were chimeric proteins dCas9-DNMT3A and dCas9 linked to a catalytic domain of DNMT3A ,7,8. EffAnother modification of dCas-based technology designed to increase methylation efficiency is coupling dCas-X with the SunTag system, which recruits multiple effector molecules  to the desired site. The principle of dCas-SunTag is attachment of GCN4 peptide repeats to dCas9 and simultaneous intracellular production of effector molecules fused with single-chain variable fragments (scFv) that are prone to interacting with GCN4-dCas9. Several up to 10 units) DNMT3A-scFv molecules bind to dCas9 via GCN4 repeats [ units DNdCas9-SunTag-DNMT3A is highly specific, and does not seem to affect the overall methylation state of the genome . It is aIn contrast, many research and potential therapeutic applications frequently require demethylation of genomic DNA, particularly to treat malignancies by activating tumor suppressors, to treat genetic diseases, or to generate or differentiate stem cells. Chimeric dCas9 proteins fused with a domain of TET1 DNA-demethylase (dCas9-TET1 or dCas9-SunTag-TET1) have been shown to effectively demethylate up to 90% of target DNA regions ,11,12. AInitial methylation of target DNA. Effective suppression of gene transcription by dCas9-DNMTs can be achieved if gRNAs target initially unmethylated or weakly methylated regions . In contMethylation sites. Using dCas9-DNMT3A results in methylation of two regions. The first one lies within 27 nt in the 3ʹ-direction from the PAM sequence, and the second is within 27 nt from 5ʹ-end of the gRNA. The site of dCas9 binding (approximately 30 nt) is not methylated ,9. MethyMethylation window. Methylation of extensive DNA regions is mandatory for stable suppression of gene function. dCas9-DNMT3A methylates regions 25–35 nt in length , and thugRNA design is one of the most important considerations affecting CRISPR-Cas function. Several factors determine effective on-target mutagenesis induced by nucleolytic CRISPR-Cas systems, including availability of the PAM sequence, gRNA nucleotide (nt) composition, and the similarity between the gRNA and its DNA target. Additionally, designing gRNAs for methylation/demethylation applications requires several other parameters to consider:Desmoplakin gene expression in the pathogenesis of idiopathic lung fibrosis [TNFα promoter hypermethylation in the development of nephropathies in diabetes [CDKN2A, RASSF1, HIC1, PTEN, and SMARCA2, improved understanding of gene function in oncogenesis [MYC proto-oncogene with its super-enhancer and thus was proposed as an effective approach to treat many oncological diseases [BRCA [SARI [dCas-DNMTs tools provide an opportunity to analyze gene function and the role of methylation in physiologic conditions and in disease. For instance, dCas9-based methylation tools helped to identify the association between promoter methylation and dysfunction of fibrosis . Moreovefibrosis . dCas9-Tdiabetes . The rologenesis ,20. The ogenesis . Generatogenesis . dCas9-bdiseases . Additioes [BRCA  and SARICA [SARI  promoterFMR1 by dCas9-TET1, for example, was shown to correct the clinical manifestations of fragile X syndrome [SNCA gene promoter led to decreased cell death in an in vitro model of Parkinson’s disease and thus can be potentially considered a new therapeutic approach [dCas9-methylation and demethylation tools can be leveraged to develop new therapeutic approaches performed at the level of epigenetics. Demethylating syndrome . Moreoveapproach .Sox1 gene by dCas9-TET1 resulted in efficient reprogramming of neural stem progenitor cells [The growing area of stem cell research and its application in regenerative medicine requires new, more advanced techniques to obtain pluripotent stem cells, maintain pluripotency, and differentiate stem cells into particular lineages. Recently, demethylation of or cells .In addition to DNA methylation, histones are another factor involved in transcriptional regulation. Heterochromatin formation includes several steps: (1) Deacetylation of H3K9 and H3K27 histone residues; (2) methylation of H3K9 and H3K27 (H3K9Me3 and H3K27Me3); and (3) methylation of DNA regions wrapped by histones ,29, and On the other hand, transcriptionally active chromatin (euchromatin) is characterized by methylated H3K4 and H3K79 histone residues and acetylated H3K9 and H3K27 residues ,36. FactTargeted modifications of epigenetics in regulatory regions or in-site recruitment of transcriptional factors is the basis of CRISPR interference (CRISPRi) and CRISPR activation (CRISPRa) approaches. CRISPRi/a approaches rely on dCas proteins linked to functional activating or repressing domains.Current techniques enabling manipulation of gene activity include siRNA/shRNA approaches, which lead to degradation of transcribed mRNAs, and cDNA overexpression approaches. Several important drawbacks limit the application of these techniques. For example, siRNA/shRNA approaches frequently show significant off-target activity , and exoTypically, CRISPRi is based on chimeric dCas-X proteins, where X is a repressive Krueppel-associated box (KRAB) domain  or enhanBoth dCas9-KRAB and dCas9-EZH2 affect genes transiently. Sustained suppression of transcription is possible if two systems (dCas9-KRAB/dCas9-EZH2) are combined with dCas DNA methylation systems  to regulatory elements, thereby recruiting preinitiation complex factors and activating target gene transcription. Gene activation by a VP16 monomer is very ineffective, so CRISPRa is usually coupled with multimers of VP16  [Another scenario is to utilize dCas to deliver herpesvirus factor VP(16), VP192) .Robust induction of gene transcription by these systems requires multiplex gRNA targeting an extended genomic region. The VPR system relies on dCas9 protein linked to the protein complex VP64-p65-Rta, where Rta is an Epstein–Barr virus transcription factor. A three-component complex, VP64-p65-Rta has considerably higher efficacy than previous CRISPRa systems, potently activating target gene transcription ,56.Casilio aptamers into gRNA, improving gRNA stability and potency [CRISPRa systems can be coupled with affinity-binding technology that enables simultaneous recruitment of multiple domains to the target site. In this setting, different CRISPRa modifications can be introduced. These can modify Cas proteins , targeting gRNAs , or both . These modified CRISPRa systems demonstrate high efficacy even with a single gRNA . SunTag  potency . SAM com potency ,60  promoter to the target to activate regulatory regions of genes. This modification of CRISPRa is based on a hybrid gRNA molecule linked to a double-stranded DNA of the CMV promoter .CRISPRa technologies are summarized in An important parameter defining the efficacy of CRISPRa/i systems is the epigenetic state of the target region and baseline gene expression levels. The following criteria should be taken into account when designing CRISPRa/i systems.Target region. CRISPRi approaches should primarily target proximal promoters or enhancers. gRNAs targeting promoters should be designed to anneal at –50 to +300 nt from transcription start site. Highest efficacy has been demonstrated for gRNAs targeting +50 to +100 nt . TranscrEpigenetic state. The most effective binding of dCas proteins occurs in areas of open chromatin determined by peaks of DNase I sensitivity . MoreoveTarget region. CRISPRa should target proximal promoters, or, for some systems , distal enhancers. CRISPRa gRNAs to promoters should be designed to interact within −400 to −50 nt from the transcription start site .Epigenetic state. The most effective activation of genes occurs when CRISPRa are recruited to the sites of DNase I hypersensitivity .Design of gRNAs for many CRISPR application is made convenient by various online resources (reviewed in ).CRISPRa and CRISPRi are increasingly used in biological studies and in development of potential medications. These approaches have been extraordinarily effective for treating metabolic disorders and diseases associated with gene malfunction, including diabetes mellitus, Duchenne muscular dystrophy (DMD), and haploinsufficiency-related disorders, as well as for generating and differentiating stem cells.As KRAB and p300 can repress and activate enhancers, these domains are used for dCas9-based screening of proposed distal regulatory elements and enhancers bound by transcriptional factors ,70.APOBEC3B and APOBEC3G to combat human immunodeficiency virus (HIV) infection [APOBECs and destroy hepatitis B virus (HBV) genomes [Shortly after they were described, CRISPRa approaches were used to activate endogenous antiviral factors nfection . Anothernfection ,73,74,75 genomes ; this me genomes ,78. CRIS genomes .CRISPRa can help treat haploinsufficiency-induced diseases by overexpressing an intact copy of the insufficient gene. This method has been utilized in vivo to treat obesity  and DravGranulin [PTEN, DKK3, or CHEK2 greatly suppresses proliferation of cancer cells [CRISPR-mediated transcriptional regulation has great potential in oncology. CRISPRi approaches have been used to repress proto-oncogenes like Granulin , while aer cells ,84,85. Aer cells .The most important examples of CRISPRa/i applications are summarized in Chromatin structure in regulatory regions determines transcriptional activity of genes. Chromatin state is regulated by complex interactions between DNA, transcription factors, and associated RNAs. Identifying factors implicated in these interactions is important for understanding fundamental aspects of transcriptional regulation.Typically, factors interacting with chromatin at a given site are studied using the chromatin immunoprecipitation (ChIP) technique and its modifications. However, ChIP has several drawbacks. It can be used to capture pre-defined transcription factors using specific antibodies but identifying new proteins and RNAs is difficult. Moreover, antibodies to pre-defined factors are limited and very expensive. Therefore, new techniques are needed to identify interacting partners of chromatin-remodeling complexes.In recent years, three dCas-based methods  were devised to identify previously unknown factors interacting with chromatin by means of high-affinity extraction and proteomics.In the CAPTURE method, a dCas9 protein contains a site for a biotintransferase enzyme that is added to cells to transfer biotin markers onto dCas9. Biotinylated dCas9 proteins complexed with adjacent proteins at the site of interest are then isolated using avidin-streptavidin interactions . CasID tCAPTURE and CasID require long incubation steps  to generate biotinylated targets, and thus cannot be used to analyze dynamic processes of chromatin remodeling, epigenetic modifications in response to exogenous stimuli, cell differentiation, and cell cycling, among others. This limitation can be overcome by using the CASPEX techniques (C-BERST and GLoPro protocols), in which a dCas9 protein linked to APEX2 peroxidase is added to cells with a reaction mixture composed of hydrogen peroxide and biotin-phenol. APEX2 induces oxidation of biotin-phenol, generating short-lived, highly reactive free radicals that biotinylate all factors in the direct vicinity of dCas9-APEX2 binding (±400 nt), which can be further analyzed by proteomics or sequencing ,120. CASTarget site. gRNAs should anneal at the most proximal area of the target region, but should not lie at sites bound by transcription factors to avoid impeding interactions between regulatory DNA elements and proteins .Off-target interactions. For better consistency, proteome analysis of chromatin architecture should be performed with validated negative controls  and should consider endogenous and non-specific biotinylation ,119,120.Distal regulatory elements are located many thousands of nucleotides from gene promoters but strongly impact gene transcription when drawn close together. Dysregulation of these processes results in aberrant gene expression and is frequently observed in human diseases, including cancer . IdentifThe CLOuD9 method involves interactions between two orthologous dCas9 proteins fused to dimerizing domains PYL1 and ABI1. One dCas9 protein interacts with a distal region, while the other targets the promoter of the gene of interest. Adding the inducer (abscisic acid) promotes dimerization of dCas9 proteins carrying dimerization domains and interaction of the bound chromosomal regions. CLOuD9 can be devised to directly manipulate the 3D architecture of chromatin, analyze distal regulatory regions, and install new intra- and inter-chromosomal links .Optimal sites of gRNA targeting for CLOuD9 can be selected in genomic browsers with the described considerations for distal regulatory regions annotated in FANTOM5  and GeneMany hereditary diseases, cancers, and mutations resulting in drug resistance are associated with single-nucleotide polymorphisms (SNPs) . EditingBase-editing systems leverage dCas proteins fused to cytidine or adenosine deaminases. Cytidine deaminases convert cytosine to uracil (C→U) with the resulting U•G mismatches being resolved by DNA repair machinery to form thymine (C→T) on the target strand and guanine (G→A) on the complementary strand ,126, whiEfficacy of cytosine base editors may be fairly low due to repair of edited nucleotides by endogenous DNA repair systems like the UNG factor. Improved efficacy of base editing was shown for nickase nCas9 (nCas9) proteins, which have a single mutated nucleolytic domain and one domain with preserved cleavage activity, linked to base-editing factors and co-expressed with UGI, an UNG inhibitor . BlockinCorrecting virtually any mutation in any DNA region has become possible by using genetically engineered dCas proteins with optimized (shortened) PAM motifs. Relieving PAM restrictions broadens the range of potential sites edited by base editing factors and provides an opportunity to treat numerous genetic disorders ,136.The major consideration when using dCas base editors is potential off-target editing of RNA, as was unexpectedly described for rAPOBEC1, TadA, and APOBEC3A ,138,139.Among cytidine deaminases, rAPOBEC1 possesses the highest deamination activity . HoweverEffector proteins of CRISPR-Cas type VI systems can directly interact with target RNAs independently of PAM, thus allowing deaminases binding to these proteins to edit RNA molecules.The REPAIR RNA-editing system is based on a dCas13b protein linked to a mutant form of ADAR2, an enzyme that catalyzes adenine deamination in dsRNA (A→I conversion) . Using tCompared to DNA editing, RNA editing has several important advantages, including a wider range of potential sites due to PAM-independent functioning of CRISPR-Cas type VI proteins and direct RNA editing by deaminases without the assistance of endogenous repair systems . DNA ediSite-specific base editors can be used to correct mutations associated with a disease phenotype or to introduce mutations to block or modify gene function.Precise base editing using CRISPR-STOP and iSTOP has become a novel tool to knock out genes by editing four potential triplets of nucleotides to generate stop codons. Introducing stop codons into the early exons of genes leads to synthesis of short, non-functional mutant proteins ,145. UnpdCas base editors were used to create in vitro and in vivo models of different diseases associated with SNPs. For instance, base editors were used to create cell lines resistant to chemotherapeutic drugs ,132,147 Pcsk9 gene was proposed as a therapeutic approach to treat atherosclerosis [Base editors proved useful for creating new therapeutic approaches. dCas-guided base editors corrected SNPs linked to hereditary diseases, such as thalassemia ,155, Marclerosis ,159.Conversely, an approach called CRISPR-Pass can be used to correct nonsense mutations by adenosine editors. Editing codons with nonsense mutations using CRISPR-Pass helps to recover production of active proteins. CRISPR-Pass was predicted to correct up to 95% mutations described in ClinVar database . dCas-baCRISPR-SKIP method was created based on dCas base editors to introduce point mutations into splice acceptor sites. Generated mutations result in exon skipping and translation of new protein isoforms with altered properties . This prhttp://www.rgenome.net/be-designer/) and BE-Analyser , has been created to design gRNAs for base-editing applications [http://www.picb.ac.cn/rnomics/BEable-GPS) has been recently created. BEable-GPS enables design of gRNA for specific applications for almost every existing base editor system [dCas base editing systems are characterized by a unique editing window. The majority of systems have a 5-nt window, which may vary if systems undergo modifications or are genetically optimized. Easy-to-use software, including BE-Designer  increases efficacy of RNA editing by dCas13b-ADAR2 .Many CRISPR-Cas systems have been employed by researchers to introduce various modifications into living organisms. Bioinformatics will allow discovery of numerous other systems in the coming years. Characterizing CRISPR-Cas and related systems has become the most important area of research in biology.Genetic engineering has enabled directed modifications of CRISPR components to create optimized and highly effective gene editing approaches. Some of these tools were reviewed in this paper; many recent achievements, however, are outside the scope of this manuscript, the most notable of which includes creation of a multiplexed Cas12a-based approach for simultaneously modulating many genes to control complex biological processes with unprecedented accuracy. This multiplexing is done by a Cas12a protein that cuts a single RNA transcript into many gRNAs targeting individual targets . Two groNew avenues in epitranscriptomics were opened by dCas tools empowered by m6A marker “writers” and m6A “erasers,” which modify the epigenetic state of RNA .Visualizing target DNA and RNA sequences is another extraordinary achievement made possible by combining dCas with fluorescent proteins for in vitro and in vivo microscopy ,169,170.The utility of new CRISPR-Cas-based methods and therapeutics could be undermined by the potential off-target activity of Cas proteins, i.e., unintended binding/cutting at undesired sites. Off-target cleavage/binding may severely compromise the utility of CRISPR-Cas-based therapeutics, disrupting genes, introducing large mutations  and contTo conclude, the field of CRISPR is currently evolving at a furious pace. Many years of research in biology, physics, and chemistry have been poured into the new CRISPR tools, allowing previously unfeasible biological manipulations and interventions. On the shoulders of giants, the CRISPR field is growing into one of the most powerful molecular tools. However, several major barriers stand before the CRISPR-Cas field, and the way these barriers are overcome will define the broadness and applicability of gene editing.


Arabidopsis. H3K27ac prevalently marks promoter-proximal regions, suggesting that H3K27ac is not a hallmark for enhancers in Arabidopsis. We provide computational and experimental evidence to confirm that distal DNase І hypersensitive sites are predictive of enhancers. The predicted enhancers are highly stage-specific across flower development, significantly associated with SNPs for flowering-related phenotypes, and conserved across crucifer species. Through the integration of genome-wide transcription factor (TF) binding datasets, we find that floral master regulators and stage-specific TFs are largely enriched at developmentally dynamic enhancers. Finally, we show that enhancer clusters and intronic enhancers significantly associate with stage-specific gene regulation by floral master TFs. Our study provides insights into the functional flexibility of enhancers during plant development, as well as hints to annotate plant enhancers.Enhancers are critical for developmental stage-specific gene expression, but their dynamic regulation in plants remains poorly understood. Here we compare genome-wide localization of H3K27ac, chromatin accessibility and transcriptomic changes during flower development in  Arabidopsis flower development providing evidence for sets of distal enhancers acting in a highly stage-specific manner.Enhancer elements can control spatial and temporal patterns of gene expression. Here the authors profile chromatin accessibility, histone modifications and gene expression during  Promoters and enhancers are noncoding DNA sequences that can be bound by multiple regulatory proteins, especially transcription factors (TFs) to activate the expression of target genes1. Active promoters and enhancers are devoid of nucleosomes, thereby rendering the DNA accessible for TF binding. While promoters locate near the transcription start site (TSS), enhancers can be up to several Mbs away from their target genes1. A single gene can be regulated by multiple enhancers with different spatiotemporal activities, resulting in a large combinatorial complexity of expression repertoires for a given set of genes2. Large-scale analyses in animal genomes showed that promoters and enhancers are distinguishable based on their stereotypical DNA features and chromatin signatures3. For example, enhancers are often associated with mono-methylation of H3 at lysine 4 (H3K4me1) and H3 acetylation marks at lysine 9 and 27 (H3K9ac and H3K27ac)4, while gene promoters differ from enhancers by their enrichment in H3K4me33. On the other hand, there is an increasing number of reports6 showing that promoters and enhancers share similar structural and functional features1.Multicellular development is controlled by precise spatiotemporal regulation of gene expression, which is largely accomplished through the activation and repression via 2. The advent of next-generation sequencing technologies and the identification of enhancer chromatin properties enable genome-wide prediction of enhancers in a high-throughput manner3, leading to the discovery of thousands of enhancer candidates in human7 and other animal genomes8. Enhancers appear to function as integrated platforms for binding of multiple TFs, often including lineage- and signal-determining  TFs9. Remarkably, cell identity gene loci are frequently associated with dense clusters of enhancers or super-enhancers with both overlapping and distinct spatiotemporal activities11. Genome-wide analyses of enhancer functions have revealed that enhancers are functionally complex and developmentally dynamic during cell differentiation12. Lineage-regulating factors, including pioneer factors and their associated TF networks, contribute to shaping enhancer repertoires during development14.Enhancers have recently been subjected to intensive investigation as there is increasing evidence showing their importance not only in developmental control but also in evolution and diseases, including cancer15. Enhancers are predominantly found in regions of accessible chromatin3, which is more sensitive to DNase I digestion than condensed chromatin. Genome-wide mapping of open chromatin regions has been conducted in the selected model and crop plant species21. In 2012, Zhang et al. reported the mapping of open chromatin in rice seedlings and callus using DNase-seq. They found that DNase I hypersensitivity sites (DHSs) are associated with highly expressed genes in both tissues, and that 42.3% and 44.5% of DHSs in seedlings and in calli, respectively, reside in intergenic regions16. The same group later identified a high overlap between TF occupancy and DHSs in Arabidopsis thaliana leaves and flowers and they found that around 90% of APETALA1 (AP1) and SEPALLATA3 (SEP3) binding sites overlap with DHSs17. Using these above-mentioned open chromatin signatures, they further carried out a genome-wide prediction and validation of Arabidopsis thaliana intergenic enhancers20. A total of 10,044 intergenic DHSs were identified as putative enhancers, of which 1644 and 2529 are leaf- and flower-tissue specific, respectively. Enrichment of both H3K27ac and H3K27me3 was reported in the genomic regions of predicted tissue-specific enhancers, with a positive correlation for H3K27ac and a negative correlation with H3K27me320. More recently, by combining the information of genome-wide DNA methylation, chromatin accessibility, and H3K9ac profiling, 1500 intergenic enhancers were predicted in maize21. Although these studies spark the renewed interest in the investigation of plant enhancer elements, genome-wide mechanisms of dynamic enhancer activities to trigger spatiotemporal gene expression in plant development have not yet been elucidated.Contrary to the fast growing knowledge of the regulatory function of enhancers in metazoans, knowledge of genome-wide landscapes of plant enhancers and their dynamic activities remains limited in the context of developmental stage-specific gene regulation18, and transcriptome dynamics (RNA-seq) in Arabidopsis thaliana at four representative stages. We found that H3K27ac prevalently marks promoters but rarely localizes in distal regulatory regions, suggesting that H3K27ac is not a hallmark for active enhancers in Arabidopsis thaliana as it is in metazoans22, and as data from rice and maize indicate24. Examination of DHS-predicted distal intergenic enhancers reveals their high-stage specificity across flower development, their functional importance in the regulation of flowering genes, as well as their high evolutionary conservation across crucifer and dicot species.Here, we used flower development as an ideal system to study enhancer dynamics and to dissect their roles in the control of stage-specific gene expression patterns by integrative analysis of genome-wide H3K27ac locations (ChIP-seq), chromatin accessibility (DNase-seq)22, and it was recently shown to highly correlate with active gene expression in plants25. Here, we further investigated the role of H3K27ac dynamics in stage-specific gene regulation. We generated a genomic atlas of H3K27ac modification across flower development in the model plant species Arabidopsis thaliana. We took advantage of a previously described floral induction system, which allows collection of synchronized flower tissue of specific developmental stages26 and that proved to be highly suitable for depicting quantitative changes in chromatin marks, accessibility, and TF binding27  and APETALA3  correlate with their expression dynamics. The AP1 locus is enriched in H3K27ac and stays open across all four time points, in line with its steady high expression level (presumably at the transgene and/or endogenous AP1 loci that are both present in the used plant line). In contrast, the AP3 locus shows increase in H3K27ac and accessibility at later stages (4 and 8 DAI), which correlates with an increase in expression , SHORT VEGETATIVE PHASE (SVP), SUPPRESSOR OF OVEREXPRESSION OF CONSTANS1 (SOC1), and AGAMOUS-LIKE 24 (AGL24), which are important for floral transition and initiation29. Another set of 340 genes showed higher H3K27ac signals and increased expression levels at 8 DAI, including floral organ identity genes AP3 and SEPALLATA . In summary, we found that H3K27ac is highly associated with gene activity during flower development. Together, our results support and refine previous research20, showing that H3K27ac is highly correlated with gene activation during floral meristem and organ development. In addition, the difference in localization of H3K27ac sites and DHSs with respect to the TSS in distal intergenic regions indicates that they may activate gene expression via distinct mechanisms.We observed that most of the H3K27ac sites are located in intragenic regions and directly downstream of the TSS Fig. . In detaArabidopsis thaliana, indicating that this mark associates with enhancer elements20. However, we identified very few distal intergenic H3K27ac peaks  and transcribed regions  H3K27ac peaks are present in intragenic regions . 5 kb enhancer flanking regions may overlap with the H3K27ac signal from distal sites, because the Arabidopsis thaliana genome is very compact with an average size of ~3 kb for intergenic regions. In summary, these results indicate that, at least in Arabidopsis thaliana, H3K27ac is not a suitable mark to predict active distal regulatory elements (including enhancers), because the majority of H3K27ac sites appear in intragenic or promoter regions and hardly coexist with DHSs in distal intergenic regions.Recent work suggested that H3K27ac colocalizes with distal intergenic DHSs in ons Fig. , and theons Fig. . The cenons Fig. , while tons Fig. , respectons Fig. . In contons Fig. . These fons Fig. . These oArabidopsis thaliana seedlings30  seedlings31  K562 cell line6  mostly locate within 300 bp from the TSS 34, which indicates that enhancers mostly target their proximal gene(s) in Arabidopsis. Based on this assumption and the fact that most of distal DHSs located less than 3 kb from the TSS of a neighboring gene , but the enrichment is slightly lower than that in promoter regions 37. We observed that enhancers showed a higher enrichment of significantly associated SNPs by GWAS than promoters 40 than promoters . Thirty reporter lines were produced, corresponding to 24 enhancer candidates with average fragment length of 1.07 kb neighboring flowering-related genes. Six of the enhancer candidates were verified using two independent constructs with opposite enhancer fragment orientation  were also chosen for validation  with expression profiles of the corresponding genes in the tested tissues  gene, a key regulator of gynoecium development43, gave specific GUS signals in the tip of the gynoecium  gene, which contributes to floral organ patterning along the proximal–distal axis44, showed strong signals in the basal part of flowers as well as the junction between flowers and stems  reporter assayues Fig. . Five ofues Fig. , which  ium Fig. , while tems Fig. . SimilarOP2 Fig. . Clear . Accordingly, nearly all the investigated TFs preferentially bind to enhancer regions  overlap between these two sets of genes  that is involved in specification of floral whorls in the meristem46 is an enhancer-associated gene in cluster 1, while AG was identified to be a target gene of a cluster 2 enhancer , and SHOOT MERISTEMLESS (STM), are associated with both candidates of intergenic and intronic enhancer elements , as exemplified by the second intron of the TSS Fig. . We idenTSS Fig. . InteresTSS Fig.  and with 48 Fig. . This sunts Fig. . This sents Fig. .Fig. 7InTARGET OF EARLY ACTIVATION TAGGED 1 (TOE1) gene . The results showed that 27 of 30 (90%) reporter lines showed an ability of triggering GUS gene expression, which supports the reliability of our enhancer prediction. More than one-quarter of the H3K27ac sites locate in distal intergenic regions in animal systems50. Similarly, around 30% of H3K27ac sites were identified to locate in intergenic regions in both rice23 and maize24, which indicates that H3K27ac could serve as an active enhancer mark in these two plant species. In contrast, in the Arabidopsis thaliana genome, our analysis confirms another report25, which showed that only a minority, ranging from 0.5 to 3%, of H3K27ac sites are located more than 1 kb upstream of the TSS , indicating that H3K27ac does not mark enhancers in Arabidopsis thaliana. However, this cannot be explained as a simple consequence of genome compactness, since, e.g., the Drosophila genome is also compact, but H3K27ac marks its enhancers51. An important question is now to understand how the diverging H3K27ac patterns are established in different plant species. In animal cells, H3K27ac deposition in enhancers is mainly mediated by the CREB-binding protein (CBP) and p300 histone acetyltransferases53. An Arabidopsis thaliana CBP/p300 homolog was reported to promote flowering by affecting expression of FLOWERING LOCUS C (FLC), but does not appear to control acetylation levels of the H3 (H3K9ac and H3K14ac) and H4 histones within FLC chromatin54. Plant and animal CBP/p300 proteins share a highly conserved C-terminal domain, which is necessary for acetyltransferase activity55. Other domains have diverged between plant and animal homologs, suggesting divergent mechanisms of recruitment to their genomic target sites56. This however does not explain the differences in H3K27ac patterns observed in Arabidopsis thaliana and rice/maize. One possible explanation is that the interactions among different types of chromatin modifications, including histone acetylation, methylation, and DNA methylation are plant species-specific. It has been shown that in rice, DNA methylation at non-CG sites positively correlates with H3K27me3 in euchromatic regions57, which is a different situation in Arabidopsis thaliana58. Whether H3K27ac mediates interactions of other chromatin features and whether the interaction modes differ between plant species is an open question to be addressed. In animal systems, H3K27me3 correlates with poised enhancers, whereas the H3K4me1 mark can correlate with poised and active enhancers59. In Arabidopsis thaliana, around 15–20% of H3K27me3 sites were found in intergenic regions60 , whereas H3K27me3 was reported to have a positive association with poised enhancers20. Only 0.6% of H3K4me1 and <1% of H3K3me3 sites are located in intergenic regions61. Other chromatin features of active enhancers and the mechanisms underlying their characteristics thus need to be further explored in Arabidopsis thaliana. Interestingly, 9% of the distal DHSs we mapped carry H3K27me3, and 31% of those H3K27me3-marked distal DHSs are actively changing across flower development.Only recently, enhancers were mapped in plant genomes, and the results revealed that those enhancer candidates correspond to accessible distal DNA fragments63, which indicates that the developmental expression dynamics might be largely controlled by distal enhancers. Intriguingly, 21 of the annotated flowering-time genes64 were associated with dynamic enhancers, and 17 (81.0%) of them were differentially expressed during flower development , which indicate that these intronic regulatory regions contain repressive or enhancing elements, as was, for example, shown for the AG second intron47. In addition, introns can enhance transcription via gene looping as was shown in yeast69, but intronic enhancers can also attenuate gene expression through eRNA transcription70. Intriguingly, 158 genes are enhancer-associated candidates with both intergenic and intronic enhancer elements. This set includes many developmental TF genes, but also other signaling-related genes, such as PIN auxin transporters 72 was grown for mapping stage-specific H3 and H3K27ac, and for gene expression profiling by RNA-seq in flowers. The same material had been used previously for generating stage-specific open chromatin data in flowers by DNaseІ-seq in the same group18. Seeds were directly sown to soil. After cold treatment for 2 days, the plants were transferred to growth chambers  with long-day conditions  at 20 °C, at light intensity of 100 μmol/m2/s.An inducible line in which the AP1 protein fused with the glucocorticoid receptor (GR) is expressed under the AP1 promoter in an 18. In brief, dexamethasone (DEX) solution  ethanol, 0.01% Silwet L-77) was applied daily to the main inflorescences from the time they reached a height of 2 cm, as drops from cut pipette tips. The first induction was applied after 8 h of light, and the following daily inductions were performed after 4 h of light. Inflorescence material was collected before the first induction for the “no DEX induced tissue”, and then 2 days, 4 days, and 8 days after the first treatment, after 8 h of light. Flower tissues of specific developmental stages were collected from the first inflorescence of pAP1:AP1-GR ap1-1 cal-1 plants. For RNA-seq, five inflorescences per replicate were harvested with liquid N2. RNA was isolated with the RNeasy Plant Mini Kit  according to the manufacturer’s recommendations, and the libraries were prepared using the TruSeq Stranded Total RNA LT Sample Prep Kit .Plants were induced by dexamethasone as described in ref. 73 with minor modifications. Briefly, the tissue was fixed with 1% formaldehyde for 20 min. After nuclei isolation, the chromatin was sonicated using a Covaris S220 sonicator to obtain the desired DNA fragment size (major band at 500 bp). The sonicated chromatin was pre-cleaned by two rounds of centrifugation with maximum speed at 4 °C. In total, 5 μl of anti-H3K27ac  or 3 μl of anti-H3  were used to precipitate the chromatin fragments that contain either all H3, or K27ac-marked H3 histones. Specificity of the anti-H3K27ac antibody was verified prior to its usage .For ChIP samples, 0.7 g of tissue was collected for one replicate into a 50 -ml Falcon tube on ice. The ChIP experiment was performed according to the published protocolArabidopsis thaliana reference genome (TAIR10) using STAR74 (version 020201). Expression levels of all annotated genes were estimated by RSEM75 (version 1.2.22). FPKM (fragments per kilobase of transcript per million mapped reads) values as defined by RSEM were added as a pseudo-value of 1e–6 (to avoid zeros) and then log2-transformed. Differentially expressed genes across the four developmental stages were identified by analysis of variance (ANOVA) based on FPKM values. The resulting p-values were adjusted for multiple comparisons by false discovery rate (FDR). Genes were considered as differentially expressed if they showed at least twofold changes with FDR < 0.05.RNA-seq reads were mapped to Arabidopsis thaliana seedlings30  and rice seedlings31  were collected from the Sequence Read Archive (SRA) database. The reanalysis results of TF ChIP-seq data for 15 floral regulators were obtained from ref. 48. A uniform computational pipeline (as described below) was adopted to process the raw data.Time-course H3K27ac and H3 ChIP-seq data were generated in this study. Published histone modification ChIP-seq data in 76 recommended by the ENCODE project and have developed an analysis pipeline48 consisting of quality control, read mapping, peak calling, assessment of reproducibility among biological replicates, and peak annotation to reprocess all raw data in a standardized and uniform manner. Specially, the quality of the raw data (FASTQ files) was evaluated with the FastQC program (http://www.bioinformatics.babraham.ac.uk/projects/fastqc/). Reads were then mapped to the Arabidopsis thaliana genome (TAIR10) using Bowtie (version 1.1.2) with parameters “–threads 8 -n 2 -m 10 -k 1–best–chunkmbs 256 -q”. Redundant reads were removed using Picard tools . Peak calling was performed using MACS277 (version 2.1.0). Duplicated reads were not considered (–keep-dup = 1) during peak calling in order to achieve a better specificity. The “–mfold” parameter was set as “2-20” to build the model. A relaxed threshold of p-value  was suggested in order to enable the correct computation of IDR (irreproducible discovery rate) values76. Following the recommendations for the analysis of self-consistency and reproducibility between replicates (https://sites.google.com/site/anshulkundaje/projects/idr), control samples were combined into one single control among the replicated experiments. Peaks across replicates with an IDR ≤ 0.1 were retained.We followed the ChIP-seq data analysis guidelineshttp://structuralbiology.cau.edu.cn/cgi-bin/hgTracks since the corresponding raw data were not available23. The analyzed wiggle track files for histone modification ChIP-seq in human K562 cell line were obtained from the ENCODE (Encyclopedia of DNA Elements) project6 at https://www.encodeproject.org/.Signal files for H3K4me2, H3K4me3, H3K9ac, and H3K27ac ChIP-seq data were downloaded from the UCSC genome browser at ap1-1 cal-1) were obtained from Pajoro et al.18. DNase-seq data analysis was performed in a way similar to that described above for ChIP-seq. Peaks  were called using MACS2 without providing an input file and with parameters “–nomodel–shift −100–extsize 200”.Floral stage-specific DNase-seq data generated from the pAP1:AP1-GR 78 (v2.25.0). If multiple H3K27ac peak regions or DHSs at a given stage resided within 500 bp to each other, they were considered as a single peak and centered on a peak having higher H3K27ac occupancy or DNase I accessibility. An alternative approach was also used to identify nearby peaks between DHSs and H3K27ac peaks, where any peaks within 1 kb of the base peak were considered.All the peak-based analyses  were performed using BEDToolsThe gene annotation file (TAIR10_GFF3_genes.gff) was downloaded from the TAIR website. The genomic coordinates of promoters were defined as 1 kb upstream of the transcription start site (TSS) of annotated protein-coding genes. Intragenic regions refer to the region between the TSS and the transcription termination site (TTS), i.e., the gene body. The rest of the genome was annotated as distal intergenic regions. Peaks were assigned to each category using their peak summits. If a peak overlaps multiple categories, only one category is used based on the following priority: intragenic > promoters > distal intergenic regions.20 to predict plant enhancers based on DHSs. We measured the distance from the midpoint of each DHS to the TSS of its closest genes, and we found that the distance follows two distinct distributions  were stitched together based on a specific distance. The stitching distance was determined to optimize that enhancers in the same intergenic region are combined, while enhancers from different intergenic regions avoid to stitch. In our analysis, we selected a stitching distance as 1.5 kb  and a minimal 35 s promoter element was incorporated into TOPO sites of pENTR/D-TOPO plasmid to generate pENTR/D-TOPOmini35S. The DNA fragment containing the candidate enhancer was amplified using primers extended by sequences containing restriction enzyme cutting sites. The digested PCR product was directly inserted into the entry vector pENTR/D-TOPOmini35S via the MCS. Next, to produce the final construct, the enhancer fragment followed by the minimal 35 s promoter was transferred into the destination vector pKGWFS7.0 using the Gateway LR Clonase II Enzyme Mix . Plant transformation was performed by dipping Arabidopsis thaliana Col-0 plants79 using the Agrobacterium tumefaciens strain GV3101. Seeds from infiltrated plants were harvested and spread on selective medium . Positive transformants were transferred to soil and grown under long-day conditions .The GUS reporter system for validating enhancer function was slightly modified from ref. 20 with minor modifications. In brief, inflorescences of independent transgenic lines produced by the same transformation were mixed in one single tube filled with GUS staining solution. Vacuum was applied for 5 min followed by 6 h of incubation at 37 °C. Tissue was cleared overnight using a 3:1 mix of ethanol and acetic acid, respectively, followed by two subsequent washes with 100% ethanol. For microscopic analysis, samples were transferred to 70% ethanol and stored at 4 °C. Pictures were taken using the Olympus LC30 microscope .The main inflorescence was harvested from each transgenic line and GUS staining was performed as describedhttp://www.flor-id.org/; 306 genes)64 or selected from Arabidopsis thaliana transcription factors with gene ontology (GO) terms containing the keywords “floral” or “flowering” (128 genes in addition). In total, we obtained 434 “flowering” genes.To link regulatory elements (including promoters and enhancers) with their associated genes, each regulatory element was assigned to its nearest TSS of 27,206 annotated protein-coding genes. Flowering genes were either collected from the flowering interactive database . DNase-seq experiments across multiple time points are affected by global confounders related to changes in the number of sites at each time point, which is not accounted for via simple depth normalization. To remedy this issue, quantification of DHSs was further quantile normalized across all time points using the normalized quantiles function from the 27 samples, we found that the dynamics of H3K27ac is independent on the dynamics of H3, indicating that H3K27ac changes do not simply reflect altered nucleosome occupancy  with a 80 online toolkit. All p-values plotted are corrected for multiple testing.Significant GO terms were identified using the agriGOhttps://cran.r-project.org/; version 3.2.3) was used to compute statistics and generate plots. The HTPmod online tool (http://www.epiplant.hu-berlin.de/shiny/app/HTPmod/) was partially used for the generation of figures. ChIP-seq data signal tracks were visualized in the WashU Epigenome Browser (https://epgg-test.wustl.edu/browser/).If not specified, R (Further information on experimental design is available in the Supplementary InformationPeer Review FileDescription of Additional Supplementary FilesSupplementary Data 1Supplementary Data 2Supplementary Data 3Supplementary Data 4Supplementary Data 5Supplementary Data 6Supplementary Data 7Reporting SummarySource Data