Bombyx mori (Lepidoptera), we analyzed the regulatory elements and functional regions of the B. mori nucleopolyhedrovirus 39 K promoter.Silkworm genetic engineering is widely used in gene function, silk engineering and disease-resistant engineering in most of Asia. Some of the earliest promoter elements are used to control the development of silkworm transgenic expression and gene therapy. However, the low expression and specificity of natural promoters limit the applications of genetic engineering. To construct a highly efficient synthetic inducible promoter in the Truncated mutation analysis of the 39 K promoter showed that the transcriptional regulatory region spanning positions − 573 to − 274 and + 1 to + 62 are essential for virus-inducible promoter activity. Further investigations using the electrophoretic mobility shift assay revealed that the baculovirus IE-1 protein binds to the 39 K promoter at the − 310 to − 355 region, and transcription activates the expression of 39 K promoter assay. Finally, we successfully constructed a synthetic inducible promoter that increased the virus-inducing activity of other promoters using the baculovirus-inducible transcriptional activation region that binds to specific core elements of 39 K .In summary, we constructed a novel, synthetic, and highly efficient biological tool, namely, a virus-inducible 39 K promoter, which provides endless possibilities for future research on gene function, gene therapy, and pest control in genetic engineering.The online version of this article (10.1186/s13036-018-0121-8) contains supplementary material, which is available to authorized users. The inducible promoter, known as the inducible regulation sequence or the inducible enhancer, is a group of promoters that can enhance the expression of exogenous genes under the stimulation of specific physical, chemical, or pathogen signals . In geneThe synthetic promoter provides stronger levels of transcription than natural promoters, as it combines a unique combination of different promoter elements and replace or redesigns sequences with various combinations of promoters –10. PrevB. mori nucleopolyhedrovirus (BmNPV)-induced promoter , and found that the 39 K promoter had the highest BmNPV-induced transcriptional activity [Autographa californica nuclearpolyhedrosisvirus (AcMNPV) 39 k gene is a delayed-early gene that is expressed in infected but not uninfected cells [We previously screened the activity of the activity . Previoued cells . Mutatioed cells . Furtherhycu-ep32 gene controlled by an inducible 39 K promoter showed high antiviral capacity in transgenic lines [B. mori cells [In our previous study, we found that virus-inducing activity of the BmNPV 39 K promoter could be further increased using enhancers such as Hr3, Hr5, Polh and PU . Simultaic lines . Furtheric lines . Moreoveri cells . TherefoTherefore, in this study, we constructed a synthetic inducible promoter by identifying the 39 K promoter regulatory regions and binding sites. First, we verified the functional domains (spanning regions − 573 to − 274 and + 1 to + 62) of the 39 K promoter by gradually introducing truncating deletions at the 5′ end, 3′ end, and intermediate regions based on characteristics of the 39 K promoter regulatory region as indicated by the dual luciferase report system assay. Then, we constructed a promoter with a shorter promoter sequence and better induction activity by analyzing the regulatory elements of the 39 K promoter and associated point mutations. Furthermore, we found that the baculovirus IE-1 protein binds to the 39 K promoter at the − 310 to − 355 region. Finally, we analyzed the 39 K promoter-inducing active region combined with specific promoters to construct inducible promoters that could efficiently and specifically activate other promoter inducible expression. The results showed that we successfully constructed a synthetic inducible promoter 39 K that could be effectively applied to research on insect gene function, disease resistance breeding, and pest control.Firefly luciferase and reference plasmid IE1 promoter-controlled Renilla luciferase were co-transfected into the BmN-SWU1 cells, Renilla luciferase as the amount of protein used for relative luciferase activity. Promoter activity was assessed by detecting changes in Firefly luciferase activity relative to that of Renilla luciferase . We co-transfected pIZ-IE0, pIZ-IE1, pIZ-IE2, pIZ-PE38 and pIZ-ME53 with p39K-DsRed and then detected DsRed at the transcriptional levels. The expression of DsRed protein was only observed in the viral-infected and pIZ-IE1 transfected BmN-SWU1 cells, but not in the pIZ-IE0, pIZ-IE2, pIZ-PE38, pIZ-ME53, and non-infected cells , probe 2 (− 386~ − 431), probe 3 (− 310~ − 355), and probe 4 (+ 2~ + 47), which were incubated with purified IE-1 derived from prokaryotic expression. The incubation of the biotin with the IE-1 protein. The incubation of biotin labeled probe 3 (− 310~ − 355) with IE-1 protein resulted in a distinct band shift in the electrophoretic mobility shift assay (EMSA), which disappeared with the addition of competitive unlabeled DNA probes   binding sequences. qPCR assays indicated that the baculovirus VP1054, P143 and P6.9 promoters exhibited a significant increase in activity compared to the original sequence after binding to the 39 K(− 310~ − 355) sequence  ubiquitin promoter CAAT to CGGT increases inducible promoter activity [In our previous studies, we showed that the P-44 (− 44 to + 133) and P-420 (from − 420 to − 611) are important regions for the transcriptional activation of the 39 K promoter, although the activity of the 39 K promoter induced by the transcriptional regulatory region was not studied in detail . To obtaactivity . In thisSpodoptera exigua, and the other economic crop pests.The AcMNPV 39 K promoter is mainly expressed by immediate early genes –39. To sIn conclusion, we constructed and optimized the synthetic baculovirus-inducible 39 K promoter that could be effectively applied for CRISPR/Cas9 gene editing and transgenic technology to construct transgene material of silkworm and provides an efficient tool for synthetic biology and gene therapy. The synthesized inducible promoters also provide new insights to improve strategies for insect genetic engineering, pest control and gene function research.B. mori ovary cell line BmN-SWU1 was cultured at 27 °C in TC-100 medium  supplemented with 10% (V/V) fetal bovine serum  and 10% (V/V) penicillin/streptomycin [prm-EGFP) containing an EGFP marker gene driven by the B. mori actin A4 promoter was created from the bacmid bMON7214, which contains the BmNPV genome [prm-EGFP construct, and viral titers were determined using the 50% tissue culture infective doses assay [The ptomycin . RecombiV genome , 42. TheFirefly luciferase (FLUC) expression vector. The 5′ truncated plasmids fragment included P-723 (− 773~ − 724 deletion), P-673 (− 773~ − 674 deletion), P-623 (− 773~ − 624 deletion), P-573 (− 773~ − 574 deletion), P-523 (− 773~ − 524 deletion), P-473 (− 773~ − 474 deletion), P-423 (− 773~ − 424 deletion), P-373 (− 773~ − 374 deletion), P-323 (− 773~ − 324 deletion), P-273 (− 773~ − 274 deletion), P-223 (− 773~ − 224 deletion), P-173 (− 773~ − 174 deletion), P-123 (− 773~ − 124 deletion), P-73 (− 773~ − 74 deletion), and P-23 (− 773~ − 24 deletion)  reporter gene were linked to the pGL3 vector, named pGL3-IE1-Rluc and used as internal reference plasmid.Previous studies have shown that the − 773 bp upstream and + 134 bp downstream motifs of the 39 K promoter transcription initiation site are critical regions for 39 K promoter activity . To analie-0, ie-1, ie2, pe38 and me53 from the BmNPV genome were cloned into a pIZ/V5-His  vector to generate pIZ-IE0, pIZ-IE1, pIZ-IE2, pIZ-PE38 and pIZ-ME53. The baculovirus-inducible promoter 39 K was cloned into the pIZ-DsRed to replace the OpIE2 promoter. The resulting p39K-DsRed plasmid was used as vector backbone for baculovirus-inducible expression of DsRed. All clones were verified by sequencing. All primers used in this study are presented in Additional file The baculovirus immediate early genes The dual luciferase expression plasmids pGL3-39 K-Fluc (450 ng) and pGL3-IE1-Rluc (50 ng) were co-transfected into the BmN-SWU1 cells. Approximately 24 h later, these were infected with BmNPV at multiplicity of infection (MOI) =10. At 72 h p.i., the cells were collected, and luciferase activities were measured with using Dual-Glo Luciferase Assay Kit (Promega) using the ultra-high sensitivity fluorescence chemiluminescence detector. Relative luciferase activity (FLUC/RLUC) was normalized to values obtained using pGL3-39 K-Fluc as control plasmid. Each experiment analysis was repeated three times.The BmN-SWU1 cells were cultured in 24-well plates . After the cells had stabilized, BmNPV immediate-early gene expression plasmids pIZ-IE0, pIZ-IE1, pIZ-IE2, pIZ-PE38 and pIZ-ME53 (0.4 μg) with the p39K-DsRed (0.4 μg) plasmid were co-transfected into cells using the X-tremeGENE HP DNA Transfection Reagent . At 48 h p.t., all cells were visualized on an Olympus inverted fluorescence microscope with the same parameter settings.Bombyx mori sw22934 gene was used as the reference. The reaction conditions of the RT-PCR reactions were as follows: 95 °C for 30 s; followed by 40 cycles at 95 °C for 5 s and 60 °C for 20 s with 1 M of each primer. All experiments were repeated three times.After the BmNPV immediate early gene expression plasmid pIZ-IE0, pIZ-IE1, pIZ-IE2, pIZ-PE38 or pIZ-ME53 with the p39K-DsRed plasmid were co-transfected into the cells, total RNA was isolated using the TRIzol RNA Extraction Kit , following the manufacturer’s instructions. RT-PCR were performed with an iTaqTM Universal SYBR® Green Supermix and CFX Connect Real-Time PCR Detection System  using primers specific for DsRed , according to the manufacturer’s recommendations.The coding region of IE-1 was amplified with specific primers IE1-F/IE1-R and cloned into the pCold-I vector and the pGX-4 T-1 vector. Positive plasmids were transformed into http://www.fruitfly.org/seq_tools/nnppHelp.html) and JASPAR CORE (http://jaspar.genereg.net/) were used. A total of four potential transcription factor binding sites were identified, which were located at positions − 486 to − 532,-386 to − 431,-310 to − 355 and + 2 to + 47 of the 39 K promoter. For EMSA, the probes were 5´-labeled with biotin (Thermo Fisher Scientific), and then the labeled oligonucleotides were annealed to produce a double-stranded probe. All probes used in this study are presented in Additional file To analyze the potential binding sites of the 39 K promoter, two different transcription factor binding site prediction programs, namely, Neural Network Promoter Prediction (w/v) native polyacrylamide gels and resolved by electrophoresis electrophoresed in TBE buffer  for approximately 1 h at 100 V on ice. The proteins were transferred onto a PVDF membrane (Roche). Bound HRP-conjugated bands were visualized using the LightShift Chemiluminescent EMSA Kit according to the manufacturer’s protocol.To evaluate the interactions between IE-1 proteins and 39 K regulatory elements, EMSA was conducted according to the guidelines of the Light Shift Chemiluminescent EMSA Kit (Thermo Fisher Scientific). After a 30 min incubation at 25 °C, reaction mixtures were loaded onto 6% , p39K-5 (contains the + 1 ~ + 136 and − 273~ − 573 fragments) and p39K-9(contains the + 1~ + 136 and − 273~ − 773 fragments). To improve the promoter activity of 39 K, point mutations of the CAAT box to CGGT at position of − 329, − 399, or − 329 and − 399 were created. A total of 12 synthetic inducible promoters were constructed in combination with truncated and point mutation vectors and designated as p39K-1 to p39K-12, respectively. All artificially inducible promoters were synthesized by Genscript  and cloned into the pGL3-basic vector.t tests using GraphPad Prism6. P values less than 0.01 were considered statistically significant.All data are expressed as the mean ± standard deviation (SD) of three independent biological experiments. Statistical analyses were performed with the Student’s Additional file 1:Figure S1. Relative luciferase assay of the BmNPV 39 K promoter CAAT motifs are involved in transcription activation Figure S2. Analysis of P39K-1 promoter regulatory element Figure S3. Application of the artificial inducible 39 K promoter to genetic engineering. Table S1. Sequences of primers used in this study. Table S2. Sequences of probes used in this study. (DOCX 156 kb)


Escherichia coli has been relieved of a common purpose and adapted to regulate virulence pleiotropically in 2 distinct genetic backgrounds. This leads to enhanced virulence of both intestinal enterohemorrhagic E. coli and extraintestinal uropathogenic E. coli by exclusive mechanisms. These findings challenge the assumption that conserved transcription factors regulate common pathways maintained within a species and suggest that transcriptional repurposing creates new primary roles on an individual basis.Bacterial pathogens emerge by adapting mechanisms of virulence, differentiating them from their nonpathogenic progenitor. Virulence factors are often encoded on accessory genomic elements not part of the core genome and therefore must be integrated into the regulatory architecture of the cell. Here, we show that a highly conserved transcription factor in  Escherichia coli pathotypes that employ distinct virulence mechanisms that facilitate specification of a different niche within the host. Strikingly, we found that the transcription factor YhaJ actively regulated unique gene sets between intestinal enterohemorrhagic E. coli (EHEC) and extraintestinal uropathogenic E. coli (UPEC), despite being very highly conserved. In EHEC, YhaJ directly activates expression of type 3 secretion system components and effectors. Alternatively, YhaJ enhances UPEC virulence regulation by binding directly to the phase-variable type 1 fimbria promoter, driving its expression. Additionally, YhaJ was found to override the universal GAD acid tolerance system but exclusively in EHEC, thereby indirectly enhancing type 3 secretion pleiotropically. These results have revealed that within a species, conserved regulators are actively repurposed in a “personalized” manner to benefit particular lifestyles and drive virulence via multiple distinct mechanisms.Tailoring transcriptional regulation to coordinate the expression of virulence factors in tandem with the core genome is a hallmark of bacterial pathogen evolution. Bacteria encode hundreds of transcription factors forming the base-level control of gene regulation. Moreover, highly homologous regulators are assumed to control conserved genes between members within a species that harbor the same genetic targets. We have explored this concept in 2  Escherichia coli devotes ∼6% of its entire genome to regulatory genes, which in turn determine what genes are expressed and therefore what functions are performed  is a zoonotic pathogen capable of causing severe diarrheal illness in humans. This pathogenesis is facilitated by colonization of the colon using a type 3 secretion system (T3SS) encoded on a pathogenicity island known as the locus of enterocyte effacement (LEE)  . This cent (LEE) –10. Furtnt (LEE) .E. coli (UPEC) are capable of colonizing extraintestinal sites such as the urinary tract and kidneys  differential expression of 123 genes, characterized largely by down-regulation of the entire LEE island (encoding a T3SS) as well as the non–LEE-encoded effector nleA (P = 1.55 × 10−4), which are both essential for virulence  (P = 6.16 × 10−7) and differential expression of the known YhaJ target gene yqjF  , 22, 23.able S1) B. Most sene yqjF .yhaJ mutant in EHEC and UPEC (referred to as ΔyhaJEHEC and ΔyhaJUPEC herein) relative to their respective WT parents, cultured under identical conditions. Similar to ΔyhaJEHEC, ΔyhaJUPEC was not defective for growth but displayed a much more restricted regulon than that of EHEC, with only 19 significant DEGs identified compared with the WT . The functional categories of these genes broke down into only 2 significantly enriched GO categories, type 1/F1C fimbrial adhesion (P = 1.15 × 10−7) and tryptophan biosynthesis (P = 4.7 × 10−8) (fimA gene (P = 0.04) specifically belonging to the T1F gene cluster suggested that YhaJ regulates this key virulence determinant of the UPEC pathotype, critical for bladder colonization  D. This wnization . Second,nditions E. This sSI Appendix, Fig. S2). We chose to investigate each natively expressed protein by engineering strains encoding 3× FLAG-tagged YhaJ in both EHEC and UPEC genetic backgrounds. We determined the global binding profile of YhaJ by enriching for chromosomal DNA immunoprecipitated with natively expressed FLAG-tagged YhaJ, identifying specific motif regions associated with these targets . This approach uncovered a unique YhaJ target map for each strain . These targets included known regulated genes  but also targets found both on the core E. coli genome (13 targets including the GAD regulator gene gadX) as well as 5 EHEC-specific sequences  (nleA (P = 8.5 × 10−4) and 2 identical autotransporters, Z1211 and Z1651, identified previously as Ag43 homologs Cah1 and Cah2 . We validated the binding of YhaJ to the extended nleA promoter region in vitro by electrophoretic mobility shift assay (EMSA) analysis and confirmed the negative regulation of this gene using an nleA::GFP reporter (P = 0.0129) in the ΔyhaJEHEC background, which we successfully complemented in trans . These data correlate well with the RNA-seq analysis in identifying directly regulated targets such as several virulence factors, the GAD acid tolerance response, and the known target yqjF  analysis. YhaJ shares >99% sequence identity (298/299 residues) in both EHEC and UPEC, with complete conservation in the DNA- and substrate-binding domains in both strains  , 26. Strand Cah2 B 27). A. ASI Appredicted . Indeed,get yqjF .SI Appendix, Table S4). Five of these binding sites were the same known YhaJ targets identified in EHEC, with similar signal enrichment . Two unique targets were identified, purD and c3206, the latter of which is a UPEC-specific hypothetical gene. Binding of YhaJ to pathotype-specific sequences was validated by EMSA analysis, demonstrating the possibility of further pathotype-specific regulatory mechanisms that are unclear under the conditions used in this study . It should be noted that all EMSAs were performed using EHEC YhaJ, confirming that the single-amino acid change in the coding sequence was not responsible for the differential binding profiles in vitro. Analysis of the peak sequences using Multiple EM for Motif Elicitation revealed almost identical predicted YhaJ motifs in both EHEC and UPEC, with high significance (E = 5.5 × 10−15) in comparison with the predicted YhaJ motif, and also matched the canonical LTTR motif structure of T-N11-A . Immunoblot analysis probing for the FLAG epitope in whole-cell lysates from both strains confirmed that expression of YhaJ in EHEC is substantially higher than in UPEC . However, ChIP-PCR analysis of 2 common YhaJ targets (yhaK and yqjF) revealed comparable signal-to-noise enrichment ratios of binding to these gene promoter regions in both strains . These results suggest that YhaJ has the potential to target common genes in both pathotypes but that its own regulation is unique in each genetic background. Nonetheless, it is apparent that a key role of YhaJ is to tailor the transcriptional program of individual pathotypes, which leads to differential expression of key virulence genes.In stark contrast to EHEC, only 7 significant YhaJ binding sites were identified in UPEC under these conditions ( T-N11-A D 21). H. HSI App T-N11-A E. SurprigadX promoter region in EHEC but not UPEC. This was highly interesting, given the significant impact that the ΔyhaJ deletion had on GAD gene expression in EHEC exclusively . Next, we validated the repression of the GAD system in EHEC by qRT-PCR analysis. ΔyhaJEHEC displayed an approximately 2.5-fold increase in expression of the GadX-regulated gene gadB (P = 0.037), whereas complementation restored WT levels of gadB expression  returned, a phenotype that was successfully complemented . Importantly, we confirmed that this phenotypic distinction in EHEC was not driven by the single-amino acid change in the YhaJ protein sequence by successfully complementing the ΔyhaJEHEC phenotype using the UPEC yhaJ allele expressed in trans . Intriguingly, despite the lack of ChIP-seq signal, YhaJ was capable of binding to the UPEC gadX promoter region in vitro by EMSA analysis in accordance with the predicted binding motif and promoter being identical between both pathotypes, suggesting that regulation of the EHEC cell circuit has been specifically tailored in vivo to control gadX directly by YhaJ, independent of any mutation in the coding or binding sequence . The data described here have revealed that YhaJ has been recruited to enhance T3SS expression in EHEC by 2 distinct mechanisms—direct activation of T3SS/prophage-encoded effector expression as well as direct repression of the GAD system, which in turn promotes T3SS expression indirectly .Natively expressed YhaJ was found to bind the lusively A. We thepression B. To teslemented C. Quanti RNA-seq D. In conin trans D. SimilayhaJUPEC revealed that this transcription factor is responsible for regulating T1F in UPEC (P = 3.2 × 10−16) upstream of the fimA gene in EHEC but not in UPEC, where enrichment was weak and almost completely absent in 1 replicate , which correlated with the transcriptome and immunoblot analysis. Complementation of YhaJ restored the phenotype, resulting in an increase in T1F-expressing cells to ∼60% of the population. These data confirm that the regulation of T1F by YhaJ at the molecular level manifests in the production of T1F at the single-cell level.Expression of T1F in  of fimA . This me of fimA D. The daE. coli isolates, pathogenic or not, possess T1F . Deletion of yhaJ in a K-12 background had no significant impact on fimA transcription, whereas in ΔyhaJUPEC the downshift was statistically significant (P = 0.0317). However, complementation of both ΔyhaJUPEC and ΔyhaJK-12 resulted in enhanced expression of fimA (P ≤ 0.005). Immunoblot analysis of FimA expression in K-12 mimicked the transcriptional data, characterized by the ability of YhaJ to regulate T1F expression only when overexpressed in trans. Furthermore, we confirmed that growth conditions were not responsible for this phenomenon . Collectively, these results have revealed that YhaJ is a functional regulator of T1F in distinct pathogenic and nonpathogenic E. coli isolates. However, pathogenic UPEC have evolved a dependency to specifically regulate T1F by YhaJ in order to achieve full expression of this virulence factor, further highlighting the potential for tailored regulatory reprogramming to have an impact on expression of key virulence genes.The majority of sess T1F . To testfimS region prompted questions about the mechanism of T1F regulation by this transcription factor. Given the strong YhaJ binding to the defective EHEC fimS element, we hypothesized that recruitment of YhaJ to fimS may occur exclusively when the promoter is orientated in the OFF phase. To test this, we performed EMSA analysis using primers that flanked the invertible element and the fimA intergenic region to amplify DNA probes of fimS in either the ON or OFF orientation exclusively. The analysis revealed that YhaJ was unable to bind UPEC fimS in the ON orientation . To confirm the specificity of this interaction, we designed 2 variants of the fimS OFF EMSA probes, mutating both the 5′ (C→T at position 2) and the 3′ (TGA→CCC at position 11 to 13) termini of the binding site, thus eliminating critical residues in the dyad symmetry of the sequence. EMSA analysis showed that mutation of either residue essentially eliminated the ability of YhaJ to bind the fimS element, thereby confirming the identification of YhaJ binding to this site exclusively in the phase OFF orientation .The design of the EMSA probes included both phase-specific rom UPEC C. This afimS site is often mediated by modulating expression of the Fim recombinases rather than binding fimS itself , thereby supporting the notion of a direct influence of YhaJ on fimS phase switching . To test this experimentally, we used a classical PCR digestion assay that determines the ratio of fimS phase ON versus OFF in a cell population. DNA of fimS and its flanks including the inverted-repeat sequences that facilitate phase inversion was amplified from UPEC cells grown under T1F-inducing conditions . Digestion of this PCR product with HinfI resulted in pairwise combinations of product sizes depending on the orientation of fimS. WT UPEC expressed ∼50% phase ON (74/485-bp bands) whereas the ΔyhaJUPEC population shifted to only 25% phase ON and the remainder phase OFF (202/357-bp bands). Complementation of YhaJ restored phase switching toward the ON orientation in excess of the WT, resulting in 75% of the population expressing fimS phase ON . These data collectively suggest that direct binding of YhaJ exclusively to phase OFF fimS facilitates inversion of the promoter element and therefore enhanced expression of T1F in pathogenic UPEC, defining a mechanism of virulence gene regulation in this pathotype.Multiple transcription factors are employed in the regulation of T1F . HoweverS itself , 28. Intphase ON D. To conE. coli isolates to investigate the prevalence of yhaJ carriage within the species  genomes. Given the distinct mechanisms uncovered in this study for YhaJ within a single species, we explored the presence of yhaJ among other bacterial pathogens. Using the same criteria as previously (presence being defined as a BLASTp score of greater than 70% sequence identity over at least 80% of the protein-coding region), we searched for carriage of yhaJ in several distinct prototypical pathogen genomes. Strikingly, this analysis identified high conservation of the yhaJ-coding sequence in the genomes from mechanistically and ecologically distinct gram-negative Salmonella, Shigella, Citrobacter, Yersinia, and Klebsiella species. Identity of the coding sequence ranged from 99% among Salmonella and Shigella isolates to 87% in Yersinia enterocolitica across 100% of the protein-coding sequence, with amino acid substitutions being largely clustered in the substrate-binding domain and complete conservation of the HTH at the N terminus  were induced in vivo through a coordinated response to host colonization in a murine model of EHEC infection (using C. rodentium)  of the LEE and the xenogenic silencing protein H-NS , 30. H-Nin vitro . Indeed,in vitro . Our anage 933-P , 34, 35.ge 933-P , 36. We dentium) . Indeed, element . MoreovefimS promoter element  directly bind fimS and are essential for its function . fimS contains 3 Lrp binding sites that facilitate DNA bending to allow correct positioning of the inverted-repeat sequences for recombination and phase variation, implying that YhaJ binding at the Lrp–fimS interface promotes T1F phase switching directly by impacting the structure of the DNA element, thus promoting UPEC virulence gene expression  mediates this phase OFF-dependent binding, priming YhaJ for regulation of fimS and subsequently resulting in release of the regulator from the element once T1F expression is initiated.In contrast, T1F in UPEC are controlled by a phase-variable inversion of the  element . Regulat element . Strikinfunction , 40. Seqpression . Furthernfection . It is ug dimers . Indeed,E. coli are adept at responding to low pH during passage through the stomach by coupling proton consumption during glutamate decarboxylation followed by efflux of the reaction byproduct GABA (gadX repression. Why would this regulation be beneficial to intestinal EHEC and not extraintestinal UPEC? Virulence regulation in response to acid is specifically blocked in E. coli that employ T3SSs (These 2 mechanisms represent highly specialized regulatory adaptations for EHEC and UPEC, given that the T3SS and T1F are instrumental for niche specification of both pathotypes . Indeed,uct GABA . GadX isuct GABA . This isoy T3SSs . Howeveroy T3SSs . Importaoy T3SSs . The exaE. coli is an incredibly diverse species. As an example, genome comparisons of EHEC, UPEC, and K-12 revealed that only 39.2% of nonredundant protein-coding sequences were conserved between the strains, driven largely by variation in horizontal gene transfer (E. coli, which is capable of colonizing distinct niches both within and beyond the intestine. Therefore, repurposing of highly conserved genes within the core genome, which are otherwise nonessential for survival, presents an intuitive way for E. coli to tailor its transcriptional architecture for performing the most important roles that the individual requires to thrive. It has been well-described that orthologous regulators can play vastly different roles between species, with perhaps the best example being PhoP that shares the regulation of only 30% of homologous gene targets between Salmonella and Yersinia (E. coli as a species (E. coli pathotypes. Our work suggests that this repurposing process may benefit the individual’s lifestyle, manifesting in pleiotropic mechanisms of virulence gene regulation by a single conserved transcription factor.transfer . Alternatransfer , 5. ThisYersinia . Further species . The extSI Appendix, Tables S5–S7. A detailed description of all methodology and associated references are in SI Appendix, Materials and Methods. This includes genetic engineering of strains, cloning, growth conditions, GFP reporter assays, qRT-PCR, RNA-seq, ChIP-seq, immunoblotting, EMSA, DNaseI footprinting, microscopy, bioinformatics, and all data analysis methods and tools. All raw sequence data have been deposited in the European Nucleotide Archive and are available under accession no. PRJEB12065.A full list of bacterial strains, plasmids, and primers used can be found in Supplementary File


Caenorhabditis elegans stage. Based on nuclear transcription profiles, we define 15,714 protein-coding promoters and 19,231 putative enhancers, and find that both types of element can drive orientation-independent transcription. Additionally, more than 1000 promoters produce transcripts antisense to protein coding genes, suggesting involvement in a widespread regulatory mechanism. We find that the accessibility of most elements changes during development and/or ageing and that patterns of accessibility change are linked to specific developmental or physiological processes. The map and characterization of regulatory elements across C. elegans life provides a platform for understanding how transcription controls development and ageing.An essential step for understanding the transcriptional circuits that control development and physiology is the global identification and characterization of regulatory elements. Here, we present the first map of regulatory elements across the development and ageing of an animal, identifying 42,245 elements accessible in at least one  The genome encodes the information for organismal life. Because the deployment of genomic information depends in large part on regulatory elements such as promoters and enhancers, their identification and characterization is essential for understanding genome function and its regulation.Caenorhabditis elegans is ideal for addressing this question, as it has a simple anatomy, well-defined cell types, and short development and lifespan. A map of regulatory elements and their temporal dynamics would facilitate understanding of the genetic control of organismal life.Regulatory elements are typically depleted for nucleosomes, which facilitates their identification using sensitivity to digestion by nucleases such as DNase I or Tn5 transposase, termed DNA accessibility . In diffActive regulatory elements have previously been shown to have different transcriptional outputs and chromatin modifications . TranscrDrosophila cell lines, it was observed that H3K4me3 and H3K4me1 levels correlate with levels of transcription at regulatory elements, rather than whether the element is a promoter or an enhancer  mutants to prevent progeny production, since they lack germ cells at the restrictive temperature. Five adult ageing time points were collected, starting from the young adult stage (day 1) and ending at day 13, just before the major wave of death.To define and characterize regulatory elements across e course . The devTo define sites that are accessible in at least one developmental or ageing stage, focal peaks of significant ATAC-seq enrichment were identified across all developmental and ageing samples, yielding 42,245 individual elements , supportC. elegans identified using DNase I hypersensitivity or ATAC-seq  suggest different potential functions. A large fraction (35.1%) generate antisense transcripts within the body of a protein coding gene, suggesting a possible role in regulating expression of the associated gene . AnotherPromoters and enhancers show general differences in patterns of histone modifications, such as higher levels of H3K4me3 at promoters or H3K4me1 at enhancers, and chromatin states are frequently used to define elements as promoters or enhancers . HoweverTo further investigate the relationship between chromatin marking and element function, we mapped four histone modifications at each developmental stage  and examined their patterns around coding promoters and enhancers. As expected, many coding promoters had high levels of H3K4me3 and were depleted for H3K4me1 . Moreove−15, Spearman's rank correlation; To investigate the nature of these patterns, we examined coefficients of variation of gene expression CV;  of the aPromoters and enhancers also share sequence features. Both are enriched for initiator INR elements, although enhancers have a slightly lower INR frequency . Promotehlh-2, ztf-11 and bed-3 genes), and found that all three drove robust expression of a histone-GFP reporter . If the lack of in vivo transcription elongation was a property of the element or initiation site itself, the GFP fusion should not be expressed. However, we observed that the two inverted unidirectional promoters both drove GFP expression. The expression patterns generated were similar in both orientations, although the ztf-11 promoter was weaker when inverted , similar to the pattern seen in mammals. Most (82.6%) are unidirectional promoters, producing a protein-coding transcript in one direction, but no stable transcript from the upstream initiation site. To test whether such upstream antisense initiation sites could function as promoters, we inverted the orientation of two active unidirectional promoters  of promoters showing changes . InteresAs for the development time course, we clustered accessibility changes in ageing. We identified eight clusters of promoters with similar accessibility changes across ageing and annotated them based on tissue biases in gene expression . This deWe then evaluated the enrichment of transcription factors at each ageing promoter cluster. The binding of DAF-16/FoxO, a master regulator of ageing , is assoC. elegans chromatin and functionally annotated them based on transcription patterns at the accessible site. This avoided the problems of histone-mark-based approaches for defining element function , L2 (20 hr), L3 (30 hr), L4 (45 hr), young adults (60 hr). Mixed populations of embryos were collected by bleaching cultures of synchronized 1-day-old adults.glp-1(e2144) were raised at 15°C on standard NGM plates seeded with OP50 bacteria. Embryos were obtained by bleaching gravid adults and then approximately 6000 placed at 25°C on 150 mm 2% NGM plates seeded with a 30X concentrated overnight culture of OP50. For harvest, worms were washed 3X in M9 and then worm slurry was frozen into popcorn by dripping into liquid nitrogen and stored at −80°C. Harvest times after embryo plating were D1/YA (53 hr), D2 (71 hr), D6 (167 hr), D9 (239 hr), D13 (335 hr).Frozen embryos or worms (1–3 frozen popcorns) were broken by grinding in a mortar and pestle or smashing using a Biopulverizer, then the frozen powder was thawed in 10 ml Egg buffer . Ground worms were pelleted by spinning at 1500 g for 2 min, then resuspended in 10 ml working Buffer A  containing 0.025% IGEPAL CA-630. The sample was dounced 10X in a 14-ml stainless steel tissue grinder (VWR), then the sample spun 100 g for 6 min to pellet large fragments. The supernatant was kept and the pellet resuspended in a further 10 ml Buffer A, then dounced for 25 strokes. This was spun 100 g for 6 min to pellet debris and the supernatants, which contain the nuclei, were pooled, spun again at 100 g for 6 min to pellet debris, and transferred to a new tube. Nuclei were counted using a hemocytometer. One million nuclei were transferred to a 1.5-ml tube and spun 2000 g for 10 min to pellet. ATAC-seq was performed essentially as in Replicate concentration courses of DNase I were performed for each stage as follows. Twenty million nuclei were digested in Roche DNAse I buffer for 10 min at 25°C using 2.5, 5, 10, 25, 50, 100, 200, and 800 units/ml DNase I (Roche), then EDTA was added to stop the reactions. Embryo micrococcal nuclease (MNase) digestion concentration courses for embryos were made by digesting nuclei with 0.025, 0.05, 0.1, 0.25, 0.5, 1, 4, 8, or 16 units/ml MNase in 10 mM Tris pH 7.5, 10 mM MgCl2, 4 mM CaCl2 for 10 min at 37C. Reactions were stopped by the additon of EDTA. Following digestions, total DNA was isolated from the nuclei following proteinase K and RNase A digestion, then large fragments removed by binding to Agencourt AMPure XP beads (0.5 volumes). Small double cut fragments < 300 bp were isolated either using a Pippen prep gel (protocol 1) or using Agencourt AMPure XP beads (protocol 2). Libraries were prepared as described in the Sequencing library preparation section below.Nuclei were isolated and then chromatin associated RNA (development series) or nuclear RNA (ageing series) was isolated. Chromatin associated RNA was isolated as in , resuspeBalls of frozen embryos or worms were ground to a powder using a mortar and pestle or a Retch Mixer Mill to break animals into pieces. Frozen powder was thawed into 1% formaldehyde in PBS, incubated 10 min, then quenched with 0.125M glycine. Fixed tissue was washed 2X with PBS with protease inhibitors (Roche EDTA-free protease inhibitor cocktail tablets 05056489001), once in FA buffer  with protease inhibitors (FA+), then resuspended in 1 ml FA +buffer per 1 ml of ground worm powder and the extract sonicated to an average size of 200 base pairs with a Diagenode Bioruptor or Bioruptor Pico for 25 pulses of 30 s followed by 30 s pause. For ChIP, 500 ug protein extract was incubated 2 ug antibody in FA +buffer with protease inhibitors overnight at 4°C, then incubated with magnetic beads conjugated to secondary antibodies for 2 hr at 4°C. Magnetic beads bound to immunoprecipitate were washed at room temperature twice in FA+, then once each in FA with 0.5M NaCl, FA with 1M NaCl, 0.25M LiCl  and finally twice with TE pH8. Immunoprecipitated DNA was then eluted twice with 1% SDS, 250 mM NaCl, 10 mM Tris pH8, 1 mM EDTA at 65°C. Eluted DNA was treated with RNase for 1 hr at 37C and crosslinks reversed by overnight incubation at 65°C with 200 ug/ml proteinase K, and the DNA purified using a Qiagen column. Libraries were prepared as described in the Sequencing library preparation section below. Two biological replicate ChIPs were conducted for each histone modification at each developmental time point . Antibodies used were: anti-H3K4me3 (Abcam ab8580), anti-H3K4me1 (Abcam ab8895), anti-H3K36me3 (Abcam ab9050), and anti-H3K27me3 (Wako 309–95259).https://ethanomics.files.wordpress.com/2012/09/chip_truseq.pdf. Briefly DNA fragments are first repaired with an End repair enzyme mix  for 30 min at 20C in 50 µl, then all DNA fragments were recovered using 1 vol of AMPure XP beads and 1 vol of 30% PEG8000 in 1.25M NaCl, and eluted in 16.5 µl of H2O. The DNA was 3’ A-tailed in 1X NEB buffer 2 using 2.5 units of Klenow 3’ to 5’ exo(minus)  and 0.2 mM ATP for 30 min at 37C in 20 µl. Illumina Truseq adaptors were then directly ligated to the DNA fragments by adding 25 µl 2X buffer, 1 µl of 0.06 nM adaptors (1 µl of 1:250 dilution of Illumina stock solution), 2.5 µl water and 1.5 µl of NEB Quick ligase (cat M2200). After 20 min at room temperature, 5 µl of 0.5M EDTA pH8 was added to inactivate the enzyme and DNA was purified using AMPure XP beads. For DNAse and MNase libraries, 1.3 volumes of beads were used; for ChIP libraries, 0.9 volumes of beads were used. DNA fragments were eluted in 20 µl of H2O. We used 1 µl to determine the number of cycles needed to get amplification to 50% of the plateau as in https://ethanomics.wordpress.com/ngs-pcr-cycle-quantitation-protocol/. Libraries were amplified by PCR by adding 20 µl of the KAPA Hifi Hotstart Ready Mix (Kapabiosystem cat KK2601) and 1 µl of 25 uM Illumina Universal primers. Libraries were then size selected. DNAse and MNase libraries were purified using 1.3 volumes of beads. For ChIP libraries, 0.7 volumes of beads were added to bind large DNA. Beads were discarded and DNA recovered from the supernatant by adding 0.75 volumes of beads and 0.75 volumes of 30% PEG8000 in 1.25M NaCl. DNA was eluted in 40 µl water and 0.8 volumes of beads used to bind the library, leaving adaptor dimers in the supernatant. DNA was eluted in 10–15 µl water, quantified using a Qubit, and analyzed using a Agilent Tapestation.DNA was converted into sequencing libraries using a modified Illumina Truseq protocol based on Reads were aligned using bwa-backtrack  in singlFor ATAC-seq, normalized genome-wide accessibility profiles from single-end reads were then calculated with MACS2  using thShort-cap and long-cap data were processed essentially as in ChIP-seq data was processed as in Stage-specific tracks used in downstream analyses were obtained by averaging normalized signal across two biological replicates. Manipulations of genome-wide signal were performed using bedtools , UCSC utTo assess the reproducibility of replicate datasets, we performed PCA using the plotPCA function in DESeq2  on peak Accessible sites were identified as follows. We first identified concave regions (regions with negative smoothed second derivative) from ATAC-seq coverage averaged across all stages and replicates. This approach is extremely sensitive, identifying a large number  of peak-like regions. We then scored all peaks in each sample using the magnitude of the sample-specific smoothed second derivative. We used IDR  on the sC. elegans genome, and WormBase WS260 genome annotations - with coordinates backlifted to WBcel215/ce10 (WS220). For convenience, Throughout this study, we used the WBcel215/ce10 (WS220) version of the For motif analyses, Inr and TATA consensus sequences were obtained from http://www.encodeproject.org or http://data.modencode.org (EOR-1). ChIP-seq profiles were manually inspected and 227 high quality datasets selected, covering 176 transcription factors  are from ; processPatterns of nuclear transcription were used to annotate elements. At each stage, separately on both strands, we assessed 1) initiating and elongating transcription at the site, 2) continuity of transcription from the site to the closest downstream gene, and 3) positioning of nearby exons (on the matching strand).To assess for transcription elongation at an accessible site, we counted 5' ends of long cap reads upstream (−250:−75), and downstream (+75:+250) of peak accessibility. We then used two approaches to identify sites with a local increase in transcription elongation. First, we used DESeq2 to test for an increase in downstream vs upstream counts (‘jump’ method). Statistical significance was called at log2FoldChange > 1.5, and adjusted p-value<0.1 (one-sided test). To capture additional regions with weak signal (‘incr’ method), we accepted sites with 0 reads upstream, at least one read in both biological replicates downstream, and three reads total when summed across both biological replicates.To assess transcription initiation, we pooled short cap across all six wild-type stages, and included two additional embryo replicates from We annotated accessible sites as coding_promoter or pseudogene_promoter if they fulfilled the following four criteria. (1) The accessible site had transcription initiation, and passed at least one of the elongation tests (jump or incr), or passed both elongation tests (jump and incr). (2) Transcription initiation mode at the accessible site was either upstream of the closest first exon, or, in the presence of a UTR, up to 250 bp downstream within the UTR. . (3) The region from peak accessibility to the closest first exon did not contain the 5' end of a non-first exon. (4) Distal sites (peak accessibility >250 bp from the closest first exon) were additionally required to (a) have continuous long-cap coverage from 250 bp downstream of peak accessibility to the closest first exon, and (b) be further than 250 bp away from any non-first exon.We then further attempted to assign a single, lower-confidence promoter to genes that were not assigned a promoter so far. For every gene without promoter assignments, we re-examined sites that fulfilled criteria (2-4), and were either intergenic, or within 250 bp of the closest first exon. We then annotated the site with the largest jump test log2FoldChange as the promoter, if it was also larger than 1.Next, sites within 250 bp of the 5' end of an annotated tRNA, snRNA, snoRNA, miRNA, or rRNA were annotated as non-coding_RNA. Intergenic sites more than 250 bp away from annotated exons that had initiating transcription, and passed the jump test were annotated as unassigned_promoter. All remaining sites were annotated as transcription_initiation or no_transcription based on whether they had transcription initiation.Elements were then annotated on each strand based on aggregating transcription patterns across stages by determining the ‘highest’ annotation using the ranking of: coding_promoter, pseudogene_promoter, non-coding_RNA, unassigned_promoter, transcription_initiation, no_transcription. Element type and coloring was then defined using the following ranking: coding_promoter on either strand => coding_promoter (red); pseudogene_promoter on either strand => pseudogene_promoter (orange); non-coding_RNA on either strand => non-coding_RNA (black); unassigned_promoter on either strand => unassigned_promoter (yellow); transcription_initiation on either strand => putative_enhancer (green); all remaining sites => other_element (blue). Accessible elements with regulated accessibility were determined as follows. All elements  were tested for a difference in ATAC-seq coverage between any two developmental time points or between any two ageing time points using DESeq2 . Sites wk-medoids, as implemented in the pam method of the cluster R package , with FPM values instead of ATAC-seq coverage values.Using single-cell RNA-seq data from C. elegans GO database. Significant enrichment was set at an adjusted p-value of 0.05, and hierarchically redundant terms were automatically removed by gProfileR.GO enrichments were evaluated using the R package gProfileR  against Prior to analysis of TF peak enrichment at annotated promoters, accessible elements considered ‘HOT’ (see above) were removed, resulting in 10,086 to be assessed by enrichment analysis. Only transcription factors with more than 200 peaks overlapping ‘non-hot’ regulatory elements were kept, to ensure sufficient data for analysis. Following this stringent filtering, 89 transcription factors could be assayed for binding enrichment. Transcription factor binding enrichment in each cluster was estimated using the odds ratio and enrichments with an associated p-value<0.01 (Fisher’s exact test) were kept. Transcription factors which did not show enrichment higher than two in any cluster were discarded. his-58 (plasmid pJA357), and site three has gfp-tbb-2 3’UTR  as in  pJA256;  in the M pJA256; .http://www.ncbi.nlm.nih.gov/geo/) under accession number GSE114494.ATAC-seq, ChIP-seq, DNase/MNase-seq, long/short cap RNA-seq data from this study, including processed tracks are available at the NCBI Gene Expression Omnibus (GEO) .Thank you for submitting your article "Chromatin accessibility dynamics across The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.Summary:The reviewers appreciated the high impact of the work, particularly as an important resource for the community. The reviewers generally agreed that the experimental designs and data analyses were rigorous and the results were well described.Essential revisions:1) A major point that needs to be addressed is the potential caveats relate to changes in cell numbers as pointed out by reviewer 2. This can be addressed textually, however the corresponding conclusions will need to modified accordingly.2) The reviewers suggested a number of clarifications, including additional quality control analyses, and clear discussion of differences in methods. These include all specific comments from reviewers 1 and 3 below.Reviewer #1:C. elegans lifespan, from development to adulthood, and, for the first time in worm, throughout several stages of adulthood. The authors identify > 40K elements with accessible chromatin in at least one of the assayed time points, with highly dynamic landscape of accessibility throughout worm lifespan. Using nuclear transcription profiling, to bypass the C. elegans specific trans-splicing phenomenon, the authors refine annotations of >15K promoter and > 19K enhancers. Both classes of elements seem to be able to drive bidirectional transcription based on follow-up reporter experiments in 2 lines.This manuscript by Janes et al., described a novel dataset resource mapping chromatin elements throughout The article does describe the resource dataset well, and the raw data is already readily available. This resource will be of broad interest to the aging and chromatin fields. A couple of points need to be further clarified, and some complementary analyses need to be performed for reproducibility and statistical soundness.glp-1 mutant, serving as an anchor point between the developmental and adult datasets. The rationale for the switch is reasonable, but it would be important to discuss how similar/dissimilar the YA ATAC-seq data is between the two strains (N2 and glp-1 mutant).1) The young adult stage profiling is performed in 2 distinct contexts: WT N2 and the 2) In the Discussion section of similarity vs. dissimilarity with previous developmental datasets, it would also be important to include the state of culture: liquid vs. solid, as this may have broad consequences on gene activation patterns, notably in the muscle tissue. The Daugherty et al., paper used solid cultures, whereas this study had liquid cultures . It would be important to include a significance of correlation test.3) In the CV analysis , it may be useful to include a statistical analysis, for instance in the form of a significance of correlation test, and maybe a scatter plot.4) In the Materials and methods section, the authors mention the use of "the Illumina TruSeq kit or a homemade equivalent". For the sake of reproducibility, it is important to include (i) a table listing which dataset was generated which each kit/method and (ii) a description of the "homemade equivalent .5) For the tissue-specific enrichment analysis , the use of a background and how it was selected needs to be included. This choice can greatly affect observed enrichment results.6) Metagene analysis are convenient representation tools but (i) they smooth away variations in the data, potentially masking heterogeneity, and (ii) have no statistical support for changes described. To fully support conclusions, the authors need to include a complementary statistical analysis for the data reported in Figure 3B, Figure 1—figure supplement 1C/D, Figure 2—figure supplement 1B/C, Figure 3—figure supplement 1B. This can be done by either including the 95% confidence interval on the metagene plots or performing a quantitative analysis using a boxplot and a non-parametric Wilcoxon rank-sum test.Reviewer #2:C. elegans along with five stages of aging adults to define accessible sites. They also collect long nuclear RNA-seq data for each time point in both time series to help classify the accessible sites into promoter and enhancer types. To further augment the developmental series in particular, the authors collected chromatin ChIP-seq data and short, capped nuclear RNA to assess chromatin state and transcription initiation, respectively. After assigning a type to the accessible regions, they cluster the promoter sites based on their accessibility over the developmental time course and the aging time course. Using single cell data from Cao et al., (2017) they find that some site clusters are associated with target genes with tissue-specific expression. They also use the single cell data in conjunction with ChIP-seq TF data to show that some TFs are preferentially associated with genes expressed in certain tissues.The authors present whole animal ATAC-seq data for six developmental stages of C. elegans community, and their evaluation of chromatin marks relative to promoters, enhancers, and the patterns of expression of the target genes should be of interest to the wider chromatin community. The fact that most sites change over time is not surprising, given that the expression of most genes changes considerably over time. This conclusion and the cluster analysis is complicated by the fact that the fraction of cells from any given tissue changes over time, and thus the fraction of reads from a peak associated with that tissue will change, even if accessibility at that site within that cell does not change over time. The clearest example is the gonad, where cells from this tissue go from being less than 1% of the total cell (genome) number to more than half over the course of larval development. An accessible site in gonad cells that was constant throughout this expansion would be expected to show a large increase over time, simply from the increasing cell number. Similarly, intestinal cells double their genomes with each larval molt. Neurons and muscle increase in L1 but not thereafter, so proportionally the signal from their accessible sites would be expected to diminish over time, even if accessibility remained constant. Indeed, the patterns of most of the assigned clusters for the developmental time course follow the expectation from cell numbers. Finally, the analysis of TF ChIP-seq data seems quite similar to that of Cao et al., except that the authors condition their analysis on overlap of ChIP-seq sites with accessible sites. However, since the overlap of accessible sites with ChIP-seq sites is very high, it is not clear what is new here.Overall, the paper is well-written and the data sets seem of high quality. The chromatin accessibility data should be of considerable interest to the In sum, the paper presents data sets that will provide an important resource for the worm community. The biological insights are modest in the present paper, but its utility to the community should produce valuable insights over time.Reviewer #3:C. elegans. In general, the experimental design and the data processing all appear rigorous and well done. By comparing the ATAC data with RNA-seq of nuclear RNAs, the authors define many promoters and putative enhancers. Moreover, the authors found that many of the accessible sites show dynamic developmental regulation, and the sites are often associated with tissue-specific gene expression. Overall, the data reported represent an important resource for the community.The Janes et al., manuscript reports ATAC seq profiling along a developmental and aging time course in whole worm 1) It will be important to show quality control analyses to assess the reproducibility of the data / between replicates.2) Similarly, MDA or PCA to show the overall relatedness of the data from the different time points will be helpful.3) For the ATAC data comparison with previously published data, the authors indicated that different peak calling parameters likely account for the differences. It will be helpful for the authors to examine their data using the previously published analysis pipelines (or vice versa) and provide some quantification of the differences / similarities between the datasets. Essential revisions:Reviewer #1:This manuscript by Janes et al., described a novel dataset resource mapping chromatin elements throughout C. elegans lifespan, from development to adulthood, and, for the first time in worm, throughout several stages of adulthood. The authors identify > 40K elements with accessible chromatin in at least one of the assayed time points, with highly dynamic landscape of accessibility throughout worm lifespan. Using nuclear transcription profiling, to bypass the C. elegans specific trans-splicing phenomenon, the authors refine annotations of >15K promoter and > 19K enhancers. Both classes of elements seem to be able to drive bidirectional transcription based on follow-up reporter experiments in 2 lines.The article does describe the resource dataset well, and the raw data is already readily available. This resource will be of broad interest to the aging and chromatin fields. A couple of points need to be further clarified, and some complementary analyses need to be performed for reproducibility and statistical soundness.1) The young adult stage profiling is performed in 2 distinct contexts: WT N2 and the glp-1 mutant, serving as an anchor point between the developmental and adult datasets. The rationale for the switch is reasonable, but it would be important to discuss how similar/dissimilar the YA ATAC-seq data is between the two strains (N2 and glp-1 mutant).glp-1 young adults is the absence of germ line tissue in glp-1 young adults. To validate this difference in the ATAC-seq data and address the reviewer’s question about similarities and differences, we compared signal at protein-coding promoters based on the tissue with maximum expression according to . Promoters of genes with the highest expression in somatic tissues show correlations between 0.87 and 0.90 (Spearman rank correlation), validating similarity between wild-type and glp-1 somatic tissue. As expected, promoters of genes with the highest expression in the gonad show a lower correlation of 0.71. Many of these latter promoters are ubiquitously active, and so also have ATAC-seq signal in somatic tissues, leading to a relatively high correlation.We make no comparisons between the developmental and ageing datasets in this paper, hence we do not discuss similarities and differences. The primary difference between wild-type N2 and Spearman's rank correlation was calculated between peak accessibility at protein-coding promoters between wild-type young adult, and glp-1 day 1 time points. Promoters were grouped by the tissue with highest gene expression of the target gene, according to L2 single-cell gene-expression data from .</2) In the Discussion section of similarity vs. dissimilarity with previous developmental datasets, it would also be important to include the state of culture: liquid vs. solid, as this may have broad consequences on gene activation patterns, notably in the muscle tissue. The Daugherty et al., paper used solid cultures, whereas this study had liquid cultures . It would be important to include a significance of correlation test.glp-1 young adults grown on solid media. Notably, ATAC-seq signals at regulatory elements of genes with muscle biased expression show equally high correlation compared to those of other somatic tissues, suggesting that media type is unlikely to play a major role in accessibility differences. Nevertheless, we added to the paper that such a difference could have some contribution. Further, in response to this point and reviewer 3 point 3, we have expanded the analyses  and discussion of similarities and differences between previous datasets (see below).In the response to point 1 above, we compared accessibility of elements in wild-type young adults grown in liquid culture and 3) In the CV analysis , it may be useful to include a statistical analysis, for instance in the form of a significance of correlation test, and maybe a scatter plot.We have added a p-value confirming the statistical significance of the correlation.4) In the Materials and methods section, the authors mention the use of "the Illumina TruSeq kit or a homemade equivalent". For the sake of reproducibility, it is important to include (i) a table listing which dataset was generated which each kit/method and (ii) a description of the "homemade equivalent .We have added a section to the Materials and methods section describing the protocol used to prepare the sequenced libraries.5) For the tissue-specific enrichment analysis , the use of a background and how it was selected needs to be included. This choice can greatly affect observed enrichment results.We have clarified this in the Materials and methods section as follows:“Using single cell RNA-seq data from , we defined tissue-biased gene expression as follows: Gene expression was considered enriched in a given tissue if it had a fold-change >= 3 between expression in the tissues with highest and second highest levels and an adjusted p-value < 0.01. This defined 5,315 genes with tissue-biased expression . For each developmental or ageing cluster of promoters, we calculated the percentage of genes with biased expression in a given tissue relative to the total number of genes in the cluster. These values were plotted in Figure 4 A and B (bar plots).”6) Metagene analysis are convenient representation tools but (i) they smooth away variations in the data, potentially masking heterogeneity, and (ii) have no statistical support for changes described. To fully support conclusions, the authors need to include a complementary statistical analysis for the data reported in Figure 3B, Figure 1—figure supplement 1C/D, Figure 2—figure supplement 1B/C, Figure 3—figure supplement 1B. This can be done by either including the 95% confidence interval on the metagene plots or performing a quantitative analysis using a boxplot and a non-parametric Wilcoxon rank-sum test.As requested, we have added 95% confidence intervals to Figure 2—figure supplement 1B,C; Figure 3B; Figure 3—figure supplement 1B. For Figure 1—figure supplement 1C and D only two data points (replicates) were available for each comparison group (assay/condition). We therefore highlighted the signal range for every group.Reviewer #2:The authors present whole animal ATAC-seq data for six developmental stages of C. elegans along with five stages of aging adults to define accessible sites. They also collect long nuclear RNA-seq data for each time point in both time series to help classify the accessible sites into promoter and enhancer types. To further augment the developmental series in particular, the authors collected chromatin ChIP-seq data and short, capped nuclear RNA to assess chromatin state and transcription initiation, respectively. After assigning a type to the accessible regions, they cluster the promoter sites based on their accessibility over the developmental time course and the aging time course. Using single cell data from Cao et al., (2017) they find that some site clusters are associated with target genes with tissue-specific expression. They also use the single cell data in conjunction with ChIP-seq TF data to show that some TFs are preferentially associated with genes expressed in certain tissues.Overall, the paper is well-written and the data sets seem of high quality. The chromatin accessibility data should be of considerable interest to the C. elegans community, and their evaluation of chromatin marks relative to promoters, enhancers, and the patterns of expression of the target genes should be of interest to the wider chromatin community. The fact that most sites change over time is not surprising, given that the expression of most genes changes considerably over time. This conclusion and the cluster analysis is complicated by the fact that the fraction of cells from any given tissue changes over time, and thus the fraction of reads from a peak associated with that tissue will change, even if accessibility at that site within that cell does not change over time. The clearest example is the gonad, where cells from this tissue go from being less than 1% of the total cell (genome) number to more than half over the course of larval development. An accessible site in gonad cells that was constant throughout this expansion would be expected to show a large increase over time, simply from the increasing cell number. Similarly, intestinal cells double their genomes with each larval molt. Neurons and muscle increase in L1 but not thereafter, so proportionally the signal from their accessible sites would be expected to diminish over time, even if accessibility remained constant. Indeed, the patterns of most of the assigned clusters for the developmental time course follow the expectation from cell numbers.When clustering promoter accessibility changes across development, clear patterns are visible. As noted by the reviewer, in some cases these patterns follow changes in cell number during development. However, this does not invalidate the clustering analysis, which aimed at identifying groups of promoters with similar patterns of accessibility across development or ageing. The patterns could be due to changes in accessibility or changes in cell number. For example, through this method we identified different groups of germ line active promoters that have greatly increased accessibility signals as the germ cell number increases, that are active in the germ line. Other patterns, such as oscillating accessibility (observed in Cluster H) or decreased accessibility after embryogenesis (Clusters Mix6 and Mix7) are likely to be due to accessibility regulation rather than changes in cell number. We clarified in the manuscript that the accessibility changes may sometimes reflect changes in cell numbers rather than the accessibility dynamics across development.Reviewer #3:The Janes et al., manuscript reports ATAC seq profiling along a developmental and aging time course in whole worm C. elegans. In general, the experimental design and the data processing all appear rigorous and well done. By comparing the ATAC data with RNA-seq of nuclear RNAs, the authors define many promoters and putative enhancers. Moreover, the authors found that many of the accessible sites show dynamic developmental regulation, and the sites are often associated with tissue-specific gene expression. Overall, the data reported represent an important resource for the community.1) It will be important to show quality control analyses to assess the reproducibility of the data / between replicates.2) Similarly, MDA or PCA to show the overall relatedness of the data from the different time points will be helpful.We have added PCA plots showing reproducibility and broad relatedness of the samples and assays in Figure 1—figure supplement 2.3) For the ATAC data comparison with previously published data, the authors indicated that different peak calling parameters likely account for the differences. It will be helpful for the authors to examine their data using the previously published analysis pipelines (or vice versa) and provide some quantification of the differences / similarities between the datasets.As suggested, we used MACS2 to call peaks on our ATAC-seq data as done by Daugherty et al., 2017 and then compared this set to the accessible sites presented in this paper, which were identified using a focal enrichment peak calling method. Overall, the MACS2 peak calls are very similar to the accessible sites reported in this study . The overlapping sites are enriched for ChIP-seq peaks and transcription initiation signal, and they are depleted for mapping at exons. The accessible sites that do not overlap MACS2 peak calls are similar to these, showing transcription initiation signal and depletion for exons, but this set is depleted for ChIP-seq peaks suggesting they may be sites active in a small number of cells. The small fraction of MACS2 peak calls that do not overlap an accessible site  are similar to the peak calls found by Daugherty et al., 2017 or Ho et al., 2017 but that are not present in our accessible sites. They are depleted for ChIP-seq peaks and transcription initiation signal, and they are enriched in annotated exons. The difference in peak calling methods therefore can account for some of the differences with previously published data. However, the fraction of such sites is relatively small indicating that data specific differences also contribute. Indeed, the peaks defined using MACS2 on the ATAC-seq data reported here still show substantial differences with those reported by Daugherty et al., 2017 . We include this analysis as a new figure  and discuss the results in the text (subsection “Defining and annotating regions of accessible DNA”). Contributing factors may be differences in signal to noise or differences in growth methods (liquid vs solid media).


Transcriptional buffering enforced during DNA replication shows that histone acetylation governs the homeostasis process and can also restrict promoters from reaching maximum transcriptional potential Imaging of transcription by quantitative fluorescence-based techniques allows the examination of gene expression kinetics in single cells. Using a cell system for the in vivo visualization of mammalian mRNA transcriptional kinetics at single-gene resolution during the cell cycle, we previously demonstrated a reduction in transcription levels after replication. This phenomenon has been described as a homeostasis mechanism that buffers mRNA transcription levels with respect to the cell cycle stage and the number of transcribing alleles. Here, we examined how transcriptional buffering enforced during S phase affects two different promoters, the cytomegalovirus promoter versus the cyclin D1 promoter, that drive the same gene body. We found that global modulation of histone modifications could completely revert the transcription down-regulation imposed during replication. Furthermore, measuring these levels of transcriptional activity in fixed and living cells showed that the transcriptional potential of the genes was significantly higher than actual transcription levels, suggesting that promoters might normally be limited from reaching their full transcriptional potential. Transcription is a key event in the gene expression pathway. Imaging of transcription in living cells by the use of fluorescence techniques has become an important tool in our understanding of the dynamic expression of genes, and has been providing unique information, in parallel to data obtained from biochemical, molecular, and bioinformatics approaches . Transcrcyclin D1 (CCND1) gene in living human cells  promoter. We found that the levels of active mRNA transcription were significantly modulated after DNA replication (S phase). Transcription that occurred after replication was easily visualized in this system since the duplicated transcribing genes on the sister chromatids were detected as gene doublets. This analysis revealed a drastic reduction in the transcription levels of these two alleles from after replication up until cell division. Specifically, the transcriptional output of the two CCND1 alleles after replication was 50% lower than that in the one allele in G1 before replication. Together, the output of the two alleles was similar to the mRNA production of one allele before replication, such that CCND1 mRNA levels remained relatively constant during the cell cycle.An important question in the field relates to how cells control mRNA transcription levels throughout the cell cycle. We have previously followed transcription from single alleles during the different phases of the cell cycle. We used a cell system that allowed real-time tagging of mRNAs transcribed from a single an cells . Using iOct4 and Nanog genes show a decrease in the transcriptional activity of each allele following replication  or under the control of the CMV promoter (D1CMVpr) (D1CMVpr gene was roughly twice that on the D1CCND1pr gene (14 ± 4 versus 7 ± 4 nascent transcripts/gene). This implied that several RNA polymerase II (Pol II) enzymes were engaged in active transcription along the genes, and modeling the data showed that successful Pol II recruitment to the promoter was twice as high when driven by the CMV promoter  . The numpromoter . Importaromatids . Surprisromatids .CCND1-MS2 genes changed slightly after TSA treatment  under TSA treatment and found enhanced fluorescence signal of the active transcription sites (single genes) for cells in G1  compared with much lower variation in untreated cells (mean difference: 3 ± 3 transcripts), . When weCCND1-MS2 genes occurred during the mid/late S phase  was observed, which took several hours after TSA addition . We manaVideo 1Download videoTranscriptional activation of a single CCND1-MS2 gene during TSA treatment. HEK293 CCND1-MS2 cells transiently expressing MS2-GFP (green) were treated with TSA. The transcribed CCND1 mRNA on the active gene (under CMV control) is seen as a bright green dot. Image acquisition started 60 min after TSA addition. Cell is imaged every 3 min for 66 min.Video 2Download videoTranscriptional activation of duplicated CCND1-MS2 genes during TSA treatment. HEK293 CCND1-MS2 cells transiently expressing MS2-GFP (green) were treated with TSA. The transcribed CCND1 mRNA on the active genes (under CMV control) is seen as bright green dots. Image acquisition started 30 min after TSA addition. Image acquisition started 30 min after TSA addition. Cell is imaged every 10 min for 110 min.Video 3Download videoTranscriptional activation of duplicated CCND1-MS2 genes during TSA treatment. HEK293 CCND1-MS2 cells transiently expressing MS2-GFP (green) were treated with TSA. The transcribed CCND1 mRNA on the active genes (under CMV control) is seen as bright green dots. Image acquisition started 13 min after TSA addition. Cell is imaged every 4 min for 44 min.mRNA expression levels can change during the cell cycle and must account for the duplication of the genetic content in the cell from S phase through G2 until cell division. Several studies that used single-molecule mRNA FISH found a 50% reduction in transcription levels after replication for a number of mammalian genes . A more CCND1 gene under the control of two very different promoters. Live-cell imaging showed that the CCND1 gene under its endogenous promoter fluctuates between “ON” and “OFF” states, each lasting up to many minutes. This pulsatile behavior has been called “transcriptional bursting” and has turned out to be an important mode of transcription in eukaryotes to fine tune the level of transcription, mainly in the case of highly regulated genes, such as CCND1. On the other hand, the CCND1 allele, driven by the CMV promoter, did not show any periods of gene inactivity, rather the gene was constantly in an “ON” state, except when undergoing cell division, as expected from an overexpression state.We have used a single-gene system that allows the detection of transcription in fixed and living cells, to follow mRNA transcription through the cell cycle . PreviouUsing quantitative RNA FISH, we found that there was at least a 50% reduction in the mRNAs transcribed from these genes after replication, for both of the promoters. This meant that the mRNA output of the duplicated alleles (after their replication) was comparable to the mRNA output of the single allele (before replication), thus demonstrating the buffering effect discussed above. In this study, we utilized protein acetylation/deacetylation to temper with the transcription driven from two promoters in mammalian cells during the cell cycle. We used TSA, which is an HDAC inhibitor that can cause histone hyperacetylation, chromatin decondensation, and gene activation. We found that preventing histone deacetylation led to an increase in the transcription levels of the duplicated alleles, thereby circumventing the buffering effect imposed during replication. In addition, the levels of transcription from the single gene were increased as well, when deacetylation was inhibited. In other words, for cells before replication, the genes exhibited expression levels that were significantly higher than normal untreated conditions. Furthermore, for cells in S/G2, the duplicated genes also showed high levels of transcription, which were similar to the transcription in the G1 cells, in stark contrast to the drastic reduction in transcription seen after replication under regular growth conditions.The live-cell data showed that TSA treatment caused a gradual increase in transcriptional activity for the alleles before replication. In contrast, following the duplicated alleles showed genes that were barely transcribing (due to passage through replication), and then a dramatic burst in transcription merely several minutes after, suggesting that TSA treatment caused a rapid and global change in the chromatin landscape of the gene allowing it to reach extremely high levels of transcription, which are usually not observed. These live-cell data also give a feeling for the time scale of histone modification effects on transcriptional activation. These observations in live mammalian cells agree with the mechanism proposed for gene dosage homeostasis in yeast cells , namely,CCND1 promoter, both transcribing the same gene from the exact same genomic locus, exemplifies that epigenetic control is only one side of the coin. The CCND1 promoter was influenced by the TSA treatment but to much lower levels compared with the CMV promoter, which was highly affected by TSA. The CCND1 promoter sequence is highly complex, containing many types of transcription factor binding sites  expressing the iversity ) were pr2 control (Life Imaging Services). For long-term imaging of transcription-site activation, several cell positions were chosen and recorded by a motorized stage .Widefield fluorescence images were obtained using the Cell^R system based on an Olympus IX81 fully motorized inverted microscope  fitted with an Orca-AG charge-coupled device camera (Hamamatsu) driven by Cell^R software. The microscope is equipped with a CFP/YFP dual-band filter and a DAPI/FITC/Tx-Red Triple Band filter set with single band excitation filters and ET GFP, ET Cy3, and ET Cy5 filter cubes (Chroma). For time-lapse imaging, cells were plated on glass-bottom tissue-culture plates with collagen coating (MatTek) in medium containing 10% FCS at 37°C. The microscope is equipped with an on-scope incubator, which includes temperature and CONature Protocols . For presentation of the movies, the 4D image sequences were transformed into a time sequence by choosing the best focus (highest intensity) plane at each time point, using in-house–generated ImageJ scripts —see detailed explanation on how to perform the tracking and generate the plots of transcription site intensity over time in the “SpotTracker plug-in for computing the transcription site trajectory” paragraph in rotocols . To imprNature Protocols  and then permeabilized with 0.5% Triton X-100 for 3 min at room temperature. After blocking with 5% BSA (in PBS), cells were immunostained for 1 h with a primary antibody, and after subsequent washes, the cells were incubated for 1 h with a secondary antibody. Coverslips were stained with Hoechst and mounted in p-Phenylenediamine mounting medium . Antibodies used were rabbit anti–CENP-F (Abcam) and Alexa-488 anti-rabbit secondary antibody (Invitrogen).Cells in FISH experiments were counterstained with the Hoechst DNA stain. The whole volume of the nucleus was imaged, and this information underwent 3D isosurface rendering using Imaris to obtain the center of mass for the nucleus, which was presented in the x, y, and z coordinates. The x, y, and z coordinates were also determined for each active gene. The distances between the active genes and the nuclear center (in micrometer) were calculated using the equation:Similarly, the distances between active genes in the same nucleus were calculated from x, y, and z coordinates obtained after performing “surface-object” fill-in in Imaris for each active gene.Total RNA was extracted from cells using the AurumTM Total RNA mini kit (Bio-Rad Laboratories Inc.). After reverse transcription using the qScript cDNA Synthesis kit (Quanta Biosciences), cDNA was amplified using the following primer pairs:HA sense: 5′-ACGATGTTCCAGATTACGCT; cyclin antisense: 5′-CAGGTCTCCTCCGCCTTC; tubulin sense: 5′-GCCTGGACCACAAGTTTGAC; antisense: 5′-TGAAATTCTGGGAGCATGAC; 18s sense: 5′-TGTGCCGCTAGAGGTGAAATT antisense: 5′-TGGCAAATGCTTTCGCTTT. RT–PCR was performed using PerfeCTa SYBR Green FastMix, ROX (Quanta Bio Sciences) on a CFX-96 system (Bio-Rad). Analysis was performed with the Bio-Rad CFX manager. Relative levels of mRNA expression were measured as the ratio of the comparative threshold cycle to internal controls (tubulin and 18S) RNA. Experiments were repeated at least three times.t test was performed to determine the significance of differences, and P's are noted in the figure legends.All FISH experiments were performed at least three times and on different days. The numbers of cells analyzed in each case (n) is noted in the actual plots themselves. A two-tailed


Polycomb Response Elements (PREs) are required to repress some developmental target genes, and are widespread in genomes, suggesting that they broadly affect developmental programs. While PREs in transgenes can nucleate trimethylation on lysine 27 of the histone H3 tail (H3K27me3), none have been demonstrated to be necessary at endogenous chromatin domains. This failure is thought to be due to the fact that most endogenous H3K27me3 domains contain many PREs, and individual PREs may be redundant. In contrast to these ideas, we show here that PREs near the wing selector gene vestigial have distinctive roles at their endogenous locus, even though both PREs are repressors in transgenes. First, a PRE near the promoter is required for vestigial activation and not for repression. Second, only the distal PRE contributes to H3K27me3, but even removal of both PREs does not eliminate H3K27me3 across the vestigial domain. Thus, endogenous chromatin domains appear to be intrinsically marked by H3K27me3, and PREs appear required to enhance this chromatin modification to high levels at inactive genes.Patterned expression of many developmental genes is specified by transcription factor gene expression, but is thought to be refined by chromatin-mediated repression. Regulatory DNA sequences called  Polycomb Response Elements (PREs) are thought to nucleate histone methyltransferase binding which then spreads across these domains. In this study, we demonstrate that two PREs near the developmental vestigial gene have distinct and separable effects on gene activation and chromatin structure. Both PREs are functional repressors in transgenes, but the PRE located near the vestigial promoter is required for gene transcription. This PRE has no effect on histone methylation of the domain. The second PRE located in the middle of the chromatin domain is required for high-level H3K27me3 of the domain, but this methylation is not required to refine vestigial gene expression. Significant chromatin methylation remains when both PREs are deleted. Our findings imply that PREs near promoters may play activating roles in gene expression in the Drosophila genome. We suggest that some domains of H3K27me3 may have little consequence for correctly patterning gene expression.Eukaryotic genes are packaged in chromatin, and their transcription relies on activators that recruit RNA polymerases and on repressive factors. In multicellular organisms, cell types have distinct patterns of gene expression, and these patterns are controlled by by the expression of cell-type-specific transcription factors and by modulating chromatin structure. The Polycomb system is one major system for the chromatin-mediated silencing of developmental gene expression, where a histone methyltransferase marks extended chromatin domains with trimethylation of lysine-27 of the histone H3 tail (H3K27me3) and forms repressed chromatin. In Drosophila, repressive regulatory elements called  Polycomb Response Elements (PREs) within domains. These elements bind multiple DNA-binding factors, recruiting the PRC1 and PRC2 complexes, including the Polycomb chromatin factor and the E(z) histone methyltransferase, respectively ZH-2A w; PVIE-260B embryos. The integrated construct (named vgQ-GAL4.CO) was used to drive UAS-GFP expression in the developing pouch of the wing imaginal disc. Finally, to produce a mutated H3.3K27M protein, we cloned the UASp promoter and the His3.3A ORF into pKC27mw, and then used site-directed mutagenesis PCR to make the K27M mutation. This plasmid was injected into y M[vas-int.Dm]ZH-2A w; PVIE-260B embryos, and integrants at the 25C site were recovered.Genomic  pKC27mw  . The P element was mobilized by crossing to the TMS, P[Δ2–3]99B transposase source, mosaic males were crossed to vgnw/CyO females, and lines were established from single animals with reduced wing phenotypes. Each mutant was characterized by sequencing an amplicon spanning the vg21-3 insertion site.The pPRE were cloned by overhang PCR into the pU6sgshort plasmid ZH-2A w embryos by Bestgene Inc . These mosaic animals were mated to w; vgnw/CyOG, and Cy+ progeny with reduced wings were used to establish stocks.Guide RNAs to direct Cas9 to the  plasmid   to first create a tandem duplication of a deleted PRE and a marker gene next to the wildtype PRE at the endogenous locus, and then in a second step to delete the wildtype PRE and the marker gene, leaving the deleted PRE in the locus. To create the tandem duplication, we used CRISPR to induce a double-strand break at a genomic target site, which invades homology on an injected plasmid, integrating it into the chromosome. In the second step, we induced expression of the ISce-I site-specific endonuclease to cleave within the tandem duplication (similar to ZH-2A w or y w1118; attP2{nos-Cas9}/TM6C,Sb Tb embryos by Bestgene Inc . Injected mosaic animals were crossed to w; P[GMR-GAL4]D P3, and progeny with YFP-positive eyes were used to establish stocks and then the order of the duplicated segments was determined by PCR. Lines with a tandem duplication in the order (mutant PRE*–UAS-YFP–wildtype PRE) were crossed to y w; P2B Sco / S2CyO, and progeny were heat-shocked to express the endonuclease. Mosaic y w / Y; PRE*–UAS-YFP–PRE / P2B Sco males were crossed to w; P[GMR-GAL4]D P3, and Sco+ males with no YFP expression were used to establish stocks. Resolution of tandem duplications was confirmed by Sanger sequencing.To do so, we cloned a pPRE and the dPRE, we injected two plasmids encoding guide RNAs targeting the pPRE into a dPRE*–UAS-YFP–dPRE tandem duplication stock, and recovered a pPRE deletion by screening for reduced wings. We then resolved the tandem duplication to delete the dPRE, producing a double mutant chromosome.To construct a mutant chromosome deleted for both the P1 y w; P[FRT-whs-FRT]G13 vgCL1/ P[FRT-whs-FRT]G13 larvae were heat-shocked at 37° for 1 hour in a water bath to induce FLP expression and mitotic recombination. Adults were examined for defects in wing morphology.Vials with We dissected wing imaginal discs from late 3rd instar larvae and fixed them for 20 minutes in 4% formaldehyde/PBST (PBS with 0.1% triton-X100).For quantitative detection of proteins in wing discs, tissues from GFP-positive controls and mutant animals were dissected and incubated with antibodies in the same well, Fixed issues were blocked with 10% goat serum/PBST, and incubated with anti-Vg  and anti-Wg  antiserum at 4° overnight, and with fluorescently-labeled secondary antibodies . All tissues were stained with 0.5 μg/mL DAPI/PBS, mounted in 80% glycerol on slides, and imaged by epifluorescence on an EVOS FL Auto 2 inverted microscope (Thermo Fisher Scientific) with a 10X objective.Wings were wetted in ethanol and mounted in 80% glycerol on slides, and photographed using a Sony digital camera mounted on a Nikon SMZ1500 stereomicroscope or with a 4X objective on an EVOS FL Auto 2 inverted microscope (Thermo Fisher Scientific).Adult heads were mounted on steel pins, immersed in mineral oil, and imaged using a Sony digital camera mounted on a Nikon SMZ1500 stereomicroscope.6 cells for each chromatin profiling experiment.S2 cells were grown to mid-log-phase in HyClone Insect SFX media (GE). We used 1x10We dissected tissues from 3rd instar larvae in Insect SFX media. We used ~10 larval brains and 20 wing imaginal discs for each chromatin profiling experiment.vgQ-GAL4.CO PT2 3rd instar larvae were dissected in SFX media and dissociated in Accutase (Sigma) for 1 hr at room temperature with occasional agitation. Accutase was blocked with 0.5 volumes of FBS. The solution was passed through a 40 μm filter and sorted for GFP fluorescence using 488 nm excitation and 530/30 nm emission filters on an BD Aria II Flow Cytometer using a flow rate of 3 (~20 μL/min) and a 100 μm nozzle. We used ~1x104 cells for each chromatin profiling experiment.We dissociated and isolated cells from the vestigial-expressing portion of wing imaginal discs as described , with th2 with Roche cOmplete protease inhibitor) at 0° for 30 minutes, and then DNA was recovered as described [https://protocols.io/private/D6B0AD2DC1431A513994A2A05AC59CDA).We used an immuno-tethered strategy for profiling histone modifications and Polycomb binding in Drosophila cells. The CUT&RUN method uses an antibody to a specific chromatin epitope to tether a protein A fused to micrococcal nuclease (p-AMNase) at chromosomal binding sites within permeabilized cells . The nucescribed . In someescribed . In all escribed . Two repD. melanogaster genome obtained from FlyBase using Bowtie2, and to the yeast genome (SacCer3) for spike-in normalization, normalizing fly profiles to the number of yeast reads. Track screenshots were produced using the UCSC Genome browser (http://genome.ucsc.edu) [X, 2, and 3 chromosomes in wildtype larval brain samples and the mean read counts in each domain were measured (Supplementary Information).Libraries were prepared as described , with 14csc.edu) . To compSequencing data are available in GEO at National Center for Biotechnology Information (GSE121028).S1 FigPRE features to bound transcription factors detected by ORGANIC native-ChIP (native-ChIP profiling reported in [Correspondence of CUT&RUN mapping of orted in ).(PDF)Click here for additional data file.S2 FigISce-I gene, and the progeny are heat-shocked. These animals are crossed to a GAL4 driver line, and progeny that do not express YFP are recovered as potential intra-chromosomal recombination events that have reduced the tandem duplication (4). Deletion of the regulatory element is confirmed by PCR amplification of the homology region and sequencing.The scheme is designed to eliminate a genomic segment (white box) through a series of targeted recombination events. In (1), the YFP donor plasmid with an internally-deleted homology region is co-injected with a CRISPR gRNA plasmid into embryos expressing Cas9. Cleavage of the chromosome by Cas9 stimulates recombination (blue lines) between the donor plasmid and the chromosome. (2) Flies with the resulting tandem duplication in the chromosome are recovered by crossing injected animals to a GAL4 driver line and screening progeny for YFP-expressing progeny. In (3), flies with the tandem duplication are crossed to animals with an heat-shock-inducible (PDF)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 Table(DOCX)Click here for additional data file.