Bacillus subtilis in synthetic biology and metabolic engineering is highly desirable to take advantage of the unique metabolic pathways present in this organism. To do this, an evaluation of B. subtilis’ intrinsic biological parts is required to determine the best strategies to accurately regulate metabolic circuits and expression of target proteins. The strengths of promoter candidates were evaluated by measuring relative fluorescence units of a green fluorescent protein reporter, integrated into B. subtilis’ chromosome. A total of 84 predicted promoter sequences located upstream of different classes of proteins including heat shock proteins, cell-envelope proteins, and proteins resistant against toxic metals (based on similarity) and other kinds of genes were tested. The expression levels measured ranged from 0.0023 to 4.53-fold of the activity of the well-characterized strong promoter P43. No significant shifts were observed when strains, carrying different promoter candidates, were cultured at high temperature or in media with ethanol, but some strains showed increased activity when cultured under high osmotic pressure. Randomly selected promoter candidates were tested and found to activate transcription of thermostable β-galactosidase (bgaB) at a similar level, implying the ability of these sequences to function as promoter elements in multiple genetic contexts. In addition, selected promoters elevated the final production of both cytoplasmic bgaB and secreted protein α-amylase to about fourfold and twofold, respectively. The generated data allows a deeper understanding of B. subtilis’ metabolism and will facilitate future work to develop this organism for synthetic biology.The use of  The goal is to assemble libraries of these elements that can be applied for the engineering of living cells.Metabolic engineering seeks to increase the synthesis of desired products elements –4. The uelements –8. Some Escherichia coli and Saccharomyces cerevisiae [et al constructed a promoter library based on the bacteriophage PL-λ promoter that was generated using error-prone PCR. The library was tested for promoter strength by measuring the downstream expression of gfp and the chloramphenicol acetyltransferase gene, and those that exhibited a linear relationship between promoter strength and reporter were selected. They then expressed a series of promoter-dxs (deoxy-xylulose-P synthase) constructs in a recombinant E. coli strain overexpressing genes (ispFD and idi) of the isoprenoid synthesis pathway, and observed the linear response of lycopene yield to promoter strength. [Yarrowia lipolytica. The final expression of humanized Renilla GFP (hrGFP) in Y. lipolytica was increased eightfold over the activity of the original endogenous promoter [Streptomyces venezuelae [S. avermitilis. The correlation between lycopene production and promoter strength, elevated lycopene titer as well, confirmed the utilization and feasibility of these expression cassettes and paved the way for further application of these promoter elements in system biotechnology [Current efforts in synthetic biology have focused on the evaluation of cis-sequences including promoters, ribosome binding sites (RBS), and terminators in both revisiae –12. Thertrength. . In a setrength. . This lipromoter . In thispromoter . In anotpromoter . 195 natnezuelae . Next, anezuelae . These schnology .B. subtilis shows significant advantages as a host for protein expression due to its efficient secretion capacity and because it is a generally recognized safe organism. It is used for applications in the detergent, textile, and pharmaceutical industries [B. thuringiensis rather from B. subtilis. In that study, Wang et al systematically identified 1203 active promoter candidates through analysis of genome-wide transcription start sites based on RNA-seq data. Additionally, they further evaluated the characteristics of 20 highly active promoters combined with the corresponding 5’-UTR to screen the highly active promoter-5’-UTR DNA region complex by directing the expression of reporter gene lacZ [dustries –20. Howedustries , many hedustries ,23. Therdustries –26 that dustries  for applene lacZ . Therefoene lacZ .trnQ exhibited higher activity than P43 in driving the transcription of both cytoplasmic and secretory proteins , enabling normalized measurement of the promoter candidates’ strengths.Here, we constructed a promoter-probe vector with GFP as a detection target and measured expression levels. We wanted to identify stress-activated promoters that could direct high-level expression under specific stress conditions, like heat shock, high salt, or ethanol to stimulate membrane stress. More than 80 promoter candidates that showed high transcription levels under multiple conditions were selected and classified according to the encoded proteins located downstream from the promoters . PromoteE. coli DH5α was used as cloning host. The plasmid-free strain B. subtilis 1A751 was used as the main host for the promoter library. Tested promoter candidates were amplified from B. subtilis 168 genomic DNA. The function and relevant properties of strains and plasmids are listed in bgaB gene of pDL with gfpmut1 [To simplify construction and utilize a strategy that did not rely on restriction enzymes, we used prolonged-overlap-PCR to replace the  gfpmut1 . PrimersB. subtilis 168 genomic DNA as template, PrimerSTAR Max DNA Polymerase mix containing dNTP and DNA polymerase , and primers  listed in ™ Cycle Pure Kit 200, Omega Bio-tek, Inc., USA) and the vector enzyme digestion products, the ligation was performed using T4 ligase  according to the instructions of the manufacturer and transformed into E. coli DH5α. Putative candidate colonies carrying cloned promoter fragments were identified by colony PCR before being validated by sequencing .Promoter candidate fragments were prepared by PCR amplification using Cells were incubated aerobically at 37°C and 220 rpm, in LB media. Antibiotics were added where appropriate . Cells for the GFP fluorescence intensity assays were incubated in LB in 96-well micro-plates.600) for the different transformants. Cells were centrifuged at 4000 rpm for 10 minutes, the supernatant was discarded, and cells were resuspended in an equal volume of double distilled water. The extinction and emission wavelength were set at 488 nm and 523 nm, respectively. B. subtilis 1A751 without chromosomal gfp was defined as the negative control. Standard deviations are based on a minimum of three statistically independent experiments.Expression of GFPmut1 was monitored using whole-cell fluorescence under the multimode microplate reader (SpectraMax M5) at an optical density of 0.4–0.6 for λ = 600 nm  can process tens of thousands of individual cells within a few seconds and obtain many parameters at the same time. In order to guarantee the accuracy of the detected results, we measured the RFU of some selected samples using FACS. For the FACS analysis, cells were grown for 6.5 h at 37°C and then were centrifuged at 12000 rpm for 2 minutes. After discarding the supernatant, cells were resuspended in phosphate-buffered-saline (PBS). Samples were analyzed using a FACS Aria Cell Sorting System  with a 100 mW, 488 nm coherent sapphire solid state laser for GFP. 2 to a final concentration of 8 mM. 5 mL cultures were used for RNA extraction according to the manufacturer’s instructions  and the PrimeScript RT reagent Kit (TaKaRa) was used to extract cDNA. Real-time fluorescence quantitative PCR (qRT-PCR) was performed with FastStart Universal SYBR Green Master (ROX)  using a 7500 system  following the manufacturer’s instructions. Based on the 2-ΔΔCt method, we calculated the gene expression level by using housekeeping gene gap as reference gene. PCR conditions were the following: reverse transcription at 50°C for 2 min, then denaturation at 95°C for 10 min, followed by 40 cycles of denaturation at 95°C for 15 s and then annealing and extension at 60°C for 1 min. The primer sequences for gap and gfp amplification are listed in Overnight cultures were inoculated at a ratio of 1:100 into 5 mL LB. After growing for 4 h and 45 min at 37°C, cells were collected for RNA isolation. For those cells containing promoter candidates from heat shock proteins, cultures were grown at 43°C instead of 37°C for 15 min before testing. Similarly, cells containing promoter candidates from cell-envelope proteins were tested by incubation in LB media for 4 h and 30 min followed by addition of ethanol to a final concentration of 4% (v/v). Cells containing promoter candidates from proteins that confer resistance to toxic metals were tested by incubation in LB media for 4 h and 30 min followed by addition of CoClThe BgaB activity assay was carried out as previously described . SamplesamyE, which can be used to facilitate double over-crossing with the chromosome [amyE has no detectable effect on growth. However, the reporter gene in pDL is bgaB, which requires complex detection procedures. Thus, to simplify screening, we exchanged this gene with gfp [B. subtilis’ genome through homologous recombination. Prolonged overlap extension PCR approaches were used to generate the pDL-GFP vector  corresponding to the sequences upstream of 84 genes were amplified with the oligos shown in d by P43 . When wehttp://linux1.softberry.com/berry.phtml?topic=bprom&group=programs&subgroup=gfindb). These promoter candidates exhibited conserved -10 boxes, which were similar to the classical “TATAAT” sequence (http://weblogo.berkeley.edu/) [e. g. the -35 boxes, when we fixed the -10 boxes  ,39. Howe10 boxes . Additiolymerase . σA reguepletion . σF, σE,rulation . Among eproteins . In addiFACS analysis was performed on bacteria growing in the logarithmic phase. Data analysis confirmed the fluorescence of GFP, positioned downstream of 10 different promoter candidates. Selected promoter candidates activated transcription at high, medium, and low levels. There was a good correlation between the data generated by the microplate reader and the FACS analysis, confirming the relative strengths of the candidate promoters .sigI, PgroES, and PftsH) and proteins that respond to stress conditions , we speculated that their expression would increase after the appropriate stress treatments. First, we measured gfp transcriptional levels by real-time fluorescence quantitative PCR for 9 different promoter candidates after treatments, such as heat-shock or high osmotic pressure treatments. Bacteria were cultured in 5 mL of LB media at 37°C for 4.5 h, and then subject to stress conditions. PsigI, PgroES, and PftsH cultures were subject to 15 min of heat shock at 43°C. This sudden temperature upshock is sufficient to induce the synthesis of heat shock proteins including both molecular chaperones such as GroES and ATP-dependent protease such as FtsH [sigI encodes the RNA polymerase sigma factor σI, and is required for growth at higher temperatures [ypuA, PytpA and PmurF in LB were supplemented with ethanol at a final concentration of 4% (v/v) for 15 min. yupA encodes a hypothetical protein, and its promoter was previously reported to be responsive to increases in the stress-responsive extracytoplasmic function ECF sigma factor sigM [ytpA encodes a protein homologous to lysophospholipase, and sporulation was impaired when ytpA was blocked [murF encodes UDP-N-acetylmuramoyl-tripeptide—D-alanyl-D-alanine ligase, which is responsible for the last step in the synthesis of cell wall peptidoglycan. PyusI, PycbR, PywrK were grown and treated with CoCl2 to a final concentration of 8 mM for 15 min, since proteins encoded by yusI, ycbR and ywrk were predicted to confer resistance to toxic metals, based on similarity. ycbR and yusI encode proteins that are similar to toxic cation resistance protein and arsenate reductase [ywrK encodes an arsenical membrane pump. There were rapid alterations in transcription levels after the treatments, confirmed by qRT-PCR results . This may be because too long time at this high temperature may inhibit vegetative growth. In particular, the temperature treatment of 48°C caused a majority of bacteria to show a slow-growth phenotype. Necessary enzymes involved in central carbon metabolic and cell division might be inhibited under this stress. If the time for heat shock was short, e.g. 15 min, there were sharp shifts in transcriptional levels detected through qRT-PCR (e.g. one hour) was essential to allow accumulation of proteins to test the response to heat shock  , we did  qRT-PCR . Howeverat shock . Howeverat shock  comparedat shock . The heamreB, PpssA, PoatA, PytpA, PyuaF, PydaH, PyjoB, and PywbO showed no changes in expression at 0.4 M or 0.6 M NaCl  ethanol. At ethanol concentrations of 6% and 8%, bacterial growth was slowed. However, we detected no significant changes in GFP expression after treatment with 4% ethanol . 11 of 46 M NaCl . At finaradA, PmreBH, PmurF, PywnJ, PyxjI, PyxzE, PtrnQ, PsigX, PsecDF, and PugtP. Except for the different promoter fragments, the backbone of pDL carrying bgaB was the same as the one carrying gfp. There was a linear correlation between the measured GFP and BgaB activities  continues to collect an increasing number of genetic parts for use as components of biological devices and systems. However, until now, most promoter information has focused on sequences that work in E. coli. There have been some attempts to discover and optimize suitable promoters for B. subtilis, for instance, the Ludwig Maximilian University (LMU) of Munich team similarly tried to “open Bacillus subtilis and its unique biology to the iGEM world” by measuring promoter activity with reporter genes (http://2012.igem.org/Team:LMU-Munich/Data). However, only a small number of the promoters they used were native to B. subtilis. Other reports have tested individual specific promoters, but there has been no comprehensive analysis of different promoter candidates derived from diverse proteins. Hence, we determined to evaluate promoters of interest and normalize their strength to the well-characterized P43.Promoters are fundamental genetic materials that determine transcription and expression. The use of these elements as biobricks will allow their use in directed synthetic biology to obtain fine-tuned and balanced expression of genes. The Registry of Standard Biological Parts (RSBP) (http://science.sciencemag.org/content/suppl/2012/02/29/335.6072.1103.DC1). We selected 84 promoter sequences mainly located upstream of heat shock proteins, cell envelope proteins, and proteins resistant against toxic metals. Tested promoter candidates showed a range of strengths relative to P43, and several of these were tested for function in different genetic circuits, indicating their use in a variety of genetic contexts to allow gene fine-tuning. One approach is using pools of thousands of synthetic, codon-usage variants to try to regulate protein production, but this process is inefficient and expensive [E. coli [If genes are expressed at a high level in favorable, unfavorable or threatening circumstances, they are likely to contain strong promoters or promoters that may respond to certain environmental signals  exhibited appreciable shifts when incubating in LB with 0.8 M NaCl at 37°C for 6.5 h. In addition, the putative stress responsive promoters were actually weaker than the constitutive promoter PtrnQ  and other kind of genes. We compared these 84 promoter candidates to the well-characterized P43 to determine the promoters’ relative strength. Tested promoters can now be considered for use as biobrick elements in B. subtilis. One strong promoter, PtrnQ, increased the secretion of α-amylase to 2.1 fold that of P43 driven expression. Other inducible promoters will be useful for fundamental research or application in industrial production.We constructed an integrated plasmid to measure the activities of promoter candidates by using a S1 FigsigI, PgroES, PftsH were heated at 43°C for 15 min after incubating at 37°C for 4.5 h. Strains carrying promoter candidates PyupA, PytpA, PmurF were incubated in LB media with 4% (v/v) ethanol for 15 min after incubating in LB media for 4.5 h. Strains carrying promoter candidates PyusI, PycbR and PywrK were incubated in LB media with 8 mM CoCl2 for 15 min after culturing in LB media for 4.5 h. B: Level of changes of expression level of GFP after specific condition treatments corresponding to equivalent cultures incubated in LB media at 37°C. Strains carrying promoter candidates PsigI, PgroES, PftsH were heated at 43°C for 1 hour after incubating at 37°C for 5.5 h. Strains carrying promoter candidates PyupA, PytpA, PmurF were incubated in LB media with 4% (v/v) ethanol for 6.5 h. Strains carrying promoter candidates PyusI, PycbR and PywrK were incubated in LB media with 8 mM CoCl2 for 1 hour after culturing in LB media for 5.5 h.A: Level of changes of mRNA level of GFP after specific condition treatments corresponding to equivalent cultures incubated in LB media at 37°C. Strains carrying promoter candidates P(TIF)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.


Early mouse development is accompanied by dynamic changes in chromatin modifications, including G9a-mediated histone H3 lysine 9 dimethylation (H3K9me2), which is essential for embryonic development. Here we show that genome-wide accumulation of H3K9me2 is crucial for postimplantation development, and coincides with redistribution of enhancer of zeste homolog 2 (EZH2)-dependent histone H3 lysine 27 trimethylation (H3K27me3). Loss of G9a or EZH2 results in upregulation of distinct gene sets involved in cell cycle regulation, germline development and embryogenesis. Notably, the H3K9me2 modification extends to active enhancer elements where it promotes developmentally-linked gene silencing and directly marks promoters and gene bodies. This epigenetic mechanism is important for priming gene regulatory networks for critical cell fate decisions in rapidly proliferating postimplantation epiblast cells.DOI:http://dx.doi.org/10.7554/eLife.09571.001 The genome contains full instructions for the development of the whole organism. The genes within the genome encode for all the proteins, but specific genes are selected to be active at the appropriate time. For this reason, there are mechanisms that can turn the genes on and off as and when required. One such mechanism is called methylation, in which a chemical group called a methyl tag is added to either the DNA or to histone proteins. DNA wraps around histone proteins to form a structure called chromatin. When histones are tagged with a methyl group, they become closely packed, and the resulting compaction of the chromatin around a gene inactivates that gene. For gene activation, the methyl tag is replaced by another tag called acetyl, which allows the chromatin to de-compact and become more accessible.Soon after fertilisation, most of the methyl tags an embryo inherits from its parents are removed and a group of stem cells is established. An opposite process takes place once the embryo “nests” in the uterus. Two enzymes called G9a and EZH2 add methyl tags to specific residues on specific histones to regulate the expression of genes at the time when cells begin to decide what tissue to become. Zylicz et al. have now investigated how these enzymes contribute to the changes in chromatin packing that occur during early mouse development that is essential for the progression of normal development.In mouse embryos that lacked the G9a enzyme, Zylicz et al. found that specific genes were inappropriately and prematurely activated early in development, including those generally involved in regulating ‘reproduction’ and 'cell death'. Similarly, embryos that lacked the EZH2 enzyme experienced the early and inappropriate activation of a different set of developmentally important genes. In addition, switches called enhancers control gene expression, and Zylicz et al. found that these regulators are also turned off by histone modifications made by the G9a enzyme. Thus, these findings provide important insights on how genes are regulated during a critical period of mouse development, when cells prepare to acquire their specific identities. This should lead to further work on the role of G9a in the hours after fertilisation; that is before the ‘programming’ events described here.DOI:http://dx.doi.org/10.7554/eLife.09571.002 Ehmt2) and enhancer of zeste homolog 2 (EZH2), respectively, are responsible for the establishment of these chromatin modifications  in E3.5 blastocysts is linked with global DNA hypomethylation  Hackett. Subsequications ; 2005. Hications .10.7554/The involvement of specific enhancer elements in these events is of particular interest as they undergo rapid epigenetic setting, for example, by becoming activated or poised with histone H3 lysine 27 acetylation (H3K27ac) and H3K27me3 modifications, respectively . SimilarIn this study, we have focused on the contribution of G9a-mediated H3K9me2 and EZH2-dependent H3K27me3 to early mouse development. We found that during the formation of postimplantation epiblast, there is a dramatic increase in H3K9me2 levels and a concomitant H3K27me3 redistribution. These events are necessary for repression of a distinct set of genes, including regulators of the germline, cell cycle, apoptosis, and development. The rapid acquisition of H3K9me2 extends to key enhancer elements, thereby reinforcing their repression. We propose that such epigenetic programming of epiblast primes a specific gene regulatory network, which is a necessary prerequisite for embryogenesis.Ehmt2 deletion (−/−Ehmt2). Loss of G9a by E6.5 resulted in reduced levels of H3K9me2 modification, and an increase in apoptotic and non-proliferative cells as judged by IF staining for cleaved Caspase 3 and Ki67, respectively  analysis of E3.5 and E5.5 embryos revealed significant enrichment of H3K9me2 in the epiblast of postimplantation embryos . Accumulectively . These cectively , consistectively .10.7554/−/−Ehmt2 epiblasts at E6.25. This revealed misregulation of 180 genes, of which 147 (~82%) are upregulated (-15), notably in clusters of Xlr, Rhox and Mage-a genes. Consistent with the known functions of these clusters, we found significant enrichment of gene ontology (GO) terms linked to hematopoiesis, sexual reproduction, and regulation cell proliferation  or Nanog  on individual egulated  . We found upregulation of 165, and downregulation of 24 transcripts (Log2(FC)>1.4, p-value<0.05)  , among waffected . ImportaTo understand the roles of H3K9me2 and H3K27me3 modifications during the transition from naïve pluripotency in the ICM of blastocysts to a primed pluripotent state in postimplantation embryos, we investigated the genome-wide distribution of these modifications. For this purpose, we optimised a low cell number chromatin immunoprecipitation with sequencing (lcChIP-seq) protocol to analyse ~25,000 pregastrulation E6.25 epiblast cells in two biological replicates Ng, et a. We inte2 p-value=0.0024). These differences are in line with H3K9me2 and H3K27me3 being linked to high and low 5-methylcytosine (5meC) levels, respectively  . First, Next, we focused on genes that are repressed upon implantation and accumulate H3K9me2 or H3K27me3. GO term analysis revealed preferential acquisition of H3K27me3 on genes associated with transcriptional regulation, embryonic organ development, blastocyst formation, and metabolism . On the Despite being derived from postimplantation embryos, EpiSCs have reduced competence for the germline fate . To inve−/−Ehmt2 and −/−Ezh2 embryos  of genes seem to be regulated by H3K9me2 deposition at the gene bodies  sESC, which self-renew without PRC2 and accumulate secondary transcriptional alterations  and ~18% (4.8 × 105/2.6 × 106) of repeats show significant H3K9me2 and H3K27me3 enrichment, respectively (6) and ~0.06% (1646/2.6 × 106) of all repeats were significantly upregulated in −/−Ehmt2 and −/−Ezh2 epiblast, respectively. By intersecting fractions of upregulated and epigenetically marked loci in each subfamily, we identified repeats that are enriched for and regulated by H3K9me2 or H3K27me3 (+/+Ehmt2 or −/−Ehmt2 epiblast cells showed upregulation of mouse transposon D (MTD), mouse transposable element b (MTEb ) and Lx8 but not of IAP repeat elements (F/Ehmt2− ESC lines expressing a tamoxifen (TAM)-inducible Cre recombinase (CreER), which were cultured in 2i/LIF medium. Following TAM treatment, day 2 EpiLCs were used for lcChIP-qPCR, which showed significant depletion of H3K9me2 upon loss of G9a at MTEb and Lx8 loci, but not IAP (We next investigated the role of G9a in regulating transposable elements (TEs) as previous studies have shown that loss of G9a in sESC leads to aberrant expression of murine endogenous retroviruses with leucine tRNA primer (MERV-L) . To thisectively . On the H3K27me3 . Direct H3K27me3 . Consistelements . To conf not IAP . Thus, Gcis regulatory elements reside   . ConsistSE57409) , we founSE57409) . As H3K9SE57409) . This efSE57409) . As withSE57409) . InteresSE57409) , while oSE57409) . To valis do not . Thus, aNotably, H3K9me2-marked enhancers retain partial enrichment of active H3K27ac mark in EpiLCs, but exhibit near-complete H3K27ac loss in EpiSCs . Consist−/−Ehmt2 embryonic phenotype affecting growth and development, these genes are enriched for the regulators of apoptosis  . We founpoptosis . To furtpoptosis . In linepoptosis . Such noOtx2 that are linked with primed pluripotency, show increased eRNA expression in EpiLCs  preamplification, we measured eRNA expression in these samples. We were able to detect 7/8 eRNAs associated with H3K9me2 marked enhancers, and 4 of these showed significant increase in expression in −/−Ehmt2embryos . Furthermore, G9a preferentially represses three clusters of X-linked genes: Rhox, Xlr and Mage-a. Two of these are imprinted, suggesting a role for H3K9me2 in this process, which merits further investigation  (For was used . Ehmt2+/e (GGOF) . This tre (GGOF) . All husF/− GGOF+veEhmt2 ESC lines were derived in 2i/LIF conditions as previously described . Cre recombination was induced by the addition of TAM. After a 2-day treatment, no Flox G9a allele was detected by genotyping.Two male escribed . Cells wescribed . To geneFor ChIP experiments, epiblast cells were isolated from E6.25 pre-gastrulating embryos coming from outbred MF1 females crossed with GGOF stud males. After recovering embryos from the decidua, Reichert’s membrane was dissected out and extraembryonic cone was also removed. Remaining tissue was used to prepare single cell suspension for sorting using MoFlo high-speed cell sorter  based on EGFP expression. The purity of epiblast cells was assessed by staining for SOX2 and was in excess of 95%. For single epiblast experiments, embryos were dissected as previously described .Total RNA was extracted using PicoPure RNA isolation Kit  or AllPrep DNA/RNA Micro Kit  with an on-column DNaseI digestion . cDNA was prepared using SuperScript III  and random hexamer primers . RT-q PCR reactions were performed using Kapa Sybr Fast qPCR kit . Single-cell RT-qPCR was performed as previously described, for detailed protocol and reagents refer to the original publication . For pri+/−Ehmt2× +/−Ehmt2 or +/−Ezh2× +/−Ezh2E6.25 epiblasts were lysed and RNA was extracted like for RT-qPCR. Quality and concentration of eluted RNA was assessed with the Agilent RNA 6000 Pico Kit . Only samples with the RNA integrity score >8 were further processed. For Ezh2, three control and three KO samples from three litters were used. For Ehmt2, four controls and four KO from four litters were used. A total of 750 pg of RNA from each sample was amplified using Ovation RNA-seq System V2 . The quality of cDNA was confirmed by measuring the expression of Ehmt2, Ezh2, Pou5f1 and Nanog by qPCR.Dissected For every sample, 1.5 μg of cDNA was sheared to ~230 bp using S220 Focused-ultrasonicator . The fragmented cDNA was then concentrated using Qiagen Reaction Cleanup Kit (MinElute). A total of 500 ng of each sample was used as input for library preparation using Encore Rapid DR Multiplex Library System . Finally, the adaptor-ligated DNA was quantified using KAPA Library Quantification Kit  and sequenced using HiSeq2000 or HiSeq2500 with single-end 40 or 50 nt read length.RNA-seq reads were all trimmed to 40 nt read length, adapters were removed, and reads were aligned with Tophat2  against Published RNA-seq datasets for E3.5 blastocysts were downloaded from the European Nucleotide Archive (ERP005749), reads were trimmed to 40 nt length, and subsequently processed in a similar manner for comparison with E6.25 epiblast using DESeq.RepeatMasker annotations for the mouse reference genome were obtained from the Univeristy of California, Santa Cruz (UCSC) Table Browser. RNA-seq reads were aligned to the mouse reference genome by using bowtie  with parameters ‘-m 1 –v 2 –-best –-strata’ in order to select reads that uniquely map to single repeat copies in the genome only. Read counts for repeat regions were normalised by the total number of RNA-seq reads that aligned to protein-coding genes and by repeat size (in kB). Statistical tests for differential expression of genomic repeat copies were performed by the R Bioconductor DESeq package.http://david.abcc.ncifcrf.gov, , 1X Protease Inhibitors) using Protein G Dynabeads  coated with antibodies specific to H3K27me3  and H3K9me2 . For H3K27me3, the ChIP beads were washed three times in ChIP W1 buffer  and further three washes with increased NP40 concentration to 1.5% (W1.5). For H3K9me2 there were two washes each in low salt , high salt  and LiCl buffer . After a final TE  wash samples were eluted, proteins digested with proteinase K, and DNA purified using phenol/chlorophorm/IAA extraction and further ethanol precipitation. For each experiment, enrichment was confirmed by qPCR for control regions . Once prepared, library DNA was resolved on a 2% agarose gel and the mononucleosome (for H3K27me3) and dinucleosome (for H3K9me2) fractions were isolated using MiniElute gel extraction kit  and sequenced using HiSeq2000 with single-end 40 nt read length.lcChIP-seq was performed by using a modified published method . BrieflyPcsk5; H3K27me3: Hoxc10; H3K27ac: Gpr20).Unless otherwise stated, lcChIP-qPCR samples were rescaled by normalizing to +ve control region . The next step involved library amplification using HiFi Library Amplification master mix  and BpmI-primer (CCGGCCCTGGAGTGTTGGGTGTGTTTGG). These reactions were incubated in a thermocycler using following conditions: 98°C for 3 min; 11–12× ; 72°C for 7 min: or 4°C as suggested. The number of cycles depended on the amount of DNA precipitated and so 11 cycles were used for H3K9me2 and 12 for H3K27me3. Amplified DNA was purified with Agencourt RNA clean XP beads. Adapter trimming was performed by BpmI digestion, secondary adaptor ligation, and a second round of digestion . Digeste6 of F/− CreER+veEhmt2 day 2 EpiLCs were used per experiment. Cells were fixed and frozen as for lcChIP. Similarly, samples were lysed with 1ml lysis buffer. After pelleting the nuclei, they were resuspended in 1 ml dilution buffer and sonicated for lcChIP. Precleared lysates were immunoprecipitated overnight with anti-H3K9me2, anti-H3K27ac, or IgG controls immobilized with Dynabeads Antibody Coupling Kit. After performing six 10 min long washes , complexes were eluted in lysis buffer. Ten percent of each sample was saved for enrichment validation. Remaining samples were diluted ten-fold and used further in lcChIP-qPCR protocol.3 × 10ChIP-seq reads were extended to a total length of 250 nt for lcChIP, and 150 or 300 nt for H3K27me3 and H3K9me2 nChIP according to selected fragment sizes. Reads were aligned to the mouse reference genome (GRCm38/mm10) using bowtie with parameters ‘–m 1 –v 2’ . ChIP-sePublished ChIP-seq datasets were downloaded from GEO . To determine active enhancers in 2i/LIF ESCs, peaks were called for p300, H3K4me1, and H3K27ac ChIP-seq datasets in ES 2i with MACS (liulab.dfci.harvard.edu/MACS). p300 peaks that intersected with an H3K27ac and H3K4me1 peak, but not with any annotated promoter region were classified as active enhancers.To classify regions as marked by H3K9me2 and H3K27me3, we have used average Log2 from two biological replicates in all the analysis. Regions were separated into three clusters by k-means method and the most highly enriched was designated as marked. For differential enrichment analysis between EpiSCs and E6.25 epiblast, EdgeR was used  .To classify epigenetic signatures of promoters and gene bodies, histone modification (Log2[ChIP/input]) and DNA methylation levels on each genomic region and expression levels of the corresponding genes were represented by n-dimensional feature vectors. Feature vectors were centre-scaled , and self-organizing maps (SOMs) were trained using the R kohonen package . After tTo classify enhancer signatures across different cell types, the same analysis was performed with feature vectors representing histone modifications and DNA methylation levels on enhancer regions (p300 peak summits ± 800 nt) in 2i/LIF ESCs, EpiLC, EpiSC and epiblast. For the representation of sets of enhancers with highly similar signatures as ranked heatmaps, the average values of the epigenetic modifications for the enhancers in each SOM node were determined and ranked by their average H3K9me2 values in EpiLCs or by their average H3K27ac values in EpiSC.http://meme-suite.org). To evaluate enrichment, 1000 sets of random regions of the same size were generated in gene regions (± 50 kB of flanking intergenic region), and the frequency of DNA-binding motifs was determined using a p-value threshold of 1e-5.Eight hundred and forty-three position-specific weight matrices were determined by high-throughput SELEX sequencing for human and mouse DNA-binding domains . EnhanceDNA was isolated from d2 EpiLC and EpiSC pellets using DNeasy blood and tissue kit . For every sample, 200 ng was sheared into ~250 bp using S220 Focused ultrasonicator . A total of 160 ng of sonicated and purified DNA was used for library preparation using Ovation Ultralow Methyl-Seq Library System . This entailed a 3.5 h bisulfite conversion of adapter-ligated DNA using EZ DNA Methylation-Direct . The DNA was amplified using seven cycles. Once libraries were prepared, they were sequenced using HiSeq2000 with paired-end 100 nt read length. Reads were quality trimmed and aligned to the bisulfite-converted genome with Bismark with parameters –n –l 40 . Genome- review process). Similarly, the author response typically shows only responses to the major concerns raised by the reviewers.eLife posts the editorial decision letter and author response on a selection of the published articles . An edited version of the letter sent to the authors after peer review is shown, indicating the substantive concerns or comments; minor concerns are not usually shown. Reviewers have the opportunity to discuss the decision before the letter is sent  and three reviewers, one of whom is a member of our Board of Reviewing Editors.Thank you for submitting your work entitled "Chromatin dynamics and the role of G9a in gene regulation and enhancer silencing during early mouse development" for peer review at The reviewers have discussed the reviews with one another and the Reviewing editor has drafted this decision to help you prepare a revised submission.Essential revisions:The three reviewers found your manuscript very interesting. However, there was consensus that currently the manuscript lacks coherence and would greatly benefit from removing parts of the data and strengthening other aspects.Below, I summarize the main discussion points raised during the review process that we would like you to address upon revision.In particular, we suggest that you could consider removing parts from the early embryo due to lack of functional relevance.The reviewers were excited by the ChIP-seq data from epiblast, but felt that additional validations (see comments from Reviewer 2) and analyses (point 4 of Reviewer 3) would maximize the impact of the study.There was also a suggestion to remove the p53 where indirect effects cannot be ruled out. However, it was also discussed that one value of the p53 ChIP result from G9a KO is demonstration that G9a loss enhances p53 binding at select enhancers, without appreciably affecting H3K27ac . The revWe also highly encourage you to further strengthen the computational analysis and specificities required. This should help in addressing a number of points raised by the three reviewers.Reviewer #1:In the current study, Zylicz and colleagues explore the role of G9a and EZH2 during early embryonic development encompassing the 2-cell stage and early blastocysts. The quantity and technical aspects of this study are very impressive. Each of the experiments provides important insights into the function of G9a and EZH2 in priming gene regulatory networks in epiblast cells. However, the experiments are disjointed and do not flow together well to make one coherent story. There is sufficient data here to produce two or more coherent stories exploring individual early findings reported by the authors. For instance, data from the 2-cell study and the transposons experiments can be removed to improve the flow of the paper as they detract from the main message of the study.1) The H3K9me2 expression levels in 2) It is not clear why the samples from the G9a M/Z and M/+ are pooled in the analysis presented in 3) During the RNA seq. analysis, why was a fold change cut-off of log2(1.6) used? Furthermore, was a false discovery rate, which is more commonly used, applied to the data? How can the authors rule out that all direct targets of G9a are changed by at least log2(1.6)?-/-G9a versus control RNA seq., G9a mRNA does not appear to be reduced (4) In the  reduced . Is ther-/-Ezh2 RNA Seq. dataset? It is not clear in the paper. Is it the same as the -/-G9a RNA Seq? The authors need to make this information clear.5) What was the cut-off for significance in the 6) -/-G9aembryos and controls.7) The authors need to further address the discrepancy in OCT4 level between their study and Yamamizu et al., 2012. It seems odd that there is such a large incongruity between the two studies. Only one line is provided in the Discussion on this topic and it does not sufficiently propose any reasons for such discrepancy. Given that lack of changes in pluripotency is central to the conclusions of this paper, the authors should undertake staining for OCT4 in -/-G9asamples, which is consistent with increased H3K9me2 at the p21 locus during ESC differentiation. The authors claim that these observations support their view that the delayed development of -/-G9a embryos is related to increased apoptosis and/or reduced proliferation, and not retainment of pluripotency. The authors have provided little evidence for this. The authors should validate their proposal in vivo by undertaking BrdU incorporation studies and phospho-H3 staining for proliferation, as well as TUNEL or active caspase-3 staining to analyse cell death.8) The authors show in -/-G9a E6.25 epiblasts (9) In addition, can the authors exclude that the expressions of important developmental genes are normal at E6.5? For instance, a very high level of Bmp4 is observed in piblasts , which c-/-G9a epiblasts. Can the authors explain its absence?10) In the E6.25 RNA Seq. data , p21 mRN-/-G9a embryos? If pluripotency is indeed unaffected, while germ line specification is presumably impaired, can the authors show normal alkaline phosphatase staining in -/-G9a embryos and not in germ cells?11) Since the authors state that a significant proportion of genes affected by G9a deletion are involved in germ line specification, the authors need to show whether germ cells are affected. Are PRDM14 and Blimp1 expression patterns normal in 12) The authors claim that 2i ESCs as primitive ectoderm (PrE). In contrast, the works from Austin Smith's lab and others  have shown that the ESC state in 2i resembles the naïve state of the epiblast. Why do the authors consider the 2i state to be similar to the PrE? Rather, ESCs in standard ESC medium (with serum) are considered to be more like E4.5 PrE.Reviewer #2:Please note that I cannot judge the stringency of the bioinformatics pipelines used in depth, and therefore my comments are focused mostly on the biology of the questions addressed and the conclusions drawn, rather than in the stringency of the computational side. I do find, in general, that the computational data is not always presented in a manner for a broad readership, and some points below suggest improvements towards this direction.Although a few of the observations documented are not particularly new, the manuscript by Zylics and colleagues builds on former data on Ezh2 and G9a in regulating development around implantation. The strongest point in, my view, is the analysis of epiblast cells in vivo at the transcriptional level and at the chromatin level (K9me2 and K27me3) genome wide. The experiments are carefully executed and in most instances the conclusions drawn are supported by the data presented.I have, however, mixed feelings about the presentation and the flow of the manuscript. It does not come out as a single, solid message, and is diluted with many pieces of data, some of which I find irrelevant for the main conclusions and I would therefore suggest to remove these parts, which encompass all the pre-implantation data (which is not strong enough), as well as the p53 data at the end, which in the end are not very strong. This would allow the authors to concentrate in a less dense manner, on the main messages of the paper based on the transitions between naïve/primed and epics states.I have some comments on the ChIP protocol validation that require in my view, additional experimental work, and some comments to draw to the phrasing and statistics throughout the manuscript, as well as clarification or additional computational analysis.The 'pregastrulation conclusion’ (paragraph four of the Discussion) is reasonable, but the preimplantation work is confusing, and poorly documented in comparison with the peri-implantation and in vitro data (e.g. statement of 2C specific gene regulation by G9a is based on only 3 genes) and does not add much to the manuscript and instead deviates the focus of attention from the pre-gastrulation cell fate transitions.All figures lack description of quantification of fluorescence intensities, as well as the N numbers for IF and quantifications. The only description is 'fluorescence intensity was normalised to DAPI', but the authors state that they used 'quantitative immunofluroescence' to analyse levels. Please add a better description and/or controls for this.In From Regarding my validation point above, the only validation presented for the lcChip-seq is a comparison of Pearson figures  based onI do not see much significance/added value on the p53 data (in the subsection “G9a Mediates Efficient Enhancer Inactivation”), and it only adds more 'density' in the manuscript, which is quite dense. Specially, how relevant  is the "15%" of H3K9me2 and H3K27ac enhancers being bound by p53?The analysis of 'proximity' of eRNA is not presented adequately, nor it is known what 'proximity' is? In kb? This cannot be inferred from the graphs presented. Can the authors do an enrichment analysis of eRNA expression (on the y axis) relative to specific distances of genes . The conclusion on page 15 on H3K9me2 domains 'extend to active enhancers targeted for silencing, which accounts for coenrichment with H3K27ac' implies a causal relationship for which there is no data.Reviewer #3:In this study Zylicz et al. set out to explore the deposition and function of repressive histone marks such as H3K27me3 and H3K9me2 during early embryonic development. The authors generated embryos deficient for G9a or Ezh2 methyltransferases and examined their gene expression profile using single epiblast RNA-seq at day E6.25, prior to the overt phenotypic manifestations. To determine which genomic loci are marked by repressive histone methylation marks in vivo, the authors performed low cell number ChIP-seq assays for H3K27me3 and H3K9me2 in E6.25 epiblasts. Strikingly, for either mark, an exceedingly small subset of marked genes is perturbed upon loss of respective enzyme, suggesting either existence of multiple redundant silencing mechanisms or these methylation events being a secondary consequence of repression. Furthermore, the set of genes that are aberrantly upregulated are non-overlapping between the two different knock outs and show therefore that in the epiblast H3K27me3 and H3K9me2 are involved in repression of different set of genes. The authors note that many intergenic enhancer regions are marked by H3K9me2 in the epiblast, and they follow up upon these observations using the in vitro cellular models. They conclude that G9a mediates efficient inactivation of a subset of enhancers, particularly those bound by p53.This study contains many interesting observations, tackles an important biological question and is generally well-executed. However, it also suffers from weaknesses that dampen my overall enthusiasm, but which could be fairly easily addressed.1) The authors claim that a subset of enhancers gains H3K9me2 in epiblast, and that this is associated with their inactivation during transition to primed pluripotency. Several issues need to be clarified here:In F/–G9aCreER EpiLCs treated with EtOH or TAM should be done systematically, across all H3K9me2 marked enhancers, and in comparison to enhancers unmarked by H3K9me2, but containing similar enrichment levels of H3K27ac. The relationship between enhancers with G9a-dependent eRNA expression and transcriptional changes at neighboring genes should be determined. To what extent transcriptional changes observed in G9a KO cells can be explained by H3K9me2/eRNA changes at nearby enhancers?2) A substantial weakness of the study is that despite the authors having all the necessary reagents in hand, the data pertaining to the functional impact of G9a on enhancer activity is limited to just a few examples, and not coherent ones either (e.g. enhancers shown in 3) Increased p53 binding upon loss of G9a may be an indirect consequence of the defect in enhancer repression, perhaps resulting in the increased enhancer accessibility- did the authors consider looking at chromatin accessibility measurements such as ATAC, DNase or FAIRE? Such data could in fact strengthen the conclusions on the functional impact of G9a on enhancer activity, regardless of the specific impact on p53.4) The authors generate valuable H3K9me2 and H3K27me3 ChIP-seq datasets from epiblast cells of E6.25 embryos, but I feel they missed the opportunity to provide a deeper comparison of their results with the H3K9me2 and H3K27me3 patterns reported from the in vitro cellular models such as EpiLC or EpiSC. What are the major similarities and differences in patterns? A systematic  comparison of H3K9me2 patterns across the genome in different cellular states would not only be broadly interesting for the community, but also relevant for the authors' own conclusions. The three reviewers found your manuscript very interesting. However, there was consensus that currently the manuscript lacks coherence and would greatly benefit from removing parts of the data and strengthening other aspects.To address this point, we have removed all observations on the effects of G9a mutation on preimplantation embryos, and focused on the transition from naïve to primed pluripotency. We also performed additional experiments on the link between p53 and G9a. Since we found an increase of activated phopho-p53 globally in cells lacking G9a see , we cannAs suggested by the reviewers, we have included additional bioinformatics analysis for detailed comparison between in vitro EpiSCs and in vivo epiblast . We haveIn response to the reviewers’ suggestion, we have expanded our analysis of in vivo IF, which convincingly shows accumulation of H3K9me2, GLP and G9a upon implantation . We alsoIn particular, we suggest that you could consider removing parts from the early embryo due to lack of functional relevance.Indeed we agree and removed this part.The reviewers were excited by the ChIP-seq data from epiblast, but felt that additional validations (see comments from Reviewer 2) and analyses (point 5 of Reviewer 3) would maximize the impact of the study.This ChIP-seq dataset is indeed novel, and now we have included additional validation by ChIP-qPCR , which sDetailed comparison between EpiSCs and in vivo epiblast including WGBSeq dataset .Analysis of ChIPseq in the context of exit from naïve pluripotency by incorporating published E3.5 RNAseq datasets .Inclusion of an epiblast sample into the enhancer analysis  as well The additional analysis shows that EpiSCs accumulate aberrant DNA methylation and loose H3K27me3 from germline genes, which might limit their competence for germline fate. By including published E3.5 ICM dataset, we are able to identify differentially expressed genes during the exit from naïve pluripotency. In this context we reveal that H3K27me3 and H3K9me2 target specific pathways independently. Finally, accumulation of H3K9me2 in EpiLCs enhancers is also seen in the in vivo epiblast.There was also a suggestion to remove the p53 where indirect effects cannot be ruled out. However, it was also discussed that one value of the p53 ChIP result from G9a KO is demonstration that G9a loss enhances p53 binding at select enhancers, without appreciably affecting H3K27ac . The revWe show that loss of G9a in EpiLCs leads to increased activation of p53 globally as judged by western blot for phopho-p53 , resultiWe also highly encourage you to further strengthen the computational analysis and specificities required. This should help in addressing a number of points raised by the three reviewers.Reviewer #1:In the current study, Zylicz and colleagues explore the role of G9a and EZH2 during early embryonic development encompassing the 2-cell stage and early blastocysts. The quantity and technical aspects of this study are very impressive. Each of the experiments provides important insights into the function of G9a and EZH2 in priming gene regulatory networks in epiblast cells. However, the experiments are disjointed and do not flow together well to make one coherent story. There is sufficient data here to produce two or more coherent stories exploring individual early findings reported by the authors. For instance, data from the 2-cell study and the transposons experiments can be removed to improve the flow of the paper as they detract from the main message of the study.We thank the reviewer for the supportive comments. We have now removed both preimplantation experiments as well as p53 ChIP. Instead we concentrate on in-depth analysis of H3K9me2 and H3K27me3 during the transition from naïve to primed pluripotent cells.1) The H3K9me2 expression levels in We have now removed most of the data on preimplantation IF staining and instead concentrated on two crucial stages (E3.5 and E5.5), which is now part of updated 2) It is not clear why the samples from the G9a M/Z and M/+ are pooled in the analysis presented in We have decided to remove all observations on preimplantation G9a mutants from this manuscript.3) During the RNA seq. analysis, why was a fold change cut-off of log2(1.6) used? Furthermore, was a false discovery rate, which is more commonly used, applied to the data? How can the authors rule out that all direct targets of G9a are changed by at least log2(1.6)?In this experiment, we used a low input protocol for single epiblast RNAseq. There is some biological variability between the control embryos as well as between KO embryos. We take that into account by using pairwise comparison between individual epiblasts to make sure that a minimum threshold is met in all control vs KO comparisons. Indeed, setting thresholds is to some extent arbitrary but is commonly used in transcriptional analysis. In 4) In the G9a-/-versus control RNA seq., G9a mRNA does not appear to be reduced . Is therEhmt2, which is cited in the source data file and is indeed significantly down-regulated. To avoid confusion, we have now updated the name of the gene to Ehmt2 in the whole manuscript.G9a is also called 5) What was the cut-off for significance in the Ezh2-/-RNA Seq. dataset? It is not clear in the paper. Is it the same as the G9a-/-RNA Seq? The authors need to make this information clear.We now make it clear in the text that the parameters used were identical to those for G9a RNAseq .6) Indeed it is true that small transcriptional changes are also possible. Such effects however are confounded by the variability between control epiblasts and technical variability introduced by using a low input RNAseq protocol. Hence we are unable to rigorously estimate and identify such transcripts. In 7) The authors need to further address the discrepancy in OCT4 level between their study and Yamamizu et al., 2012. It seems odd that there is such a large incongruity between the two studies. Only one line is provided in the Discussion on this topic and it does not sufficiently propose any reasons for such discrepancy. Given that lack of changes in pluripotency is central to the conclusions of this paper, the authors should undertake staining for OCT4 in G9a-/-embryos and controls.ntrG9ac and KO epiblasts  The authors show in  G9a-/-samples, which is consistent with increased H3K9me2 at the p21 locus during ESC differentiation. The authors claim that these observations support their view that the delayed development of G9a-/-embryos is related to increased apoptosis and/or reduced proliferation, and not retainment of pluripotency. The authors have provided little evidence for this. The authors should validate their proposal in vivo by undertaking BrdU incorporation studies and phospho-H3 staining for proliferation, as well as TUNEL or active caspase-3 staining to analyse cell death.+/+G9a and 5 -/-G9a embryos we confirm increased rate of apoptosis in E6.5 mutant embryos. Indeed we also observed increased numbers of non-proliferative Ki67+ve cells. This indicates that loss of G9a results in increased apoptosis and reduced proliferation.In 9) In addition, can the authors exclude that the expressions of important developmental genes are normal at E6.5? For instance, a very high level of Bmp4 is observed in G9a-/-E6.25 epiblasts , which cIn this study we show that loss of G9a leads to developmental delay, reduced proliferation and increased apoptosis. We report that there is no delay in the exit from pluripotency but there is upregulation of multiple developmentally relevant genes as well as some repeat elements. We have added observations on Nanog and Oct4-GFP, which remain unchanged in mutant embryos. Unfortunately while it is not possible to validate all RNAseq findings, we have however undertaken the task of doing so for some germline and proliferation genes . A poten10) In the E6.25 RNA Seq. data , p21 mRN G9a-/-epiblasts. Can the authors explain its absence?Cdkn1a it is under this name in the source data file and is indeed significantly up-regulated. We have updated the name for Cdkn1a in the whole manuscript.p21 is also called 11) Since the authors state that a significant proportion of genes affected by G9a deletion are involved in germ line specification, the authors need to show whether germ cells are affected. Are PRDM14 and Blimp1 expression patterns normal in G9a-/-embryos? If pluripotency is indeed unaffected, while germ line specification is presumably impaired, can the authors show normal alkaline phosphatase staining in G9a-/-embryos and not in germ cells?Prdm14 or Blimp1. Based on this observation, we posit that germline specification will remain unaffected. To address this issue, we collected severely delayed -/- ΔPE-Oct4-GFP+ve E8.5G9a embryos. Whole-mount staining clearly showed a small population of +veGFP and +veAP2g putative PGCs at the base of allantois (Here we show that loss of G9a results in upregulation of multiple late germline cell fate regulators. However RNAseq experiments showed no difference with respect to llantois  A. The n12) The authors claim that 2i ESCs as primitive ectoderm (PrE). In contrast, the works from Austin Smith's lab and others  have shown that the ESC state in 2i resembles the naïve state of the epiblast. Why do the authors consider the 2i state to be similar to the PrE? Rather, ESCs in standard ESC medium (with serum) are considered to be more like E4.5 PrE.A recent study from Austin Smith’s lab shows that 2i/LIF ESC might be more similar to primitive ectoderm of E4.5 embryos . However there is no direct genome-wide comparison between 2i/LIF ESCs, and different in vivo stages. Since there is also a lack of rigorous terminology in the field, we have decided to consistently use the most frequently used term: ICM (inner cell mass).Reviewer #2:[…] I have, however, mixed feelings about the presentation and the flow of the manuscript, which does not come out as a single, solid message, and is diluted with many pieces of data, some of which I find irrelevant for the main conclusions and I would therefore suggest to remove these parts, which encompass all the pre-implantation data (which is not strong enough), as well as the p53 data at the end, which in the end are not very strong. This would allow the authors to concentrate in a less dense manner, on the main messages of the paper based on the transitions between naïve/primed and epics states.We thank the reviewer for a positive feedback about the quality of work presented and its interest for a broad readership. We have addressed a number of issues to make the manuscript more coherent. In particular, we have removed the work on preimplantation G9a mutant embryos as well as the p53-related work, and concentrated our attention on the transition between naïve and primed pluripotency in vivo. In this respect we have included an analysis of E3.5 ICM RNAseq. This allowed us to identify specific pathways repressed upon implantation and the epigenetic mechanisms involved in this process. We now show that regulators of metabolism and transcription are preferentially targeted for H3K27me3 accumulation. On the other hand H3K9me2 is linked to regulators of meiosis. We also provide comparison between in vivo epiblast and EpiSCs on the epigenetic level. This revealed substantial accumulation of DNA methylation in EpiSCs especially at germline related promoters, concomitantly with the loss of H3K27me3. This observation is consistent with the diminished competence of EpiSCs for PGC fate.The 'pregastrulation conclusion’ (paragraph four of the Discussion) is reasonable, but the preimplantation work is confusing, and poorly documented in comparison with the peri-implantation and in vitro data (e.g. statement of 2C specific gene regulation by G9a is based on only 3 genes) and does not add much to the manuscript and instead deviates the focus of attention from the pre-gastrulation cell fate transitions.We have decided to remove all work on preimplantation G9a mutants from this manuscript.All figures lack description of quantification of fluorescence intensities, as well as the N numbers for IF and quantifications. The only description is 'fluorescence intensity was normalised to DAPI', but the authors state that they used 'quantitative immunofluroescence' to analyse levels. Please add a better description and/or controls for this.This is now addressed in the revised manuscript. Every IF experiment was performed in at least 3 biological replicates, which is clearly stated in figure legends, including the numbers of embryos analysed, and how the signal was measured. For In >0 are actually significantly enriched when compared to all genic regions as they reach levels typical for silent intergenic regions.From (This data is now presented in 2 test). We have also performed an analysis of H3K9me2 vs H3K27me3 at all promoters . Classification of all promoters reveals that only ~0.3% show dual H3K9me2 and H3K27me3 marking. This result is consistent with a high level of anti-correlation that is statistically significant with p-value of 0.0024 , and it only adds more 'density' in the manuscript, which is quite dense. Specially, how relevant  is the "15%" of H3K9me2 and H3K27ac enhancers being bound by p53?-/-G9a cells is most likely an indirect effect. We decided to remove this part, and instead focus on the transition from naïve to primed pluripotency in vivo.We can confirm that a significant proportion of H3K9me2 enriched enhancers are also enriched for p53. However we have also found that loss of G9a leads to global activation of the p53 pathway. Thus increased recruitment of p53 to enhancers in The analysis of 'proximity' of eRNA is not presented adequately, nor it is known what 'proximity' is? In kb? This cannot be inferred from the graphs presented. Can the authors do an enrichment analysis of eRNA expression (on the y axis) relative to specific distances of genes .We have now updated this information, which is now in The conclusion on page 15 on H3K9me2 domains 'extend to active enhancers targeted for silencing, which accounts for coenrichment with H3K27ac' implies a causal relationship for which there is no data.Indeed H3K9me2 accumulation does not seem to be actively targeted to specific loci, but rather extends to regions silenced or undergoing repression. However, in our view this phrase does not imply causal relationship.Reviewer #3:This study contains many interesting observations, tackles an important biological question and is generally well-executed. However, it also suffers from weaknesses that dampen my overall enthusiasm, but which could be fairly easily addressed.1) The authors claim that a subset of enhancers gains H3K9me2 in epiblast, and that this is associated with their inactivation during transition to primed pluripotency. Several issues need to be clarified here:In  of H3k9me2 status at these regions?This point is directly addressed in 2) A substantial weakness of the study is that despite the authors having all the necessary reagents in hand, the data pertaining to the functional impact of G9a on enhancer activity is limited to just a few examples, and not coherent ones either  Increased p53 binding upon loss of G9a may be an indirect consequence of the defect in enhancer repression, perhaps resulting in the increased enhancer accessibility- did the authors consider looking at chromatin accessibility measurements such as ATAC, DNase or FAIRE? Such data could in fact strengthen the conclusions on the functional impact of G9a on enhancer activity, regardless of the specific impact on p53.We have now found that increased recruitment of p53 to enhancers is most likely due to activation of this pathway upon loss of G9a. Nevertheless we performed DNAseI-qPCR hypersensitivity assay to address potential increased accessibility of the loci . However4) The authors generate valuable H3K9me2 and H3K27me3 ChIP-seq datasets from epiblast cells of E6.25 embryos, but I feel they missed the opportunity to provide a deeper comparison of their results with the H3K9me2 and H3K27me3 patterns reported from the in vitro cellular models such as EpiLC or EpiSC. What are the major similarities and differences in patterns? A systematic  comparison of H3K9me2 patterns across the genome in different cellular states would not only be broadly interesting for the community, but also relevant for the authors' own conclusions.We have now included an in-depth comparison between the epiblast in vivo and EpiSC in vitro . This in


In mammals, ChIP-seq studies of RNA polymerase II (PolII) occupancy have been performed to reveal how recruitment, initiation and pausing of PolII may control transcription rates, but the focus is rarely on obtaining finely resolved profiles that can portray the progression of PolII through sequential promoter states.Here, we analyze PolII binding profiles from high-coverage ChIP-seq on promoters of actively transcribed genes in mouse and humans. We show that the enrichment of PolII near transcription start sites exhibits a stereotypical bimodal structure, with one peak near active transcription start sites and a second peak 110 base pairs downstream from the first. Using an empirical model that reliably quantifies the spatial PolII signal, gene by gene, we show that the first PolII peak allows for refined positioning of transcription start sites, which is corroborated by mRNA sequencing. This bimodal signature is found both in mouse and humans. Analysis of the pausing-related factors NELF and DSIF suggests that the downstream peak reflects widespread pausing at the +1 nucleosome barrier. Several features of the bimodal pattern are correlated with sequence features such as CpG content and TATA boxes, as well as the histone mark H3K4me3.We thus show how high coverage DNA sequencing experiments can reveal as-yet unnoticed bimodal spatial features of PolII accumulation that are frequent at individual mammalian genes and reminiscent of transcription initiation and pausing. The initiation-pausing hypothesis is corroborated by evidence from run-on sequencing and immunoprecipitation in other cell types and species. Regulation of mRNA transcription is dependent on the recruitment and engagement of available RNA polymerase II (PolII) to the appropriate genes at the required times. A coordinated series of events involving PolII in complex with both general and specific transcription factors is known to start with recruitment ,2, contiDrosophila melanogaster, localization of a PolII peak at 40±20 base pair (bp) downstream from the hsp70 transcription start site (TSS) was inferred from the length of terminated run-on transcripts . RNA expression data and lower resolution ChIP-seq data for PolII and H3K4me3  are avaipd: total number of reads in downstream feature in bimodal peak; π: putative pause-release index, the ratio of gene-body PolII density to promoter-proximal downstream peak enrichment density; PIC: pre-initiation complex; PolII: RNA polymerase II; pu: total number of reads in upstream feature in bimodal peak; ρ: putative promoter-escape index, the normalized ratio of the bimodal occupancy difference; RNA-seq: RNA isolation followed by deep-sequencing; TSS: transcription start site; Ubxn2b: UBX domain protein 2B.a.u.: arbitrary units; bp: base pair; ChIP-seq: chromatin immunoprecipitation followed by deep sequencing; DSIF: DRB-sensitivity inducing factor; GAII: Genome Analyzer II; kb: kilobase; NELF: Negative elongation factor; PAS: polyadenylation site; PCR: polymerase chain reaction; The authors declare that they have no competing interests.MQ wrote and ran analyses, produced the figures and co-wrote the manuscript. CG analyzed RNA-seq data. FN designed the analyses and conceived the project. KBG directed the analyses and wrote the manuscript. All authors approved the manuscript.Table of selection criteria for genes used in the different figures. This table provides criteria on expression, isolation or fitting parameters used to select genes for the different figures of the paper.Click here for fileGenomic profiles of PolII around TSSs for the four different kind of tags and specific shifts. The first sign (+ / -) refers to the coding strand of the gene and the second sign to the mapping strand of the tag. (a) Average profiles without any shifting. (b) Profiles after shifting tags mapping on the minus strand by 100 base pairs (sequencing length). (c) Profiles after applying an additional shift of 74 base pairs  to realign the four different profiles. a.u., arbitrary units.Click here for fileExamples of bimodal PolII promoter-proximal profiles with different peak height ratios and convergence of the algorithm. (a–h) ChIP-seq profiles of PolII in a 2-kb window centered on the TSS for eight different mm9 (NCBI37) annotated genes, chosen to have the first peak very near the TSS without correction and with mRNA microarray expression in the top quartile. CpG content (NCBI37) and the location of the 110 bp separation are included.  Promoters with peak height ratios 1.64, 1.23, 2.20,  peak height ratios 0.87, 0.66, 0.66, and  peak height ratios 1.01, 0.92. (i) Convergence of the fitting score for 100 iterations for 20 random genes. a.u., arbitrary units.Click here for fileBidirectional promoters RNA-seq and distribution. (a) RNA-seq coverage from the first position of each sequenced read near TSSs for expressed transcripts, separated into the following categories: all expressed , expressed and isolated with no other TSS or PAS within 1 kb , those expressed with an oppositely directed TSS less than 1 kb upstream  and those expressed with an oppositely directed TSS between 170 and 200 bp upstream . The irregular downstream signal is due to individually highly expressed transcripts. (b) Histogram of the position of the nearest upstream opposite TSSs for all genes. a.u., arbitrary units.Click here for fileCorrelation between PolII and CAGE transcription start sites. Correlation between the peak position of 5′ ends of CAGE tags (data from FANTOM liver sample) and the first peak of our PolII ChIP-seq profiles, relative to NCBI37 annotated TSS for expressed genes with a CAGE signal. Transcripts are selected according to expression (>6.0), existence of CAGE signal near their TSSs, and a good PolII fit (>0.8) with our model (N=620). Transcripts with alternative TSSs are also excluded.Click here for fileClustering analysis of ChIP-seq signal with sequence and mRNA expression. This clustering shows general trends and some very specific high-TATA promoters with high expression, in contrast with most TATA promoters showing low expression. PolII seems to be highly correlated with expression, as does H3K4me3, as expected [expected .Click here for fileManaging duplicates for high-coverage genomic profiles of PolII around the TSS. (a) Mean PolII profile for 10,773 genes (coding on plus strand) keeping duplicate tags (black), without duplicates (green), same but scaled by 5 (blue) and with duplicates filtered  (red). (b) Same as (a), but for the top 10% microarray signal promoters. (c) Histogram of mean tag occupation between +70 and +130 (biggest peak region) for the top 10% of expressed promoters for lower coverage data. (d) Same as (c) but for 5 × higher-coverage sequencing showing saturation of signal. a.u., arbitrary units.Click here for fileCpG and GC-content profiles around TSSs for stratification in Figure 6. It is known that high GC content can bias Illumina sequencing towards fewer reads. These panels show that the GC content near the promoter did not create the observed bimodal feature. (a) Genomic profiles of CpG for classes of promoters separated by quantiles formed on the number of CpG in a ±1-kb window around the TSSs. The TATA >2% group is defined as the genes with the top 2% TATA score. (b) Stacked histograms of the number of CpG in a ±1-kb window around the TSSs. A small number of TATA genes are shown in orange. (c) Same as (a) but for mean GC content. (d) Same as (b) but for mean GC content. The colors are for the same groups as in (a). A small number of TATA genes are barely visible in the stacked histograms.Click here for fileDifference between microarray and RNA-seq to determine expression. (a) Correlation between microarray and RNA-seq inferred expression . (b) Correlation between microarray and RNA-seq inferred expression after quantile normalization of both datasets, R2=0.87, P<2.2×10-16. (c) Correlation between average PolII signal at TSSs and microarray expression. (d) Correlation between average PolII signal at TSSs and RNA-seq expression. (e) Average profile of PolII at TSSs for quantiles of expression based on microarray data. (f) Average profiles of PolII at TSSs for quantiles of expression based on RNA-seq. a.u., arbitrary units.Click here for fileTable of genes and properties selected for analysis. This table provides transcript name, microarray expression, TATA score, CpG count, GC content and nearest gene-neighbor distances. Some genes are not classified as alone because they have a nearby alternative TSS or PAS of a neighboring gene.Click here for file


Drosophila controls the level of regulated secretory activity in NE cells. To pursue its mechanisms, we have performed two independent genome-wide analyses of DIMM's activities: (i) in vivo chromatin immunoprecipitation (ChIP) to define genomic sites of DIMM occupancy and (ii) deep sequencing of purified DIMM neurons to characterize their transcriptional profile. By this combined approach, we showed that DIMM binds to conserved E-boxes in enhancers of 212 genes whose expression is enriched in DIMM-expressing NE cells. DIMM binds preferentially to certain E-boxes within first introns of specific gene isoforms. Statistical machine learning revealed that flanking regions of putative DIMM binding sites contribute to its DNA binding specificity. DIMM's transcriptional repertoire features at least 20 LDCV constituents. In addition, DIMM notably targets the pro-secretory transcription factor, creb-A, but significantly, DIMM does not target any neuropeptide genes. DIMM therefore prescribes the scale of secretory activity in NE neurons, by a systematic control of both proximal and distal points in the regulated secretory pathway.Neuroendocrine (NE) cells use large dense core vesicles (LDCVs) to traffic, process, store and secrete neuropeptide hormones through the regulated secretory pathway. The dimmed (DIMM) basic helix-loop-helix transcription factor of  In the mammalian hypothalamus, a small cohort of neuroendocrine (NE) neurons produces the peptide hormones vasopressin (VP) or oxytocin (OX) for release into the blood via the hypophysial portal system. Peptides like VP and OX must travel long distances, in sufficient quantities and at the appropriate times to deliver organism-critical physiological information. Thus to perform their cellular functions, NE neurons like the VP- and OX-expressing neurons must coordinate and respond to a complex set of physiological, cellular and biochemical requirements . They muin vitro and in vivo suggest that such cellular properties result from sophisticated and cell-intrinsic genetic programs  REprograms ; and  TF DIMM is an important component of this genetic regulatory program. By virtue of its normal expression, and its loss-of-function phenotypes, we have proposed that DIMM is required to support the dedicated, high secretory capacity of NE neurons that produce many diverse NE peptides  ,16. DIMMganelles , and it ganelles . LikewisPhm and the cytochrome b-561 isoform CG1275. The latter is an integral LDCV membrane protein that provides reducing equivalents from the cytosol to the LDCV lumen to replenish the stores of ascorbate  cofactor that is oxidized with each reaction cycle; . To extdimm::myc transgene was combined with a temperature-sensitive tub-GAL80ts element and c929-GAL4, which is inserted in a dimm enhancer and overlaps almost completely with DIMM protein  and (ii) c929-GAL4; tub-GAL80ts maternal strain (negative control). Following crosslink reversal, DNA was processed according to the Affymetrix® Chromatin Immunoprecipitation Assay Protocol (P/N 702238 Rev. 3). For each sample, 10 μl of undiluted ChIP DNA or 1:10-diluted input DNA was amplified by linear polymerase chain reaction (PCR)-based amplification. We used quantitative PCR as described by Menet et al. .We performed chromatin immunoprecipitation (ChIP) as previously described ,23. Brie protein . Animalsal. . The foin vivo DIMM target Phm demonstrates a distinct signal peak over its first intron that overlaps in the (#1 – #2) and (#1 – #3) normalizations, whereas (#3 – #4) showed no binding . Statistically significant deviations of signal from baseline were calculated for this twice normalized raw signal at P-value ≤1 × 10−4 with a naïve peak caller algorithm (Cistrome). Visual output from all three MAT analyses performed  can be directly compared to each other as long as the window minima and maxima are identical.Thus, an identical number of arrays were used for experimental and control samples, with the same number of biological replicates and DNA amounts hybridized to tiling arrays. Analysis and normalization was carried out as follows: samples from #1 were normalized against input in #2 in MAT. Samples from #3 were normalized against their input in #4 in MAT. In order to provide additional stringency and as a means of independent verification, ChIPed DNA from experimental samples in #1 was normalized directly against ChIPed DNA in controls in #3 in MAT. Next, raw signals from MYC ChIP signal normalized to its input of the control sample (#3–#4) were subtracted from the experimental group MYC ChIP signal normalized to its input (#1–#2). Raw signal derived from normalizing MYC ChIP in the experimental group to MYC ChIP in the control group (#1–#3) was then added to the subtracted signal (#1 – #2) – (#3 – #4). This is represented by the following equation: [(#1 – #2) – (#3 – #4)] + (#1 – #3). We found that signal peaks obtained from (#1 – #2) – (#3 – #4) normalization coincided with peaks from (#1 – #3) normalization in majority of cases. Therefore, we felt that obtaining binding peaks in the same location defined by these two different normalization steps enhanced the data fidelity. For example, the known http://www.broadinstitute.org/cancer/software/GENE-E/). All other graphs were produced in OS X R version 3.0.2 GUI 1.62 or in Microsoft Excel 2011. Cistrome SeqPos was used to detect statistically significant DNA binding motifs  were predicted using DNAshape, a high-throughput method for inferring DNA shape parameters from sequence . Models et al.  and subsequent RNA-Seq. This strain is essentially wild-type with respect to DIMM physiology, as evidenced by normal neuropeptide staining (data not shown). Young flies (5–12-days old) grown at 25°C on standard Drosophila cornmeal media were anesthetized with carbon dioxide and collected on ice. We dissected brains of 140 (first experiment) and 180 flies (second experiment) within a 2–3-h time period in cold saline, as in Nagoshi et al. .Fly brains were then centrifuged at 1000 x g for 30 s in a microcentrifuge. Frozen L-cysteine-activated papain  was activated at 37°C for 20 min immediately prior to the end of dissection. We then added 450 μl of activated papain to the brains, resuspended them and then incubated with papain for 20 min at room temperature. Papain digestion was quenched by adding 1.5 ml of Schneider's medium supplemented with 1% heat-inactivated Fetal Calf Serum. The sample was centrifuged at 500 x g for 30 s at room temperature. Brains were washed two more times and were finally resuspended in 600 μl of Schneider's medium supplemented with 1% Fetal Calf Serum (FCS).Papain-digested brains were then triturated 30 times with a flame-rounded P1000 filter tip (medium tip opening), 30 times with a flame-rounded P1000 filter tip , 30 times with a flame-rounded P200 filter tip (large opening), 40 times with a flame-rounded P200 filter tip (medium tip opening) and 20 times with a flame-rounded P200 filter tip . Pipette volumes used for trituration were 500 and 150 μl for the P1000 and P200 pipettes, respectively. Trituration efficiency was moderate, such that very small pieces of brain tissue were still visible under a dissection microscope at the end of the procedure.We strained the brain homogenate through a sterile 70-micron cell strainer (Fisher Sci) mounted on a 50-ml Falcon, then centrifuged briefly at 400 rpm at 4°C. Flow through containing filtered dissociated cells was then strained through a 35-micron sterile cell strainer  mounted on a 50-ml Falcon, then centrifuged briefly at 200 rpm. 450 μl of dissociated single cells were collected in a 6-ml BD Falcon tube and transported on ice to the Washington University Siteman Flow Cytometry Core for FACS sorting.c929+ cells in the adult fly brain  gate was set based on established criteria and experience of the Core's personnel with the sorter. Sorting GFP+ and GFP− cells was completed within 1 h of the start of sorting. Roughly, 1–3% of all cells in the samples were GFP+, which is consistent with the number of ly brain . In ordely brain . The pilAt the end of sorting, cells were transferred directly into Qiagen's RLT buffer supplemented with beta-mercaptoethanol (Qiagen RNA MinElute kit). Most investigators harvesting nano scale RNA samples for microarray gene expression profiling use the Arcturus PicoPure kit ,39. ThisSamples with pooled GFP+ and GFP− RNAs were then submitted to the Genome Technology Access Center (Washington University Genetics Department). RNA quality was then checked by Qubit (Invitrogen), NanoDrop  and Bioanalyzer (Agilent) quality control assays. Neither sample showed signs of degradation or DNA contamination. Thirty-five nanograms of RNA from GFP+ cells left and 35 ng of RNA from GFP− cells were processed for sequencing on Illumina's HiSeq 2000 platform.Because Illumina's deep sequencing protocols require 10 μg of RNA, the samples were amplified with the NuGen Ovation RNA-Seq system, a single primer-based RNA amplification product that uses isothermal amplification ,45. AfteDrosophila dm3 r5.50 genome release  was equal to 9.435933 × 10−11. Three hundred and thirty seven ChIP-chip associated transcripts enriched at 1.5-fold or higher with expression level greater or matching that of Pick1 in the c929-GFP+ sample yielded a total of 212 genes.There were a total of 1809 ChIP-chip peak-associated transcripts. 366 transcripts were not expressed in either sequenced sample. We applied a threshold to the data according to absolute gene expression by searching for genes expressed at low levels, that are nevertheless known to be enriched in ck1 gene  displayec929-GAL4+ (c929+) neurons for purification by directing their expression of GFP . Figure +  cells . Those results confirmed earlier suggestions of accurate sorting and high purity between the two samples: the e Figure . Figure peptides , and a ‘peptides . Phm is NE cells . We obtas Figure . Therefoc929+ cells express diverse neuropeptides, all at high levels , eclosion hormone (Eh) and IFamide are DIMM+: the c929-GFP+ cells likewise demonstrated a high degree of enrichment of Pdf, Eh and IFa by RNA-Seq  proctolin neurons are largely DIMM− and most tachykinin-expressing (Tk+) neurons are local interneurons and not DIMM+ NE cells . Figurec929-GFP+ cells against previously characterized Drosophila neuronal cell subpopulations. Figure c929-GFP+ cells express lower levels of the GABAergic marker Gad1, the serotonergic marker Ddc, the cholinergic marker VAchT and the glutamatergic marker VGlut compared to randomly sorted c929-GFP− cells. These findings demonstrate that c929+ cells are transcriptionally distinct from other neuronal subpopulations known to engage predominantly in conventional (i.e. non-peptidergic) neurotransmission.We also wanted to compare c929+ population with those from other purified Drosophila adult brain cells, including Kenyon cells, Octopaminergic cells and a generic neuronal population (elav+) , svr (CPD/E) and Phm) are all enriched in +c929 neurons, though not exclusively. For example, mRNA levels of key NE proteins like the PC2-associated 7B2, the cytochrome b-561 CG1275 and the copper transporter ATP-7 also display relative high levels in purified octopaminergic cells .We also compared the RNA-Seq results of the ) Figure ). Notablin vivo throughout the genome. For this purpose, we employed a tagged ChIP-chip strategy  in two independent DIMM ChIP experiments. Descriptions of the loci are provided in Supplementary Table S2. To evaluate the success of the tagged ChIP approach, we examined DIMM occupancy at its known binding site in the first intron of Phm : indeednsortium ) to detePhm, CG1275 and mael  known DIMM targets such as l Figure : these te et al. ); (ii) tl. (amon—) and carmon—(svr—); as welRegarding the positions of DIMM binding sites at their target genes, ChIP-chip signals were strikingly enriched near transcription start sites and depleted near transcription termination sites Figure  and C. APhm, we next queried bound sequences for binding sites in an unbiased manner. A motif-calling algorithm identified the CCATATGG motif as the statistically most enriched motif : >90% oIntron 1 . FinallyIntron 1 . Based oin vivo TF-DNA binding  as unbound sites and E-boxes within ChIP-chip peak regions as bound sites. Whereas the E-box cores of these two groups of target sites were identical in their sequence composition, predictive models that used features derived from flanks of the E-box cores performed better in distinguishing bound from unbound binding sites than a random classification. The model performance was evaluated based on the ROC curve and the calculated AUC. An AUC value of 0.5 indicates a random classifier. For the two types of E-boxes with either the CATATG or CAGCTG core, we compared different models with the goal to identify features that distinguish bound from unbound putative DIMM target sites. These features included DNA sequence and shape features , as it was previously shown for bHLH TFs that DNA shape exerts the effect of the genomic flanks on binding specificity . DIMM transactivated 12 of the 16 candidate regulatory fragments to significant levels. Interestingly, many of the tested enhancers produced inductions that were many fold higher than the strongest inductions recorded previously for target genes Phm, mael and CG6522 , we wished to assess the overlap in gene lists so as to define a high-confidence list of DIMM targets. Here we describe the basis for creating the overlap. As shown in Table c929+ over c929− cell transcriptomes. Secondly, their level of expression exceeded 0.983129 FPKM (Fragments per kilobase of transcript per million mapped reads), which is the level of expression in c929+ cells of the gene Pick1. Pick1 levels were chosen as a threshold because they displayed the lowest level of expression for any gene known to be enriched in c929/DIMM+ neurons  did not CG17293—,21. To ec929+ cells, is more difficult to exclude. Future experiments must take this possibility into consideration as individual targets are evaluated. Finally, the risk that identified DIMM binding sites may lack fidelity, due to use of a tagged DIMM over-expression strategy, is a potential concern. We note that Yao et al.  contamination of the two cell populations during sorting, (ii) mis-calling of adjacent genes due to their overlap around a single DIMM binding site or (iii) the use of DIMM over-expression in our experimental design. First, regarding the degree of cell sorting purity, we incorporated ultrastructural analysis of dissociated, FACS-sorted neurons to provide electron microscopic evidence that at least some NE neurons within the population were structurally intact. The percentage of cells displaying LDCV was low, but given the challenging treatment by which cells were purified, and the resulting transcriptional profiling, we submit cell health was not compromised. Second, as we described in Figure o et al.  explicitPhm by binding to specific E-boxes in its first intron . Therefore, the ChIP-chip-identified DIMM-binding E-boxes, derived from analysis of 384 genomic fragments bound by DIMM in vivo, matched previously identified E-boxes that DIMM binds to in order to transactivate its targets. This finding increases confidence in the significance of other sites that share these E-box signatures.Previous work demonstrated that DIMM transactivated the amidating enzyme t intron . That en control . Similar control . InteresrSurvey; ): http:/in vivo binding , CSP and betaTUB56D. ATP7 is a dedicated copper transporter, enriched in NE neurons .et al. , Pfrx, Pgk, chic (Profilin), eIF-4a, RpS16, RpS2, capt (adenylate cyclase associated protein1). Two additional DIMM targets are highly related (though not the most highly related Drosophila genes) to the corticotroph LDCV proteins prolyl-4-hydrolase (ERp60) and a dynein light chain . Thus more than 10% of the DIMM targets here identified are likely components of LDCV as schematized in Figure Extensive proteomics analysis has identified hundreds of proteins resident on human LDCV . Gauthieet al.  identifiet al. have shown that CREB-A is a critical coordinating factor in the normal dedication of secretory capacity , and vrille and a few bHLH proteins on the list including HLH4C, sima and the orange-domain containing cwo (clockwork orange). Several of these have previously been implicated in control of ER capacity in high-level secretory cell types  that help process neuropeptide precursors transiting through the trans-Golgi to specific secretory granules  and siler . Some oizations . DIMM trboxylase ). To datschizo, atl, Arf79F (the Drosophila Arf1/2/6 ortholog), RhoGEF3 and RanGAP. Of special note in this context is the target Rab2: it represents a critical point of regulation in the transport of COPI vesicles between the ER and the Golgi. Genetic analyses have shown that Rab2, along with a network of effectors, GAPs and interacting proteins, is required for proper sorting of soluble and trans-membrane LDCV components  and alan shepherd (shep) all are RNA binding proteins with potential broad-scale regulation of the translational capacity of NE cells. Control of specific RNA binding proteins could be a mechanism by which dimm regulates neuropeptide mRNA stability. The ps gene has previously been implicated in pro-secretory functions in salivary glands, wherein the loss of function phenotype includes a defect of apical secretion . It is  α and β—.Supplementary Data are available at NAR Online.