The advent of high-throughput sequencing has allowed genome wide profiling of histone modifications by Chromatin ImmunoPrecipitation (ChIP) followed by sequencing (ChIP-seq). In this assay the histone mark of interest is enriched through a chromatin pull-down assay using an antibody for the mark. Due to imperfect antibodies and other factors, many of the sequenced fragments do not originate from the histone mark of interest, and are referred to as background reads. Background reads are not uniformly distributed and therefore control samples are usually used to estimate the background distribution at any given genomic position. The Encyclopedia of DNA Elements (ENCODE) Consortium guidelines suggest sequencing a whole cell extract  sample, or a mock ChIP reaction such as an IgG control, as a background sample. However, for a histone modification ChIP-seq investigation it is also possible to use a Histone H3 (H3) pull-down to map the underlying distribution of histones. In this paper we generated data from a hematopoietic stem and progenitor cell population isolated from mouse fetal liver to compare WCE and H3 ChIP-seq as control samples. The quality of the control samples is estimated by a comparison to pull-downs of histone modifications and to expression data. We find minor differences between WCE and H3 ChIP-seq, such as coverage in mitochondria and behavior close to transcription start sites. Where the two controls differ, the H3 pull-down is generally more similar to the ChIP-seq of histone modifications. However, the differences between H3 and WCE have a negligible impact on the quality of a standard analysis. As sequencing grows cheaper and more efficient  or a mock pull down. The WCE is a sample of the sheared chromatin taken prior to immunoprecipitation and is often referred to as the “input,” whereas a mock pull down gives an estimation of background by pulling down an irrelevant target using a non-specific antibody such as IgG. Both of these options emulate some of the biases present in a ChIP-seq data set but a mock pull-down is believed to be more similar to the background signal of the ChIP sample as it emulates more steps in the processing of the sample. However, it can be difficult to retrieve sufficient amounts of DNA from a mock immunoprecipitation to give an accurate estimation of the background and so a WCE sample is by far the most common control sample used  along the DNA. Therefore, using an H3 pull-down as a control sample gives a measure of the enrichment in relation to the presence of a histone. For example, if a histone modification antibody had a slight affinity for all histones whether or not they had the modification, the H3 pull-down could account for this background. This is slightly different to a WCE control that not only misses the immunoprecipitation process in the protocol but also attempts to measure the density of a modified histone relative to a uniform genome. Here we investigate which background sample is the most efficient at reducing noise and extracting biologically relevant information from histone modification ChIP-seq data.To our knowledge there are no studies comparing WCE or IgG to Histone H3 immunoprecipitation as a control sample, and there are few studies using H3 immunoprecipitation as a control. In this paper we use new unpublished data from a mouse hematopoietic stem and progenitor cell population that includes WCE, H3, and trimethylation of lysine 27 on histone H3 (H3K27me3) ChIP-seq samples, together with RNA-seq expression data, to study the differences between WCE and H3 pull down as control samples. This data set shows that H3 samples share some features with the H3K27me3 samples that are not present in the WCE sample, but that these biases do not have a significant impact in most standard analyses.The first part of this paper studies the genome wide properties of the WCE and H3 samples and looks for differences and similarities between the two types of background samples. In the results section we firstly compare each background sample to histone modification ChIP-seq and expression data. We then compare which control is most successful in extracting correlation between histone modifications and expression.+ and Sca1+. Similarly, adult bone marrow hematopoietic stem and progenitor cells for RNA-seq were sorted based on lineage  negative, c-Kit+ and Sca1+ cell surface marker expression. Approximately 250,000 cells were used for each ChIP, whereas 30,000–100,000 cells were used to prepare RNA for the RNA-seq.The mouse hematopoietic stem and progenitor cell population for ChIP was isolated from E14.5 fetal livers from C57BL/6 mice by fluorescence-activated cell sorting based on the following cell surface marker profile: lineage  negative, c-KitFor chromatin immunoprecipitation (ChIP), formaldehyde cross-linked cells were sonicated in a Covaris sonicator. A small fraction of sonicated material was retained as the WCE sample and the remainder was incubated with either an antibody against H3 (AbCam) or H3K27me3 (Millipore) overnight at 4°C. Immune complexes were purified by incubation with protein G beads (Life Technologies) at 4°C for an hour. Cross-links were reversed by incubation at 65°C for 4 h before DNA fragments were purified with the ChIP Clean and Concentrator kit (Zymo). Sequencing libraries were prepared using the TruSeq DNA Sample Prep Kit (Illumina) and sequencing was performed on a HiSeq2000 (Illumina).ChIP-seq data was generated for the histone mark H3K27me3 in a hematopoietic stem and progenitor cell population isolated from E14.5 mouse fetal liver from C57BL/6 mice. There are three replicates of H3K27me3 ChIP-seq, with approximately 16, 17, and 18M reads each, two H3 ChIP-seq replicates with approximately 24 and 27M reads each, and one WCE with 44M reads. We also generated three RNA-seq replicates from a hematopoietic stem and progenitor cell population isolated from the bone marrow of adult mice that had received fetal liver cell transplants with approximately 17 M reads each. The reads are 100 bp single end reads sequenced by Illumina HiSeq technology. Data is available from GEO (GSE59419).http://hgdownload.soe.ucsc.edu/goldenPath/mm10/bigZips/chromFa.tar.gz).We used default Bowtie 2 version 2.2.3 with the --very-sensitive-local preset and all other settings as default to align the ChIP-seq and WCE reads where data should map directly to the genome. To properly handle RNA fragments that span exon junctions, alignment for the RNA-seq data was performed using TopHat version 2.0.8 with the --b2-very-sensitive preset and all other setting with default parameters. Alignment was performed against mm10  of b tries with an expectation value of pib.The aligned reads were filtered for mapping quality of 20 or more, and assigned to 100 and 1000 bp consecutive, non-overlapping bins over the genome based on the center of the read. The smaller bin size is used in the gene coverage analysis to give a sufficient resolution compared to a typical fragment size, while the larger bin size is used for count distribution and differential enrichment analysis, trading some resolution for more statistical power. For some analyses the larger library sizes are downsampled to match the smallest. We want to keep a fraction B bins are assigned a random number of reads from a Poisson distribution with an expectation value of λ =Nmin/B.For comparison purposes, we generated random counts based on a Poisson distribution Figure . SpecifiplotMA function in the limma R package  of exon length (RPKM). The read count was increased by one read per million reads in the library (cpm increased by one). Enrichment level was determined in the same fashion, but using the full gene length (including introns) and adding 0.5 to the RPKM instead of to the cpm, to even out the background levels between the samples.The average coverage over genes and promoters was determined from the 100 bp bin counts. Each gene was assigned 150 bins, with bin size 1/50 of the gene width, covering the gene and one gene width on either side. These bins were assigned coverages by averaging the read counts of all overlapping 100 bp bins. Bins in the same position of each gene were then averaged over genes in the same expression quartile. The average coverage in a bin was calculated as the mean over the bin and the two neighboring bins to make the plot smoother. Genes with extremely high RPKM (larger than 100) were excluded from the analysis, to allow the mean to be calculated on a linear scale without being dominated by a few outlying genes. In our dataset, all the removed genes are ribosomal or mitochondrial.All code for the analysis can be found in the supplementary material. In addition a flow chart outlining the analysis steps is shown is Supplementary Figure Using an immunoprecipitation of Histone H3 as a background sample is attractive for accounting for uneven coverage across the genome due to both technical and biological artifacts. Specifically, an H3 pull-down not only mimics all the steps in the ChIP-seq processing but data also locates the possible regions of the genome that have the H3 protein and therefore the potential to harbor a histone modification. In order to assess the possible advantages in using an H3 control we began by comparing H3 with a standard WCE background sample.As we have outlined, control samples are often used to cancel background reads that can lead to false signals in the histone modification samples. In order to verify that the controls indeed have structure beyond random sampling, such as enriched or depleted regions, we examined the distribution of reads across the genome. Initially we counted the number of reads in 1 kb bins across the genome and compared the count distributions between WCE, H3 and simulated random counts from a Poisson distribution. To account for different library sizes, the larger libraries were downsampled to match the smallest one (see Section Methods). The WCE and H3 count distributions are very similar to each other and they both display heavier tails compared with a Poisson distribution, thus implying non-random structures in the data , and these regions are known to cause false positives in CHIP-seq data . The enriched regions that are detected with both background samples have highly correlated peak scores Figure . This shUsing any of the controls on our data set improved the quality of the analysis. Without the controls, only 9565 peaks were called in the H3K27me3 samples, and many biologically relevant peaks were lost  for the highly expressed genes, whereas the H3 and H3K27me3 samples display a dip or trough at the TSS. The dip for H3 and H3K27me3 is consistent with a depletion of nucleosomes at the TSS  in the gene body or the promoter (defined as 4 kb centered at the TSS) for the H3K27me3 mark Table . We thenAs expected, H3K27me3 enrichment over both the gene body and the promoter show an anti-correlation with expression. However, dividing by a control sample greatly improves the strength of the correlation for both the gene body and promoter. The WCE background improved the correlation slightly more than the H3 samples, especially for the promoter region. Both controls have a fairly strong positive correlation to expression, indicating that there likely is a positive background contribution to the H3K27me3 correlation, canceling out part of the negative correlation. This background contribution was removed by dividing by the control samples, and the full negative correlation from the histone modification appears.To investigate this effect further, we took data from Adli et al.  on H3K27We have generated ChIP-seq data for Histone H3, H3K27me3, and WCE samples from a hematopoietic stem and progenitor cell population isolated from E14.5 mouse fetal liver from C57BL/6 mice, and mRNA-seq expression data from a hematopoietic stem and progenitor cell population isolated from the bone marrow of adult mice that had received fetal liver cell transplants. We used these data, together with publicly available data, to compare WCE and H3 for their efficacy as control samples for modified histone ChIP-seq data.Using WCE or H3 as a control yields slightly different interpretations of the corrected data. Dividing a histone modification ChIP-seq sample by a WCE background normalizes the sample against genome and fragmentation biases, with no explicit regard to the underlying histones. In contrast, dividing by a H3 background estimates the enrichment relative to the position of histones in the sample. Which of these two measures is more appropriate depends on the experiment, and the type of biology being probed. For example, in a study looking at the relationship between the H3K27me3 density and the compactness of the genome it may be more relevant to compare H3K27me3 density to a WCE control. On the other hand, using H3 as a background sample might be more relevant for a study looking at the how PRC2 affects the methylation of histones tails where we need to know which histones are modified. However, most experiments with ChIP-seq of histone modifications do not have the precision to tell the two interpretations apart, and we will focus on which control sample can extract the most information from the experiment.We found, as has previously been observed, that both the WCE and H3 samples have more features and structures than would be expected from randomly distributed reads. For example, both controls are more enriched over highly expressed genes than over lowly expressed genes. We compared read counts in 1 kb bins between WCE and H3 and found that most features of the read distributions are similar between background samples. The notable exception to this was mitochondrial DNA where no H3 histones are present. The non-random enrichment features seen in both background samples can occur from biological sources, such as accessibility of the DNA, stability of the interaction between DNA fragments and targeted proteins as well as technical processes such as PCR artifacts and sequencing biases. Furthermore, biases can arise from the data analysis, with mappability perhaps being the most influential. These error sources are also expected to be present in ChIP-seq of histone modifications, and thus the WCE and H3 are suitable as background controls, with the majority of the structures in both WCE and H3 capable of canceling out biases.When the data is averaged over a large number of genes, a more relevant difference between the control samples become apparent. WCE shows more enrichment over the TSS for expressed genes, while H3 and H3K27me3 show a trough at the TSS. The trough seen in both the H3 and H3K27me3 pull-down is likely due to nucleosome depletion specifically at the TSS where the transcriptional machinery is accessing the DNA , and the peak scores had a Pearson correlation of 0.996. We believe that in the majority of cases the choice of which background sample is used will make a negligible difference to the results. Therefore, the use of WCE or input as a standard control sample is well justified.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


These data indicate that the protein can act as repressor or activator and is mainly involved in transcriptional control of sugar uptake and in the switch between glycolysis and gluconeogenesis. The aim of this study was to complement the in vitro data with an in vivo analysis using ChIP-seq to explore the genome-wide binding profile of TrmBL1 under glycolytic and gluconeogenic growth conditions.Several in vitro transcription experiments validated the in vivo identified TrmBL1 binding sites. Furthermore, this study provides evidence that TrmBL1 is also involved in transcriptional regulation of additional cellular processes e.g. amino acid metabolism, transcriptional control or metabolic pathways. In the initial setup we were interested to include the binding analysis of TrmB, an additional member of the TrmB family, but western blot experiments and the ChIP-seq data indicated that the corresponding gene is deleted in our Pyrococcus strain. A detailed analysis of a new type strain demonstrated that a 16 kb fragment containing the trmb gene is almost completely deleted after the first re-cultivation.The ChIP-seq analysis revealed under gluconeogenic growth conditions 28 TrmBL1 binding sites where the TGM is located upstream of coding regions and no binding sites under glycolytic conditions. The experimental confirmation of the binding sites using qPCR, EMSA, DNase I footprinting and P. furiosus genome classified TrmBL1 as a more global regulator as hitherto known. Furthermore, the high resolution of the mapped binding positions enabled reliable predictions, if TrmBL1 activates (binding site upstream of the promoter) or represses transcription (binding site downstream) of the corresponding genes.The identified binding sites in the The online version of this article (doi:10.1186/s12864-015-2360-0) contains supplementary material, which is available to authorized users. Pyrococcus furiosus a total number of 85 putative transcription factors (TFs) can be found, which represent about 4 % of all open reading frames (ORFs) [Basal transcription in archaea relies on a eukaryotes-like transcription machinery and promoter elements, whereas, transcriptional regulation is based on mainly bacteria-like transcriptional regulators –3. Theses (ORFs) . 13 of ts (ORFs) –14.P. furiosus [Thermococcales_Glycolytic_Motif (TGM) with the consensus sequence TATCAC-N5-GTGATA serves as palindromic DNA recognition element for TrmBL1 binding in vitro and in vivo [Two of them, TrmB and TrmBL1 (TrmB-like protein 1), play a crucial role in transcriptional control of genes involved in sugar transport and metabolism in furiosus ,14–16. Tfuriosus –19. The furiosus . In contfuriosus ,11. The  in vivo ,11,20. T in vivo ,11. TrmBin vitro analysis of TrmB and TrmBL1 revealed crossregulation of both factors on some promoters, e.g. the TM and maltodextrin-specific-ABC-transporter (MD) system [in vivo. Currently, only a few ChIP studies exploring archaeal species are available, mainly for the halophilic strain Halobacterium salinarum-NRC1 and the hyperthermophilic crenarchaea Sulfolobus solfataricus and Sulfolobus acidocaldarius [A detailed ) system . Thus, waldarius –26. Mostaldarius ,28. Recealdarius .in vivo. For this purpose a previously described ChIP protocol of our group for the hyperthermophilic archaeon P. furiosus was successfully improved for a ChIP-seq approach [P. furiosus genome under steady state glycolytic or gluconeogenic growth conditions exposed the function of TrmBL1 as global regulator for sugar transport and metabolism and revealed novel and unexpected genes which are in addition under the transcriptional control of TrmBL1.The aim of this study was to dissect the specific role of TrmB and TrmBL1 as transcriptional regulators of genes encoding enzymes involved in sugar uptake, glycolysis and gluconeogenesis in a genome-wide manner approach . The ideP. furiosus type strain DSM3638 was obtained from the Deutsche Sammlung von Mikroorganismen und Zellkulturen (DSMZ) recently and after growth in SME complex media the strain was prepared for long time storage. Cells were grown under anaerobic conditions in nutrient rich medium based on SME [P. furiosus cells (1:100 dilution) cultivation was done at 95 °C overnight or until the appropriate cell density was reached.d on SME  and suppAll used plasmids and primers are shown in the supplement  using recombinantly expressed and purified TrmB and TrmBL1 proteins . The IgGP. furiosus were prepared from 20 ml cell cultures with a cell density of approximately 1x108 cells per ml. After harvesting cells were resuspended in PBS supplemented with protease inhibitor mix  and treated with glass beads using a FastPrep24  for cell lysis. After removal of cell debris by centrifugation the protein concentrations of the supernatants were determined by Bradford assay. Western blot experiments were done as described previously [The recombinantly expressed and purified proteins TrmB, TrmBL1 and TrmBL2 were obtained as previously described ,17,37. Ceviously .P. furiosus cells were transferred to SME minimal medium supplemented with either starch (glycolytic inoculation culture 1) or sodium pyruvate (gluconeogenic inoculation culture 1) for adaptation to glycolytic or gluconeogenic growth conditions. Moreover, P. furiosus cells grown under gluconeogenic conditions were transferred additional three times in SME minimal medium supplemented with pyruvate (gluconeogenic inoculation culture 2). These three cell cultures were used for cultivation of P. furiosus in 15 L bio-fermenters containing the appropriate medium (samples: glycolytic culture 1 (starch 1) and gluconeogenic cultures 1 and 2 (pyruvate 1 and 2)). After the cells reached a cell density of 1 to 1.5x108 cells/ml  fixation was done directly in the bio-fermenter at 95 °C with a final concentration of 0.1 % (v/v) formaldehyde. After 20s the crosslinking reaction was stopped by adding glycine to a final concentration of 15 mM and the bio-fermenter was straight away cooled down to 20 °C for harvesting the crosslinked P. furiosus cells [Formaldehyde crosslinking was done according to Liu et al. . After rus cells .Formaldehyde-treated cells were disrupted by sonication using the Branson Sonifier  until an average fragment length of 250 bp to 500 bp was obtained . Eluted complexes and input samples were incubated overnight at 65 °C for reversal of the crosslink. After treatment with RNase A and Proteinase K ChIP enriched and input DNA was purified via the QIAquick PCR purification kit  and stored at −20 °C. For each culture (glycolytic culture/starch 1 and gluconeogenic culture/pyruvate 1 and 2) the immunoprecipitation step was repeated once .For immunoprecipitation (IP) 5 μg of purified polyclonal antibodies raised against TrmBL1 or Phr was coupled to 50 μl Dynabeads Protein G for immunoprecipitation  according to the manufactures instructions. Antibody coupled magnetic beads were resuspended in 500 μl nd 1x TE . ElutionLibrary preparations were done according to the NEBNext ®-ChIP-Seq library prep reagent set for Illumina protocol . For multiplex sample preparation the NEBNext® Multiplex oligos (primer set 1 and 2)  were used and libraries were PCR amplified by the NEBNext®High Fidelity Master Mix . Libraries were pooled in equimolar ratios and sequenced using the Illumina HiSeq 2000 platform (read length = 50 b) . For further analysis only the demultiplexed and quality filtered reads  were used.P. furiosus DSM3638 genome using Bowtie2 with default settings [Q-value cutoff = 1.00E-5 and the maximum duplicate tags at the same position were adjusted to the minimal value sufficient for building the paired-peak model. Following sample combinations were analysed: starch 1 IP1 versus starch 1 input, starch 1 IP2 versus starch 1 input, pyruvate 1 IP1 versus pyruvate 1 input, pyruvate 1 IP2 versus pyruvate 1 input, pyruvate 2 IP1 versus pyruvate 2 input and pyruvate 2 IP2 versus pyruvate 2 input. Using these settings no significant peaks were detected in the samples starch 1 IP1 and 2. Moreover, from the peaks called in the samples pyruvate 1 IP1 and 2 and pyruvate 2 IP1 and 2 only those were considered for further analyses which were present in at least three from the four samples  [The consensus TF binding site for each peak region was calculated as midpoint of the sites detected by MACS2 in the different samples. The DNA sequences surrounding these midpoints in the range of 350 bp downstream and upstream were used for De-novo motif discovery by MEME ,44 using by FIMO  using a ettings) .P-value cut-off < 1.0E-3. The 14 bp consensus sequence of the BRE- and TATA-box (based on 27 P. furiosus promoter sequences) was loaded as position-frequency matrix reported by vandeWerken et al. [Scanning for promoter occurrences in the detected ChIP-enriched was performed by FIMO  search un et al. . The scan et al. . Function et al.  and KEGGn et al. ,51.E. coli DH5α cells. Correct plasmids were purified using the QIAprep plasmid isolation kit  and used as PCR template for generating DNA templates used in in vitro assays. For EMSA assays templates were PCR amplified using corresponding primers  using corresponding primers . After incubation at 80 °C for 30 min the transcripts were separated on a denaturing 8 % polyacrylamide gel. Transcription products were visualized using a fluorimager.Assays were done as described previously ,52. ReacA computational analysis revealed a very similar organization of the two transcriptional regulators TrmB and TrmBL1. Both proteins contain in the N-terminal region a highly conserved helix-turn-helix motif as DNA-binding-domain (45 % amino acid sequence identity) and an effector-binding domain in the C-terminal region ,15. To e6 tag at the N-terminus, the electrophoretic mobility of the endogenous TrmBL1 was slightly reduced. In contrast, the antibody raised against TrmB showed a reaction with recombinant TrmB and a cross-reaction with TrmBL1 but not TrmBL2  were analysed and one under glycolytic conditions (starch 1). Figure P. furiosus genome under both conditions. Sequence analyses of all samples including inputs revealed two distinctive features: 1. The sequences contained nearby no hits in the published genome sequence from 1,613,140 to 1,629,427. This finding indicates that this part of the genome is deleted in the strain used for our experiments. 2. In the glycolytic input and immunoprecipitation samples we observed a strong accumulation in the genomic coverage of mapped reads from position 628,000 to 797,000.TrmBL1 ChIP-seq experiments were performed using crude extracts from formaldehyde treated in vitro and in vivo [Applying MACS2 we could identify in total 37 significantly enriched regions in the whole genome under gluconeogenic growth conditions  gene (PF1602) as a negative control  served as negative control for specific enrichment using the TrmBL1 specific antibody for immunoprecipitation [phosphofructokinase (pfk) gene was detected under both growth conditions  showed a strong ChIP-enrichment under both conditions. This demonstrates that the efficiency of formaldehyde crosslinking under both growth conditions was sufficient for successful ChIP experiments and that the absence of TrmBL1 binding events under glycolytic growth conditions using ChIP is specific for TrmBL1.We used ChIP-qPCR assays as an alternative method to verify some of the sequence enrichments of the ChIP-seq experiments. The data were normalized using the percent input method and the promoter region of the rol Fig.  and b. Apitation ,30. Usinin vitro and in vivo [P-value = 5.44E-11; Wilcoxon rank-sum test; AME). Additionally, scanning for this consensus signature throughout the whole P. furiosus genome identified in total 70 motif occurrences with a P-value less than 1E-5 (FIMO). 57 % can be connected to 30 ChIP-enriched regions, whereas 43 % are associated with further 29 sites . This indicates the high spatial resolution of the ChIP-seq approach, which was already described in previous reports [Previous studies showed that the TGM serves as palindromic DNA recognition element for TrmBL1 binding  in vivo ,11,15,20 in vivo . De-novo reports .Fig. 4TrP. furiosus grown on carbohydrates or peptides showed that 13 of 20 transcription units harbouring a TGM downstream of the corresponding promoters are downregulated under gluconeogenic growth conditions, whereas six of seven transcription units containing a TGM upstream of their promoters are upregulated under gluconeogenic growth conditions ; [glyceraldehyde-3-phosphate dehydrogenase  seems to be the only gene which exhibits promoter bound TrmBL1 under gluconeogenic conditions and which most likely plays a role in gluconeogenesis instead of glycolysis [Binding 28 promoter regions in the PF1933); ,56. Furtycolysis .P. furiosus (Table L-asparaginase (PF2047) or a transmembrane transporter of the major facilitator superfamily  and various genes encoding hypothetical proteins with unknown function . One newly identified binding site under gluconeogenic conditions is located upstream of the pyruvate-ferredoxin oxidoreductase (por) δ subunit gene (PF0967), which is part of a polycistronic operon transcribed from PF0971 to PF0965 [pyrolysin (PF0287) and a membrane dipeptidase (PF0874), which are participating in proteolysis.In addition to the known binding sites, our ChIP-seq analysis also revealed 14 novel TrmBL1 binding sites in the genome of o PF0965 . FurtherP. furiosus, which contain the TGM and which are located in close proximity to promoter regions. First of all, EMSAs were carried out to confirm specific binding of TrmBL1 to 15 selected putative binding regions (nine known and seven novel binding sites). These EMSA experiments clearly demonstrated binding of TrmBL1 to all tested templates  confirmed the presence of an additional promoter within the polycistronic operon of PF0971 to PF0965 , which may play a role in sugar uptake. In addition, the identified binding sites upstream of PF0967 and PF1476 pointed to a higher-ranking influence of TrmBL1 on transcriptional regulation: The first one is located within an operon transcribed from PF0971 to PF0965 [In vitro experiments confirmed that the binding of TrmBL1 represses transcription starting from the promoter upstream of PF0967  and the l-asparaginase (PF2047) and experimental confirmation is in perfect agreement with published data [The ChIP-seq data also revealed that some of the identified binding sites are located upstream of the promoter. A previous tivation . Thus, thed data ,54. In bhed data ,7.fructose-1,6-bisphosphatase gene  was detected in our study. Previous results showed TrmBL1 mediated activation of the transcription of this gene for P. furiosus and T. kodakarensis [P. furiosus genome confirmed the previously reported presence of a corresponding motif sequence in the PF0613 promoter region . Gene expression microarray analyses of P. furiosus cells, which were grown on a variety of glucans, revealed differential transcriptional responses to this different carbon sources [P. furiosus grown on carbohydrates or peptides [P. furiosus was grown in the presence of S0 with peptides for gluconeogenic and with maltose for glycolytic conditions. For the ChIP-seq experiment P. furiosus was grown in the absence of S0 with sodium pyruvate for gluconeogenic and with starch for glycolytic conditions. Furthermore, the methods are different: ChIP-seq gives a picture about TrmBL1 molecules bound to DNA and the microarray experiment provides information about quantified RNA molecules. Nevertheless, the ChIP-seq technique complements the microarray data and it increases the number of available global in vivo methods for the hyperthermophilic euryarchaeon P. furiosus to study gene regulatory networks in more detail. In the case of the TrmBL1 network it enabled confirmation of known targets of TrmBL1 mediated transcriptional control. The corresponding genes encode enzymes which participate in sugar uptake, glycolysis and gluconeogenesis. Furthermore, the identification of novel binding sites and the experimental verification clearly indicate that TrmBL1 is also involved in regulation of genes encoding enzymes involved in additional cellular processes e.g. proteolysis, amino acid metabolism, transcriptional control or metabolic pathways. The TrmBL1-regulated targets obtained from ChIP-seq are summarized in Fig. H. salinarium NRC-1. In this case TrmB plays an important role for sensing disposability of a carbon source and controlling the appropriate transcriptional response by its own or together with additional regulators [Unexpectedly, no binding of TrmBL1 to the promoter region of the karensis ,11. Addi sources ,64. Thispeptides . For thegulators ,65,66.FiWhile ChIP-seq became a widely used approach to study genome-wide protein-DNA interactions in bacterial and eukaryotic model organisms in vivo, it has been hitherto rarely applied in archaeal systems. Our ChIP-seq analysis of TrmB and TrmBL1 increased the number of available in vivo approaches to analyze gene regulatory networks in P. furiosus, which represents beside T. kodakarensis one widely used archaeal model organism within the order Thermococcales. In concert with the well-established in vitro assays of the P. furiosus transcription system, it represents a powerful tool, which can not only help to understand regulation of gene expression, but also to dissect the underlying mechanisms. This technique lead to two major findings: A, in the used P. furiosus strain `DSM3638´ a 16 kb fragment harboring the TM-system including TrmB was deleted. Thus, function of TrmB in regulation of sugar metabolism could not be studied using this strain; B, In contrast, using ChIP-seq for mapping of TrmBL1 binding sites in a genome wide manner for P. furiosus in vivo revealed an extended function of TrmBL1 as global regulator. TrmBL1 not only regulates genes involved in sugar metabolism, but it also controls transcription of genes involved in various additional metabolic pathways and biological processes as proteolysis or the amino acid metabolism www.ebi.ac.uk/arrayexpress) under accession number E-MTAB-3959. Further data are included as additional files.ChIP-seq raw data are available in the ArrayExpress database (


We tailored a chimeric regulator, termed Qλ, between the CI protein of the λ phage and the BzdR repressor from Azoarcus sp. strain CIB that responds to benzoyl‐CoA. When the Qλ was expressed in the appropriate Escherichia coli cells, it was able to reprogram the lytic/lysogenic λ phage decision according to the intracellular production of benzoyl‐CoA. Our results are also an example of how generating new artificial regulators that respond to effectors of choice may be useful to control different cellular processes.In this work, we explore the refactoring of the circuitry of  The XRE (xenobiotic response element) family of transcriptional regulators is the second most extended family of regulators in bacteria with an helix‐turn‐helix (HTH) DNA‐binding motif similar to that of the well‐characterized Cro protein of λ phage  lack the motifs involved in dimerization  and recognizes the inducer molecule benzoyl‐CoA alleviating BzdR repression on the target promoter  medium  and 5‐C2 .Plasmid pNLCI expressing the β‐galactosidase activities were measured using permeabilized cells as described by Miller  similar to that of control cells lacking the CI repressor, revealing that, as expected, the λNTCI protein is unable to repress the PR promoter. On the contrary, cells expressing the Qλ chimera exhibited a 10‐fold decrease in the β‐galactosidase activity (Fig. λ was repressing efficiently the PR promoter. When the E. coli cells expressing the Qλ chimera and the BzdA ligase were grown in the absence of benzoate, the PR promoter activity was inhibited (Fig. PR was observed when increasing concentrations of benzoate was added to the culture medium, reaching β‐galactosidase levels similar to those of the control cells lacking CI at benzoate concentration above 0.5 mmol/L (Fig. The tight repression of the ity Fig. , indicatted Fig. , but a sl/L Fig. .λ is able to repress the activity of the PR promoter (Fig. λNLCI lacks the motifs involved in dimerization and therefore, does not bind to PR (Di Lallo et al. λ chimera. It was suggested that the LCBzdR domain has a LID‐like region that suffers a significant conformational change in the presence of the benzoyl‐CoA inducer molecule, which would be then transmitted to the NBzdR domain through the linker region. This benzoyl‐CoA‐induced conformational change triggers a structural modification at the DNA‐binding surfaces of the protein without affecting its dimeric state, which would end with the release of the regulator from the target promoter (Durante‐Rodríguez et al. λ chimera controlling the PR promoter can be predicted (Fig. Analytical centrifugation and electron microscopy studies demonstrated that BzdR is a dimeric protein in solution (Durante‐Rodríguez et al. ter Fig. , and it ted Fig. .λ/PR regulatory couple becomes a new artificial regulatory system that responds to an unusual inducer molecule, benzoyl‐CoA, and it constitutes an interesting alternative to current conditional gene expression systems based on the CI repressor and the PR promoter.All these results allowed us to conclude that the Qλ is a functional protein that retains the activities predicted for its two constituent domains, namely recognition and binding to the target PR promoter by the N‐terminal λNLCI domain, and to the inducer molecule benzoyl‐CoA by the C‐terminal LCBzdR domain (Fig. λ chimera was used to refactor the lytic/lysogenic decision circuit of the λ phage using benzoyl‐CoA as the input signal of the engineered circuitry (Fig. λ device constitutes a molecular gate able to execute an ORN logic operation (Silva‐Rocha and de Lorenzo λ, the inducer benzoyl‐CoA and the target promoter PR, and the output is the induction of the lytic cycle except in the case of the presence of Qλ without the inducer benzoyl‐CoA (Fig. This work shows that the interkingdom chimera Qain Fig. . The Qλ try Fig. . In thisCoA Fig. .λ chimera, LCBzdR becomes a novel functional module that might be useful in the field of synthetic biology for engineering regulators à la carte that respond to benzoyl‐CoA, an inducer molecule that behaves orthogonal with respect to most microbial cells. Although this work has shown the value of the LCBzdR module by addressing the control of the λ PR promoter, one can foresee the fusion of this module to the DNA‐binding domain of a wide variety of transcriptional regulators that control the activity of promoters driving the expression of genes involved in many different cellular processes. These novel devices designed à la carte would be useful to reprogram crucial cell functions, but also for engineering novel conditional gene expression systems of biotechnological interest that respond to benzoyl‐CoA as the effector molecule.Modular experimental systems are needed to artificially control biological networks. As demonstrated here with the QNone declared.


The hierarchical levels of genome architecture exert transcriptional control by tuning the accessibility and proximity of genes and regulatory elements. Here, we review current insights into the trans-acting factors that enable the genome to flexibly adopt different functionally relevant conformations. In its untangled, unfolded and completely linearized state, the human genome has a length of ~2 m. To fit it into a nucleus with a diameter of ~10 μm, DNA is wrapped around histone octamers, creating strings of nucleosomes that can be further organized into higher-order levels of compaction –5, whichTo exert stimulatory or repressive effects on transcription, accessible regulatory DNA elements must be in close spatial proximity to susceptible genes. Enhancers promote transcription by providing a binding platform for transcription factors  that canChromosomes are structured such that domains with a similar chromatin signature cluster spatially, a phenomenon first appreciated by traditional microscopy studies. Centromeres and flanking pericentromeric repeat regions of different chromosomes aggregate and form microscopically visible chromocenters in interphase nuclei . SimilarStudies using a derivative of chromosome conformation capture (3C) known as ‘Hi-C’ have revealed that long-range genomic contacts segregate TADs into an active (A) and inactive (B) compartment . Based oTo evaluate these issues, it is important to keep in mind how chromosome folding changes during cell division. Spatial genome organization is generally studied in non-synchronous cells, of which interphase cells make up the biggest proportion. In interphase nuclei, chromosomes are decondensed and organized hierarchically into the transcriptionally relevant structures described above. To prepare for cell division, chromosomes untangle and condense, while transcription ceases almost entirely. Mitotic chromosomes no longer show preferential higher-order contacts or compartmentalized TAD-based organization , and it As can be expected from stochastically reshuffled chromatin, inter-TAD and inter-chromosomal contacts showed high levels of variation between cells in a single-cell Hi-C experiment . MoreoveA chromatinized DNA fiber is assumed to behave essentially as a polymer, with a certain flexibility that allows random collisions between regions of the chromatin fiber. The likelihood for two sites to autonomously find each other in nuclear space decreases when their linear distance increases , 61. TheThe loops formed between TAD boundaries seem to exemplify the longest-range contacts that are stably and reproducibly formed between specific pairs of sequences. Although the mechanisms that underlie the looping of TAD boundaries are largely unknown, numerous reports have identified transcriptional repressor CTCF and the cohesin complex at the sites that anchor these loops , 18, 62.Cohesin is a protein complex that forms a large ring-like structure to hold the sister chromatids together after DNA replication. In recent years, cohesin has also been found to bind to chromatin in post-mitotic cells –74. CoheHox gene cluster allowed active chromatin marks to expand into a normally repressed domain [Depletion of CTCF through knockdown resulted in an increased inter-TAD contact frequency, whereas intra-TAD contact numbers were reduced . By contd domain . In summShh gene and its posterior limb-bud enhancer, which are located 1 Mb away from each other at opposite ends of a TAD, exist in such a pre-formed looped configuration that is stable throughout development and that is maintained even after deletion of the enhancer [Shh expression to ectopic sites elsewhere in the developing limb bud [Currently, two types of enhancer-promoter loops are distinguished: pre-established loops and loops formed de novo, or permissive and instructive conformations, respectively . Pre-forenhancer . Mutatiolimb bud , demonstlimb bud , 87. Thelimb bud . Bookmarlimb bud  in unrellimb bud .A recent study provided a first systematic insight into the genome-wide pervasiveness of each loop type across a series of cultured cell lines. While the majority of loops appeared conserved among most of the assessed cell lines and between species, hundreds of tissue-specific enhancer-promoter loops were also uncovered, which nearly always corresponded with strongly increased transcriptional output of the gene involved . FormatiFactors such as CTCF and cohesin seem to be major contributors to the formation and architecture of TADs, whereas other factors appear to be involved in the segregation of TADs into nuclear subcompartments containing similar types of chromatin domains. The rules that govern the relative positioning of TADs in the interphase nucleus must be considered in the context of the genome adopting an energetically favorable conformation upon unfolding after exit from mitosis. Because TADs are parts of much larger chromosomes, the engagement of stable inter-TAD contacts by one TAD imposes constraints on the sampling space of its neighboring TADs. Some regions, in particular the (peri-)centromeric parts of the chromosomes and the ribosomal DNA (rDNA) gene clusters, appear relatively dominant in determining their preferred genomic neighborhood because they find each other in nearly every cell. Others, which might include the olfactory receptor gene clusters and the PcG-bound regions, also retain some autonomy in choosing partners to contact in the nuclear space. Because of this, most of the remaining TADs (and genes) must passively adapt to the resulting configurations . In a prSwitches between A and B compartments occur for at least a third of the genome during early development, often in a lineage-restricted fashion . The obsIf not transcription, what is it that keeps active TADs together? Principles similar to those underlying local chromatin loop formation might well drive spatial juxtapositioning of TADs and set up tissue-invariant as well as tissue-specific higher-order topologies. Promoters marked by trimethylation on lysine 4 of histone 3 (H3K4me3) co-localize not only within TADs but also in the larger nuclear space in a largely tissue-invariant manner , 99, 100Loops, domains, and compartments define the shape of the genome, and all topological levels contribute to the functioning of the genome. Domain organization seems conserved and exhibits an invariance that is remarkable given the observation that TADs are not detected during mitosis . DespiteAt each level of structural organization, chromatin-associated factors shape the genome. CTCF and cohesin play important roles in chromatin looping—they anchor loops that create chromosomal domains (TADs) and loops that recruit enhancers to their target genes. CTCF might exert its action through self-dimerization or through recruiting cohesin. The observation that loops preferably form between convergent CTCF binding sites Fig.  might ha


Expression of lrp1 is confined to early root primordia and meristems and is auxin-inducible. Based on its primary protein structure, LRP1 is predicted to be a transcription factor. This notion is supported by exclusive LRP1 localization in the nucleus and its ability to activate downstream gene activity. Based on the observation that lrp1 transcription is completely repressed in the semi-dominant gain of function mutant rum1, it was demonstrated that the lrp1 promoter is a direct target of RUM1 proteins. Subsequently, promoter activation assays indicated that RUM1 represses the expression of a GFP reporter fused to the native promoter of lrp1. Constitutive repression of lrp1 in rum1 mutants is a consequence of the stability of mutated rum1 proteins which cannot be degraded by the proteasome and thus constitutively bind to the lrp1 promoter and repress transcription. Taken together, the repression of the transcriptional activator lrp1 by direct binding of RUM1 to its promoter, together with specific expression of lrp1 in root meristems, suggests a function in maize root development via the RUM1-dependent auxin signalling pathway.Only little is known about target genes of auxin signalling downstream of the Aux/IAA-ARF module. In the present study, it has been demonstrated that maize  Zea mays L. exhibits a complex root stock architecture which comprises embryonically formed primary and seminal roots and postembryonic lateral and shoot-borne roots  proteins are involved in auxin signal transduction by interacting with ARF (Auxin Response Factor) proteins. These Aux/IAA–ARF complexes regulate the transcription of early auxin-responsive genes such as Aux/IAAs, SAURs, and GH3s by ARF binding to their auxin-responsive elements (AuxREs) in their promoters  proteins in bidopsis . Arabidoructures . SWP1, wlrp1 activity in maize is regulated by binding of the Aux/IAA protein RUM1 to the lrp1 promoter. Subsequent analyses demonstrated that LRP1 functions as a transcriptional activator of downstream gene expression which is in line with its localization in the nucleus. In summary, the auxin-inducible LRP1 protein is involved in maize auxin signal transduction downstream of rum1 which regulates the initiation of lateral and seminal roots.In the present study it has been demonstrated that Seeds of the maize inbred line B73 were germinated in paper rolls as previously described  and LA-Taq Polymerase (TaKaRa) following the manufacturer’s guidelines. The housekeeping gene actin1 (Genebank AC: AY104722) was used as standard with the oligonucleotide primers Actin-fw and Actin-rv (see Supplementary Table S1 at JXB online). All PCR experiments were repeated in four biological replicates to conﬁrm the reproducibility of the results.Semi-quantitative RT-PCR experiments were performed with RNA extracted from pools of primary root samples. For root-type-speciﬁc expression studies in the wild-type, lrt1  and rum1Lrp1 transcripts were assayed relative to myosin  were used to analyse these gene expression patterns (see Supplementary Table S1 at JXB online).For qRT-PCR experiments, total RNA was extracted from pools of different root tissues and subsequently treated with RNase-free DNaseI as previously described .Transcript abundance of lrp1–GFP plasmid, the open reading frame of lrp1 was PCR amplified from the GAL4DB-LRP1 plasmid (Lab AC: 761) using ZmLrp1-KpnI-fw and ZmLrp1-BspHI-rv, and then introduced into the plant transformation vector CF203 at the restriction sites KpnI and BspHI  yielding a construct containing a constitutive cauliflower mosaic virus (CaMV) 35S promoter at the 5′ end of the coding sequence of lrp1 and a 3′ in-frame GFP sequence followed by an rbcs E9 terminator (Lab AC: 755). The subcellular localization experiment was performed by transiently transforming the plasmid 35S::ZmLrp1–GFP into Arabidopsis Col-0 protoplasts grown in suspension culture for 3 d in the dark. Protoplasts were generated according to In order to construct the maize lrp1 was amplified by nested PCR with oligonucleotide primers ZmLrp1-luc-fw, ZmLrp1-luc-rv and ZmLrp1-luc-SmaI-fw, ZmLrp1-luc-KpnI-rv from cDNA of 5-day-old maize primary roots (see Supplementary Table S1 at JXB online). These sequences were subsequently introduced into the control effector at the SmaI and KpnI sites (Lab AC: 761). The reporter, effector, and reference plasmids were co-transformed into Arabidopsis Col-0 protoplasts (The control effector vector containing the GAL4 DNA binding domain (Lab AC: 1002), the reporter vector with firefly luciferase , and the reference reporter vector with Renilla luciferase (Lab AC: 999) were constructed as previously described  via a TriStar multimode microplate reader LB 941 . Measurement of LUC activity was repeated three times for each transformant and LUC values were normalized with the internal control Renilla LUC values. Each transformation was independently repeated three times.in situ hybridization probes were cloned into the pGEM-T Easy vector (Promega) and ampliﬁed using a combination of a gene-speciﬁc and a M13 forward or M13 reverse primer, respectively. All probes were transcribed using an in vitro transcription kit containing digoxigenin-labelled UTP (Roche). In situ hybridization experiments were performed according to Root samples were ﬁxed in 4% formaldehyde in phosphate-buffered saline overnight, dehydrated in an increasing ethanol series, and embedded in parafﬁn wax . Tissue sections (7 μm) were prepared using a Leica rotary microtome 2035 and transferred on Superfrost Plus slides (Microm). Templates for all lrp1 with the oligonucleotide primers ZmLrp1-EMSA-fw and ZmLrp1-EMSA-rev from pZmLrp1-pGEM (Lab AC: 387) and subcloned into pGEM-T easy (Lab AC: 496). EMSA experiments were performed as described in the Promega technical bulletin TB110 (www.promega.com/tbs/tb110/tb110.pdf). The 75bp probe used for the DNA-protein binding reaction was labelled with [γ-32P]-ATP  with a T4 polynucleotide kinase . 30 μg of the RUM1 raw protein extract containing recombinant GST-RUM1 fusion proteins were incubated with [γ-32P]-ATP-labelled DNA fragments and 1 μg of poly-(dI-dC) in 10× buffer  in a total volume of 30 μl. The reaction product was analysed on a 4% non-denaturing polyacrylamide gel. The specificity of GST-RUM1 binding was controlled by using 50× excess of the specific competitor (unlabelled target sequence) and λ-DNA (Fermentas) as the unspecific competitor, respectively.A 75bp probe containing an AuxRE motif in the central position was amplified from the 2kb promoter sequence of lrp1 were amplified by PCR with oligonucleotide primers pZmLrp1-XbaI-fw and pZmLrp1-XhoI-rv (see Supplementary Table S1 at JXB online) from pZmLrp1-pGEM (Lab AC: 387) using Pfu DNA Polymerase (Fermentas) and cloned into the GFP reporter vector . The full-length open reading frame of rum1 was cloned into the binary vector pUC-SPYCE which contains a C-terminal c-Myc-tag as previously described (pZmLrp1-pGTKan was co-transformed with 20 μg of effector vector RUM1-SPYCE or blank-SPYCE (The promoter fragments containing AuxRE of Arabidopsis SHORT INTERNODES-RELATED SEQUENCE (SRS) gene family comprises ten members. Among those, the LRP1 gene encodes a protein that is expressed during early lateral primordia formation. To gain a comprehensive overview of this plant-specific gene family of transcription factors in maize, the Arabidopsis LRP1 protein sequence (Genbank AC: AT5G12330) was used as a query for homology searches in maizegdb.org. As a result, nine SHORT INTERNODES-RELATED SEQUENCE (SRS) proteins designated LRP1 and LRP1-Like1 (LRL1) to LRP1-Like8 (LRL8) were identified (see Supplementary Table S2 at JXB online). All nine maize genes were assigned to the two maize subgenomes which emerged as a consequence of a whole genome duplication 5–12 million years ago. Hence, all members of the maize gene family were already present in the maize genome before the last whole genome duplication (www.skraelingmountain.com/datasets/maize_indexed_by_subgenome.csv). Maize lrl1, lrl3, lrl4, lrl6, and lrl8 were assigned to subgenome 1, while lrp1, lrl2, lrl5, and lrl7 were assigned to subgenome 2. Among the nine genes, three pairs of paralogues were identified (see Supplementary Table S2 at JXB online).The Arabidopsis and maize protein families phylogenetic reconstructions were performed . By contrast, expression in young primary roots of 1–2cm length was significantly lower than in all other tissues. Finally, expression in seminal roots was significantly higher than in all analysed stages of primary root development but significantly lower than expression in crown roots. In summary, primary, seminal, and crown roots displayed discrete expression levels that distinguished between these root types. Lateral roots displayed a similar expression level as seminal roots that was significantly higher than 1–2cm primary roots but lower than crown roots.Root-type and development-specific expression patterns of maize ot types . Expresslrp1 in more detail, in situ hybridization experiments were performed in postembryonic lateral roots and crown roots. These root types were selected because the formation of these roots can be observed after germination, while primary and seminal roots are formed early during embryo development deep inside the maize seed. In both root types, expression of lrp1 was confined to early root primordia and meristems  5′-TGTCTC-3′ (once) and 5′-TGTC-3′ (three times)  . Auxin-iμM 1-NAA . The expArabidopsis Col-0 protoplasts were performed. LRP1–GFP proteins were exclusively localized in the nucleus , and the LRP1-C terminal domain, which is predicted to be a protein-protein interaction domain , suggest nucleus . By cont nucleus .Arabidopsis protoplasts. The effector plasmids consisted of the yeast GAL4 DNA binding domain (GAL4DB) as a control or the GAL4DB fused in-frame with the coding sequence of lrp1 (GAL4DB-LRP1) driven by a dual 35S promoter  experiment with recombinant GST-tagged RUM1 was performed (lrp1 containing an AuxRE (Auxin Responsive Element) motif in a central position  and cotransfected with RUM-effector or Blank-effector constructs . It was demonstrated that the presence of RUM1 repressed the expression of the GFP reporter fused to the native lrp1 promoter by 42% relative to the control which was arbitrarily set at 1  family of plant-specific transcription factors comprises ten members  to lrl8 (see Supplementary Table S2 at JXB online).The  members . Among tormation . Homologlrp1-like gene family, three pairs of paralogous genes (66% of the gene family members) have been retained, while for three additional genes (33% of the gene family members) one paralogue was lost by partial fractionation (see Supplementary Table S2 at JXB online). Similarly, in the larger Aux/IAA gene family of maize, seven pairs of paralogues have been retained (52% of ancient genes) in addition to 13 genes (48% of ancient genes) assigned to a subgenome without a paralogue  genes assigned to a subgenome without having a paralogue belonged to subgenome 1. Similarly nine of 14 such Aux/IAA genes of maize (64%) were assigned to subgenome 1.About 5–12 mya maize underwent a whole genome duplication which led to the emergence of two subgenomes designated maize 1 and maize 2  maize lrp1-like genes it was possible to determine the Arabidopsis homologue .Supplementary Table S2. Characteristics of the lrp1-like gene family in maize .Supplementary Table S3. Statistical analysis of differential lrp1 gene expression in various root types according to


Xenopus embryos, the three TBP family factors are all essential for development and are required for expression of distinct subsets of genes. Here, we report on a non-canonical TBP family-insensitive (TFI) mechanism of transcription initiation that involves mesoderm and organizer gene expression. Using TBP family single- and triple-knockdown experiments, α-amanitin treatment, transcriptome profiling and chromatin immunoprecipitation, we found that TFI gene expression cannot be explained by functional redundancy, is supported by active transcription and shows normal recruitment of the initiating form of RNA polymerase II to the promoter. Strikingly, recruitment of Gcn5 , a co-activator that has been implicated in transcription initiation, to TFI gene promoters is increased upon depletion of TBP family factors. TFI genes are part of a densely connected TBP family-insensitive T-box-Otx2-Gsc interaction network. The results indicate that this network of genes bound by Vegt, Eomes, Otx2 and Gsc utilizes a novel, flexible and non-canonical mechanism of transcription that does not require TBP or TBP-related factors.Embryonic development relies on activating and repressing regulatory influences that are faithfully integrated at the core promoter of individual genes. In vertebrates, the basal machinery recognizing the core promoter includes TATA-binding protein (TBP) and two TBP-related factors. In  Highlighted article: A network of embryonic genes, many of which are expressed in the mesoderm and the organiser, can initiate transcription through a non-canonical mechanism. The gene expression patterns underlying embryonic development are orchestrated by highly complex gene regulatory networks. Compared with single-cell eukaryotes, metazoans have expanded repertoires of protein-coding genes involved in transcriptional regulation to support these networks , but howDrosophila and has only been found in insects  and TBP-associated factors (TAFs). In this canonical mechanism of transcription initiation TBP binding represents a rate-limiting step before the recruitment of RNA polymerase II (RNAPII) to the core promoter of protein-coding genes . However insects . In vert insects . TLF is in mouse . TBP2, win mouse . Core inin mouse . TBP2 rein mouse . TBP is in mouse . TBP, TLin mouse .in vitro  of early blastula (stage 7) and early gastrula (stage 10.5) embryos, with additional filtering for more than 2.8-fold (log2 1.5) change in expression between these stages. Strikingly, among these developmentally activated transcripts, a total of 180 were not affected by ablation of TBP, TLF or TBP2 (Table S1), raising the possibility that some transcripts do not require these factors for the rate-limiting step of transcription initiation.TBP, TLF and TBP2 are all essential for gastrulation and for transcription of partially overlapping subsets of genes in  embryos . We aske embryos , specifi embryos A. Early vegt, which is expressed both maternally and zygotically .To test whether the transcripts involved were actively transcribed, α-amanitin was injected into fertilized eggs to inhibit RNAPII. Embryonic transcription is required for the onset of gastrulation  and its otically , was rednscripts D. Almostnscripts A or werenscripts D. This sTogether, these results indicate that a subset of actively transcribed developmental genes do not require normal levels of TBP, TLF or TBP2 for transcription. However, these experiments were performed with individual knockdowns of each of the TBP family members, raising the question whether TBP family members could act redundantly.tbp, tbp2 and tlf antisense oligonucleotides. We used DMED-modified oligonucleotides that lead to RNaseH-mediated degradation of the targeted mRNA . The full set of TFI genes was hardly affected by TBP family TKD . At a false discovery rate of 10%, only four TFI genes were decreased . The finding that TFI genes are robustly transcribed under TKD conditions suggests that none of the TBP-related factors are required for the rate-limiting step of transcription of these genes and that functional redundancy of TBP family of initiation factors does not play a major role in this process.To test possible redundant functions of TBP, TBP2 and TLF in the transcription of TFI genes, we depleted all three family members by microinjecting a combination of ted mRNA . The speted mRNA . Morpholted mRNA A. We ver RT-qPCR C. By conmily TKD D, with tfgf8 and spry2 but moderately decreased at genes such as zic1 and gsc. Assessing RNAPII recruitment using an antibody recognizing the unphosphorylated CTD domain of RNAPII did not uncover altered RNAPII recruitment to TFI genes in TKD embryos . Concordantly, analysis of RNAPII pausing at TFI orthologues using X. tropicalis RNAPII ChIP-seq data . Together, the results did not reveal a role for post-initiation regulation in TFI transcription but rather highlighted the fact that the initiating form of RNAPII can be robustly recruited at TFI genes under TKD conditions.A prominent role has been identified for promoter-proximal pausing of RNAPII in eukaryotic gene regulation . This raseq data  did not goosecoid (gsc), otx2, foxd3, notochord homeobox (not), zic1, noggin (nog), spry2, admp, eomesodermin (eomes) and vegt. Therefore, we investigated the functional characteristics of the TFI genes. We assessed the spatial localization of TFI gene transcripts using available transcriptome datasets of dissected embryonic tissue of early gastrula (stage 10) embryos, including dorsal blastopore lip , ventral marginal zone , animal cap  and the central part of the yolk plug  (2 1.5) higher at the animal pole compared with the vegetal pole. Of these transcripts 12 were TFI , and at the dorsal blastopore lip eight transcripts were enriched relative to the ventral marginal zone . By contrast, no TFI gene transcripts overlapped with the 43 transcripts that were more highly expressed at the ventral marginal zone compared with the dorsal blastopore lip (nog-dkk1)-induced transcripts, which represent transcripts induced by an ectopic organizer . Also, an extended organizer cluster (Table S3). TFI genes were enriched in functional categories linked with dorso-ventral neural tube patterning, negative regulation of muscle development, induction of organ formation, regulation of transcription, chromatin assembly and DNA-protein complex assembly. This illustrates that, apart from mesoderm and organizer gene expression, TFI genes also contribute to other developmental processes.We noticed that many TFI gene transcripts have developmental functions in both mesendoderm specification and the Spemann-Mangold organizer, including well-known genes such as vegetal) . Among 1pore lip A. This organizer . Four cl cluster  was enri cluster B. To chain vitro and is recruited to promoter histone modifications . To examine the role of Gcn5 in TFI gene expression we investigated Gcn5 binding by ChIP using two different Gcn5-specific antibodies , Gcn5 protein was depleted from promoters in antisense-injected embryos compared with controls using ChIP analysis  but involution was affected and the embryos entered developmental arrest . To assess the specificity of Gcn5 knockdown (KD), we carried out rescue experiments using in vitro-transcribed mRNA encoding the human protein. The results showed that the phenotype of antisense-injected embryos can be attributed to knockdown of gcn5 . Moreover, the phenotype could also be rescued using Gcn5 with a mutated HAT domain, suggesting that HAT activity is not required for early development .In l arrest D with siTable S4). Among decreased transcripts [125 at false discovery rate (FDR) 0.1] are those associated with gene ontologies of chromatin modifications , regulation of actin filament polymerization, ubiquitin-dependent degradation and glycogen metabolism . Among increased transcripts (40 at FDR 0.1) only regulation of transcription was a significant gene ontology (Table S6), notably contributed to by the TFI transcription factor genes gsc and not. In addition, three other TFI genes were upregulated in Gcn5-KD embryos, representing a small but highly significant overlap . Moreover, transcripts affected by Gcn5-KD and TKD showed similar responses under these conditions  and transcripts upregulated by Gcn5-KD also increased in TKD embryos . These data demonstrate that Gcn5 is important for early embryonic gene transcription, but do not support a model of obligatory and non-redundant TFI transcription initiation by Gcn5.To determine how embryonic transcription is changed by the knockdown of Gcn5, we generated transcriptome profiles of early gastrula (stage 10.5) control and Gcn5-KD embryos in duplicate by RNA sequencing . In control embryos, Gal4-VP16 activated transcription vigorously . Strikingly, in TKD embryos, VP16 activation also occurred, albeit with some delay. When basal transcription was analyzed , reporter expression levels appeared to be significantly higher in TKD embryos than in controls, similar to some of the TFI gene transcripts  and transcription driven by a strong activator.Gcn5 has been implicated in targeting activator proteins to the promoters of inducible genes , hence win yeast . Althougnscripts C. This rFig. S3B). Strikingly, Gcn5 showed the opposite pattern with more than 7-fold stronger binding to the promoter in TKD embryos compared with control embryos. Moreover, robust histone acetylation was detected in both samples. These results show that both basal and activator-dependent transcription can occur under TKD conditions and that compensatory recruitment of Gcn5 might occur in the absence of TBP and TBP-related factors.To relate transcription levels to promoter binding, we carried out ChIP-qPCR experiments to detect TBP and Gcn5 at the promoter under VP16-activated conditions. Additionally, we quantified acetylated histone H3 and histone H4 in control and TKD embryos. The promoter was bound by TBP and relatively little Gcn5 in control embryos. TBP binding was abolished in TKD embryos A, as expgsc, fgf8 and eomes is significantly higher in TKD embryos than in water-injected controls. Other TFI genes recruit Gcn5, but binding was either unaffected by TKD or decreased. The TBP-dependent mark3 gene recruited some Gcn5 but this was unchanged upon TBP family depletion, similar to spry2. TBP binding was strongly reduced in TKD embryos.We asked whether a similar compensatory binding is observed at endogenous TFI promoters under TKD conditions. We analyzed Gcn5 binding in TKD embryos and compared it with controls. We confirmed the expected loss of TBP binding in TKD embryos B. The reP-value 9.3×10−13, Fig. S4A). It has been reported that the T-box binding factors T (Xbra), Vegt and Eomes, which are expressed in the marginal zone, are co-recruited at the regulatory regions of target genes . Furthermore, Vegt, Otx2 and Gsc form a highly interconnected network that displays all possible mutual interactions between these factors and the genes encoding them, with intertwined putative auto-regulatory, feed-forward and multi-component circuitry . Downstream TFI genes show a higher degree of coordinated binding; many are bound by four, five or six transcription factors . TFI genes tend to be upregulated in gsc morphant embryos . The effects of combined Lhx1, Otx2 and Otx5 knockdown (only otx2 is a TFI gene) are less clear. Whereas organizer-expressed TFI genes gsc, foxa4 and admp are expressed at lower levels in the triple morphant (lhx1/otx2/otx5) embryos, foxd3, not, rhob and otx2 itself are upregulated . Additional interactions, possibly including those mediated by other TFI transcription factors, might explain these non-parsimonious gene regulatory relationships. Together, the data uncover a TFI gene network centered on putative auto-regulatory and multicomponent circuitry of T-box, Otx2 and Gsc binding; the majority of the TFI genes bind these TFI transcriptional regulators.To further assess the contribution of transcriptional regulators to TFI transcription, we examined the involvement of TFI genes in the gene regulatory network of mesendoderm specification . Strikinet genes . Also thquencing . Four ofircuitry A. TFI ge factors A,C. We c factors  on TFI gin vitro, TBP binding is a rate-limiting step for transcription . We have not determined whether Gcn5 binds as a complex to TFI promoters, but the results suggest that the SAGA complex, which is structurally similar to TFIID , as well as additional TFIIA-like and TAF-like factors , 2014. Icription . There acription , whereascription . Apart faffected D. Howeveaffected . Even thaffected . This suto TFIID , could pto TFIID . In yeasto TFIID . Our GcnFig. S4). It should be noted that these TFI transcription factor genes are expressed in spatially overlapping domains, with the T-box genes mainly expressed in the marginal zone , and otx2 and gsc expressed in the organizer. In this genomic interaction network, no attempt has been made to infer activating or repressive influences. T-box factors tend to activate mesodermal target genes  were used for in vitro fertilization. All procedures were performed after obtaining approval from the Radboud University Ethics Committee for Experimental Animal Research (Ru-dec 2014-122).Outbred gcn5 (kat2a) mRNA, a DMED-modified oligonucleotide Gcn5-AS[BJ220], antisense to position 220-237 of the BJ072879 EST, was designed: 5′-T+C+A+A+A+CACAAGC+C+G+G+G+T+T-3′ (+ denotes DMED-modified linkages). 0.8 ng of Gcn5-AS[BJ220] was used for knockdown. In rescue experiments, mRNA transcribed from pcDNA3.1-Myc-His-hGCN5 was used (In situ TUNEL (Tdt-mediated dUTP nick end labeling) analysis for detection of apoptosis was performed in whole mount as described  was performed using TM4 MeV (http://www.tm4.org/) (RNA was isolated using Trizol (Life Technologies) and RNeasy columns (Qiagene). Reverse transcription was performed with Superscript II (Life Technologies) and cDNAs were measured using iQ SYBR Green Supermix and a C1000 thermal cycler CFX96 reader system (Bio-Rad). For microarray analysis, 10 µg total RNA was processed with Affymetrix one-cycle kit. Labeling and hybridization was done according to Affymetrix GeneChip instructions. Microarray data were scaled with GeneChip Operating Software (GCOS) by comparing samples with stage 10.5 control embryos and transferred to Spotfire Decision Site 7.3 for analysis. K-means clustering (m4.org/) .X. laevis genome assembly JGI9.1, downloaded from Xenbase  was performed as described previously . Antibodin vitro-transcribed mRNAs  to express a fusion protein of the Gal4 DNA-binding domain and the VP16 activation domain  or Gal4 DNA-binding domain  to obtain activating and non-activating conditions on 0.15 ng of a co-injected DNA template containing an HSV-tk promoter with five Gal4 binding sites. CAT reporter transcripts were measured using RT-qPCR.Embryos at 1-cell stage were injected with 0.3 ng


Sulfolobus acidocaldarius that activates the expression of a β-alanine aminotransferase gene, which is involved in β-alanine degradation. In contrast to classical Lrp-like transcription factors, BarR is not responsive to any of the α-amino acids but interacts specifically with β-alanine. Besides the juxtaposed β-alanine aminotransferase gene, other regulatory targets of BarR have not yet been identified although β-alanine is the precursor of coenzyme A and thus an important central metabolite. The aim of this study is to extend the knowledge of the DNA-binding characteristics of BarR and of its corresponding regulon from a local to a genome-wide perspective.The Leucine-responsive Regulatory Protein (Lrp) family is a widespread family of regulatory transcription factors in prokaryotes. BarR is an Lrp-like transcription factor in the model archaeon We characterized the genome-wide binding profile of BarR using chromatin immunoprecipation combined with high-throughput sequencing (ChIP-seq). This revealed 21 genomic binding loci. High-enrichment binding regions were validated to interact with purified BarR protein in vitro using electrophoretic mobility shift assays and almost all targets were also shown to harbour a conserved semi-palindromic binding motif. Only a small subset of enriched genomic sites are located in intergenic regions at a relative short distance to a promoter, and qRT-PCR analysis demonstrated that only one additional operon is under activation of BarR, namely the glutamine synthase operon. The latter is also a target of other Lrp-like transcription factors. Detailed inspection of the BarR ChIP-seq profile at the β-alanine aminotransferase promoter region in combination with binding motif predictions indicate that the operator structure is more complicated than previously anticipated, consisting of multiple (major and auxiliary) operators.S. acidocaldarius. Furthermore, this work reveals that the BarR regulon overlaps with that of other Lrp-like regulators.BarR has a limited regulon, and includes also glutamine synthase genes besides the previously characterized β-alanine aminotransferase. Regulation of glutamine synthase is suggestive of a link between β-alanine and α-amino acid metabolism in The online version of this article (doi:10.1186/s12864-016-2890-0) contains supplementary material, which is available to authorized users. Sulfolobus spp. and Halobacterium salinarum NRC1, thereby unravelling the regulon and physiological role of these factors [Microorganisms sense and respond to environmental perturbations by a variety of gene regulatory mechanisms, of which regulation by transcription factors is a major mechanism. Archaea, which constitute a prokaryotic phylogenetic domain distinct from Bacteria, are characterized by a eukaryotic-like basal transcription machinery and bacterial-like regulatory transcription factors . Recentl factors –9.lrp-type genes is restricted to only half of the bacterial genomes [lrp-type genes with an average of five paralogs per genome [One of the most abundant and best characterized regulatory transcription factor family in archaea is the bacterial/archaeal Leucine-responsive Regulatory Protein (Lrp) family , also kn genomes , all arcr genome  suggestir genome . This isr genome , 13–17, r genome , 17.Members of the Lrp family consist of approximately 150 amino acids and are characterized by an amino-terminal helix-turn-helix (HTH) DNA binding domain and a carboxy-terminal αβ sandwich oligomerization and ligand response domain, called “Regulation of Amino acid Metabolism” (RAM) domain, which are connected by a flexible linker region , 12. LrpSulfolobus solfataricus and Halobacterium salinarum, a large overlap was observed in the DNA-binding locations of two or more Lrp-like transcription factors [Pyrococcus Lrp-like transcription factors [Just like their bacterial counterparts, archaeal Lrp-family transcription factors are either local regulators, involved in the regulation of a limited number of adjacently located genes , 19 and/ factors , 8, demo factors , 20, or  factors .Sulfolobus acidocaldarius with a non-proteinogenic amino acid ligand [barR gene resulted in a decreased exponential growth rate in the presence of exogenous β-alanine in the growth medium. Furthermore, gene expression analysis demonstrated that BarR activates the expression of the adjacent aminotransferase gene, but only upon β-alanine supplementation. In contrast, BarR auto-activates the expression of its own gene in a β-alanine independent manner. Heterologously produced BarR protein displays an octameric state in solution and forms a single nucleoprotein complex by interacting with multiple sites in the 170-bp long intergenic region separating the barR and aminotransferase gene. In vitro, DNA binding is specifically responsive to β-alanine upon direct interaction of this amino acid with the ligand-binding pocket [BarR is an Lrp-type transcription factor in d ligand . Indeed,d ligand . DeletioSulfolobus spp. demonstrate that there is an overlap in the regulon of BarR and of other Lrp-like factors.Previously, we have focused only on the study of local interactions and regulatory effects of BarR in the genomic neighbourhood of its own gene . Here, wSulfolobus acidocaldarius was cultured while continuously shaking at 75 °C in Brock medium [S. acidocaldarius DSM639 was used, S. acidocaldarius MW001 [barR [k medium  supplemeus MW001  and MW0001 [barR  were groS. acidocaldarius DSM639 was cultured while continuously shaking at 75 °C in Brock medium supplemented with 0.2 % casamino acids, 0.2 % sucrose, 0.02 mg/ml uracil and if mentioned, with 10 mM β-alanine. Crosslinked and sheared DNA was prepared from 200 ml cultures grown until reaching an optical density (OD600 nm) of 0.3 as described before [Sulfolobus spp. cells were cooled down before performing formaldehyde crosslinking at a constant temperature of 37 °C, here crosslinking was performed immediately after the culture was taken out of the incubator at 75 °C [Additional file ChIP-seq analysis was performed for biological duplicates. d before  with theS. acidocaldarius DSM 639 genome (NC_007181.1) with Burrows-Wheeler Aligner (BWA 0.7.10) [−8), followed by a manual curation. ChIP-seq results were visualized by IGV version 2.3.2 [ChIP was performed with polyclonal anti-BarR rabbit antibodies, which were previously validated for specificity , using D 0.7.10)  with def 0.7.10)  was usedon 2.3.2 . DNA seqon 2.3.2 . All rawon 2.3.2 .Escherichia coli and purified from inclusion bodies as described before [32P and using S. acidocaldarius genomic DNA as a template. Probes were designed to harbour the predicted binding motif. EMSAs were performed as described previously [Recombinant His-tagged BarR was overexpressed in d before . Electrod before  of whicheviously . All binS. acidocaldarius MW001 and S. acidocaldarius MW001ΔbarR cultures using an RNeasy mini kit (Qiagen). Residual genomic DNA was removed by treatment with Turbo DNase (Ambion) according to manufacturer’s instructions. First-strand cDNA was synthesized from 1 μg RNA with a SuperScript III First-Strand Synthesis SuperMix kit (Invitrogen). Primers [Additional file Saci_0691 (encoding RNA polymerase subunit A) and Saci_1336 (encoding TATA binding protein). A paired t-test was performed to validate differential expression.Total RNA was isolated from exponentially growing S. acidocaldarius genome. Upon sequencing the input samples, no obvious bias was observed with the read count evenly distributed across the genome . Genes located in the direct neighbourhood of the peaks have a variety of functions, including amino acid metabolism  and sugar metabolism (gluconolactonase). Our analysis did not reveal binding in the neighbourhood of a malonate semialdehyde dehydrogenase gene (Saci_1700), which catalyzes the second step in β-alanine degradation and is genomically co-localized with and regulated by the orthologous gene/protein in Sulfolobus tokodaii [The largest fraction of the BarR binding loci are exclusively located in intragenic regions and moreover, besides the ene Saci_00, whichbarR/Saci_2137 intergenic region, in which BarR interacts with multiple regularly spaced binding sites [The interaction between BarR protein and in vivo bound genomic regions was validated in vitro by employing EMSAs for a selection of eight high-enrichment ChIP-seq peaks Fig. . In adding sites . All othSimilarly as with the in vivo observations, the effect of β-alanine on the protein-DNA interaction varied for the different targets Fig. . The com−4 . The locations and regular spacing of the three sites is reflected by the three peak summits in the ChIP-seq profile  and/or displaying a binding event in the neighbourhood of their promoter region increasing the probability that BarR binding affects gene expression . Gene expression was monitored both in the absence and presence of 10 mM β-alanine.Next, we determined whether or not BarR is involved in the regulation of the genes adjacent to the identified ChIP-seq binding regions. We performed qRT-PCR to analyze the effect of barR strain as compared to the isogenic MW001 , were downregulated 2.7-fold and 2.4-fold respectively in ΔbarR versus WT in the presence of 10 mM β-alanine. Hence, BarR also seems to activate glutamate synthase in response to β-alanine, thereby connecting the regulation of β-alanine to amino acid metabolism.Only 2 out of the 7 tested genes displayed a significantly different expression in the MW001Δ001 Fig. . These gin vitro validation of binding for most of these non-regulatory sites, it is unlikely that they are false positive artefacts of the ChIP-seq analysis. Also for other transcription factors, either in archaeal, bacterial or eukaryotic organisms, proof is accumulating that specific binding on the genome without an apparent regulatory output is a common feature of both global and local regulators [The 5 other tested genes did not show expression differences in both genetic backgrounds  encoded by the Saci_2320/Saci_2321 is a major binding target of the glutamine-responsive non-specific binding protein Sa-Lrp [S. solfataricus, the gltB promoter is associated with the lysine-responsive LysM [S. acidocaldarius, which harbours a LysM ortholog, directly upstream of the promoter  identified in this study Fig.  is one opp. Fig. . Indeed,n Sa-Lrp . In the ive LysM  through ter Fig. . Furtherith LysM . Curiousnditions , 7, 48. gltB promoter as it starts at 433 bp upstream of the Saci_2320 translational start  different Lrp-like regulators bind to adjacent binding sites in the same control region (shown in this work); ii) they interact through protein-protein interactions resulting in genomic co-association [barR has been shown to be regulated by Sa-Lrp [It is interesting to note that the ociation , 20, 32,ociation , and iv)ociation , 48. ForSaci_2137 aminotransferase and glutamine synthase. Besides its local role in the regulation of β-alanine degradation, we also demonstrate that BarR displays an overlapping regulon with other Lrp-like regulators by sharing glutamine synthase as a target. This adds to the growing body of evidence that Lrp-like regulators have connected functions and that the Lrp family is an important TF family for archaeal physiology.In conclusion, the ChIP-seq analysis presented in this work provides useful insights into the functioning and physiological role of BarR. We provide proof that BarR is a dedicated and mainly local acting transcriptional activator and that it has a limited regulon composed of its own gene, the ChIP, chromatin immunoprecipitation; ChIP-seq, chromatin immunoprecipitation combined with high-throughput sequencing; CoA, coenzyme A; EMSA, electrophoretic mobility shift assay; FFRP, feast/famine regulatory protein; gltB, glutamine synthase; HTH, helix-turn-helix; Lrp, leucine-responsive regulatory protein; OD, optical density; RAM, regulation of amino acid metabolism; RT-qPCR, reverse transcriptase quantitative polymerase chain reaction


Functional regulatory regions in eukaryotic genomes are characterized by the disruption of nucleosomes leading to accessible chromatin. The modulation of chromatin accessibility is one of the key mediators of transcriptional regulation, and variation in chromatin accessibility across individuals has been linked to complex traits and disease susceptibility. While mechanisms responsible for chromatin variation across individuals have been investigated, the overwhelming majority of chromatin variation remains unexplained. Furthermore, the processes through which the variation of chromatin accessibility contributes to phenotypic diversity remain poorly understood.We profiled chromatin accessibility in liver from seven strains of mice with phenotypic diversity in response to a high-fat/high-sucrose (HF/HS) diet and identified reproducible chromatin variation across the individuals. We found that sites of variable chromatin accessibility were more likely to coincide with particular classes of transposable elements (TEs) than sites with common chromatin signatures. Evolutionarily younger long interspersed nuclear elements (LINEs) are particularly likely to harbor variable chromatin sites. These younger LINEs are enriched for binding sites of immune-associated transcription factors, whereas older LINEs are enriched for liver-specific transcription factors. Genomic region enrichment analysis indicates that variable chromatin sites at TEs may function to regulate liver metabolic pathways. CRISPR-Cas9 deletion of a number of variable chromatin sites at TEs altered expression of nearby metabolic genes. Finally, we show that polymorphism of TEs and differential DNA methylation at TEs can both influence chromatin variation.Our results demonstrate that specific classes of TEs show variable chromatin accessibility across strains of mice that display phenotypic diversity in response to a HF/HS diet. These results indicate that chromatin variation at TEs is an important contributor to phenotypic variation among populations.The online version of this article (doi:10.1186/s13072-016-0078-0) contains supplementary material, which is available to authorized users. Accessible (open) chromatin is a common feature of active regulatory regions in eukaryotic genomes , 2. The Initial investigations into the relationship between variation of chromatin accessibility and genetic variation have begun to elucidate some principles. Examination of chromatin signatures in individuals with diverse ancestries revealed extensive variation in regulatory regions and evidence of heritability of these signatures . ChromatIn addition to single nucleotide variants, transposable elements (TEs) constitute a major portion of genomic variation , 10. AppThere is growing evidence that TEs have evolved for the benefit of the host, contributing to host genome expansion and genetic innovation . TEs canTo study the roles of TEs in chromatin accessibility variation, we chose seven strains of inbred mice that have differential response to a “western” high-fat, high-sucrose (HF/HS) diet  and perfPrevious studies have reported strain-specific heterogeneity in physiological response to HF/HS diet feeding , 30. In p values . Similarly, we classified the bottom 5 % of sites as the common set of sites. Variable sites display substantial heterogeneity in patterns of chromatin accessibility across the strains . As an example, the variable chromatin site at the Adi1 locus in Fig. p = 0.00017, Fisher’s exact test). DNA transposons are not enriched at either variable or common sites .Interestingly, although TE sequences generally display less accessible chromatin, there are more TEs observed at variable chromatin sites than at common chromatin sites . This difference between variable and common sites was further exemplified when we grouped individual LINEs into subfamilies . However, for SINE elements, there was no significant age difference observed between variable and common chromatin sites . DNA transposons that overlap variable chromatin show slight enrichment at older elements . However, DNA transposons contribute to a much smaller population of variable chromatin sites as compared to other classes of TEs  and plotted the distribution of the evolutionary age of all elements as well as those at variable and common sites separately in each of the classes Fig. f. In conIn order to understand the regulatory roles of younger LINEs, we examined the chromatin accessibility differences at all LINEs ranked by their evolutionary age Fig. a. To betp < 2.2 × e−16, Wilcoxon's rank-sum test). In addition, the binding motif for another liver TF, C/EBPα, is also enriched at variable sites containing older LINEs .TEs have been shown to contain transcription factor binding sites, and contribute to the evolution of the mammalian TF binding repertoire , 27, 42.p = 2.3 × e−9, Wilcoxon's rank-sum test). To confirm the results, we performed chromatin immunoprecipitation (ChIP) using antibodies targeting STAT3, a member of the STAT protein family known to be active in the liver [Intriguingly, variable chromatin sites containing younger LINEs are most enriched for the binding motif of STAT proteins Fig. a, which he liver . Using qTo further investigate the impact of variable chromatin at TEs to phenotypic diversity among strains, we used the genomic regions enrichment of annotations tool (GREAT)  to identMup19 and Mup5 are shown in Fig. As an example, several TE-associated variable chromatin sites are found in the major urinary protein (MUP) gene locus. Two LINE-associated variable sites proximal to UDP glucuronosyltransferase 2 family, polypeptide B37 (Ugt2b37), a member of UGT family . We further tested two additional variable LINEs and showed the deletion of each leads to the dysregulation of nearby metabolic genes. Deletion of an L1Md_F2 located 11 kb upstream of Ugt2b37 also leads to significant reduction in Ugt2b37 expression . We also deleted an Lx8 LINE element 6 kb downstream of suppressor of defective silencing 3 homolog (Suds3). Suds3 encodes a protein component of the SIN3 histone deacetylase (HDAC) corepressor complex, which has been shown to play a regulatory role in metabolic control in the liver [Suds3, which indicates a potential suppressor function of the Lx8 . These results validated that variable TEs contribute to the regulation of metabolic genes in liver cells.To validate the function of TEs at variable chromatin sites in regulating nearby gene expression, we used the CRISPR-Cas9 system to generate deletion of TE sequences in H2.35 cells, a cell line derived from BALB/c hepatocytes. We first tested an LTR located 1 kb upstream of he liver . DeletioGiven that sites displaying chromatin variation at TEs are enriched in metabolic pathways, we hypothesized that variable TE sequences regulate nearby metabolic genes in response to diet. Our previous work has demonstrated that HF/HS diet leads to chromatin remodeling at regulatory regions in the liver . We therEnpp1 gene, which encodes a pyrophosphatase, and has been shown to be related to type 2 diabetes [Enpp1. All together, we found approximately 30 % of polymorphic TE sites are bound by liver TFs . These results suggest that widespread chromatin variation at TEs is a general feature in mouse liver.To further validate that the epigenetic variation at TEs in liver is not only restricted to the seven inbred strains of mice, we compared the CpG methylation levels from livers of 25 inbred mouse strains . ConsistWhile previous studies have identified a genetic component to chromatin variation , the mecWe have previously shown that variation in chromatin accessibility across three strains of mice in response to diet depends on genetic factors , 58. We Epigenetic variability can occur both inter-strain and inter-individual. In our study, we used duplicates of each strain of mice for chromatin accessibility profiling and employed a computational pipeline see “” sectionTEs have been shown to play an important role in expanding the TF binding repertoire during mammalian evolution , 27. SupWe further investigated possible mechanisms of chromatin variation at TEs. TE polymorphism explains at least 6 % of the TE contribution to chromatin variation. Previous work has shown that less than 10 % of these structural variants result in detectable gene expression changes .Epigenetic mechanisms, such as DNA methylation, have been shown to play an important role in suppression of TE activity in somatic cells . We showagouti viable yellow (Avy) gene, for which a TE exists upstream of the Avy gene [Avy gene and therefore leads to differential coat color and obesity susceptibility [Our finding that TEs contribute to chromatin variation and metabolic gene regulation suggests that the phenotypic diversity observed across the strains is at least partially due to the regulatory role of TEs. One of the classical models of TE contribution to phenotypic diversity is the Avy gene . Variatitibility , 65. FurIn summary, our study has revealed that specific classes of TEs, especially younger LINEs, can impact chromatin accessibility variation in liver of different inbred strains. We further demonstrate that TEs regulate tissue-specific genes which may result in downstream phenotypic diversity.Mice were obtained from The Jackson Laboratory and were bred at the University of California, Los Angeles. Male A/J, AKR/J, BALB/cJ, C57BL/6J, C3H/HeJ, CBA/J and DBA/2J mice were maintained on a chow diet  until 8 weeks of age. Then they were given a high-fat, high-sucrose diet  for 8 weeks. During the feeding period, body fat percentage was tracked as described previously . Mice weHematoxylin and eosin (H&E) staining and Oil red O staining were performed on liver sections by the Pathology Core at the City of Hope using standard procedures.Formaldehyde-assisted isolation of regulatory elements (FAIRE) was performed on flash frozen liver tissues from two biological replicates in each strain as previously described . IsolateIn order to eliminate the mapping biases caused by inter-strain sequence variation, we first generated a pseudo-genome for each non-reference strains by introducing SNPs from each strain into the reference mouse genome (mm9) . We thenFor the analysis of FAIRE-seq and RNA-seq coverage at LINEs Fig. , we mappM) measures how often the sequence found at the particular location will align within the whole genome. M = 1 means unique match in the genome, S = 0.5 means two matches in the genome, and so on. All the tracks shown here are in the form of signals ranging from 0 to 1.In order to mitigate mapping biases, we generated mappability scores for the reference (C57BL/6J) and non-reference pseudo-genomes. We used the genome multitool (GEM) mapper  to generTo identify accessible chromatin sites from FAIRE-seq reads for each library, F-seq was used with default parameters and a 400 bp feature length . To findp-values from DESeq. The 5 % with smallest adjusted p-values were considered as variable chromatin sites, whereas the 5 % with biggest adjusted p-values were considered as least variable (common) chromatin site among the seven strains  (findMotifsGenome.pl)  to identifs tool , and onlifs tool  of the Hifs tool .Chromatin immunoprecipitation (ChIP) was performed with an anti-STAT3 antibody  and IgG control using standard ChIP protocols. Fragmented chromatin was assessed for enrichment at specific sites by quantitative PCR quantitation. The ΔΔCt method was utilized to evaluate enrichment of target DNA and normalized to input DNA. qPCR primer sequences at the L1Md_F2 are in Additional file For each TE tested, two guide RNAs (gRNAs) were designed to generate specific deletion of the TE sequence in H2.35 cells, a cell line derived from BALB/c hepatocytes. All gRNAs . Converted genomic DNA was used for PCR . SimilaIn order to investigate the enriched biological function of the genes nearby accessible chromatin sites, we used genomic coordinates (UCSC mm9) of accessible chromatin sites as input for genomic regions enrichment of annotations tool (GREAT) version 3.0.0 . Gene reRNA-seq data from livers of C57BL/6J and A/J mice fed with HF/HS diet were obtained from GEO (accession numbers GSE55581 ). CTCF C