Schizosaccharomyces pombe. Cells lacking HIRA experiencea global reduction in nucleosome occupancy at gene sequences, consistent with the proposedrole for HIRA in chromatin reassembly behind elongating RNA polymerase II. In addition, wefind that at its target promoters, HIRA commonly maintains the full occupancy of the−1 nucleosome. HIRA does not affect global chromatin structure at replicationorigins or in rDNA repeats but is required for nucleosome occupancy in silent regions ofthe genome. Nucleosome organization associated with the heterochromatic(dg-dh) repeats located at the centromere is perturbed by loss of HIRAfunction and furthermore HIRA is required for normal nucleosome occupancy at Tf2 LTRretrotransposons. Overall, our data indicate that HIRA plays an important role inmaintaining nucleosome architecture at both euchromatic and heterochromatic loci.HIRA is an evolutionarily conserved histone chaperone that mediatesreplication-independent nucleosome assembly and is important for a variety of processessuch as cell cycle progression, development, and senescence. Here we have used a chromatinsequencing approach to determine the genome-wide contribution of HIRA to nucleosomeorganization in  In some contexts HIRA is necessary for transcriptionalactivation. For example the induction of hip1Δ) was digested with MNase to generate a DNA ladderwith a highly similar molecular weight distribution to our wild type control sample  of protein coding genes. Typically chromatin in these regions isorganized with a nucleosome depleted region (NDR) followed by a well ordered nucleosomearray that extends from the TSS and packages the transcribed region.hip1Δ cells. Loss of HIRA did not result in anychanges to the NDR or the +1 nucleosome peak indicating that HIRA is not required forthe maintenance of chromatin structure around the 5′ end of genes, at least at aglobal level. Nonetheless, the amplitudes of the nucleosome peaks from +4 onwardswere reduced indicating that HIRA does contribute to the maintenance of chromatinassociated with ORFs. As HIRA has been linked to a variety of aspects of transcriptional control,hip1Δ mutant wassuggestive of a decrease in nucleosome occupancy and consistent with this view westernblotting revealed a significant reduction in histone protein levels in cells lacking HIRA Therefore as predicted, loss ofcorrect nucleosome spacing exacerbates the growth defects associated with HIRAinactivation.The reduction in the average peak height in the hip1Δ strain is consistent with thisfinding. To further investigate this we analyzed the nucleosome profiles of a group ofgenes which have been shown to produce cryptic transcripts when HIRA function isabsent.hrp1+ locus loss of HIRA function resulted in markedchanges to the MNase profile which extended throughout the entire gene and into theneighboring genes (atg12+ andpap1+) . In contrast, the other genes we inspectedexhibited relatively modest changes to their nucleosome profiles in thehip1Δ background . An example of this is thedbp7+ gene, where changes to nucleosome occupancy weremainly observed at the 3′-end of the gene and downstream of the transcriptiontermination site. It therefore appears that relatively small changes to nucleosomearchitecture may be sufficient to result in increased levels of cryptic transcripts. HIRA suppresses aberrant transcription from the bodies of geneship1Δsamples. Similar to the results from the genome-wide mapping studies, the qPCR analysisalso indicated that occupancy of nucleosomes near hrp1+(designated hrp1_5137) and the 3′ end of the dbp7+gene (dbp7_1927) were reduced in hip1Δ whereas the occupancy ofnucleosome located at the 5′ (dbp7_10) was similar in wild type andhip1Δ.In order to confirm some of the differences in the nucleosome profiles that were observedin S. pombe coding genes. HIRA-repressed genes were found to have obviousdifferences in their chromatin organization as average nucleosome peaks associated withthe coding sequences of these genes were poorly ordered and the height of the peaks waslower than the global average  promoters. Indeed theexpression of approximately 4% of fission yeast genes is increased by loss of HIRAfunction.hht2+-hhf2+ as theirexpression outside of S-phase is repressed in a HIRA-dependent manner.hht2+-hhf2+ aredivergently transcribed from a short promoter, and analysis of our MNase profiles revealedthe presence of a −1 nucleosome peak in the center of this region. Since themajority of fission yeast cells in an asynchronous culture will be in G2, this chromatinconfiguration is likely to represent a repressed promoter state. Consistent with thishypothesis the promoter nucleosome peak occludes the AACCCT box which is a binding sitefor the GATA-type factor, Ams2 and the Myb domain protein, Teb1, which activate thetranscription of histone genes.hip1+resulted in a marked reduction of this peak, suggesting that HIRA promotes the occupancyof this promoter nucleosome to suppress the inappropriate expression of histone genes and downstream (DS).S. pombe (like those in resting human CD4+ T cells) areassociated with nucleosomes.S. pombe tRNAgenes aligned by TSS are consistent with this earlier report as we detected a peakcentered at +20 relative to the TSS  suggesting that HIRA does not contribute to the globalorganization of chromatin at replication origins.Recently, the HIR complex has been implicated in the repression of rDNA transcription inmat) type locus and also at pericentromericrepeats.hip1+ deletion upon the nucleosomeprofile at pericentromeric dg-dh repeats. This revealed that loss of HIRAresulted in changes to specific peaks rather than a uniform reduction in occupancy acrossthe entire repeat region . qPCR analysis alsoindicated that deletion of hip1+ resulted in a reductionin the occupancy of the +2 nucleosome  experience a global reduction innucleosome occupancy. This is consistent with previous studies which revealed that thegenomes of fission yeast HIRA mutants are more accessible to DNA damaging agents.Here we have determined the global impact of HIRA upon nucleosome architecture and inagreement with previous evidence, find that this histone chaperone plays roles in themaintenance of both euchromatic and heterochromatic regions of the genome. We demonstratethat cells lacking HIRA  which enforcesilencing of the underlying repeat sequences.HIRA has been linked to the regulation of both LTR retrotransposons and retroviruses.S. pombe strains−h), SW577 (−hip1::ura4+h), NT5 (−ade6− ura4-D18 leu1–32h), AW046(+ hrp3::kanMX ade6− leu1–32ura4-D18h), SW700 (− hip1::ura4+ade6− ura4-D18 leu1–32h), CsG349(− hip1::ura4+ hrp3::kanMXade6− ura4-D18 leu1–32h).Routine culture and genetic manipulation was performed as previously described.7 cells were harvested following addition oftrichloroacetic acid (TCA) to a final concentration of 10%. Cells were resuspendedin 200 μl 10% TCA and then disrupted using a beadbeater with 0.75 mlof glass beads using 2 pulses of 15 sec with 1 min on ice in between. A500 μl aliquot of 10% TCA was added, the lysate was recovered from thebeads which was then clarified by spinning at 13 000 rpm in a microcentrifuge. Theresulting pellet was washed 3 times in acetone, dried and resuspended in30 μl 100 mM Tris-HCl (pH 8.0), 1% w/v SDS, and 1 mM EDTA.Samples were analyzed on SDS-PAGE gels and subjected to protein gel blotting usinganti-histone H3 (Abcam ab1791) and anti-tubulin (TAT-1) antibodies.Approximately ∼4 × 10595 = 0.75–8.0 in YE5S at 30°C,crosslinked for 20 min at 30°C using 1% formaldehyde and quenched by theaddition of glycine to 125 mM. Cells were washed once in CES buffer  and resuspended in500 μl of CES buffer with 0.5mg Zymolase 100-T. Cells were spheroplasted at30°C for up to 1 h and then washed twice with ice cold 1.2 M sorbitol.Spheroplasts were then resuspended in 800 μl NP-S buffer .Spheroplasts were then divided into 4 200 μl aliquots and each aliquot was mixedwith 300 μl of NP-S buffer. Three aliquots were digested with between75–187.5 units of MNase (USB) for 10 min at 37°C. The fourth was retainedas an undigested control. MNase digestion was terminated by adding EDTA [pH 8.0] to afinal concentration of 50 mM and SDS to 0.2%. Reactions were incubated at65°C overnight with 0.2 mg/ml proteinase K and 10 μg RNAse. DNA waspurified by extracting twice with phenol:chloroform followed by ethanol precipitation (0.1volumes of 3 M sodium acetate followed by 2 volumes of ethanol). Pellets were washedin 70% ethanol and resuspended in water containing 10 μg/ml RNase andincubated at 37°C for 30 min. Triplicate digests were pooled and treated with100 U unmodified T4 polynucleotide kinase (NEB) for 30 min at 37°C to remove3′-phosphate groups left by MNase. DNA was extracted once more withphenol:chloroform, re-precipitated with sodium acetate and ethanol, washed with 70%ethanol, dried and re-suspended in TE (pH 7.5).Cells (100 ml) were grown to ODDNA fragments were end repaired, 3′-adenylated and ligated to indexed adapterswithout size selection using Nextflex reagents . Libraries wereamplified with 8 cycles PCR using Kapa HiFi PCR master mix (Anachem), primers removed withGeneRead size selection protocol (QIAgen) before quantification by Bioanalyser DNA 7500assay. Libraries were pooled, denatured, diluted to 6 nM before clustering in asingle lane of a high output Illumina flowcell. Sequencing (100 nt) was undertaken ona HiSeq 2500 using TruSeq SBS v3 reagents (Illumina).Paired reads were aligned to the ASM294v1.17 reference genome using Bowtie 0.12.7 hip1Δ cells were performed asdescribed above. For each strain 3 biological replicate samples (independent from thoseused for sequencing) were pooled and analyzed on 1% TAE agarose gels. Gel slicescontaining mononucleosomal DNA were excised, frozen at -80°C and spun through0.45 μM Spin-X columns (Costar). Samples were phenol extracted and ethanolprecipitated and resuspended in TE (pH7.5). dsDNA concentration was measured using a Qubitfluorometer (Life Technologies). 20 ng of mononucleosomal DNA and was used in qPCRreactions using the PrimerDesign Mastermix kit. Reactions using the equivalent amount ofgenomic DNA were included as a control. The primers used for this analysis are listed inTable S1.MNase digests of wild type and


As exome sequencing gives way to genome sequencing, the need to interpret the function of regulatory DNA becomes increasingly important. To test whether evolutionary conservation of cis-regulatory modules (CRMs) gives insight into human gene regulation, we determined transcription factor (TF) binding locations of four liver-essential TFs in liver tissue from human, macaque, mouse, rat, and dog. Approximately, two thirds of the TF-bound regions fell into CRMs. Less than half of the human CRMs were found as a CRM in the orthologous region of a second species. Shared CRMs were associated with liver pathways and disease loci identified by genome-wide association studies. Recurrent rare human disease causing mutations at the promoters of several blood coagulation and lipid metabolism genes were also identified within CRMs shared in multiple species. This suggests that multi-species analyses of experimentally determined combinatorial TF binding will help identify genomic regions critical for tissue-specific gene control.DOI:http://dx.doi.org/10.7554/eLife.02626.001 Stretches of DNA called cis-regulatory modules (or CRMs for short) could help researchers to identify the regions of DNA that are most important for controlling genes. CRMs are regions where multiple transcription factors—proteins that control when and how genes are expressed—bind to DNA. As important biological pathways are often regulated by more than one transcription factor, CRMs are therefore a good target when looking for DNA regions that, if mutated, are likely to cause disease.If a stretch of DNA performs an important role, it is often conserved throughout evolution. This is often observed for genes that make proteins. Indeed, DNA regions that specify critical amino acids that make up proteins are often conserved across distantly related species. However, unlike the changes made to the amino acid encoding parts of genes, it is currently a challenge to predict which changes in the rest of the genome will affect gene expression.One reason for this challenge is that transcription factor binding sites are rapidly evolving. This rapid evolution means that strictly comparing DNA sequences between species may fail to identify where transcription factors like to bind in the genome. Numerous experimental efforts have therefore been made to map these sites. These have revealed that there are a huge number of regions in the human genome that can bind transcription factors: hundreds of thousands of sites, far more than there are genes. For this reason, there is a great interest in revealing which of these regulatory regions are critical for maintaining normal levels and timings of gene expression.Ballester et al. compared the binding sites of four transcription factors responsible for regulating liver function in humans, macaques, mice, rats, and dogs. About two-thirds of these binding sites were found in CRMs. Less than half of the CRMs in humans were also CRMs in another species—but Ballester et al. found that these shared CRMs are predominantly in charge of regulating the essential biological pathways that allow the liver to function correctly. In addition, Ballester et al. identified several examples of disease-causing DNA mutations in shared CRMs that affected the expression of genes that make up pathways such as the blood clotting cascade. Genome-wide association studies also uncovered common variants for liver-related traits that were enriched for the CRMs found in more than one species, further supporting their importance.As transcription factors work in different ways in different tissues, further studies are now required to expand these observations to organs other than the liver. Future work is also needed to investigate the function of thousands of conserved CRMs whose role in liver gene regulation remains unknown.DOI:http://dx.doi.org/10.7554/eLife.02626.002 The combinatorial binding of transcription factors to DNA define the gene regulatory regions that are essential for achieving spatial and temporal gene expression . The rapDrosophila , FAIRE, and DNase I footprinting assays in combination with high-throughput sequencing have unmasked what was previously a hidden landscape of active DNA regions . The comosophila . It remaDrosophila enhancers are more likely to be found in regions with conserved TF binding events detected by ChIP (Comparing DNA between species has long been employed to identify transcription factor (TF) binding sites that comprise gene regulatory regions e.g., . Indeed, by ChIP .Associating common genetic variation with complex traits is another powerful way to identify functional regulatory DNA in the human genome. Over 80% of the most significant single nucleotide polymorphisms (SNPs) associated with human phenotypes and disease occur within non-coding regions of the genome . Recent To test whether evolutionary conservation of cis-regulatory modules (CRMs) gives insight into human gene regulatory function, we determined transcription factor (TF) binding locations of four liver-enriched TFs in liver tissue from: two primates (human and macaque) estimated to have diverged 29 million years ago; two rodents (mouse and rat) estimated to have diverged 25 million years ago; and dog which diverged during the mammalian radiation along with primate and rodent lineages .The liver is a suitable tissue for studying vertebrate gene regulation. It is a relatively homogenous tissue with approximately 75% of the nuclei in the liver coming from hepatocytes . Both thHomosapiens [Hsap], Macaca mulatta [Mmul], Canis familiaris [Cfam], Mus musculus [Mmus], and Rattus norvegicus [Rnor]) using chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq)  was determined in primary liver in five species (hIP-seq) . The anthIP-seq) . As expehIP-seq) , the knohIP-seq) .10.7554/Similar to what was observed for previous CEBPA and HNF4A ChIP-seq experiments, only a minority of ONECUT1 and FOXA1 bound regions overlapped orthologous, TF-bound regions in a second species, a relationship we refer to here as “shared” TF binding see . The rapDrosophila (Tissue-specific TFs are known to bind in close proximity to form cis regulatory modules (CRMs). Similar to what has been done for multi-TF binding analyses in osophila  and mousosophila , we defiosophila . The numosophila . We builosophila . Using tosophila . We founosophila .As we found for individual TFs, the location of CRMs appears to have evolved rapidly . For exa−238). For example, 32 of the 35 CEBPA binding events previously found to be bound in orthologous regions in five vertebrate species , indicating increased selection pressure on higher order combinatorial TF binding . TF bind species  fell witTo test how combinatorial binding and TF binding conservation relate to liver gene function, we classified our set of human CRMs  and singletons  into phylogenetic categories . CRMs we−149 and p < 10−212 for HNF4 respectively; −149 and p < 10−212 respectively; TF binding events contained in CRMs were enriched for their respective TF's DNA binding motif, in addition to other liver TF binding motifs, including those profiled in this study . Support−130) from the Disease Ontology database and metabolism of lipids and lipoproteins (q = 2.96 × 10−73) from MSigDB Pathway . These enrichments were driven by genes involved in the metabolism of xenobiotics by the cytochrome P450 gene family   . Given tatabase) , these rSingleton TF binding events were predominantly enriched for their respective motif, but were not enriched for the motifs from the other three TFs profiled in this study . Support−4, moderate:10−3 and lenient 10−2) based on the comparison between the theoretical and empirical PWM weight score distribution observed for each peak collection as previously described  for each TF. We set three p-value threshold cut offs (stringent:10escribed . As expeescribed . Our resescribed .−5), were obtained   . This st−16) −3; . Using a−16) −3; . In sum,The number of reproducibly bound human regions obtained by ChIP-seq often exceeds the number of genes in the genome and so may require prioritization before experimental validation. Ranking ChIP-seq peak regions based on peak enrichment scores is one logical way to prioritize ChIP-seq peaks . We compAs expected, the HNF4A CRMs ranked by peak intensity showed higher read counts than the shared set of CRMs and both CRM sets showed strong, centralized motif enrichments . HoweverIn order to determine whether shared CRMs associate with human diseases and phenotypes, we asked: (1) if the phenotype-associated single nucleotide polymorphisms (SNPs) in a curated collection of GWAS , blood lipid , and drug response  categories were all enriched for shared CRMs (2 ≥ 0.8) to define the boundaries of each GWAS SNP gave similar results. For example, liver-related GWAS SNPs were enriched for Deeply shared CRMs when LD was taken into consideration  Deeply shared CRMs. For example, we found lead GWAS SNPs related to liver  involved several loci including TRIB1, ABCG8, APOB, SORT1, TOMM40, APOA5 and HNF1A. Lead SNPs for fibrinogen  occurred in LD with the fibrinogen locus. C-reactive protein  enriched for Deeply shared CRMs near CRP itself in addition to RORA, MLXIPL, HNF1A, BAZ1B, and IRF1 loci . However, unlike what we found for shared CRMs in liver, super-enhancers obtained from the liver cancer cell line HepG2 were not enriched by the liver-related lead GWAS SNPs  and lipid homeostasis   . This daichment) . We founIn this analysis of known functional and disease causing regulatory mutations from the HGMD database, it is worth noting that most of the examples we found overlapping Deeply shared liver CRMs resided close to the TSS. As most TF binding of the factors we profiled occur outside of proximal promoters, it is likely that many more human mutations that regulate genes through long-range interactions remain to be found. Just as gene sequencing has uncovered a diverse array of mutations for most disease genes, we expect that disruption of conserved TF bound regions will be found to have pathological consequences.There is a great interest in identifying and mechanistically characterizing regulatory SNPs. Such approaches require limiting the genomic search space, finding the function of identified mutations, associating the mutation with target gene(s) and addressing the tissue-specificity inherent in transcriptional regulation. To limit the search space, the genome must be distilled to the active functional regions where mutations are likely to be pathological. To determine the function of mutations in gene control regions, the trans-acting molecules  whose regulation of a particular locus is disrupted need to be identified. Finally, because transcriptional regulatory networks are highly tissue-specific, regulatory regions can only be accurately done within the tissue concerned.In this study, we demonstrated that genomic regions harboring shared combinatorial TF binding were enriched in a tissue-specific manner for essential biological pathways, common DNA variants associated with complex traits, and regulatory DNA mutations associated with rare diseases. In addition to the requisite measures of ChIP-seq data quality and reproducibility, it could be argued that combinatorial binding of transcription factors, relevant to the cell type of interest, increases the likelihood that the region identified is biologically important. However, more than half of the human liver TF binding sites detected in our study are in CRMs. In many cases, this makes CRM clustering on its own an insufficient filter for prioritizing TF binding sites for further study. Given the rapid turnover of TF binding within a mammalian lineage , requiriAlthough insightful, the costs and challenges of performing comparative combinatorial TF binding in multiple species, tissues, developmental stages, and environmental conditions limits its widespread use as a method for finding enhancers. Computational strategies that forgo strict DNA constraint for more flexible criteria, such as shared clusters of motifs, show great promise . For exaIt is also becoming clear that integrative approaches to enhancer discovery can outperform predictions made using single criteria . We compMDM2 and contributes to carcinogenesis in humans by increasing levels of MDM2, a negative regulator of TP53  is found in the first intron of the  of TP53 . This SN of TP53 . This exOur results suggest that conserved liver regulatory regions reside near SNPs or rare mutations associated with liver related phenotypes. The most striking disease associations we observed involved the blood coagulation pathway. This pathway is perhaps one of the best-studied biological pathways and has long served as a model system for understanding human disease gene mutations. This rich history allowed us to observe, perhaps for the first time, how recurrent TF binding mutations found within conserved combinatorially occupied TF binding sites can be afflicted on several members of the same pathway. Conserved combinatorial control regions were also found near proteins that are part of the coagulation and complement system . The interplay between the coagulation and complement system proteins has long been appreciated  and HNF4a antibody ARP31946  were used as previously described . FOXA1 aChIP-seq data generated for this study includes: CEBPA, FOXA1, ONECUT1, and HNF4A in rhesus macaque, FOXA1 in human, and FOXA1 and ONECUT1 in dog. Experiments used in this study that have been previously reported by our team include: ChIP-seq experiments for CEBPA and HNF4A for human and dog ; Human aChIP-seq and input reads from each species were aligned with MAQ  using dehttp//www.ebi.ac.uk/∼swilder/SWEMBL/; For each TF, at least two biological replicates were performed and aligned to their respective genomes  Landt e. SequencMotif discovery was conducted with MEME  using thpeak-motifs from RSAT  and external motifs coming from JASPAR (Vertebrate core 2009 version) (Search for secondary motifs was done using rom RSAT  with defversion)  and UniPversion)   fell within 300 bp see . All othShared binding events and CRMs were identified using the 9-way Enredo-Pecan-Ortheus EPO;  multipleLiver RNA-seq data from the same species were used to analyze if CRM status and conservation were related to gene expression levels. Polyadenylated mRNA levels were assessed using previously described RNA-seq data . We first filtered these data with prinseq-lite (v0.15) and fastx (v0.0.13): we trimmed both read ends with a quality threshold of 20, and we then discarded those reads that were shorter than 35 nucleotides, had more than 5% of Ns, a dust score bigger than 10 , and more than 5% of the bases with a quality inferior to 30. This subset of high quality reads was then mapped to the genome using BWA . We retrieved mapped reads and filtered them further by removing reads with a mapping quality below 20 (including multireads). In the case of paired-end data, we also removed all reads that were not properly paired. Finally, we calculated exon expression levels using htseq-count (HTSeq v0.5.3p3) and averaged those to produce gene expression estimates. TF binding sites not found in CRMs (Singletons) or within CRMs (Modules) were associated with the nearest gene. The FPKM (Fragments Per Kilobase of exon per Million reads) for each gene was recorded (obtained from the Human BodyMap 2.0 dataset from Illumina) and displayed as a heatmap .We first compiled data relevant to transcriptional regulation from ENCODE, for all cell lines. For each ENCODE data set, we then calculated its observed overlap with each of our ChIP data sets  by counting the number of regions that overlap by at least 1 bp. We then built a distribution of expected overlap values from 1000 iterations of randomizing the input regions, by shuffling each one into a random genomic region chosen from among the DNaseI hypersensitive regions in any cell type . The distribution of the overlap scores from the randomized data resembles a normal distribution, which we used to generate a Z-score and p-value for the observed number of peaks that overlap each real data set see .Functional enrichment of ChIP-seq data was performed using the online tool GREAT version 2.0.2 . ImportaHuman CRMs that had TF binding in syntenic regions in at least two additional species (n = 5046) were intersected with the Human Gene Mutation Database . A representative network analysis of these genes was obtained using the GeneMANIA server using default parameters . Figure. Using tTo define the locations of each regulatory region, we sliced the genome into categories: TSS ±3 kb, intronic, intergenic, and exonic. We obtained all transcripts (exons and introns) defined by the Ensembl genebuild, keeping the longest features. Any regions falling within ±3 kb of a TSS was characterized as the TSS ±3 kb category. In the event of complex gene arrangements or regions bridging two categories, we prioritized the locations as follows: TSS ± 3 kb > intron > intergenic > exon. Conservation scores were obtained from the Ensembl Compara database . Genomic2 values were obtained using the Ensembl Variation Perl API (2 ≥ 0.8). Alternatively, each GWAS lead SNP was given a window of ±2.5 kb. The GWAS catalog (25 August 2011) was manually summarized into 25 categories using the given Disease Trait, Experimental Factor Ontologies . Similarly, the author response typically shows only responses to the major concerns raised by the reviewers.eLife posts the editorial decision letter and author response on a selection of the published articles . An edited version of the letter sent to the authors after peer review is shown, indicating the substantive concerns or comments; minor concerns are not usually shown. Reviewers have the opportunity to discuss the decision before the letter is sent  and 2 reviewers (Drs Mike Beer and Ross Hardison).Thank you for sending your work entitled “Multi-species, multi-transcription factor binding highlights conserved control of tissue-specific biological pathways” for consideration at The Senior editor and the reviewers discussed their comments before we reached this decision, and the Senior editor has assembled the following comments to help you prepare a revised submission.There are several major points that need to be addressed in the revised document (please see below). In addition both reviewers have suggested a reorganization of the display items.Reviewer 1:1) A main result is that most CRMs “are evolving rapidly”, but to be precise, what “conserved” means here is that the sequences are not “alignable by EPO.” This is naively in conflict with 2) Details of CRM construction are too sparse, and it is not very clear what CRM composition is until Supplemental 3) How sensitive are the results to the specific cutoffs used for ChIP-seq signal to quantify a binding event vs. non-event? The analysis should be performed on different replicates to test this. How many CRMs change their composition using only one repl to build them vs. the other? Also, it seems a bit inconsistent to say that the ENCODE quality control standards are used for the replicates if later only the replicate which gives the most peaks is used for downstream analysis. If both replicates don't give similar results, how robust are the conclusions?4) Motif detection is good, but enrichment should be quantified. The fraction of CRM sequences which have motifs present above some cutoff PWM score for each of the 4 PWMs should be reported for all CRMs and singletons. E.g., how many singleton HNF4A binding regions have a PWM instance above some cutoff, compared to how many singleton sites for the other 3 factors have a HNF4A PWM score above that same cutoff?Reviewer 2:The current manuscript is difficult to read and understand. I have several recommendations for revisions, starting with some major re-organization.1) The logical flow is fairly strong in the Results, but the data referred to are dispersed across many pages of Figures and Figure supplements. Also the order of the main figures does not fit with the presentation in the Results: it really is not used until the third section. I strongly recommend re-organizing the figures. Start with some of the current Figure 1 supplements, specifically 2) 3) The description and interpretation of the data in 4) 5) The Discussion should address what is missed by focusing on only combinatorial binding, only conserved binding, and both. Clearly, many fewer bound sites are examined by doing this filtering, but the enrichment for likely function is substantial. What are the potential costs of taking this approach?6) I would like to see a paragraph in the Discussion comparing the advantages of filtering vs integration. Are there integrative approaches that would emphasize the features shown to be useful here  while not completely excluding other binding sites?7) What is the null model for the tests of enrichment for GWAS SNPs in CRMs, singletons ? In prev Reviewer 1:1) A main result is that most CRMs “are evolving rapidly”, but to be precise, what “conserved” means here is that the sequences are not “alignable by EPO.” This is naively in conflict withshowing that TFBS are conserved in all species. It seems that the authors have the ability to investigate what is evolving, either: 1) CRM TFBS composition (binding sites evolving in our out), 2) TFBS linear arrangement (binding sites reordered), or 3) CRM-gene association (entire CRMs relocating and losing synteny). Another possibility is that all 3 of these features are conserved, but what is called lack of conservation is simply a failure of EPO alignment to detect the conserved TFBS arrangement and composition. There are computational approaches specifically designed for this case (where PWMs and TFBS are known) which outperform EPO for this task (compared in Su Teichman Down 2010) and something along the lines of Kim, He, Sinha 2009; Sinha, He 2007; He, Ling, Sinha 2010; all in PLOS Comp Bio, should be utilized.We thank the reviewer for pointing out the ambiguity on what we define as being conserved in this study. This is relevant to several other comments below. We have now replaced the term “conserved” with “shared” to make it clear that CRMs or Singletons that overlapped in the EPO multiple sequence alignment are what we are focusing on. This overlap in the EPO-MSA did not require more than 10 bp and was not based on CRM content or motif alignment. To better make this point, and to address reviewer 2’s comment about organization of the manuscript, we created a new Using five mouse species/strains we recently described the evolution of CRM content and turnover see . Based oOur new While current methods which use only sequence properties will not necessarily be able to distinguish liver CRMs from all regulatory regions, these computational methods are highly relevant to compare to our dataset. We looked into the above papers and the methods reviewed in Su et al. 2010. From this paper the “Regulatory Potential Score” appeared to be the most promising and accessible regulatory prediction dataset we could compare to our data. Using the GAT tool We also compared our data to a recent paper, which employed a novel method that successfully integrates a variety of functional data and sequence properties to predict developmental enhancers . This me2) Details of CRM construction are too sparse, and it is not very clear what CRM composition is until Supplemental, which should be in, and numbers of singletons should be added, not buried in the supplementary material. If a CRM changes its TFBS composition across species, but the sequence is alignable, is it still considered conserved?This is a crucial comment raised also by reviewer 2. We have now provided a new Figure  illustraWe also clarified the legends on the CRM building in what is now 3) How sensitive are the results to the specific cutoffs used for ChIP-seq signal to quantify a binding event vs. non-event? The analysis should be performed on different replicates to test this. How many CRMs change their composition using only one repl to build them vs. the other? Also, it seems a bit inconsistent to say that the ENCODE quality control standards are used for the replicates if later only the replicate which gives the most peaks is used for downstream analysis. If both replicates don't give similar results, how robust are the conclusions?We asked how building human CRMs with: 1) individual ChIP-seq biological replicates or 2) using a different peak caller (MACS), affected the phylogenetic classification of CRM/Singletons. We built human CRMs with the replicate that gave the most peaks “Hi rep” and with the replicate that gave the fewest peaks “Lo rep”. We also used the MACs peak caller at an FDR of 0.05, which is more permissive at calling peaks than SWEMBL. The results for this comparison is tabulated and plotted in 4) Motif detection is good, but enrichment should be quantified. The fraction of CRM sequences which have motifs present above some cutoff PWM score for each of the 4 PWMs should be reported for all CRMs and singletons. E.g., how many singleton HNF4A binding regions have a PWM instance above some cutoff, compared to how many singleton sites for the other 3 factors have a HNF4A PWM score above that same cutoff?We thank the reviewer for this suggestion. We performed this analysis and have incorporated the results into the paper  for each TF”). This allowed us to highlight that singleton TF binding events have a great fraction of high quality motifs compared to CRMs.Reviewer 2:The current manuscript is difficult to read and understand. I have several recommendations for revisions, starting with some major re-organization.1) The logical flow is fairly strong in the Results, but the data referred to are dispersed across many pages of Figures and Figure supplements. Also the order of the main figures does not fit with the presentation in the Results: it really is not used until the third section. I strongly recommend re-organizing the figures. Start with some of the current Figure 1 supplements, specifically, 4, 5 to show the basic data, and how you constructed the CRMs, and the amount of conservation for TF bound sites and CRMs. Then go to the current, which describes how the CRMs are categorized by extent of conservation.We have taken the reviewer’s suggestion and re-organized our figures as recommended. We have also added an additional summary  to illus2)and the many supplemental figures have multiple problems. The authors have developed an excellent way of displaying the GREAT results, but they flood the reader with too much information. A better-digested and focused set of key results needs to be featured. The text does have a good focus; however, the text and figures are not closely aligned. The specific examples of significant enrichments in the text are not listed in the main, and the reader has to scan through four or five pages of figure supplements to find the data being discussed. One figure highlighting the key enrichments needs to be refined from all this material. Also, the method for assigning likely target genes is not stated in the main text. This is a very important point for interpreting the data, and it should be stated in the Results as well as in the Methods.We have now condensed the enrichment analysis into one Figure  as sugge-130) from the Disease Ontology database and metabolism of lipids and lipoproteins (q = 2.96 x 10-73) from MSigDB Pathway  The description and interpretation of the data inneed to be more accurate. The data in panel B are over-interpreted in the legend and in the Results. The expression of presumptive targets is not limited to liver (“uniquely expressed”) but the expression levels are higher there. The text says “Unlike CRMs, conserved singletons do not show a strong increase in liver-specific gene expression.” In fact, presumptive targets of singletons show a similar pattern to the presumptive targets of CRMs, but the levels of expression are lower.-16) (We revised the description in the legend for -16) . Using a-16) . In sum,Is the decrease in signal for deeply shared singletons significant, or is this related to a small number of targets to examine? Also, the legend should specify the RNA-seq data used in panel A. The top comparison inseems to be between the expression levels of presumptive targets for deeply conserved CRMs and lineage-specific singletons, but it has a surprisingly high p-value; this should be clarified.-3). The reason for this high p-value is likely due to the fact that some very highly expressed liver genes have multiple CRMs close by. Our plot does not show the outliers, which include highly expressed liver genes like Albumin, fibrinogen , complement genes, and many of the acute phase response genes . This analysis has been added to the Results section.We have clarified the data source for 4)main and Figure 6–figure supplement 1: The authors are making a critical point but the connections between the text and the Figures are not stated clearly. In the Results, the authors give p-values for enrichment of about 0.005 to 0.008 and refer to. However, those p-values are MUCH smaller, and correspond to the analysis in the next sentence, after separation by conservation categories. However, the reader is referred to Supplemental File 4, whereas they really need to look at! The fact that the enrichments are robust to different ways of dealing with potentially functional SNPs in proximity or LD is a strong point and accurately stated in the Results. However, the titles to the figure legends  are the same, and it takes some careful reading to figure out what is different about the two figures.We have now removed the results for the “Any shared” enrichments from the text , and focused our discussion on the deeply shared CRMs. We have corrected the Figure legends. We have also redone 5) The Discussion should address what is missed by focusing on only combinatorial binding, only conserved binding, and both. Clearly, many fewer bound sites are examined by doing this filtering, but the enrichment for likely function is substantial. What are the potential costs of taking this approach?We have now included this important point in the Discussion, with the text starting “Just as using DNA constraint as a sole criterion for enhancer finding has its limitations, using filtering approaches that require conserved combinatorial binding will also miss important regulatory events near genes of interest”.6) I would like to see a paragraph in the Discussion comparing the advantages of filtering vs integration. Are there integrative approaches that would emphasize the features shown to be useful here  while not completely excluding other binding sites?We have addressed this comment in the Reviewer 1, comment 1 and have created a paragraph in the Discussion, which should address comment 5 above as well.7) What is the null model for the tests of enrichment for GWAS SNPs in CRMs, singletons ? In previous studies, the null model was restricted to SNPs on the genotyping array that were not associated with a trait but were matched to the trait-associated SNPs in several important ways, e.g. allele frequency, position relative to gene structure, and proximity to the transcription start site.We implemented two null models to further test the significance of the enrichments we found. First we shuffled the GWAS SNP summary annotation 1,000 times. Using each random set, we annotated CRMs and singletons with the summaries assigned to overlapping SNPs as described for


In thiscontext, orthogonal means that T7 RNAP will not transcribe genes driven by native E.coli promoters, and native polymerases in E. coli will not recognize T7RNAP's special promoter—that is the two transcriptional systems leave each otheralone. Interestingly, T7 RNAP drives transcription so strongly that, if left unregulated, it canquickly exhaust cellular resources and lead to cell death. Because of this, T7 RNAP has beenleveraged in many situations calling for protein over-expression (Studier & Moffatt, et al, T7 RNAP has had a long relationship with biotechnology and is renowned for its compactness andtranscriptional activity. This single subunit polymerase strongly drives transcription from aminiscule 17-bp promoter that is orthogonally regulated in in vitro (Ikeda & Richardson, Given the growing interest in the development of synthetic gene circuits, researchers have takena renewed interest in T7 RNAP. The orthogonality, transcriptional activity and promoter malleabilityof T7 RNAP make the enzyme uniquely suited for use in synthetic gene circuits. Importantly, anymodifications made to the enzyme increase the possible functionality of circuits. For instance, werecently utilized a split version of T7 RNAP in conjunction with promoter specificity mutants tocreate a library of transcriptional AND gates (Shis & Bennett, et al take the idea of splitting T7 RNAP for novel regulatoryarchitectures one step further. Instead of settling for the one split site already discovered, theauthors first streamlined a transposon mutagenesis strategy (Segall-Shapiro et al,Segall-Shapiro et al expands the utility ofT7 RNAP in orthogonal gene circuits. Until now, while T7 RNAP has been attractive for use insynthetic gene circuits, the inability to regulate its activity has often prevented its use.Splitting the protein into fragments and regulating the transcription complex by fragmentavailability brings the regulation of T7 RNAP closer to the regulation of multi-subunit prokaryoticRNA polymerases. Sigma fragments direct the activity of the transcription complex much likeσ-factors, and the alpha fragment helps activate transcription in the same way asα-fragments of prokaryotic polymerases. For additional regulation, the authors note that thetripartite T7 RNAP can be further split at the previously discovered split site to create afour-fragment enzyme.The tripartite T7 RNAP presented by Segall-Shapiro et al, E. coli. Finally, synthetic genecircuits driven primarily by T7 RNAP create the possibility of easily transplantable gene circuits.A synthetic gene circuit driven entirely by fragmented T7 RNAP would depend more on fragmentavailability than unknown interactions with host metabolism. This would enable rapid prototyping ofsynthetic gene circuits in laboratory-friendly strains or cell-free systems (Shin & Noireaux,More nuanced regulation using split T7 RNAP may be possible with the addition ofheterodimerization domains that can drive the specific association of fragments. This strategy hasbeen successfully applied to engineer specificity and signal diversity in two-component signalingpathways (Whitaker


Cerrena sp. strain HYB07 with validated reference genes. A high laccase activity of 280.0 U/mL was obtained after submerged fermentation for 5 days. Laccase production and laccase gene transcription at different fermentation stages and in response to various environmental cues were revealed. HYB07 laccase activity correlated with transcription levels of its predominantly expressed laccase gene, Lac7. Cu2+ ions were indispensable for efficient laccase production by HYB07, mainly through Lac7 transcription induction, and no aromatic compounds were needed. HYB07 laccase synthesis and biomass accumulation were highest with non-limiting carbon and nitrogen. Glycerol and inorganic nitrogen sources adversely impacted Lac7 transcription, laccase yields, and fungal growth. The present study would further our understanding of transcription regulation of laccase genes, which may in turn facilitate laccase production as well as elucidation of their physiological roles.Laccases can oxidize a wide range of aromatic compounds and are industrially valuable. Laccases often exist in gene families and may differ from each other in expression and function. Quantitative real-time polymerase chain reaction (qPCR) was used for transcription profiling of eight laccase genes in  White-rot fungi secrete ligninolytic enzymes such as lignin peroxidases, manganese peroxidases, versatile peroxidases, and laccases Wong, . LaccaseUnraveling gene expression patterns is important for elucidating gene function as well as metabolic engineering to improve yields of desired products. Northern blotting, semi-quantitative reverse transcription-polymerase chain reaction (RT-PCR), and quantitative real-time PCR (qPCR) have been used to determine mRNA abundance. Laccase production, often at the level of transcription, responds to various environmental signals such as metal ions, aromatic compounds, and carbon and nitrogen sources and concentrations , expression regulation of Cerrena laccase genes remains largely unknown. We have isolated a white-rot fungus Cerrena sp. strain HYB07 with high laccase yields in a short production cycle. Two HYB07 laccases  have been characterized; they have different pH and temperature optima, substrate ranges and catalytic activity , carbon/nitrogen ratios and carbon and nitrogen sources was investigated. The present work will provide a theoretical foundation for elucidating the complex molecular mechanism underlying laccase expression regulation in Cerrena sp. HYB07 and pave the way for its commercialization and utilization.The genus Cerrena sp. strain HYB07 : maltodextrin, 60; peptone, 10; ammonium tartrate, 1.6; KH2PO4, 6; MgSO4·7H2O, 4.14; CaCl2, 0.3; NaCl, 0.18; CuSO4·5H2O, 0.0625; ZnSO4·7H2O, 0.018; and vitamin B1 0.015. This medium was also referred to as the control, regular or HNHC (high nitrogen and high carbon) medium in this manuscript.2+ or Zn2+ ions were not added to the fermentation medium; aromatic compounds, including 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS), caffeic acid, ferulic acid, guaiacol, p-hydroxybenzoic acid, nicotinic acid, syringic acid, and vanillic acid, were individually added at a final concentration of 0.5 mM. ABTS was purchased from Sigma-Aldrich (USA), and all other aromatic compounds were purchased from Sinopharm Chemical Reagent Co., Ltd (China) or Aladdin (China). For media with different carbon/nitrogen ratios, HNLC (high nitrogen and low carbon) medium contained 6 g dextrin instead of 60 g; LNHC (low nitrogen and high carbon) contained 1 g peptone and 0.16 g ammonium tartrate instead of 10 and 1.6 g, respectively; LNLC (low nitrogen and low carbon) medium contained 6 g dextrin, 1 g peptone, and 0.16 g ammonium tartrate. For media with different carbon sources, dextrin was replaced with glucose (monosaccharide), fructose (monosaccharide), maltose (disaccharide), sucrose (disaccharide), or glycerol at the same concentration of 6%. For media with alternative nitrogen sources, peptone was substituted with 10 g NH4NO3 or ammonium tartrate, while 1.6 g ammonium tartrate in the original medium recipe remained the same. Since our preliminary experiments showed that addition of aromatic compounds on day 0 (the time of culture inoculation) impaired fungal growth, aromatic compounds were added on day 2; all other treatments started from day 0. Laccase activity was measured on day 6. For each treatment, two independent experiments were carried out with three replicates for each experiment.To test the effects of inducers on laccase production, Cu2+ or Zn2+, various carbon/nitrogen ratios  and alternative carbon and nitrogen sources .Subsequently, selected samples were analyzed with qPCR. For growth phase experiments, mycelia were harvested every 24 h from days 1 to 6. For ABTS and guaiacol treatments, control and treated fungal cultures were taken on the fourth day of fermentation. For all other treatments, the control and treated cultures were collected on the second day, when biomass reached maximum and extracellular laccase activity was on exponential increase. These other treatments included: media with no additional CuExtracellular laccase activity was spectrophotometrically assayed at 30°C and pH 3.0 with ABTS at 420 nm. One unit of enzyme activity was defined as the amount of enzyme needed to oxidize 1 μmol ABTS in 1 min. All measurements were carried out in triplicate.For biomass measurements, triplicate cultures were harvested at the same time as for qPCR analysis. Mycelia were filtered with pre-dried Whatman filter paper, dried in an oven at 70°C for 24 h and weighed.Mycelia from three biological replicates were pooled, and total RNA was extracted with Trizol  according to the manufacturer's instructions. RNA quantity was measured with a NanoDrop 2000 UV-Vis spectrophotometer . The ratios of the absorbance at 260 and 280 nm of the samples were between 1.8 and 2.0. RNA integrity was checked by 1% agarose gel electrophoresis before reverse transcription (data not shown).12−18 primer and 1 μM 18S-rRNA-specific primer (the reverse qPCR primer for 18S rRNA) . Each reaction contained 2 μg total RNA, 0.5 μg oligo-(dT)Lac1-8) and housekeeping genes were designed by PrimerQuest , and the amplicon sizes ranged from 91–220 bp.qPCR primers for the eight laccase genes Lac-8 and ho18S rRNA as the target to check for DNA presence. No-template negative controls were included every run to detect possible contamination or carryover.qPCR was performed on an Applied BioSystems 7500 Real-Time PCR system . Each reaction mixture (20 μL) contained 10 μL 2 × TransStart Top Green qPCR SuperMix , 0.4 μL 50 × Passive Reference DyeII, forward and reverse primers (each at 200 nM), and 2 μL cDNA (1:50 diluted). Amplification was carried out as follows: an initial denaturation step of 94°C for 30 s, followed by 40 cycles of 94°C for 5 s and 60°C for 34 s. All reactions were performed in triplicate. RT negative controls (containing RNA template without reverse transcription) were run for every sample by using −▵▵Ct relative quantification strategy , β-tubulin, Cyt-c (cytochrome c oxidase subunit 1), GAPDH , RPB2 (RNA polymerase II second largest subunit), and TEF1 , under various experimental conditions were evaluated with geNorm  of reference genes based on pairwise variation (Vn∕n+1) analysis between the normalization factors NFn and NFn+1. The recommended cutoff value (0.15) was adopted, so the minimal number of reference genes was decided from the first Vn∕n+1 value lower than 0.15.Expression stability of seven candidate reference genes, including 2+, no Zn2+, ABTS, guaiacol, and the respective controls); Group C consisted of four samples cultivated under different carbon/nitrogen ratios ; Group D consisted of six samples cultivated under different carbon or nitrogen sources ; Group E contained all the samples. Groups C and D shared the same 2nd-day control sample fermented in the regular medium, which was also a control for Group B in addition to a 4th-day control (for aromatic compound treatment). Samples were grouped for laccase gene transcription analysis based on selected reference genes.Samples were divided into five groups for reference gene selection. Group A consisted of six samples collected on days 1 to 6; Group B consisted of six samples under different induction conditions 2, NaMoO4, and H3BO3 did not influence or negatively influenced laccase production, whereas Cu2+ and Zn2+ stimulated laccase production. Indeed, when Cu2+ or Zn2+ ions were not added to the fermentation medium, extracellular laccase activity was lowered by 99.95 and 31.78%, respectively   Figure . The higCerrena sp. HYB07  was observed with glycerol Figure . Ammoniu2+ or Zn2+; (3) presence of ABTS or guaiacol; (4) alternative carbon source glucose, sucrose or glycerol; (5) alternative nitrogen source NH4NO3 or ammonium tartrate.To better understand the mechanism underlying laccase synthesis, qPCR was used to explore the effects of growth phases, inducers, carbon/nitrogen ratios, as well as carbon and nitrogen sources on laccase gene transcription. Based on laccase production studies, the following parameters were selected: (1) days 1–6 of fermentation; (2) no supplementary Cu18S rRNA, ATP6, Cyt-c, GAPDH, RPB2, TEF1, and β-tubulin was analyzed with geNorm  for different growth phases (Group A); GAPDH and Cyt-c for different induction conditions (Group B); ATP6 and TEF1 for various carbon/nitrogen ratios (Group C); and GAPDH and Cyt-c for various carbon or nitrogen sources (Group D)  in the absence of Cu2+ ions , Lac6 (19.3-fold), and Lac8 (7.1-fold). In the two low nitrogen media, similar responses were observed, regardless of the carbon concentration. Lac4 was most remarkably up-regulated by limiting nitrogen, followed by Lac6, 3, 8, 5, and 2. Low carbon or nitrogen concentrations inhibited expression of Lac7 (by 11.0- to 16.7-fold) and Lac1 (by 10.1- to 3.2-fold).More dramatic differences were seen with various carbon/nitrogen ratios Figure . Lac2 waLac2, 4, 5, 6, and 8 by 13.1- to 2.1-fold. On the other hand, glycerol suppressed Lac7 expression by 17.9-fold; Lac1 expression was also reduced, albeit to a lesser degree (2.4-fold).Glucose and sucrose slightly down-regulated transcription of most laccase genes Figure . GlyceroLac2, 3, 4, 5, and 8, responded to the inorganic nitrogen source NH4NO3 with enhanced expression (with Lac3 and 4 exhibiting highest fold changes of >6).Ammonium tartrate up-regulated transcription of Lac3, 4, 6, and 8. Lac7 mRNA levels were low with both inorganic nitrogen sources  identified multiple putative cis-acting transcription regulation sites within the promoter of the eight laccase genes in both orientations, in . Lac6 promoter contained the highest number (4) of ACE1 copper-responsive transcription factor binding sites, followed by 2 in Lac4 promoter and 1 in Lac2 and 8 promoters. Promoters of Lac3 and 5 did not contain any MRE or ACE1 sites. Xenobiotic response elements (XREs) were found in five promoters except for Lac1, 2, and 6 promoters.Genomatix  of potential carbon source-responsive elements , has high specific activity, wide substrate specificity and strong decolorization ability . Lac2 transcription was greatly induced under low carbon conditions; of its eight predicted CSREs, three were adjacent (within the region of -456 to -417 upstream of ATG); this was reminiscent of the distribution pattern of three CSREs in the promoter of MDH2  required for gluconeogenic growth of Saccharomyces cerevisiae , and (2) GAPDH. Contradicting or overestimation of the expression values were obtained by the two normalization strategies (Supplementary Figure We selected the appropriate reference genes for laccase gene transcription profiling. Housekeeping genes are commonly used as normalization references in relative quantification qPCR experiments, although they may show expression variability with different experimental factors (Kozera and Rapacz, Cerrena sp. HYB07. Cu2+ ions, carbon/nitrogen ratios and certain nutrient types exerted remarkable influence on its laccase yields. Lac7 was the main laccase gene under expression throughout the fermentation cycle, and its transcript abundance was correlated with laccase yields under various experimental conditions. Lac7 transcription was up-regulated by copper and zinc ions and down-regulated by scarcity of nitrogen and carbon. The advantages of Cerrena sp. HYB07 for industrial production were manifested. Efficient laccase synthesis by HYB07 did not require toxic xenobiotic compounds. Furthermore, high expression levels of Lac7 under high carbon and high nitrogen conditions allow for accumulation of fungal biomass for laccase production. More research is needed to experimentally validate functionality of the putative cis-acting regulatory elements in the laccase promoters and decipher the complex regulatory network underlying laccase expression. Future work can also be directed to engineer the strong Lac7 promoter to drive expression of other, including laccase, genes.The present study provided insights into laccase production by JY, JL, and XY designed the research, JY and GW performed the experiments, JY and TN analyzed the data and wrote the manuscript, JL and XY contributed reagents.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.


Lhx1 expression in the epiblast marks the entire definitive endoderm lineage, the anterior mesendoderm, and midline progenitors. In proteomic experiments, they characterize a complex comprised of Lhx1, Otx2, and Foxa2 as well as the chromatin-looping protein Ldb1.Costello et al. demonstrate that Smad4/Eomes-dependent  Lhx1 in the visceral endoderm. Here we demonstrate Smad4/Eomes-dependent Lhx1 expression in the epiblast marks the entire definitive endoderm lineage, the anterior mesendoderm, and midline progenitors. Conditional inactivation of Lhx1 disrupts anterior definitive endoderm development and impedes node and midline morphogenesis in part due to severe disturbances in visceral endoderm displacement. Transcriptional profiling and ChIP-seq (chromatin immunoprecipitation [ChIP] followed by high-throughput sequencing) experiments identified Lhx1 target genes, including numerous anterior definitive endoderm markers and components of the Wnt signaling pathway. Interestingly, Lhx1-binding sites were enriched at enhancers, including the Nodal-proximal epiblast enhancer element and enhancer regions controlling Otx2 and Foxa2 expression. Moreover, in proteomic experiments, we characterized a complex comprised of Lhx1, Otx2, and Foxa2 as well as the chromatin-looping protein Ldb1. These partnerships cooperatively regulate development of the anterior mesendoderm, node, and midline cell populations responsible for establishment of the left–right body axis and head formation.Gene regulatory networks controlling functional activities of spatially and temporally distinct endodermal cell populations in the early mouse embryo remain ill defined. The T-box transcription factor Eomes, acting downstream from Nodal/Smad signals, directly activates the LIM domain homeobox transcription factor  Shortly after implantation, Nodal and Wnt signaling pathways coordinately instruct the symmetrical cup-shaped epiblast, the founder tissue of the embryo proper, to become appropriately patterned and give rise to the three primary germ layers: the ectoderm, endoderm, and mesoderm . The antEomesodermin (Eomes) has been identified as a key regulator acting downstream from dose-dependent Nodal/Smad signals    signals . During n the PS . Additio the AVE . Recent 1 (Lim1) . Lhx1 ismesoderm . Loss-ofovements . Decreasncations .Eomes-dependent Lhx1 expression in the epiblast. As for the Eomes+ cell population , Lhx1 is expressed throughout the VE overlying the epiblast A and a sLhx1 expression in the VE   . The genepiblast E,F. Smad, and DE . Smad4 cepiblast G.+ cells, we engineered a dual-purpose Lhx1iCreIRESLacZ reporter allele carrying LacZ and Cre expression cassettes introduced under the control of endogenous Lhx1 regulatory elements . The LacZ reporter is transiently expressed at E6.5 in the AVE and nascent mesoderm and slightly later in the ventral node, AME, and midline. At early somite stages, a second domain of Lhx1.LacZ expression was detectable in the lateral nephrogenic mesoderm. To further characterize Lhx1+ derivatives, Lhx1iCreIRESLacZ/+ males were mated to females carrying either the Rosa26RLacZ or Rosa26RYFP reporter allele . To globally visualize YFP+ Lhx1 descendants, we used confocal microscopy and three-dimensional (3D) rendering software  resource targeting vector . The resulting Lhx1Δ/−:Sox2CreTg/+ (hereafter referred to as Lhx1ΔEpi) mutant embryos  appear morphologically normal at early stages but, by E9.5, display marked cardiac defects, including abnormal looping, expanded pericardium and cardia bifida, and a marked reduction of anterior endoderm and neural tissue . By E10.5, all Lhx1ΔEpi mutants are growth-retarded and necrotic .Partial loss (∼70%) of  defects . To compr strain  togetherHhex and Hesx1 mRNA is severely compromised  and confocal imaging of immunofluorescence data, the number of Cer1+ cells is significantly reduced , indicative of a disturbance in DE intercalation or delay of Afp down-regulation.We observed in Lhx1ΔEpi mutants that expression of the ADE markers promised A,B. Foxaivatives . Lhx1ΔEpmidbrain C. Howevepression C. The No reduced D,E. Afp Lhx1’s contributions to DE emergence, we exploited the well-characterized Afp:GFP transgenic reporter strain (high). At late bud (LB)-EHF stages in wild-type embryos, the lateral posterior surface is comprised predominantly of Sox17high DE cells, corresponding to the earliest ADE progenitors exiting the PS  expressed in the anterior midline mesendoderm and posterior notochord precursors initiates dorsal–ventral patterning of the overlying neural plate  via an autoregulatory feed-forward loop that establishes the L–R body axis  . Considering that the DE plays an essential role in relaying signaling cues from the node to the LPM  E. A simi mutants . Despite the LPM , failureLhx1 functional contributions, we tested the ability of wild-type and Lhx1-null embryonic stem (ES) cells to differentiate toward APS fates in the presence of high doses of ActivinA  . Of these, we focused on 25 transcripts misregulated at both time points: 22 down-regulated and three up-regulated  were markedly reduced. Additionally, several novel candidate Lhx1 target genes were identified: Pkdcc overlaps with Lhx1 expression in the AVE, ADE, and AME  to EHF stages . Interestingly, Shh, Col2a1, Epb4.1l5, and Shroom3—genes previously shown to be required for proper midline, node, and neural morphogenesis  or a C-terminal (Lhx1-SF) StrepFlag (SF) sequence  display a spectrum of node and midline defects . GREAT analysis revealed embryonic morphogenesis, anterior/posterior pattern specification, and morphogenesis of embryonic epithelium as terms associated with Lhx1-binding events D. De novAnalysis of the genomic distribution of binding sites relative to the nearest transcription start site (TSS) revealed peak enrichments 5–500 kb on either side of and not immediately proximal to (<5 kb) the TSS, suggesting that Lhx1 may preferentially bind to enhancer regions F. To evaHesx1 locus, including a regulatory element in the 5′ untranslated region (containing two Lhx1-binding motifs) and a 3′ distal enhancer . We conclude that Lhx1 directly regulates components of the Wnt pathway.Several putative Lhx1 target genes were represented in our ChIP data set. For example, Lhx1 binding was detected at two distinct regions at the enhancer . Lhx1 Chn exon 1 H. Embigiithelium , is down embryos  and, as  embryos A. Thus, zd8 gene H. Moreovcultures D. AdditiNodal enhancer (NDE) contains Rbpj-binding sites governing Notch-dependent Nodal expression  element responsible for controlling Nodal expression levels in the PS  and FM1 (forebrain/midbrain1) enhancer regions   revealedLhx1 expression in the epiblast. Moreover, ChIP-seq analysis revealed Lhx1 enrichment at the Tcf/Lef-dependent Nodal-proximal epiblast enhancer. These findings strongly suggest that Lhx1 acts synergistically with the Wnt signaling pathway to sustain the positive feedback loop that amplifies Nodal signaling in the PS necessary to specify APS progenitors . Procollagen IIA mutants display decreased Shh expression in the midline and partially penetrant head truncation phenotypes  and Shisa2  are significantly down-regulated. Importantly, ChIP-seq experiments identified several Wnt pathway genes—including Fzd8, Sfrp1, and Tcf7l2—as direct Lhx1 targets.The present results confirm and extend earlier work suggesting that tterning . Our traOtx2, coexpressed with Lhx1 in the AME, regulates Lhx1 expression levels  also phenocopy those seen in Lhx1-null embryos  from the German Research Center for Environmental Health. AsiSI-linearized vector (15 µg) was electroporated into CCE ES cells, and neomycin-resistant colonies were screened by Southern blot analysis using the restriction enzyme and the probe combination shown in Supplemental Figure. S2. The offspring derived from two independent correctly targeted clones were crossed with FLPe mice  embryos.;Sox2Cre , ROSA26RA26RLacZ , ROSA26RSA26RYFP , Lim1+/−   was intrLhx1-null ES cell lines were derived from Lhx1Δ/+ intercross blastocysts in 2i/LIF medium: N2B27 medium  supplemented with 1 µM PD0325901, 3 µM CHIR99021, and LIF (Millipore). Established ES cell lines were maintained in DMEM (Invitrogen) with 15% FBS, 1% nonessential amino acids, 0.1 mM β-mercaptoethanol, and 1000 U/mL recombinant LIF (Millipore). To induce DE formation, ES cells were seeded at low density (5 × 103 cells per milliliter) in the absence of LIF in bacteriological-grade plates, and 50 ng/mL ActivinA (R&D systems) and 20 ng/mL EGF (Peprotech) were added after 48 h in N2B27 medium ; and counterstained with DAPI and/or Alex fluor 633 phalloidin (Invitrogen). The antibodies used are listed in Supplemental Table S2. Laser-scanning confocal data were acquired on an Olympus FV1000 or Zeiss LSM880, and image data were processed using ImageJ, ZEN software, and Bitplane Imaris software.2. Specimens were mounted on aluminum stubs with double-sided tape and coated with gold and were viewed at 5 kV on a JEOL scanning electron microscope.Embryos fixed in 2.5% glutaraldehyde for at least 24 h were post-fixed with osmium tetroxide, dehydrated with a graded alcohol series, and critical point-dried from liquid COLhx1-null  and wild-type control ES cell lines induced to differentiate into DE at days 4, 5, and 6. cRNA was hybridized to Illumina Mouse WG-6 v2 Expression BeadChips as described previously (P < 0.05) were analyzed by using DAVID Bioinformatics Resources 6.7 (http://david.abcc.ncifcrf.gov).RNA was prepared and analyzed by one-step and quantitative RT–PCR (qRT–PCR) as described  using theviously . DiffereWISH and X-gal staining were performed as before . The antTo generate stably expressing SF-tagged Lhx1 sublines, linearized pCAG-SF-Lhx1-IRES-Puro , pCAG-Lhx1-SF-IRES-Puro , or pCAG-SF-Lhx1-cmER-IRES-Puro vectors were introduced by electroporation, and drug-resistant clones were selected in 1 μg/mL puromycin and screened by Western blot analysis. For SF-Lhx1-cmER activation, 1 μg/mL 4-hydroxytamoxifen  was added to the culture medium. P19CL6 cells were induced to differentiate via DMSO addition as previously described .P-value of ≤1 × 10−5 were considered significant. For comparison, H3K4me1, H3K4me3, H3K27ac, and p300 ChIP-seq peak coordinates were downloaded from NCBI Gene Expression Omnibus (GEO) accession numbers GSE31039 and GSE36027, while Otx2 and Foxa2 were downloaded from NCBI GEO accession numbers GSM1355169 and GSM993787, respectively. Regions of overlap between the ChIP-seq peaks identified in the present study and other published data sets were compared using custom Perl scripts.For ChIP-seq analysis, two independent SF-Lhx1-cmER-expressing clones and control P19CL6 cells were induced to differentiate for 4 d in the presence of DMSO and tamoxifen. ChIP was performed as described  using anStrepTactin pull-down experiments were performed using nuclear extracts from SF-Lhx1 , Lhx1-SF , or SF-Lhx1-cmER stably transfected or control P19Cl6 cells induced to differentiate for 4 d. Twenty micrograms of Avidin per milligram of extract was added to block endogenous biotin, and nuclear extracts were treated with 1.25 U/mg benzonase. For large-scale precipitation, 15 mg of nuclear extract was incubated with StrepTactin Superflow resin  for 2 h, and the bound fraction was recovered in elution buffer  and subjected to electrophoresis in a 4%–20% miniprotean TGX gel . Gel-excised fragments were digested with trypsin and analyzed by MS. Data were acquired on a Thermo Q Exactive mass spectrometer coupled to a Dionex RSLC nano-high-performance liquid chromatography system. Raw data files were converted to .MGF file format and analyzed using the Central Proteomics Facility Pipeline , and labThe microarray and ChIP-seq data have been deposited in NCBI GEO with accession number GSE70958.


Coronary artery disease (CAD), including myocardial infarction (MI), is a common complex disease that is caused by atherosclerosis. Although a large number of genetic variants have been associated with CAD, only 10% of CAD cases could be explained. It has been proposed that low frequent and rare genetic variants may be main causes for CAD. SIRT3, a mitochondrial deacetylase, plays important roles in mitochondrial function and metabolism. Lack of SIRT3 in experimental animal leads to several age-related diseases, including cardiovascular diseases. Therefore, SIRT3 gene variants may contribute to the MI development. In this study, SIRT3 gene promoter was genetically and functionally analyzed in large cohorts of MI patients (n = 319) and ethnic-matched controls (n = 322). Total twenty-three DNA sequence variants (DSVs) were identified, including 10 single-nucleotide polymorphisms (SNPs). Six novel heterozygous DSVs, g.237307A>G, g.237270G>A, g.237023_25del, g.236653C>A, g.236628G>C, g.236557T>C, and two SNPs g.237030C>T (rs12293349) and g.237022C>G (rs369344513), were identified in nine MI patients, but in none of controls. Three SNPs, g.236473C>T (rs11246029), g.236380_81ins (rs71019893) and g.236370C>G (rs185277566), were more significantly frequent in MI patients than controls (P<0.05). These DSVs and SNPs, except g.236557T>C, significantly decreased the transcriptional activity of the SIRT3 gene promoter in cultured HEK-293 cells and H9c2 cells. Therefore, these DSVs identified in MI patients may change SIRT3 level by affecting the transcriptional activity of SIRT3 gene promoter, contributing to the MI development as a risk factor. Coronary artery disease (CAD) is a common complex disease, which is a leading cause of human death around the world. Myocardial infarction (MI) is a specific type of CAD. Atherosclerosis, an inflammatory and metabolic disease, is the main cause for CAD and MI. Known risk factors include hypertension, smoking, diabetes, hyperlipoproteinemia and hypercholesterolemia. Though genome-wide association studies have identified more than 50 genetic loci to CAD, these genetic variants account for only 10% of cases . To dateSirtuins (SIRTs), a family of nicotinamide adenine dinucleotide (NAD+)-dependent deacetylases, have been involved in a wide range of cellular processes, including aging, calorie restriction, stress resistance, apoptosis, inflammation, mitochondrial function and circadian clock. Dysfunctional SIRTs have been implicated in a variety of age-related diseases, including cardiovascular diseases ,6. SevenSIRT3 has been demonstrated to protect cardiomyocytes from aging, oxidative stress and dysregulated metabolism, and suppresses cardiac hypertrophy ,16. In cSIRT3 gene expression has been studied and reported in several human diseases. SIRT3 gene expression is increased in hepatocellular carcinoma cells and human embryonic kidney cells (HEK-293) under hyperglycemic conditions . DecreasAll MI patients  were recruited between July, 2012 to November, 2014, from Cardiac Care Unit, Division of Cardiology, Affiliated Hospital of Jining Medical University, Jining Medical University, Jining, Shandong, China. All MI patients were diagnosed according to international guideline criteria: ischemic symptoms, ECG changes (ST-segment elevation or depression), typical rise of biochemical markers of myocardial necrosis (troponin or creatine kinase-MB), or coronary angioplasty. Patients with valvular heart disease, cardiomyopathy, myocarditis, or postrevascularization of the coronary arteries were excluded from this study. Ethnic-matched healthy controls  were recruited from the same hospital. Controls with familial MI history were excluded. In this study, 342 MI patients and 346 controls were initially recruited. Since DNA sequencing for some samples were failed, total 319 MI patients and 322 controls were finally included. The research was carried out according to the principles of the Declaration of Helsinki. This study was approved by the Human Ethic Committee of Affiliated Hospital of Jining Medical University. Written informed consents were obtained.Peripheral leukocytes were isolated and genomic DNAs were extracted. SIRT3 gene promoter (1200bp upstream to the transcription start site) was sequenced and analyzed. Two overlapped DNA fragments, 764bp (-1200bp~-437bp) and 678bp (-498bp~+180bp), were generated by PCR. PCR primers were designed based on genomic sequence of the human SIRT3 gene , which were shown in Expression vectors were constructed by subcloning wild type and variant SIRT3 gene promoters into luciferase reporter vector (pGL3-basic) and dual-luciferase activities were examined. Briefly, DNA fragments of wild type and variant SIRT3 gene promoters  were generated by PCR and then subcloned into KpnI and Hind III sites of pGL3-basic to generate expression vectors. The PCR primers with KpnI or HindIII sites were shown in The quantitative data were represented as mean ± SEM and compared by a standard Student's t-test. DSV frequencies in MI patients and controls were analyzed and compared with SPSS v13.0. P<0.05 was considered statistically significant.In this population, total 23 DSVs, including 10 SNPs, were identified. The locations and frequencies of the DSVs and SNPs were shown in Six novel heterozygous DSVs, g.236956G>T, g.236878_79ins, g.236634C>T, g.236583A>C, g.236460T>C and g.236458G>A, were only found in two controls. Chromatograms of these novel DSVs were shown in http://jaspar.genereg.net/). The DSVs identified in MI patients may abolish, create and modify the putative binding sites for transcription factors. For example, the DSV g.237307A>G may abolish the binding sites for SPIB [Spi-B transcription factor (Spi-1/PU.1 related)] and myeloid zinc finger 1, and create the binding sites for estrogen-related receptor beta and nuclear receptor subfamily 4 group A member 2. The DSV g.237270G>A may abolish the binding sites for hairy/enhancer-of-split related with YRPW motif protein 2 and the dimer between hypoxia-inducible factor 1-alpha and aryl hydrocarbon receptor nuclear translocator, and create the binding sites for doublesex and Mab-3 related transcription factor 3, HLTF (helicase-like transcription factor) and MEIS1. The SNP g.237030C>T (rs12293349) may create the binding sites for zinc finger and BTB domain containing 7B, insulinoma-associated 1, MEIS1 and SOX10 [SRY (sex determining region Y) box 10]. The DSV g.237023_25del may abolish the binding site for SPIB. The SNP g.237022C>G (rs369344513) may abolish the binding site for SPIB and create the binding site for FOXD2 (forkhead box factor D2). The DSV g.236653C>A may abolish the binding site for SOX10 and create the binding sites for caudal-related homeobox transcription factor 1, homeobox factors, motor neuron and pancreas homeobox 1, NKX6-1 , NKX6-2 and NK-related factor NOTO. The DSV g.236628G>C may abolish the binding sites for E74-Like factor 5, Ets-variant gene 5, chorion-specific transcription factor GCMb, neurogenic differentiation factor 2, SAM pointed domain containing ETS transcription factor and THAP domain-containing protein 1. The DSV g.236557T>C may abolish the binding sites for FOS transcription factor L1, transcription factor JUND and MEIS1 and create a binding site for HLTF. The SNP g.236473C>T (rs11246029) may abolish the binding sites for zinc finger protein 263, SP4 (specificity protein 4), KLF14 (Kruppel-like factor 14) and SP8, and create a binding site for E2F transcription factor 6. The SNP g.236380_81ins (rs71019893) may abolish the binding sites for SP1, SP2, KLF5 and KLF16, and create binding sites for TFAP2A , TFAP2B, TFAP2C, ZIC1 (zinc finger transcription factor 1) and ZIC4. The SNP g.236370C>G (rs185277566) may abolish the binding sites for early growth response protein 1, KLF16, SP1, SP2 and SP3.The SIRT3 gene promoter was analyzed with JASPAR program (Wild type and variant SIRT3 gene promoters were cloned into luciferase reporter vector (pGL3-basic) to generate expression constructs. After transfected into cultured cells, rat cardiomyocyte cells (H9c2) and human embryonic-kidney cells (HEK-293), dual-luciferase activities were assayed to examine the transcriptional activities of the SIRT3 gene promoter. In H9c2 cells, the DSVs only identified in MI patients or the DSVs found in MI patients with higher frequencies, g.237307A>G, g.237270G>A+g.236370C>G+g.236380_81ins, g.237030C>T (rs12293349), g.237023_25del, g.237022C>G (rs369344513), g.236653C>A+g.236473C>T and g.236628G>C, significantly repressed the transcriptional activities of the SIRT3 gene promoter to different extents P<0.05, . HoweverWe further examined effects of the DSVs on the transcriptional activities of the SIRT3 gene promoter in HEK-293 cells. As shown in To date, few studies have associated the SIRT3 gene with human diseases. A SNP rs11246020 (NC_000011.10:g.233067C>T) in the human SIRT3 gene, a nonsynonymous point mutation (V208I) which reduces its enzymatic activity, may enhance the susceptibility to metabolic syndrome . A SNP rThe human SIRT3 gene is localized to the chromosome 11p15.5, and encodes an NAD-dependent mitochondrial deacetylase of 399-amino acids containing an N-terminal mitochondrial targeting signal and a central catalytic domain –42. SIRTA series of downstream substrates of SIRT3, as well as histone, have been identified. SIRT3 deacetylates and activates several enzymes that are critical in maintaining cellular ROS levels and promote resistance to oxidative stress, including superoxide dismutase 2 (SOD2) and isocitrate dehydrogenase 2 (IDH2) ,45–49. IIn this study, we genetically and functionally analyzed the SIRT3 gene promoter. The DSVs and SNPs of the SIRT3 gene promoter identified in MI patients may alter transcriptional activity of SIRT3 gene promoter and change SIRT3 level, contributing to the MI development as a risk factor. The investigation into the molecular mechanisms by which SIRT3 gene promoter activity are affected are being conducted in our laboratory. Therefore, our findings may provide a genetic basis for further translational and clinical studies for MI patients.


Microtus levis in fibroblasts, trophoblast stem cells, and extraembryonic endoderm stem cells and confirmed origins locations by ChIP approach. We found that replication could be initiated in a significant part of XIC. We also analyzed state of XIC chromatin in these cell types. We compared origin localization in the mouse and vole XIC. Interestingly, origins associated with gene promoters are conserved in these species. The data obtained allow us to suggest that the X inactivation center of M. levis is one extended replication initiation zone.DNA replication initiates at specific positions termed replication origins. Genome-wide studies of human replication origins have shown that origins are organized into replication initiation zones. However, only few replication initiation zones have been described so far. Moreover, few origins were mapped in other mammalian species besides human and mouse. Here we analyzed pattern of short nascent strands in the X inactivation center (XIC) of vole  DHFR locus and mouse β-globin and IgH loci [DNA replication is required for duplication of the genome and subsequent cell division. First stage of this process is initiation, which occurs at specific sites termed replication origins. About 30,000–50,000 origins are activated in each cell cycle, nonetheless, the total amount of origins is much larger . SeveralIgH loci . AlthougIgH loci –9 recentIgH loci ,11. OrigIgH loci ,13. NeveMicrotus levis. XIC is required for inactivation of X chromosome in female mammals and comprises several long non-coding nuclear RNA, among which Xist, Tsix, and Enox are the most conservative [Xist, its transcript coats the entire X chromosome and leads to its heterochromatinization and gene silencing [Tsix is a negative regulator of Xist in rodents and represses Xist expression during early embryogenesis [Xist and Tsix differs between the active and inactive X chromosomes. Enox is involved in Xist activation and counting of X chromosomes [Mus musculus and M. levis [Enox, Xist, Tsix, and Slc7a3 [Enox, Xist and Tsix demonstrate high sequence similarity with their mouse orthologs. In contrast to mouse, vole XIC lacks a regulatory element, Xite, which was replaced with Slc7a3 gene as a result of chromosome rearrangement. Several origins were previously mapped in a part of the mouse XIC containing Enox, Xist, and Tsix [M. levis.In this study, we analyzed replication initiation and chromatin state in the X inactivation center (XIC) of vole ervative –20. Duriilencing –23. Tsixogenesis ,24–26. Tomosomes . AlthougM. levis ,28–30. Vd Slc7a3 ,31. Enoxand Tsix ,33. To uUsing qPCR, we analyzed pattern of short nascent strands (SNS) in vole extraembryonic cells—trophoblast stem (TS) and extraembryonic endoderm stem (XEN) cells and in somatic cells—fibroblasts. We found six SNS peaks corresponding to replication origins. Comparative analysis revealed that almost all origins in the XIC are conserved between mouse and vole. We confirmed origin locations within the vole XIC in fibroblasts by ChIP analysis of a subunit of origin recognition complex (ORC). We also analyzed chromatin marks specific to open and closed chromatin states. The data obtained allowed us to suggest that the vole XIC is one replication initiation zone.Xist exons 5, 6, and 7 (Enox promoter (site 3), in the exon 1 of Xist (sites 9 and 11), near the Xist 3’ end (site 19), in the Tsix promoter (site 25), in the Slc7a3 gene (site 29)  also shows significant enrichment in XEN cells. In fibroblasts, we identified four SNS peaks that located in the exon 1 of Xist (sites 9 and 11), near the Xist 3’ end (site 19), in the Tsix promoter (site 25)  Fig  and 1C. site 25) . SeveralTsix promoter and at the sites 14 and 15 located in the intron 3 and exon 4 of Xist correspondingly. Several ORC binding sites did not match SNS peaks and were localized at a distance. Some models suggest that replication initiation may occur at some distance from ORC binding site in the case of expansion of MCM complexes from this site or recruiting MCM to the distal sequences by DNA looping [To validate origin locations we analyzed ORC binding to the vole XIC in fibroblasts using ChIP approach. ORC is a key component of the pre-replication complex, which is required for origin licensing and activity . We used looping . Several looping ,46. In sin vitro that human ORC bound preferentially to single-stranded DNA and RNA containing G4 motifs [Xist exon 1, which had origin activity in all cell lines analyzed. This region contained five tandemly located G4 motifs and two of them showed the highest score predicted by QGRS mapper. However, only three of twelve ORC binding regions lied in a close proximity to G4 motifs in the vole XIC . Other ORC binding sites were located several kb from the nearest G4 motif. More precise mapping of ORC binding and additional investigations are needed to understand relationships between ORC and G4 motifs or structures in mammals.Recent genome-wide origins mapping studies have demonstrated that a significant part of the human, mouse and drosophila origins is associated with G-rich DNA, which potentially can form G-quadruplexes (G4 motifs) ,47. G4 m4 motifs . To inve4 motifs . Twenty-Xist exon 1, where we detected significant reduction of H3 level in all three cell lines  in the ll lines . We suppEnox (sites 2 and 4) and downstream of Tsix transcription start site (sites 22–24) (Xist 3’ end (site 19), in exon 1 of Tsix (site 24) and in the Slc7a3 5’ region (site 30) (Enox (site 4), in the promoter and exon 1 of Xist (sites 6–9), introns 1 and 3 of Xist  and in the region located 6 kb downstream of Tsix transcription start site (site 20)  and decreased towards the Xist promoter. In XEN and TS cells, the most significant H3K9ac peak is observed in first Tsix exon, that is consistent with high expression level of this gene in the extraembryonic cell lines  in fibroblasts  . In TS csite 30) . In fibrsite 20) . In the ines Fig . In controblasts .Enox (site 3) and Tsix promoter (site 25) , the Xist 3’ region (sites 16–18), from region located 5 kb downstream to region located 4 kb upstream of Tsix transcription start site (sites 21–26), and in the region located close to the Slc7a3 transcription start site (site 30)  and trimethylation of histone H3 on Lys 27 (H3K27me3). Unlike open chromatin, closed chromatin state may decrease origin efficiency. However, H4K20me1 is suggested to play an important role in origin licensing ,57. More 25) Fig  and 5B.  25) Fig . Howeversite 30) . FinallyXist allele on the active X chromosome is characterized by trimethylated histone H3 on Lys 9 and hypermethylated CpG dinucleotides [Xist promoter of M. levis, in contrast to the murine one, seems to have an open chromatin structure in fibroblasts. We suggest that the silent state of vole Xist may be maintained by antisense transcription of Tsix whose last exon overlaps the Xist promoter. Indeed, Tsix transcripts were previously identified in vole fibroblasts and other differentiated cell lines [It is interesting to note that in differentiated murine cells, promoter of the inactive leotides . The Xisll lines . HoweverMicrotus levis in three cell types  and identified that this locus contains six replication initiation sites.In the last years hundreds of thousands replication origins were identified in the human genome ,11, few Replication initiation pattern in fibroblasts is slightly different from that in XEN and TS cells. In fibroblasts, XIC contains less active origins. Origin efficiency and activity may change during cell differentiation as has been shown in several works ,11,39–42DHFR locus of Chinese hamster, contains large number of pre-RC binding sites and the strongest sites of pre-RC binding do not coincide with preferred sites of replication initiation [ORC binding was analyzed in XIC using ChIP approach to confirm origin locations. We revealed at least twelve ORC binding regions. Most ORC binding regions were associated with nascent strands peaks or located proximately. High ORC density in the vole XIC also may imply that XIC represents a replication initiation zone. The most studied replication zone, itiation .Xist. It should be noted that λ-exonuclease digestion is less efficient on DNA with high GC content [Replication origins of higher eukaryotes are not characterized by consensus sequence. However, several genome-wide studies report that a significant part of murine and human origins is associated with G4 motifs ,47. G4 m content ,68. The  content .Drosophila melanogaster and Arabidopsis thaliana genomes [Tsix promoter was active in all three cell lines whereas the region was acetylated in XEN and TS cells but not in fibroblasts. The opposite situation was observed for the origin in the Xist exon 1. In summary, we did not find a strong association of open chromatin marks with origins activity in XIC. We did not reveal ORC association with H3.3 histone variant. Some evidences suggest that only double histone variant H3.3/H2AZ corresponding to labile nucleosomes is colocalized with ORC binding sites [Only part of the total pool of origins is known to be activated in each S phase. It is still poorly understood what factors determine origin choice. Origin firing may be regulated by chromatin structure. We investigated open chromatin marks  and closed chromatin marks (H4K20me1 and H3K27me3) in the vole XIC in XEN, TS cells, and fibroblasts. It is known that histone acetylation is often associated with active replication origins and may stimulate origin firing –53. H3.3 genomes –71. Origng sites ,73.Enox, in the Tsix promoter in XEN cells, the exon 1 of Xist, and Slc7a3 in XEN and TS cells. Genome-wide analysis of human replication origins and H4K20 monomethylation revealed that the histone modification located to the regions with high origin density and colocalized with origins [Xist 3’ end and in the Tsix promoter. Identification of replication timing pattern in vole XIC and its association with chromatin marks analyzed will be subject for further investigations.H4K20me1 is thought to participate in origin licensing ,57. H4K2 origins . H4K20me origins . We founEnox promoter, the promoter, exon 1 and intron 7 of Xist, and the Tsix promoter. We assume that origins associated with Enox, promoter and exon 1 of Xist, and promoter of Tsix are conserved in the two rodent species  cells and fibroblasts are similar [Several origins were previously mapped in the mouse XIC ,33. The  species . These o similar ,75. TherDHFR locus, mouse β-globin and IgH loci [M. levis is a replication initiation zone.To date only few mammalian loci have been described as replication initiation zones. These are Chinese hamster IgH loci ,5,6. MouIgH loci . Recent IgH loci ,11. BaseThe study was carried out according to “The Guidelines for Manipulations with Experimental Animals.” The study was approved by the Ethical Committee of the Institute of Cytology and Genetics, Novosibirsk, permit number: . Animals were provided by Animal House Facility of the Institute of Cytology and Genetics SB RAS. Animals were sacrificed by cervical dislocation.M. levis were derived and cultured as described previously [Primary embryonic fibroblasts of eviously ,78. TS aeviously ,37,38.Total DNA was isolated with DNAzol from dividing cells according to the manufacturer’s instructions with addition of proteinase K treatment step as described previously . Nascent7 cells was carried out by adding formaldehyde (Sigma) to a final concentration of 1% to the culture medium for 5 minutes at room temperature and stopped by addition of glycine (Sigma) to a final concentration of 125 mM. Cells were washed twice with ice-cold PBS and lysed in Lysis Buffer №1 . Then nuclei were incubated in Lysis Buffer №2  for 10 minutes, and chromatin was sheared in Lysis Buffer №3  by sonication into fragments ranging from 100 to 600 bp. 1/10 volume of 10% Triton X-100 was added to sonicated chromatin, cell debris was removed by centrifugation at 14000 rpm for 10 minutes. Supernatant was collected and incubated with antibodies overnight. As negative control of ChIP we performed reaction without antibodies. Dynabeads Protein G (Life Technologies) was used to collect antibody-protein complexes. The complexes were washed five times with RIPA buffer  and once with TE  containing 50 mM NaCl. After elution with 1% SDS-50 mM Tris-HCl pH 8.0–10 mM EDTA crosslinks were reversed by overnight incubation at 65°C. Proteinase K was added to a final concentration of 200 μg/ml for 2 h at 55°C. DNA was extracted with QIAquick PCR purification kit (QIAGEN). Obtained DNA was analyzed using real-time PCR. Significance of differences was estimated using one-way ANOVA test. The antibodies used for ChIP are presented in ChIP was performed according to a protocol published previously  with sevPCR was carried out with Taq DNA polymerase using iCycler iQ5 real-time detection system (Bio_Rad) or LightCycler 480 PCR System (Roche). Detection of amplificated products was performed using TaqMan probes. Sequences of primers and probes are given in RNA was isolated using TRIzol from XEN, TS cells, and fibroblasts. cDNA was synthesized using total RNA by SuperScript III (Life technologies) reverse transcriptase at 55°C according to the manufacturer’s instructions. PCR was carried out at the following parameters: 95°C for 5 min and 35 cycles of 95°C for 15 s, 58°C for 15 s, and 72°C for 30 s. Primer pairs are given in Western blotting was performed as described previously . Total cStatistical analysis was performed using one-way ANOVA and F-test. Variances between sites were compared. The value at each site was compared with the mean value obtained from all sites in the locus using F-test. In the analysis of results obtained from ChIP with ORC4 antibodies the value at each site was compared with the values at neighboring sites using F-test.S1 Checklist(PDF)Click here for additional data file.S1 Fig(TIF)Click here for additional data file.S2 FigDiagram shows results of quantitative PCR analysis of ChIP with antibodies to H3 in XEN, TS cells, and fibroblasts. Legends are shown in the S2 Fig. At least two independent experiments were performed, PCR were made in duplicate. ±SD is given. Significant differences * P≥0.95 (one-way ANOVA test).(TIF)Click here for additional data file.S3 Fig(TIF)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 Table(DOCX)Click here for additional data file.S4 Table(DOCX)Click here for additional data file.