Connection of the heart to the systemic circulation is a critical developmental event that requires selective preservation of embryonic vessels (aortic arches). However, why some aortic arches regress while others are incorporated into the mature aortic tree remains unclear. By microdissection and deep sequencing in mouse, we find that neural crest (NC) only differentiates into vascular smooth muscle cells (SMCs) around those aortic arches destined for survival and reorganization, and identify the transcription factor Gata6 as a crucial regulator of this process. Gata6 is expressed in SMCs and its target genes activation control SMC differentiation. Furthermore, Gata6 is sufficient to promote SMCs differentiation in vivo, and drive preservation of aortic arches that ought to regress. These findings identify Gata6-directed differentiation of NC to SMCs as an essential mechanism that specifies the aortic tree, and provide a new framework for how mutations in GATA6 lead to congenital heart disorders in humans. In mammals, effective delivery of oxygenated blood from the heart to the systemic circulation relies on physical separation from deoxygenated blood in the pulmonary circulation. This separation is contingent upon two critical developmental events: cardiac septation, including division of the outflow tract (OFT) into the ascending aorta and the pulmonary trunk ; and comThis need for separation and the consequences of cyanosis have made understanding the mechanism(s) of OFT septation and AA remodeling a high priority. In addition to haemodynamics , cardiacBy combining microdissection and global transcriptomes analysis, we identify the transcriptional signature underlying NC differentiation to vascular SMCs, uniquely in the aortic arches destined for reorganization into the mature aortic tree. Computing TFs binding levels predicts GATA as main transcriptional regulators in the areas colonized by cardiac NC. We show that Gata6 is sufficient to promote NC differentiation to SMCs in vivo, and also to preserve AAs that normally regress. Our work identifies Gata6 as a crucial regulator of vessel fate and vascular remodelling, both of which are critical for normal development of the mature aortic tree.Acta2, Tagln, Cnn1 and Myocd, which are highly expressed in SMCs  and OFT at two defined developmental stages, E10.5  and E11.5 (TS19), by RNA-seq analysis . The las in SMCs . Myocd entiation  and funcntiation . In sum,Transcriptomic analyses revealed a high enrichment in transcripts related to the process of SMCs differentiation in the PBA/OFT relative to BA2. Therefore, we analyzed the presence of SMCs in the BA region of mouse embryos. BAs are traversed by five embryonic AAs, which connect the heart with the paired dorsal aortae and allow blood circulation throughout the embryo. AAs develop in a rostro-caudal sequence, beginning around E8.5 with formation of the AA1, which traverses BA1 . Within We next examined the distribution of vascular SMCs in these vessels. At E9.5, none of the AAs was associated with vascular SMCs, but we detected vascular SMCs in the dorsal aorta and the OFT . At E10.Gata6 conditional inactivation in the cranial NC and in SMC results in abnormal development of the great vessels and OFT  driving gene expression in PBA/OFT. Binding of multiple TFs, or collaborative DNA binding, can counteract nucleosome repositioning, facilitates access of each TF to DNA and leads to increased binding levels . We reas and OFT . Consist PBA/OFT . Next, w PBA/OFT . Consist PBA/OFT , and in  PBA/OFT , just be PBA/OFT .Gata6 and Gata4 loci, which suggest that GATA TFs regulate their own genes in the PBA/OFT , which is essential for cardiac NC differentiation to SMCs (Myocd (Jag1 and Myocd loci (Jag1 Cis Regulatory Element (CRE) one and Myocd CRE 1–2; VISTA was reported to drive heart-specific activity , we identified 5122 bound regions with fold enrichment (FE) ≥ 10 . Gata6 p PBA/OFT . Accordita6 gene . To charta6 gene   to monitor SMC differentiation, and observed ectopic SMCs in the BA2 of all embryos expressing Gata6 in this BA at E10.5 (5/5)  5D and . Small c0.5 3/5; –4. Conve0.5 3/5;  or unrel0.5 3/5; . We extrng Gata6 . ConcomiThe mature arterial tree emerges from the selective regression, survival and reorganization of pre-existing embryonic vessels. Migration of the cardiac NC is a vital requirement for this process. However, how the cardiac NC instructs remodeling and specifies particular AAs for survival has been unclear. Here we identify the TF Gata6 as a crucial regulator of NC differentiation to vascular SMC fates. We find that, in normal embryos, the distribution of Gata6 in the branchial area mirrors colonization by cardiac NC, as it is highly abundant in BAs3-6 and essentially absent from the BAs1-2. Additionally, we show that Gata6 is sufficient both to initiate SMC development and to support the survival of those AAs that are normally not populated by cardiac NC, and regress at early stages of AA reorganization. We propose that Gata6 instructs cardiac NC to generate SMCs, and that the subsequent association of those SMCs with the caudal AAs selects these vessels for reorganization into the mature circulation .Gata6 and Gata4 loci, together with the high levels of Gata4, Gata5 and Gata6 transcripts in the PBA/OFT, suggest that GATA TFs regulate their own genes. However the mechanism that initiates and restricts expression of GATA TFs to the cardiac NC is not clear. The BA2 appears to be a non-permissive environment for cardiac fate . Positive auto-regulatory loops are a common feature of gene regulatory network. Gata6 occupancy at iac fate . Secondaiac fate  progenitiac fate , in the Gata4, Gata5 and Gata6 in PBA/OFT relative to BA2. Computing binding levels of general regulators, combined with sequence analysis, is a novel approach which successfully identified tissue-specific instances of combinatorial binding. TFs collaborate in competing with nucleosome to gain access to underlying DNA  via direct activation of Myocd and Jag1, to promote differentiation of SMCs.Sequence analysis predicted GATA TFs binding at regions with high Meis binding signal in the PBA/OFT. Enrichment of GATA signature motifs at these regions was accompanied by a significantly higher expression of ying DNA . Increas1, Myocd . GenomicMyocd expression  causes Alagille syndrome, a congenital disorder associated with OFT and great vessels defects , become associated with SMCs, while vessels that regress (AA1-2) do not. This correlation extends to a number of experimental conditions affecting normal remodeling of the AAs. For instance, in  by SMCs . Similarby E11.5 . Likewisby E11.5 . In embrby E11.5 . Thus, Sby E11.5 . Indeed,by E11.5 . TogetheChanges in blood flow lead to asymmetric remodelling of the embryonic circulation, and regression of right AA6 . We cannWild-type (CD1) mice were time-mated to obtain embryos for microdissections. For experiments, embryos were not selected for gender and were used between E10.5 and E11.5.Wild-type zebrafish were raised in the Animal Facility at the University of Manchester and in the University of Massachusetts Medical Center Zebrafish Facility.Experiments on animals followed the local  legislations concerning housing, husbandry, and welfare.a2::Gata6 transgenic construct contained the BA2 enhancer of the Hoxa2 gene  series and stored at −20°C until further processed for imaging. For gene expression analysis, embryos were isolated at E10.5 and BA2 were dissected from individual embryos and snap frozen in dry ice. RNA was extracted from individual BA2 pairs using RNeasy Plus Micro Kit (Qiagen), transcribed into cDNA and analysed using StepOnePlus Real_Time PCR Systems (Life Technologies) and PrimerBank primers , cloned into pCR8/GW/TOPO vector (Life Technologies) and recombined using the Gateway system (Life Technologies) to an enhancer test vector that includes a strong midbrain enhancer  as an internal control. The mutant enhancers were generated by Genscript in a pUC57 vector, PCR amplified and cloned into Minitol2-GwB-zgata2-GFP-48 as described above. Zebrafish embryos were collected from natural spawning. The plasmid DNA was injected into the cytoplasm of embryos at the one-cell stage. Injected embryos were visualized at 48 hr post fertilization using a Leica fluorescent stereomicroscope. Fisher Exact test was performed to test the changes in activity of the wildtype and mutant enhancers.AB_10705521), Meis  and H3K27ac . Following Chromatin-immunoprecipitation (ChIP), DNA libraries were constructed using the TruSeq ChIP Sample Preparation Kit . The final purified product was sequenced on an Illumina HiSeq2500 instrument. For histone ChIP-seq, single-end reads were trimmed to 50 base pairs (bp) and mapped to mouse reference sequence (mm9/NCBI37) using Bowtie v1.0.0 (RRID:SCR_005476). Peak calling was done using MACS2.0 (SCR_013291). For Gata6 and Meis ChIP-seq, read pairs (R1 and R2) were filtered using Trimmomatic v0.32 (SCR_011848) using paired-end mode, to remove adapters, and truncated reads (3') with a base sequence quality of <Q20. Filtered reads <50 bp were removed. Filtered paired reads were mapped to mouse reference sequence (mm9/NCBI37) using Bowtie2 v2.2.3 with default parameters. Mapped paired-reads were filtered with 'samtools' v0.1.19, to remove reads with mapping quality <Q30 and discordant pairs (i.e. incorrect orientation and/or > 500 bp apart). Peak calling was done using MACS 2 v2.1.0. Binding regions were reported with a minimum q-value of 0.05. For all ChIP-seq only paired reads belonging to chromosomes 1–19, X and Y were used in downstream analyses. Narrow peaks (TF ChIP-seq) were filtered using FE ≥ 10. Each experiment was performed in duplicate; for H3K27Ac and Meis ChIP-seq, two replicates were intersected and peaks present in both replicates were used in downstream analyses. For Gata6 replicate 1 was used for downstream analysis; replicate 2 resulted in fewer binding regions with FE ≥ 10 (=693), which were almost entirely contained in replicate 1 (97%). Details of all ChIP-seq experiments  are provided in SCR_005807) (http://great.stanford.edu/) and the ‘basal plus extension’ association rule. The comparison of genome coordinates used GALAXY (findMotifGenome’ module of the HOMER package (SCR_010881) on Gata6 peaks with FE ≥ 10, extended 100 bp from the summit position in each direction. DiffReps (SCR_010873) was used to detect differential binding of Meis across PBA/OFT and BA2. Meis ChIP-seq experiments in PBA/OFT and BA2 (binding locations) were compared using a 200 nt sliding window. Regions with logFC ≥3 binding in PBA versus BA2 were selected and intersected with Meis ChIP-seq 200nt summits in PBA, FE ≥ 10, for de novo motif discovery using HOMER. The workflow is summarized in CD1 mice were time-mated to obtain branchial arches and OFT from E115 embryos. ChIP-seq has been described in detail . The ant MACS2.0  (RRID:SCic v0.32  (RRID:SC_005807)   using the RNA-seq data. H3K27ac signals for all DE genes were represented by the average RPM (reads per million mapped reads) values of all peaks annotated to the respective gene. For all upregulated (or downregulated) genes, average RPM of their associated regions in PBA (or BA2) were divided by the average RPM values of the corresponding regions in BA2 (or PBA).Heatmaps for Gata6 and H3K27ac peaks in PBA/OFT and BA2 were generated using the histogram matrix produced by ‘SCR_013035)  (SCR_012802) , pooling 3–5 pairs of BAs for each sample. Embryos with 38–39 (TS17) and 48–50 somites (TS19) were used for E10.5 and E11.5 time points, respectively. RNA-seq was performed in duplicate and the quality of duplicates assessed using PCA. Library preparation of samples was performed using the Illumina TruSeq Stranded mRNA Sample Preparation Kit (Illumina). Fastq files for each tissue were mapped against the mouse genome (mm9) using the spliced aligner Tophat   with def_001647) , which e_012802) . Multipl_012802) . LogFC oAB_393571, 1:100) or Gata6, washed and incubated overnight at 4°C with α-SMA, Cy3-conjugated  and goat anti-rat IgG Alexa 488-conjugated . After washing, embryos were dehydrated and mounted in Methyl Salicylate  for clearing. Images were collected on a Leica TCS SP5 AOBS inverted confocal microscope and processed using ImageJ (v1.48). Amira software  was used to create the reconstructions of complete z-stacks of wild-type and transgenic embryos. Sagittal sections of paraffin embedded E10.5 embryos were labeled using the antibodies described above. In situ hybridization was carried out as described previously (Meis1 probe (a gift from Dorothea Schulte).Immunofluorescence on whole mount embryos was adapted from previously described protocols . Embryoseviously , using MThe ChIP-seq and RNA-seq experiments have been submitted to ArrayExpress. . In the interests of transparency, eLife includes the editorial decision letter and accompanying author responses. A lightly edited version of the letter sent to the authors after peer review is shown, indicating the most substantive concerns; minor comments are not usually included.eLife. Your article has been reviewed by three peer reviewers, and the evaluation has been overseen by a Senior Editor. The reviewers have elected to remain anonymous.Thank you for submitting your work entitled "A tissue-specific, Gata6-driven transcriptional program instructs remodeling of the mature arterial tree" for consideration by eLife.Our decision has been reached after consultation between the reviewers. Based on these discussions and the individual reviews below, we regret to inform you that your work will not be considered further for publication in eLife. However, they also raised many concerns that would need to be dealt with for the manuscript to be considered further. Because eLife has a policy that papers are only considered for revision if they can be revised within a two month time-frame. The consensus was that the required changes would take considerably longer. Therefore, we cannot accept the paper at this time but would encourage you to make the required changes and submit a new paper that addresses the reviewers' comments. We would then make every effort to return the paper to the same reviewers. I hope you find the reviews helpful in revising the manuscript.As you will see from the full reviews, appended below, the reviewers find your paper very interesting and potentially appropriate for Reviewer #1:The manuscript by Losa et al. describes a transcriptional program that is driven by GATA-6 and instructs the remodeling of the arterial tree, as indicated in the title. The results show that the neural crest cells differentiate into vascular smooth muscle cells only around aortic arches that are going to survive and reorganize. This process is driven by the transcriptional program driven by GATA-6.This is a very interesting paper that however suffers from some bias that are not necessarily introduced by the AA, but are present in most of the literature on Chipseq and similar technologies. However these bias do not affect the final conclusions of the manuscript nor the results of the reported experiments, I feel. However, I believe that they should be taken care of. The fact that several other AA draw conclusions in a certain way does not mean that their conclusion is correct.I have the following observations.a) The authors have used Meis1 binding sites to detect tissue-specific combinatorial TF occupancy. They should more carefully explain the basis of this choice.b) The AA use data-base consensus sequences to identify, for example, Meis1 binding sites. In particular they use a six bp consensus. This is not correct. Indeed, this consensus is used by other transcription factors of the same family and, in particular, by the Pbx1-Meis1 transcription dimer. This dimer, however, also binds to the same consensus that the AA identify as Hox-Pbx. This is not a mistake as this binding site indeed binds ALSO Hox-Pbx. However, the AA's choices may in part bias the results on the identification of other TF, or at least of their selectivity.I don't believe that these problems affect the results presented in the paper. However, the literature, in particular the data banks, are too full of ill-conceived data, like those on some consensus binding sites. The AA do not mention wherefrom they obtain the used consensus sites. I stress the importance of the use of the data obtained in actual experiments rather than those from data banks.Reviewer #2:Losa et al. provided evidence for the identification of a GATA transcriptional program in posterior branchial arch tissues that is required for the survival and reorganization of aortic arches. Analysis of ChIP-seq data allows the characterization of GATA6 peaks at the jag1 and Myocd loci. The authors hypothesize that regulation of these genes would promote development of the aortic arches into mature bloods vessels.In general, this study is an interesting investigation combining ChIP-seq data and in vivo validations. This is interesting because GATA6 is a critical factor for cardiovascular development and that remodeling of branchial aortic arches is still unclear. Yet, I remain unconvinced as to the role of GATA6-Jag1/Myocd in the branchial arches could regulate the survival and reorganization of these tissues. While, the regulation of Jag1 and Myocd by GATA6 is likely, the mechanistic insights from this paper remain incomplete and could benefit from a more expanded analysis.1) Rostro-caudal progression of branchial arches depends on a developmental timing of the embryogenesis. The choice of developmental stages E10.5 and E11.5 for a comparative analysis does not allow a perfect differential study. The authors should indicate why they used these stages for their RNA-seq analysis.2) In 3) Vascular persistence of the most anterior aortic arches could be associated with the formation of the head, which reduce the pressure of blood in this region. Yashiro et al. (2007) have demonstrated that blood pressure is responsible for remodeling of the great arteries. The authors should discuss how haemodynamics could influence genetic program during the formation of aortic arches.4) The use of Meis binding to detect tissue-specific is intriguing. The author should better justify their choice, especially because their model proposed at the end does not include such 'ubiquitous' factor.5) Motif for GATA transcription factors was among the most highly overexpressed sequences but was not alone since other Forkhead, T-box or TEAD motifs were also enriched, together with Meis motifs. The authors use a shortened to jump to GATA without clear arguments.6) Sequence for the TEAD family of transcription factors was often associated with Gata6 peaks . Again, 7) The authors used zebrafish to validate the Cis Regulatory Element identified in Myocd and jag1 loci. However, Data presented are not convincing, particularly in terms of images quality. Please clarify whether the CREs are expressed in zebrafish vascular system.8) Gata6 mutant should be used to validate whether jag1 and Myocd are regulated by this factor.9) a2:Gata6 embryos were used as a model of gain of function. The authors should use these embryos to show an up-regulation of jag1 and Myocd. Persistence of AA2 is not obvious in the embryos showing in 10) "The presence of SMCs in all the transgenic embryos with persistent AA2 suggests that the primary effect of Gata6 is to generate SMCs and that the presence of these cells can, in most cases, stabilize the AA2 and promote its survival." This sentence is confusing, if the AA2 survivals, that implies that there is less apoptosis. It does not seem that this mechanism was involved in the persistence of the AA2.Reviewer #3:This is a very nicely presented paper that uses a combination of embryo imaging, transcriptome analysis, ChIP-seq analysis and in vivo mutagenesis (mouse and fish) to identify a critical role for Gata6 in controlling smooth muscle cell (SMC) differentiation from neural crest cells to support the developing posterior arch arteries. Importantly the authors demonstrate that it is the recruitment of these SMC that is crucial for the maintenance of the posterior arch arteries so that they can persist and remodel into the aortic arch arteries, whereas the anterior arches, without recruitment of SMC, are able to regress. Forced expression of Gata6 in Hox-expressing neural crest cells causes the anterior arch arteries to persist and become invested in SMC.The sequencing and bioinformatics analysis all appears to have been conducted to a very high standard.There are some considerations, however, with the embryo work that need to be addressed.The development of the arch arteries (AA) in the mouse is a rapid process with the formation and regression of the first 2 AA occurring within the E9.5 stage, and the remodelling stage occurring during E11.5. Therefore it is important that the authors accurately describe the stage of embryo development, particularly within E9.5, at analysis. This is conventionally done by somite counting and should be achievable from the images already acquired. The authors should also state how well stage-matched the embryos are within the experimental groups, and this should be done for all experiments where embryos are used (immunostaining and sequencing). It is well known that embryos from the same litter can be at different stages of development as determined by somite number.Only whole-mount images of stained embryos (immuno and in situ) are presented. Although the images are of high quality it is not always obvious which tissue type or layer is being stained. Confirmation can only be achieved through double immunostaining of sections, or sectioning of the in situ stained embryos. This would clarify the location of the cells stained and give confidence to the conclusions drawn from these images. In particular this would be useful for the Gata6/SMA stained embryos shown in [Editors’ note: what now follows is the decision letter after the authors submitted for further consideration.]eLife. Your article has been reviewed by three peer reviewers, and the evaluation has been overseen by Marianne Bronner as the Senior Editor and Reviewing Editor. The reviewers have opted to remain anonymous.Thank you for submitting your article "A tissue-specific, Gata6-driven transcriptional program instructs remodeling of the mature arterial tree" for consideration by The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.Summary:This much improved manuscript investigates the genetics underlying development of the connection of the heart with systemic circulation. Using several embryonic species, the authors conclude that preservation of some  embryonic vessels results from differentiation of neural crest cells into smooth muscle cells around those vessels that are due to be preserved and reorganized. They identify Gata 6 as crucial in this process. Gata 6 is expressed in smooth muscle cells and drives their differentiation through MyoCD and Jag1. They also identify Meis1 as an important player in the process since it allows Gata 6 binding through a chromatin effect.Essential revisions:1) The manuscript needs some rewriting as it is difficult to read because the "real" ChIP-seq peaks cannot be derived from data with a threshold q<0.05 which is not sufficiently stringent compared to papers using comparable techniques. For example, this results in the identification, of 50,000 Meis1 peaks whereas, using a more stringent threshold one gets 5,000. In the end, the authors only use those peaks and genes which have a high fold enrichment. Are the conclusions based on "all" peaks or only on the subset with high fold enrichment? The authors should clarify this and are encouraged to reevaluate their data using higher stringency.2) The reader needs a clearer view of the actual data. A table stating the total number of reads, number of identified peaks (or reads), statistical thresholds, should be presented. [Editors’ note: the author responses to the first round of peer review follow.]Reviewer #1:[…] This is a very interesting paper that however suffers from some bias that are not necessarily introduced by the AA, but are present in most of the literature on Chipseq and similar technologies. However these bias do not affect the final conclusions of the manuscript nor the results of the reported experiments, I feel. However, I believe that they should be taken care of. The fact that several other AA draw conclusions in a certain way does not mean that their conclusion is correct.I have the following observations.a) The authors have used Meis1 binding sites to detect tissue-specific combinatorial TF occupancy. They should more carefully explain the basis of this choice.The same point has been raised by reviewer 2; we thank both reviewers for the opportunity to provide additional information to clarify the rationale of this approach.The approach we have used is based on the observation that two or more TFs (binding to relatively short stretches of DNA) can compete with the repositioning of nucleosome on DNA, while TF binding in isolation are not so efficient in doing that. Based on this phenomenon, or ‘collaborative DNA binding’, we expect binding of TFs to DNA to become more efficient (i.e. higher binding levels) in the event of combinatorial binding. We would also expect combinatorial binding (and the binding motifs recognized) to reflect concentration of TFs in the nucleus, i.e. to be tissue-specific. Based on the above, changes in the binding levels of any TF across multiple tissues (provided the TF of choice is present in multiple tissues), could be used as ‘sensors’ to detect tissue-specific instances of TF combinatorial occupancy. Meis is expressed in both BA2 and PBA. Most importantly, Meis binding is very widespread (Meis TFs bind to tens of thousands of regions) and lends itself very well to the interrogation of a large portion of the genome.We have added a few explanatory sentences to the Results section , to explain this approach. To support the choice of Meis as a widespread ‘sensor’ for collaborative binding, we analysed ATAC-seq data obtained from E10.5 BA2. We found an extensive overlap between Meis binding and ATAC-seq, with Meis occupying 60% of accessible chromatin regions in the BA2. This overlap is quite remarkable when considering the different experimental approaches used (ATAC-seq vs Meis ChIP-seq) and the different embryonic stage (E10.5 vs E11.5). This analysis has been added to b) The AA use data-base consensus sequences to identify, for example, Meis1 binding sites. In particular they use a six bp consensus. This is not correct. Indeed, this consensus is used by other transcription factors of the same family and, in particular, by the Pbx1-Meis1 transcription dimer. This dimer, however, also binds to the same consensus that the AA identify as Hox-Pbx. This is not a mistake as this binding site indeed binds ALSO Hox-Pbx. However, the AA's choices may in part bias the results on the identification of other TF, or at least of their selectivity.We entirely agree that it is important to use motifs derived from actual experiments. Whenever possible (in most cases), we have used motifs identified in ChIP-seq experiments  Rostro-caudal progression of branchial arches depends on a developmental timing of the embryogenesis. The choice of developmental stages E10.5 and E11.5 for a comparative analysis does not allow a perfect differential study. The authors should indicate why they used these stages for their RNA-seq analysis.We carefully considered including earlier time points over a developmental time course to allow comparing earlier BA2 stages versus later PBAs stages. As part of the rostro-caudal progression mentioned by the reviewer, new AAs are being formed posteriorly. The area corresponding to the PBAs changes over time, with the addition of new arteries from E9.5 until E10.5. Specifically, AA4 and AA6 appear at E10.0 and E10.5 respectively. These changes in the PBA tissues are not ideal for the BA2/PBA comparison . Taking this into account, we decided to use E10.5 as the earliest time stage, because the PBA is ‘complete’, and E11.5 as the latest stage, because shortly after (E12.0) the aortic arches lose their left-right symmetrical organization. To take into account rostro-caudal progression we compared late PBA (E11.5) to early BA2 (E10.5), but this did not change the results, presumably because differences are already established at the earliest time point .2) In The enrichment of myocardium transcripts is indeed another feature of the PBA/OFT tissue. It is most likely caused by the presence of the OFT, included to preserve the physical integrity of the AA3-6 and also as a landmark to allow dissection of comparable material across different embryos. While this feature does not prevent the identification of differences between anterior and posterior aortic arches, we agree with the reviewer that is important to clarify this point.The following sentence has been added to the Results section:“PBA/OFT-enriched genes also included transcripts highly expressed in the myocardium, owing to the OFT component .”3) Vascular persistence of the most anterior aortic arches could be associated with the formation of the head, which reduce the pressure of blood in this region. Yashiro et al. (2007) have demonstrated that blood pressure is responsible for remodeling of the great arteries. The authors should discuss how haemodynamics could influence genetic program during the formation of aortic arches.This is indeed a valid suggestion; we have discussed a potential role for this mechanism at the end of the Discussion.4) The use of Meis binding to detect tissue-specific is intriguing. The author should better justify their choice, especially because their model proposed at the end does not include such 'ubiquitous' factor.The approach we have used is based on the observation that two or more TFs (binding to relatively short stretches of DNA) can compete with the repositioning of nucleosome on DNA, while TF binding in isolation are not so efficient in doing that. Based on this phenomenon, or ‘collaborative DNA binding’, we expect binding of TFs to DNA to become more efficient (i.e. higher binding levels) in the event of combinatorial binding. We would also expect combinatorial binding (and the binding motifs recognized) to reflect concentration of TFs in the nucleus, i.e. to be tissue-specific. Based on the above, changes in the binding levels of any TF across multiple tissues (provided the TF of choice is present in multiple tissues), could be used as ‘sensors’ to detect tissue-specific instances of TF combinatorial occupancy. Meis is expressed in both BA2 and PBA. Most importantly, Meis binding is very widespread (Meis TFs bind to tens of thousands of regions) and lends itself very well to the interrogation of a large portion of the genome.We have added a few explanatory sentences to the Results section , to explain this approach. To support the choice of Meis as a widespread ‘sensor’ for collaborative binding, we analysed ATAC-seq data obtained from E10.5 BA2. We found an extensive overlap between Meis binding and ATAC-seq, with Meis occupying 60% of accessible chromatin regions in the BA2. This overlap is quite remarkable when considering the different experimental approaches used (ATAC-seq vs. Meis ChIP-seq) and the different embryonic stage (E10.5 vs E11.5). This analysis has been added to 5) Motif for GATA transcription factors was among the most highly overexpressed sequences but was not alone since other Forkhead, T-box or TEAD motifs were also enriched, together with Meis motifs. The authors use a shortened to jump to GATA without clear arguments.We have rephrased the text to explain the focus on GATA TFs:Gata6, together with Gata4 and Gata5, wasamong the most significantly enriched transcripts in PBA/OFT  Sequence for the TEAD family of transcription factors was often associated with Gata6 peaks . Again, We have explored the potential role of the GATA/TEAD module in the posterior aortic arch transcriptional network. First, we calculated the co-occurrence of TEAD and GATA motifs in Gata6 peaks. We found that the occurrence of TEAD and GATA (most Gata peaks contain a GATA motif) is much more frequent than expected by chance  and suggests that TEAD and GATA may indeed bind together in this embryonic area. Within Gata peaks, the average distance of the GATA-TEAD motifs is about 40nt . Gata6 pFrequencies of co-occurring Gata:TEAD motifs in Gata6 peaks7) The authors used zebrafish to validate the Cis Regulatory Element identified in Myocd and jag1 loci. However, Data presented are not convincing, particularly in terms of images quality. Please clarify whether the CREs are expressed in zebrafish vascular system.We used transgenesis in zebrafish to establish regulation of Jag1 and Myocd enhancers by GATA TFs in vivo. We measured transgenes’ activities in hundreds of embryos to generate robust, statistically significant results . In ordeBecause transient transgenesis is characterized by mosaic expression of the transgene, a careful investigation of the transgene expression pattern would require establishing stable lines. We initially established lines for Myocd CRE1, whose activity is consistent with the developing heart and vasculature. A picture of GFP reporter activity driven by Myocd CRE1 has been added to 8) Gata6 mutant should be used to validate whether jag1 and Myocd are regulated by this factor.9) a2:Gata6 embryos were used as a model of gain of function. The authors should use these embryos to show an up-regulation of jag1 and Myocd. Persistence of AA2 is not obvious in the embryos showing in We thank the reviewer for this excellent suggestion, which has significantly improved the manuscript. We have chosen to use a gain of function system to address this request and quantified the levels of Jag1 and Myocd transcripts in transgenic embryos overexpressing Gata6 in the BA2. We generated new a2-Gata6 transgenic embryos, isolated BA2 from individual embryos, extracted RNA and quantified transcripts using qPCR. We found a significant increase in Myocd and Jag1 transcripts in the BA2 of all embryos overexpressing Gata6 compared to wild-type. The increase in Jag1 and Myocd levels, following Gata6 overexpression in BA2, reflect their differential expression in PBA versus BA2. Specifically, Jag1, whose levels are around 3 times higher in PBA vs BA2, is upregulated around 2 fold in transgenic embryos. Myocd transcript levels, which are over 50 fold higher in PBA versus BA2, are generally increased to much higher levels in transgenic embryos. The expression variability across transgenic embryos (relative to wild-type embryos) is consistent with each embryo having an independent transgene integration site. These data have been added to We believe that upregulation of Jag1 and Myocd transcripts in response to Gata6 overexpression, together with Gata6 binding at functional enhancers within Myocd and Jag1 loci and the requirement of intact GATA motifs for enhancers’ activity, conclusively establishes Jag1 and Myocd as Gata6 direct targets.We also used the same experiment to quantify the expression of vascular SMC-specific markers in the BA2 of transgenic embryos. Notably, the 3 transgenic embryos (2-3-4), which displayed blood in the BA2, a sign of a patent artery, had significantly higher levels of Acta2, Cnn1 and Tagln1 in the BA2 relative to wild-type, while embryo 1 (which did not show blood in the BA2 and presumably had no ectopic artery) showed similar levels of these transcripts to wild-type embryos. These data provide additional support to the ectopic differentiation of SMC in the BA2 of a2-Gata6 embryos and complete the analysis presented in Gata6 in SMCs and in the cranial NC leads to AAs and OFT defects without obvious abnormalities in vascular SMC development . The relatively ‘normal’ process of vascular SMC differentiation in these mutants is likely to reflect relatively healthy levels of its upstream regulators, i.e. Jag1 and Myocd. We have discussed possible redundancy with Gata4 and /or Gata5, which are also highly expressed in the PBAs similar to Gata6, as a possible explanation.Regarding point 8, we have serious reservations that Gata6 mutants would not conclusively address the functional link between Gata6 and Myocd and Jag1 genes. Targeted inactivation of To best visualize the persistent AA2, we have modified 10) "The presence of SMCs in all the transgenic embryos with persistent AA2 suggests that the primary effect of Gata6 is to generate SMCs and that the presence of these cells can, in most cases, stabilize the AA2 and promote its survival." This sentence is confusing, if the AA2 survivals, that implies that there is less apoptosis. It does not seem that this mechanism was involved in the persistence of the AA2.We agree with the reviewer; survival has been replaced with preservation in the last sentence of the subsection “5. Forced expression of GATA6 in the neural crest generates SMCs”.Reviewer #3:[…] There are some considerations, however, with the embryo work that need to be addressed.The development of the arch arteries (AA) in the mouse is a rapid process with the formation and regression of the first 2 AA occurring within the E9.5 stage, and the remodelling stage occurring during E11.5. Therefore it is important that the authors accurately describe the stage of embryo development, particularly within E9.5, at analysis. This is conventionally done by somite counting and should be achievable from the images already acquired. The authors should also state how well stage-matched the embryos are within the experimental groups, and this should be done for all experiments where embryos are used (immunostaining and sequencing). It is well known that embryos from the same litter can be at different stages of development as determined by somite number.This is an important point. We have added the number of somites as follows:RNA-seq : We poolConfocal analysis of AAs development : somite Gata6 and Gata6/SMA Immunofluorescence : somite Confocal and expression analysis of transgenic embryos : EmbryosThe only experiments where somites numbers are not available are ChIP-seq. Careful selection or recording of developmental stages is impractical for these experiments, which require a high number of embryos.Only whole-mount images of stained embryos (immuno and in situ) are presented. Although the images are of high quality it is not always obvious which tissue type or layer is being stained. Confirmation can only be achieved through double immunostaining of sections, or sectioning of the in situ stained embryos. This would clarify the location of the cells stained and give confidence to the conclusions drawn from these images. In particular this would be useful for the Gata6/SMA stained embryos shown in To clarify the location of the cells stained, we have added double immunostaining on section, using Gata6 and α-SMA antibodies (3I). The picture shows SMA-positive cells surrounding AA3, and localization of SMA to Gata6-expressing cells.In addition we have added an individual zstack from confocal analysis (3H), which shows the presence of differentiating SMC (SMA-positive) in the proximal region of BA4, in Gata6-positive areas.[Editors' note: the author responses to the re-review follow.]Essential revisions:1) The manuscript needs some rewriting as it is difficult to read because the "real" ChIP-seq peaks cannot be derived from data with a threshold q<0.05 which is not sufficiently stringent compared to papers using comparable techniques. For example, this results in the identification, of 50,000 Meis1 peaks whereas, using a more stringent threshold one gets 5,000. In the end, the authors only use those peaks and genes which have a high fold enrichment. Are the conclusions based on "all" peaks or only on the subset with high fold enrichment? The authors should clarify this and are encouraged to reevaluate their data using higher stringency.We thank the reviewers for the opportunity to clarify these issues.As correctly mentioned by the reviewers, we have not used all peaks for downstream analyses, but only high confidence peaks with fold enrichment (FE) values higher than 10. This resulted in the elimination of a large fraction of peaks detected by MACS2. More specifically, in addition to q-value < 0.05, which is MACS2 default cutoff to call significant regions, we have applied an additional stringent cutoff of FE ≥10 to all transcription factors ChIP-seq, i.e. to ‘narrow’ peaks. Additionally, for Meis ChIP-seq downstream analysis, we have used peaks FE≥10, which were present in both replicates.As a FE≥10 cutoff is too stringent for ‘broad’ peaks, for histone ChIP-seq (whose peaks are wider and flatter because of nucleosome distribution on chromatin), we selected peaks present in both replicates for downstream analysis.p-value, and detected the main motif in most of the binding regions.One of the standards prior to peak calling is to ensure that the IP experiment contains more than 10 million aligned short reads, and the newly added table (see point below) shows that all ChIP experiments fulfil this pre-requirement. The other standard measurement of the quality of peaks detected in transcription factors ChIP-seq experiments is motif search. For both Meis and GATA ChIP-seq, Homer motif search highlighted a main motif with high To clarify how peaks were selected for downstream analysis, we have enclosed a diagrammatic figure, which highlights the selection of FE≥10 as a step of the workflow (1) Materials and methods: Narrow peaks (TF ChIP-seq) were filtered using FE≥10. Each experiment was performed in duplicate; for H3K27Ac and Meis ChIP-seq, two replicates were intersected and peaks present in both replicates were used in downstream analyses.2) Materials and methods: Details of all ChIP-seq experiments  are provided in 3) Materials and methods: Regions with logFC≥ 3 binding in PBA versus BA2 were selected and intersected with Meis ChIP-seq 200nt summits in PBA, FE≥10, for de novo motif discovery using HOMER.4) Materials and methods: The workflow is summarized in 5) Materials and methods: Details of all RNA-seq experiments  are provided in 6) 7) 8) 9) In the previous version, the analysis presented in 10) 11) 2) The reader needs a clearer view of the actual data. A table stating the total number of reads, number of identified peaks (or reads), statistical thresholds, should be presented.We thank the reviewers for the valuable suggestion. We have added a table, which contains the total number of reads, number of peaks and other relevant values for the various steps of the workflow, for all the ChIP-seq and RNA-seq experiments. This is named ‘


Thus, we examined the effect of ICB on vascular smooth muscle cell (VSMC) proliferation, a key feature of diverse vascular diseases. When VSMCs primary cultured from rat thoracic aorta were stimulated with PDGF (1–10 ng/ml), cell proliferation and osteopontin (OPN) expression were concomitantly up-regulated, but these effects were attenuated when cells were treated with MPIIIB10, a neutralizing monoclonal antibody for OPN. In aortic tissues exposed to PDGF, sprouting VSMC numbers increased, which was attenuated in tissues from OPN-deficient mice. Furthermore, VSMC proliferation and OPN expression induced by PDGF were attenuated dose-dependently by ICB (10 or 30 μg/ml). Reporter assays conducted using OPN promoter-luciferase constructs showed that the promoter region 538–234 bp of the transcription start site was responsible for transcriptional activity enhancement by PDGF, which was significantly inhibited by ICB. Putative binding sites for AP-1 and C/EBPβ in the indicated promoter region were suggested by TF Search, and increased binding of AP-1 and C/EBPβ in PDGF-treated VSMCs was demonstrated using a ChIP assay. The increased bindings of AP-1 and C/EBPβ into OPN promoter were attenuated by ICB. Moreover, the PDGF-induced expression of OPN was markedly attenuated in VSMCs transfected with siRNA for AP-1 and C/EBPβ. These results indicate that ICB inhibit VSMC proliferation by inhibiting the AP-1 and C/EBPβ signaling pathways and thus downregulating OPN expression. Vascular smooth muscle cells (VSMCs) are essential regulators of vascular function ,2. In hePrevious studies have demonstrated that OPN levels were elevated in human atherosclerotic plaque ,10 and nSchisandra chinensis (SC) has a long history as a medicinal herb and is a traditional component in oriental medicines [edicines ,20. Seveedicines ,22. In tedicines ,24. Alsoedicines  reportedUnder pathological conditions, VSMCs exhibit phenotypic changes characterized by loss of contractility, abnormal proliferation, migration, and matrix secretion . This sySchisandra chinensis (SC) as described previously [n-hexane, chloroform (CHCl3), and methanol (MeOH). The hexane extract (308 g) was evaporated in vacuo and chromatographed on a 40 μm silica gel  column (100 × 10 cm) using step gradient elution . Fraction 1  was separated on a silica gel column (100 × 3.0 cm) using 15% acetone in dichloromethane (CH2Cl2) to obtain nine fractions, and the second fraction  was separated on a silica gel column (100 × 3.0 cm) using 15% acetone in CH2Cl2 to yield ICB (316 mg). Pure ICB (purity > 99%) was identified by high-performance liquid chromatography on a Phenomenex Luna C18 column  using an acetonitrile-water-alcohol gradient at a flow rate of 1.0 ml/min.α-Iso-cubebene (ICB) was purified from dried fruits of eviously . BrieflyAll animal procedures conformed with the Guide for the Care and Use of Laboratory Animals published by the US National Institute of Health , and the experimental protocols were approved by the Pusan National University Institutional Animal Care and Use Committee. All genotyping, including that of OPN deficient mice was performed by PCR using a protocol provided by the Jackson Laboratory . Wild-type (WT) control mice (C57BL/6J) were purchased from Jackson Laboratories.Platelet derived growth factor (PDGF) was purchased from Sigma , and OPN (sc-21742) and β-actin (sc-47778) antibodies were purchased from Santa Cruz Biotechnology Inc. . Horseradish peroxidase (HRP)-conjugated IgG antibody (Santa Cruz Biotechnology Inc.) was used as the secondary antibody. PCR primers were from Bioneer (Seoul). AP-1 (10024-2-AP) antibody was purchased from Proteintech , and C/EBPβ (ab15049) antibody from Abcam . Restriction enzymes were supplied by Promega .ACUGUAGAUUGCUUCUGUA (sence) and UACAGAAGCAAUCUACAGU (antisense); C/EBPβ, GACAAGCUGAGCGACGAGU (sence) and ACUCGUCGCUCAGCUUGUC (antisense).AP-1 and C/EBPβ siRNA oligonucleotides were synthesized by Bioneer . siRNA molecules were transfected into cells using Lipofectamine 2000 siRNA transfection reagent , according to the manufacturer's instructions. siRNA sequences against AP-1 and C/EBPβ were as follows: AP-1, 2 inhalation, and then primary VSMCs was cultured from thoracic aorta. Briefly, excised aortas were cut into ~1 mm2 segments, and placed as explants in a cell culture dish containing DMEM  with 10% FBS (Gibco BRL). Cells were maintained in DMEM containing 10% FBS and antibiotic-antimycotic (Gibco BRL) at 37°C.Sprague-Dawley rats  were sacrificed by CO5 cells) were treated with MTT working solution , and incubated at 37°C for 1 hr. OD values of solution was obtained at a wavelength of 450 nm by ELISA. Relative proliferation rates were determined by comparing cells with control cells.An MTT assay was used to determine the proliferation rates of VSMCs. Briefly, cells . Membranes were blocked with 5% skim milk in TBST and incubated overnight with primary antibody in 5% skim milk. Blots were washed with TBST, and incubated with HRP-conjugated secondary antibody for 2 hrs. Blots were developed using ECL Western blot detection reagents (Amersham). Membranes were re-blotted with anti-β-actin antibody (Santa Cruz Biotechnology) as an internal control.5'-CCGATGAGGCTATCAAGGTC-3'; reverse, 5'-ACTGCTCCAGGCTGTGTGTT-3').OPN mRNA levels in VSMCs were quantified by RT-PCR using GAPDH mRNA as an internal standard. Total RNA was isolated from cells using Quiazol  and reverse transcribed into cDNA using the Improm-II Reverse Transcription System (Promega). cDNA amplification was performed using primers specific for OPN , and then cloned into pGL3-basic to generate a pLuc-OPN-2284 construct. Additional deletion constructs lacking distal promoter sequences (denoted pLuc-OPN-538 and pLuc-OPN-234) were prepared by digesting pLuc-OPN-2284 with restriction enzymes .A series of constructs of OPN promoter in luciferase expression vector pGL3-basic (Promega) were prepared. The OPN promoter was amplified from genomic DNA using the following PCR primers . Cells were transfected with plasmids using Lipofectamin 2000 Transfection Reagent , according to the manufacturer's instructions. Cell lysates were prepared using the passive lysis buffer from the Promega assay system  and luciferase activity was determined using the dual luciferase reporter assay system (Promega).7 cells) and fixed with formaldehyde (1%). Cell pellets were then resuspended in shearing buffer containing protease inhibitors , sonicated with a Misonixsonicator 3000 , centrifuged, and diluted 10-fold in ChIP dilution buffer. Chromatin samples were incubated at room temperature for 90 minutes with assay well bound AP-1 and C/EBPβ antibody, and hybridized at 65°C for 4 hrs. Released DNA was collected through the GenElute Binding Column G, and immunoprecipitated chromatins were analyzed by PCR using the following OPN gene promoter primers . The cycling parameters were; 63°C for 1 min, 95°C for 30 sec, followed by 40 amplification cycles.Chromatin immunoprecipitation (ChIP) analysis was performed using the Sigma ChIP kit  according to the manufacturer's instructions with minor modifications. Briefly, VSMCs were inoculated into a 15-cm dish  followed by Turkey’s multiple comparison test or unpaired Student’s t-test were used to determine the significance of differences. Statistical significance was accepted for p value < 0.05.To investigate the effect of PDGF on OPN expression in VSMCs, cells were stimulated with PDGF (10 ng/ml) for 24 hrs, and OPN mRNA and protein levels were determined by RT-PCR and Western blotting, respectively. OPN mRNA levels in PDGF-treated cells started to increase after 2 hrs of PDGF treatment and continued to increase until 24 hrs . LikewisTo investigate the functional role of OPN in PDGF-induced VSMC proliferation, primary cultured VSMCs from rat thoracic aorta were pretreated with MPIIIB10 , and then cell proliferation was induced by PDGF. MTT assay results showed that PDGF (1–10 ng/ml) dose-dependently increased VSMC proliferation . The incAs shown in To determine the effects of ICB on PDGF-induced VSMC proliferation, cells were pretreated with 10 or 30 μg/ml of ICB for 2 hrs, and then stimulated with 10 ng/ml of PDGF for 48 hrs. Microscopic images of VSMCs cultured on 12 well plates  and the To determine the effects of ICB on PDGF-induced OPN expression in VSMCs, cells were stimulated with 10 ng/ml of PDGF for 12 hrs in the presence of ICB at 10 or 30 μg/ml. As shown in cis-acting elements in OPN promotor, three OPN luciferase constructs were established . As shown in To identify the responsible To determine the effect of ICB on PDGF-induced OPN transcription, VSMCs were transfected by pLuc-OPN-538 for 24 hrs, pretreated with ICB, and then stimulated with PDGF. As shown in This study importantly shows PDGF increases OPN expression in VSMCs and subsequently enhances VSMC proliferation. In addition, ICB was found to attenuate VSMC proliferation and OPN expression induced by PDGF. Increased bindings between AP-1 or C/EBPβ and OPN promoter in PDGF-stimulated cells were demonstrated by a ChIP assay, and these bindings were attenuated by ICB. These results suggested that ICB attenuated PDGF-induced VSMC proliferation by inhibiting the AP-1 and C/EBPβ signaling pathways and consequently down-regulating OPN expression in VSMCs.A number of studies have demonstrated that OPN is important for VSMC proliferation and migration into intima ,31. In pSchisandra chinensis (SC) has long been used as a tonic, sedative, astringent, anti-aging agent, and to treat cardiovascular symptoms in Korea, China and Japan [The proliferation of VSMCs plays an important role in the development and progression of cardiovascular diseases, including atherosclerosis ,36, and nd Japan ,40. The nd Japan ,41. In ond Japan . The relnd Japan , which sTherefore, in the present study, we investigated the effects of ICB on VSMC proliferation and OPN expression after stimulating cells with PDGF. Our findings indicated that ICB, a novel small molecule purified from SC, efficiently and dose-dependently inhibited VSMC proliferation. In addition, ICB potently inhibited OPN expression via transcriptional inhibition in PDGF-stimulated VSMCs. Based on our results and those of other studies in which OPN expression was found to be regulated by several mechanisms, including gene expression at the transcriptional and translational levels ,43. The cis-acting element responsible for PDGF-induced OPN transcription in VSMC. Using the sequence motif search of TFSearch software (http://mbs.cbrc.jp/research/db/TFSEARCH.html), putative transcription factor binding sites for AP-1 and C/EBPβ were identified between -538 bp and -234 bp relative to the transcriptional initiation site in OPN promoter, and subsequently, ChIP assay demonstrated the increased binding of AP-1 and C/EBPβ in PDGF-treated VSMCs. Moreover, the PDGF-induced increase in OPN expression was also markedly attenuated in VSMCs transfected with siRNA for AP-1 and C/EBPβ. These results suggested that the transcription factors, AP-1 and C/EBPβ, regulate OPN expression in PDGF-stimulated VSMCs.In the hope of identifying a potential strategy for treating vascular remodeling diseases, we also investigated the inhibitory effect of ICB on PDGF-induced OPN expression at the transcriptional and translational levels. To identify the regulatory element in OPN promoter responsible for gene transcription, a 2,284 kb 5' fragment of the open reading frame of OPN was cloned by PCR. In our study, the luciferase reporter activity of pLuc-OPN-538 in VSMCs exposed to 10 ng/ml of PDGF was about 5-fold higher than the control, whereas this increase was not observed in cells transfected with the pLuc-OPN-234 construct. These results suggest that the -538 ~ -234 region of OPN promoter is the To determine the effect of ICB on PDGF-induced OPN transcription, VSMCs were transfected by the pLuc-OPN-538 construct for 24 hrs. When VSMCs were stimulated with PDGF in the presence of ICB, PDGF-enhanced luciferase activity in cells transfected with pLuc-OPN-538 was markedly attenuated, suggesting a potential inhibition of OPN transcription induced by PDGF. In addition, the increased bindings of AP-1 and C/EBPβ into OPN promoter in PDGF-stimulated cells was attenuated by ICB, indicating that AP-1 and C/EBPβ were major ICB-targeted transcription factors involved in OPN expression in VSMCs.Summarizing, our experimental results suggested ICB inhibits PDGF-induced VSMC proliferation by inhibiting the AP-1 and C/EBPβ signaling pathways and consequently down-regulating OPN expression. We believe the findings of the present study shed light on the mechanism responsible for the anti-atherogenic activity of ICB.


SLAMF1 gene encodes CD150, a transmembrane glycoproteinexpressed on the surface of T and B-lymphocytes, NK-cells, dendritic cells, andsubpopulations of macrophages and basophils. We investigated the functionalregulatory polymorphisms of the SLAMF1 locus associated withautoimmune processes, using bioinformatics and a mutational analysis of theregulatory elements overlapping with polymorphic positions. In the reportergene assay in MP-1 and Raji B-cell lines, the enhancer activity of theregulatory region of the locus containing the rs3753381 polymorphismdemonstrated a twofold increase upon the introduction of the rs3753381 minorvariant (G → A) associated with myasthenia gravis. An analysis of thenucleotide context in the vicinity of rs3753381 revealed that the minor versionof this polymorphism improves several binding sites for the transcriptionfactors of FOX and NFAT, and RXR nuclear receptors. All mutations that disruptany of these sites lead to a decrease in the enhancer activity both in MP1 andin Raji cells, and each of the two B-cell lines expresses a specific set ofthese factors. Thus, the minor variant of the rs3753381 polymorphism maycontribute to the development of myasthenia gravis by modulating SLAMF1expression, presumably in pathogenic B-lymphocytes.The  SLAMF1 .T.T27].TKT-cells, 34.A sSLAMF1 gene, including the promoter (297-0 with respectto the translation start site) and three enhancer elements of approximately 2.5kb, two of them located in the third intron and one at a distance of 3 kbpafter the coding sequence [SLAMF1 mRNA is controlled bythe EBF1, SP1, STAT6, IRF4, NF-kB, ELF1, TCF3, and SPI1/PU.1 transcriptionfactors, which bind to the promoter and enhancer regions.Recently, we described several regulatory regions that control the expressionof the sequence . TheactSLAMF1 gene locus (hereinafter enhancers E and D),where two polymorphisms, rs3753381 and rs11265455, associated withautoimmune processes, are localized. We studied the effect of each of thesepolymorphisms on the expression of the SLAMF1 gene in B cells.The enhancer E comprising rs3753381 polymorphism is located in the third intronof the SLAMF1 gene, and enhancer D is locatedat a distance of 1.5 kbps before the coding region of the gene.This paper presents data on two additional enhancer elements of theSLAMF1 gene locus showedthat both the minor and major variants of rs11265455 have almost no effect onthe activity of the SLAMF1 promoter, whilethe minor variant of the rs3753381 polymorphism (located in enhancer E)increases the activity of the SLAMF1 promoter more thantwofold. We identified FOX, RXR, and NFAT as nuclear protein families whosebinding depends on the allelic variant of rs3753381 and have pointed at theparticular members of these families which are specifically expressed in theinvestigated cell lines .Our study of polymorphisms in the Cell culture and transfection procedureL-glutamine, antibiotics, essentialamino acids, HEPES, and sodium pyruvate. Transfection was performed using theNeon Transfection System  at the rate of 2 ×106 MP-1 cells and 7 × 106 Raji cells pertransfection. Luciferase activity was assayed after 24 hours using a DualLuciferase Assay kit .MP-1 and Raji cells were cultured in a RPMI medium (PanEco) supplemented with10% fetal calf serum, Plasmid ConstructsTable 2.Genetic engineering manipulations were carried out using standard techniques;enzymes produced by Fermentas/ThermoScientific (Lithuania) were used. In orderto produce the constructs pGL3-rs3753381 (G) and pGL3-rs11265455 (A), sequencesof the enhancers E and D, respectively, were amplified with primers containingthe restriction sites SalI and BglII  andthen cloned into a WT SLAMF1 vector cleaved Bioinformatics analysis of binding sitesSLAMF1 gene locus were analyzed usingpublic ChIP-Seq data for the B-lymphoblastoid cell line GM12878  available in the UCSCGenome Browser [The genomic segments in the vicinity of the rs3753381 and rs11265455polymorphisms of the  Browser . We cons Browser . Predict Browser . The eff Browser  with theThe analysis of differential gene expressionThe MP-1 and Raji samples analyzed in our study were obtained in . The resSLAMF1 enhancerThe minor variant of rs3753381 polymorphism increases the activity of theSLAMF1 gene, A, B, and C [Fig. 1A,enhancers A and B are shown bygray arrows). In our study, we chose two additional alleged regulatory regionsto analyze the possible impact of single nucleotide polymorphisms on theregulation of SLAMF1 expression: rs3753381polymorphism is located in the putative enhancer E (the third intron ofSLAMF1), and rs11265455 polymorphism is located in theputative enhancer D, which is 1,500 bp upstream of the SLAMF1 codingregion (shownby red arrows). These regulatory elements were cloned in two stages into a WT SLAMF1 vector [SLAMF1 promoter activity,which confirms the function of D and E as potential transcription enhancers.We have previously described the promoter and three enhancers of theB, and C .Next, single substitutions were introduced into the sequences of the enhancerelements D and E so as to replace the existing rs3753381 and rs11265455 alleleswith alternative variants associated with the development of type 2 diabetesmellitus and myasthenia gravis, respectivelycompared to the previously described [Both putative enhancer elements increase escribed control Figure 1Bshows that the presence of a minor variant ofrs3753381 polymorphism increases the activity of enhancer E in both cell lines,and the minor variant of rs11265455 polymorphism has no significant effect onthe activity of enhancer D in any of the examined lines. Therefore, weproceeded with studying the rs3753381 polymorphism in more detail.Mutations at the RXR and FOX transcription factor binding sites reduceenhancer E activity in the case of minor variant of rs3753381polymorphism.We performed a bioinformatics analysis of the transcription factor bindingsites which could be affect ed by the studied polymorphisms in order to explainthe significant increase in enhancer E activity when a minor variant (A) ofrs3753381 polymorphism was introduced. We analyzed the sites that overlappedwith rs3753381 and its allelic variant using the PERFECTOS-APE software. It wasfound that different members of the NFAT, RXR, and FOX families could bind tothe rs3753381 polymorphism region and that their binding sites were stronger inthe case of the minor variant (A). The predicted sites were mutated, and theeffects of the mutations were tested in a system with a reportergene P-value of 0.001 or better for thewild-type sequence with the A allele. Then, we considered only thosepredictions where the affinity decreased or remained unchanged in all thealternative versions of the sequence .Only the proteins expressed in the MP-1 and Raji cell lines were selected forfurther analysis.Mutations in the RXR and FOX binding sites significantly reduce the activity ofthe enhancer with respect to the minor variant of rs3753381. The results wereverified using a detailed bioinformatic analysis of the genomic sequencestraddling the rs3753381 polymorphism. We selected the most reliable models ofthe binding sites from the HOCOMOCO database and conducted a joint analysis ofall six sequence variants (rs3753381 (G), mut RXR (G), mut FOX (G), rs3753381(A), mut RXR (A), mut FOX (A), using PERFECTOS-APE. We filtered only thepredicted sites having a  and mut RXR (G) constructs).The Raji cell line is characterized by a high expression of RXRB and NR2C1,whose binding sites can be affected by the mut RXR mutation and, therefore, adisturbed binding of each of them can contribute to a reduction in enhancer Eactivity. As for the FOX factors, whose sites can be affected by the respectivemutation, FOXA2 is highly expressed in the MP-1 cell line. NFAC (NFATC2 andNFATC3) proteins, which potentially bind to the same site, are expressed in theRaji cell line. Further, each mut FOX (A), mut FOX (G), mut RXR (A), and mutRXR (G) can affect the HNF4G binding site, and this causes a decrease inenhancer E activity in these constructs in MP-1 cells. When summarizing data onthe mut RXR and mut FOX mutations, it can be assumed that the mut RXR mutationis associated with disrupted binding of HNF4G, RXRB, NR4A2, COT2, and PPARG inMP-1, and RXRB and NR2C1 in Raji, while the mut FOX mutation can disrupt thebinding of HNF4G and FOXA2 in MP-1 and NFATC2, and NFATC3 in Raji. Thus, achange from the major variant of the rs3753381 polymorphism (G) to the minorrs3753381 (A) may change the binding of the RXR, FOX, and NFAC transcriptionfactors, which are different in the case of MP-1 and Raji cell lines. TheHOCOMOCO motif database covers only 600 of more than 1,500 human transcriptionfactors [HNF4G, NR4A2, COT2, and PPARG are actively expressed in the MP-1 cell line,which may explain the significant decrease in enhancer E activity in the caseof damaged binding sites of the aforementioned factors due to the mut RXRmutation factors : We cannSLAMF1 locus associated with autoimmune processes, indicatinga possible relationship between the rs3753381 and rs11265455 polymorphisms andthe regulation of SLAMF1 gene expression. Weexplored the association between the minor variant of rs3753381 and the morethan twofold increase in the activity of the SLAMF1 enhancerusing the experimental model of human B-lymphoblastoid cell lines. Thebioinformatics analysis of the sequences of the minor and major variants of thepolymorphisms predicted that transcription factors of the NFAT, FOX, and RXRfamilies likely contribute to the increase in enhancer E activity in the caseof the minor variant of the rs3753381 polymorphism. It was shown that mutationsin the predicted binding sites reduce the activity of the enhancer E carrying aminor variant of the rs3753381 polymorphism. It was also found that change inthe allelic variant of the rs11265455 polymorphism has no significant impact onSLAMF1 gene expression. Our study demonstrates the functional significance of the polymorphisms of the


While the absolute residence times estimates can depend on imaging acquisition parameters due to sampling bias, our results indicate that only a small proportion of factors are specifically bound to chromatin at any given time. Interestingly, the glucocorticoid receptor and its cofactors affect each other’s dwell times in an asymmetric manner. Overall, our data indicate transient rather than stable TF-cofactors chromatin interactions at response elements at the single-molecule level.Population-based assays have been employed extensively to investigate the interactions of transcription factors (TFs) with chromatin and are often interpreted in terms of static and sequential binding. However, fluorescence microscopy techniques reveal a more dynamic binding behaviour of TFs in live cells. Here we analyse the strengths and limitations of  Transcription factors (TFs) are thought to regulate gene expression by stably binding to target DNA elements. Here, the authors use single-molecule tracking to analyse the dynamic behaviour of steroid receptors TFs and show that most specific interactions with chromatin are transient and dynamic. Under this paradigm, the recruitment of multiple molecular partners progressively stabilizes the structure and facilitates the recruitment of other factors in a static and well-ordered manner2For decades, transcription factors (TFs) have been thought to operate by binding their genomic targets stably to form well-defined macromolecular complexes that remain intact and biologically functional for minutes or hours at a time12With recent advances in fluorescence imaging, it has become possible to track individual TF molecules in single live cells6910111213141511In this study, we show that only a small percentage of TF molecules (∼5–10%) are specifically bound to chromatin at any given time. We also show that, given the multi-exponential nature of the distribution of residence times, the measured kinetic parameters for TF binding can depend on the image acquisition parameters. Therefore, the dwell time for a given factor must be evaluated over a range of conditions to develop a rigorous understanding of its dynamic behaviour. Finally, we report an asymmetric modulation between GR and its known cofactors GRIP1, BRG1 and AP-1 at the single-molecule level. Collectively, our single-molecule studies affirm the general model where many transcription factors are highly dynamic during their chromatin-binding activity.549) HaloTag ligandIn SMT, individual protein molecules are imaged in time-lapse and their spatial-temporal trajectories are recorded in real timermax for more than Nmin consecutive frames) or unbound (see Methods). From the bound population, we could then compute the duration of each binding event: we observed a continuum of residence times exponentially distributed  prior to imaging. Using a custom-made tracking software (see Methods), individual localizations of single molecules are classified as belonging to a bound track segment , therefore abolishing specific DNA-binding activity Multiple studies have shown that different GR ligands can influence the mobility and binding of GR to chromatin2425P<0.001), the bound fraction is very similar (P=0.41) between stably integrated and transiently transfected HaloTag-GR (P=0.67)  . OverallLive-cell binding studies using FCS, FRAP and SMT techniques have yielded widely divergent estimates of the chromatin-bound fraction of TFs and their residence timesTherefore, to detect whether highly stable single molecules exist, we tracked HaloTag-GR in Dex-treated cells under a wide range of interval acquisition times . AcquisiP<0.05) than that of HaloTag-GR and -PR. It is tempting to speculate this could reflect TF activity of the unliganded forms of ER and AR, as previously reported elsewhere29To study the changes in binding dynamics of steroid receptors before and after activation, we tracked HaloTag-fused GR, oestrogen (ER), progesterone (PR), and androgen (AR) receptors in the 3617 cell line in both untreated and cognate hormone-treated conditions. A two-exponential decay model was required to characterize each receptor in all conditions . For eacActivation of all steroid receptors increased the fast and slow bound fractions, while the proportion of unbound molecules was reduced . Signifi313233We next analysed how known GR partners would respond to receptor activation. To this end, we tracked HaloTag-fused GR-interacting protein 1 (GRIP1), and SNAP-tag fused BRG1, a major ATPase subunit of the SWI/SNF chromatin remodelling complex. GRIP1 is a well-known coactivator of GR3537To confirm that the increase in GRIP1’s residence time and bound fraction is due to the direct interaction of GR with GRIP1, we tracked HaloTag-fused GRIP1 interaction-defective mutantThe GR-dependent changes in GRIP1 action suggest that GR can alter the binding dynamics of important co-regulators. A major regulator of GR action in 3617 cells is AP-1, which modulates GR binding at 40% of its binding sites40The dominant negative a-FOS, which contains an acidic extension in its N terminus, effectively inhibits the DNA binding of c-JUN while having no effect on the heterodimerization of c-JUN-a-FOSChIP-seq analyses have shown that AP-1 modulates GR action by being an initiator of GR bindingin vitro biochemistry with naked DNA and in vivo ChIP-seq approaches, postulates that TFs are sequentially and stably (minutes–hours) recruited to DNA. Conversely, the live cell microscopy view, grounded on fluorescence techniques such as FCS, FRAP and more recently SMT, holds that TFs are transiently bound (milliseconds–seconds) to the template. For a comprehensive understanding of TF action, the genomic and live cell microscopy perspectives must eventually be resolved within a single comprehensive model. Genomic studies indicate that hormonal activation results in binding of receptors to chromatin313233Two mutually exclusive views have been proposed regarding TF dynamics on chromatin: the genomic view, based on in vitro drastically affects the long-lived binding events of several TFs in vivo61247Several lines of evidence now point to the ‘slow fraction’ measured by single-molecule experiments as the molecules interacting with authentic regulatory sites. Introduction of mutations that abolish DNA binding We also demonstrate that the estimates of average residence time can depend on the imaging acquisition parameters, when multi-exponential distributions of residence times are observed. Hence, determination of absolute average residence times should be taken with caution. Previous reports have attempted to deal with this issue with no clear resolution of the problem949Binding characteristics of BRG1 resemble to those of a TF, consistent with the concept that complexes are formed between Swi/Snf proteins and various TFs within the nucleusOur single-molecule imaging data support the concept that many TFs as well as different co-regulators are highly dynamic during their chromatin-binding activity6910111214In conclusion, TF dwell times at authentic response elements are quite brief for the increasing number of factors that have been investigated. These studies must now be extended to the direct analysis of dynamics at known regulatory sites, and the corresponding linkage to real-time transcriptional output for promoter(s) dependent on those sites. Although this is an ambitious goal, it is likely technically possible with the rapidly evolving methodology available in live cell microscopy.L-glutamine (Life Technologies).Dexamethasone (Dex), corticosterone (Cort), Progesterone (Prog), 17β-estradiol (E2) and Dihydrotestosterone (DHT) were purchased from Sigma-Aldrich . All cell lines were routinely cultured in DMEM high-glucose supplemented with 10% fetal bovine serum (FBS)  and 2 mM −1 tetracycline (Sigma-Aldrich) to prevent expression of a stably integrated GFP-GRL-glutamine. Knock-out of GR in 3617 cells (KOGR cells) was achieved by CRISPR-Cas9 technology−1. A volume of 2 ml of this virus solution was used to infect 200,000 KOGR cells. At 48 h post transduction, the cells were selected with 500 μg ml−1 Hygromycin (Sigma-Aldrich).3617 mouse mammary adenocarcinoma cellsSgfI and PmeI sites. The pEGFP-c-FOS expresses the rat c-FOS with EGFP fused in the N-terminal domain under the CMV promoter. It has been generated by PCR amplification from pcDNA3-FLAG-Fos WT and sub cloned into the pEGFP-C1 backbone  with KpnI and BamHI sites. The pHaloTag-a-FOS expresses the human a-FOS with HaloTag fused in the N-terminal domain under CMVd1 promoter. It has been generated by PCR amplification from pRev-TRE-aFos and sub cloned into the pFN22K backbone with SgfI and PmeI sites. The pEGFP-a-FOS expresses the human a-FOS with EGFP fused in the N-terminal domain under the CMV promoter. It has been generated by PCR amplification from pRev-TRE-aFos and sub cloned into the pEGFP-C1 backbone with SalI and BamHI sites. The pHaloTag-c-JUN expresses the mouse c-JUN with HaloTag fused in the N-terminal domain under CMVd1 promoter. It has been generated by PCR amplification from Flag-JunWT-Myc (Addgene plasmid #47443) and sub cloned into the pFN22K backbone with SgfI and PmeI sites. The pHaloTag-GRIP1 expresses the mouse GRIP1 with HaloTag fused in the N-terminal domain under CMVd1 promoter. It has been generated by PCR amplification from pEGFP-GRIP1 and sub cloned into the pFN22K backbone with SgfI and PmeI sites. The pHaloTag-GRIP1mutant (GRIP1mut) expresses mouse GRIP1-L693A-L694A-L748A-L749A with HaloTag fused in the N-terminal domain under CMVd1 promoter. It has been generated by PCR amplification from pEGFP-GRIP1mut and sub cloned into the pFN22K backbone with SgfI and PmeI sites. The pSNAP-tag-BRG1 expresses the human BRG1 with SNAP-tag fused in the N-terminal domain under CMV promoter. It has been generated by PCR amplification of SNAP from pSNAPf  and sub cloned into the mCherry-hsBRG1 backbone with AgeI and SalI sites. This sub-cloning replaced the mCherry sequence with the SNAP sequence. The pRevTRE-HaloTag-GR contains HaloTag-GR in tetracycline regulated retroviral vector under minimal CMV promoter. It has been generated by PCR amplification from pHaloTag-GR and sub cloned in to the pRevTRE (Clontech) backbone with AgeI and MfeI sites.The pHaloTag-GR expresses the rat GR with HaloTag  fused in the C-terminal domain under the CMVd1 promoterFor protein isolation, cells were grown 24 h with or without tetracycline (for expression of integrated GFP-GR). Subsequently, the cells were washed with cold PBS and collected with PBS-containing protease inhibitors . Cell pellets were suspended into RIPA buffer . Protein concentrations were measured by Bradford assay, and 30 μg of protein extracts were separated by electrophoresis on 4–20% Mini-PROTEAN TGX Stain-free gels . Separated proteins were transferred to Trans-Blot Turbo PVDF membranes (Bio-Rad) using Trans-Blot Turbo transfer system (Bio-Rad) using manufacturer’s instructions. After blocking with 5% milk in TBS+0.3% Tween, the membranes were probed with the following primary antibodies: anti-GR , anti-GAPDH , and anti-GRIP1  in 5% milk in TBS+0.3% Tween overnight with rocking at 4 °C. After four washes with TBS+0.3% Tween solution, membranes were probed with HRP-conjugated secondary mouse or rabbit antibodies  for 1 h in 5% milk in TBS+0.3% Tween. After four washes with TBS+0.3% Tween, the membranes were incubated with Super Signal Pico detection reagent  and visualized using ChemiDoc MP imaging system (Bio-Rad). Images of full membranes shown in For RNA isolation, cells were grown for 24 h in DMEM medium containing 10% charcoal-stripped FBS. Cells were collected after 1 h of 100 nM Dex treatment. RNA was extracted using the PureLink RNA mini kit (Invitrogen) according to the manufacturer’s instructions. Subsequently, cDNA was generated from 1 μg RNA using the iScript cDNA Synthesis Kit (Bio-Rad). Real-time quantitative PCR was performed using the iQ SYBR Green Supermix (Bio-Rad) on a CFX96 Touch Real-Time PCR Detection System (Bio-Rad). Primer sequences were designed to amplify only nascent RNA, using PCR amplicons that cross an exon–intron or untranslated region (UTR)-intron boundary. β-actin was used to normalized the data, which is expressed as fold induction relative to each cell line vehicle treatment. Primers used for quantitative PCR are: Per1, forward 5′-CTTCTGGCAATGGCAAGGACTC and reverse 5′-CAGCATCATGCCATCATACACACA-3′; Sgk, forward 5′-GAAACAGAGAAGGATGGGCCTGAAC-3′ and reverse 5′-GATCTCAGCTCCAGCACCACCAC-3′; Orm, forward 5′-ATTCTTGTCATGGTGAGCCTCCTGC-3′ and reverse 5′-GCTCAGGGTCTCATTGGTGATAGGG-3′; b-actin, forward 5′-GCTGGAAAAGAGCCTCAGGGC-3′ and reverse 5′-CGCATCCTCTTCCTCCCTGGAG-3′.For depletion of GRIP1, 5 million cells were electroporated with 10 μg of ON-TARGETplus Non-Targeting Control Pool  or ON-TARGETplus SMARTpool mouse Ncoa2  using BTX T820 Electro Square Porator  with three 10 ms pulses using low voltage pulse length and 140 V peak pulse. The cells were grown for 48 h and subjected to a second round of electroporation as before. However, in the second electroporation, 1 μg of HaloTag-GR was also electroporated with additional siSCR or siGRIP1 to the cells. The cells were grown for 24 h, and subsequently either proteins or RNAs were isolated; or single-molecule tracking of GR was performed as indicated.549. Fluorescence was detected with a GaAsP detector in photon-counting mode.Images were taken at the CCR, LRBGE Optical Imaging Core facility  in an LSM 780 laser scanning microscope  equipped with an environmental chamber. We used a × 63 oil immersion objective . The excitation source was 488 nm for GFP and 561 nm for JF549) HaloTag ligand549 was used because higher amounts of dye-generated excessive label density. For SNAP-tag, 3617 cells were treated with 250 nM of JF549 SNAP-tag ligand for 40 min. All cells are then washed three times for 15 min with phenol red-free DMEM media (Invitrogen) to remove the unbound fluorescent molecules. Subsequently, the cells were treated with or without 100 nM of the indicated hormones for 20 min before imaging. In transient transfections, regardless of the DNA amount transfected, imaged cells had 30–100 diffraction-limited spots at the two-dimensional plane. This is a similar number of spots observed in cells with stably integrated HaloTag-GR treated with an order of magnitude less fluorescence dye than in transient transfections.Cells were transiently transfected with the indicated pHaloTag-, pSNAP-tag- or GFP-fusion proteins using jetPRIME reagent , under conditions that do not generate overexpression of the HaloTag construct . BrieflyThe custom-built microscope from the CCR, LRBGE Optical Microscopy Core facility is controlled by μManager software , equipped with a × 150, 1.45 numerical aperture objective , a 561 nm laser , an acousto-optic tunable filter  and HILO illuminationrmax) (both obtained from the motion of immobile histones) have been used to define bound portions of each particle’s track. Because there is a chance that even a fast diffusing molecule will move less than these thresholds, a further constraint on the minimum number of time points in the bound segment for each particle (Nmin) is used to reduce to <1% the contribution of diffusing molecules to the survival histogramNmin depends on the frame rate, and those used for the various intervals are presented in B, which is calculated by first isolating the localization events that have been assigned to bound molecules NB and by then dividing NB for the total number of detected particles (including those molecules not assigned to tracks because they appear for just a single frame). All survival histograms are corrected for photobleaching, which is characterized separately for each movie, by fitting the frame-dependent number of detected particles to a bi-exponential decayS(t), is fit by least squares to a mixed exponential decay with two rate constants, kns=1/Tns and ks=1/Ts:Residence times and bound fraction are determined by the fitting to the survival distributionB is the bound fraction, and Fns is the fraction of particles non-specifically bound. To check for over-fitting, the distribution is also fit to a single-component exponential:where ks1 and ks2:and to a three-component exponential, with two different specific binding decay constants, F-test to ensure that the two-component model gives a significantly improved fit over the single- and three-component decay. The Box-plots represent the distribution of dwell times in the short-lived fast fraction (Fns) and long-lived slow fraction (1−Fns) (Fns and 1−Fns (t-test.and the fits are compared using an  (1−Fns) . Using tnd 1−Fns , the popThe data sets generated during and/or analysed during the current study are available from the corresponding author upon reasonable request.How to cite this article: Paakinaho, V. et al. Single-molecule analysis of steroid receptor and cofactor action in living cells. Nat. Commun.8, 15896 doi: 10.1038/ncomms15896 (2017).Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.